Patent application title: METHODS AND COMPOSITIONS FOR EVALUATING BREAST CANCER PROGNOSIS
Timothy J. Fischer (Raleigh, NC, US)
Clark M. Whitehead (Apex, NC, US)
Douglas P. Malinowski (Hillsborough, NC, US)
Douglas P. Malinowski (Hillsborough, NC, US)
Raphaël Marcelpoil (Grenoble, FR)
Didier Morel (Grenoble, FR)
TriPath Imaging, Inc
IPC8 Class: AG01N33566FI
Class name: Chemistry: analytical and immunological testing biospecific ligand binding assay
Publication date: 2009-10-29
Patent application number: 20090269856
Patent application title: METHODS AND COMPOSITIONS FOR EVALUATING BREAST CANCER PROGNOSIS
Timothy J. Fischer
Douglas P. Malinowski
Clark M. Whitehead
ALSTON & BIRD LLP
TriPath Imaging, Inc
Origin: CHARLOTTE, NC US
IPC8 Class: AG01N33566FI
Patent application number: 20090269856
Methods and compositions for evaluating the prognosis of a breast cancer
patient, particularly an early-stage breast cancer patient, are provided.
The methods of the invention comprise detecting expression of at least
one, more particularly at least two, biomarker(s) in a body sample,
wherein overexpression of the biomarker or a combination of biomarkers is
indicative of breast cancer prognosis. In some embodiments, the body
sample is a breast tissue sample, particularly a primary breast tumor
sample. The biomarkers of the invention are proteins and/or genes whose
overexpression is indicative of either a good or bad cancer prognosis.
Biomarkers of interest include proteins and genes involved in cell cycle
regulation, DNA replication, transcription, signal transduction, cell
proliferation, invasion, proteolysis, or metastasis. In some aspects of
the invention, overexpression of a biomarker of interest is detected at
the protein level using biomarker-specific antibodies or at the nucleic
acid level using nucleic acid hybridization techniques.
1. A method for evaluating the prognosis of a breast cancer patient, said
method comprising detecting overexpression of at least one biomarker in a
sample from said patient, wherein said biomarker is selected from the
group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC
14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9,
and MCM6, wherein overexpression of said biomarker is indicative of
prognosis, and thereby evaluating the prognosis of said breast cancer
2. A method for evaluating the prognosis of a breast cancer patient, said method comprising:a) obtaining a sample from said patient;b) contacting said sample with at least one antibody, wherein said antibody specifically binds to a biomarker protein, wherein said biomarker protein is selected from the group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, and MCM6;c) detecting binding of said antibody to said biomarker protein;d) determining if said biomarker protein is overexpressed in said sample, wherein overexpression of said biomarker protein is indicative of a poor prognosis; and,e) thereby evaluating the prognosis of said breast cancer patient.
3. The method of claim 2, wherein said biomarkers are selected from the group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, and MCM6.
4. A kit comprising at least two antibodies, wherein each of said antibodies specifically binds to a distinct biomarker protein that is indicative of poor prognosis of a breast cancer patient, and wherein the biomarker proteins are selected from the group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, and MCM6.
5. The kit of claim 4, wherein said biomarker proteins are selected from the group consisting of E2F1, SLPI, MUC-1, src, p21ras, and PSMB9.
6. The kit of claim 4, wherein said kit further comprises chemicals for the detection of antibody binding to said biomarker protein.
7. The kit of claim 4, wherein said kit is used with a commercial antibody binding detection system.
8. The kit of claim 4, wherein said kit further comprises a positive control sample.
9. The kit of claim 4, wherein said kit further comprises instructions for use.
CROSS REFERENCE TO RELATED APPLICATIONS
This application is a divisional application of U.S. Utility application Ser. No. 11/233,510, filed Sep. 22, 2005, which claims the benefit of U.S. Provisional Application Ser. No. 60/612,073, filed Sep. 22, 2004, and U.S. Provisional Application Ser. No. 60/611,965, filed Sep. 22, 2004, all of which are incorporated herein by reference in their entirety.
REFERENCE TO A SEQUENCE LISTING SUBMITTED AS A TEXT FILE VIA EFS-WEB
The official copy of the sequence listing is submitted concurrently with the specification as a text file via EFS-Web, in compliance with the American Standard Code for Information Interchange (ASCII), with a file name of 372587SequenceListing.txt, a creation date of May 14, 2009, and a size of 161 KB. The sequence listing filed via EFS-Web is part of the specification and is hereby incorporated in its entirety by reference herein.
FIELD OF THE INVENTION
The present invention relates to methods and compositions for evaluating the prognosis of a patient afflicted with breast cancer, particularly early-stage breast cancer.
BACKGROUND OF THE INVENTION
Breast cancer is the second most common cancer among American women, less frequent only than skin cancer. An American woman has a one in eight chance of developing breast cancer during her lifetime, and the American Cancer Society estimates that more than 250,000 new cases of breast cancer will be reported in the U.S. this year. Breast cancer is the second leading cause of cancer deaths in women, with more than 40,000 Americans expected to die from the disease in 2004.
Improved detection methods, mass screening, and advances in treatment over the last decade have significantly improved the outlook for woman diagnosed with breast cancer. Today, approximately 80% of breast cancer cases are diagnosed in the early stages of the disease when survival rates are at their highest. As a result, about 85% percent of breast cancer patients are alive at least 5 years after diagnosis.
Despite these advances, approximately 20% of women diagnosed with early-stage breast cancer have a poor ten-year outcome and will suffer disease recurrence, metastasis, or death within this time period. The remaining 80% of breast cancer patients diagnosed at an early stage, however, have a good 10-year prognosis and are unlikely to need, or benefit from, additional aggressive adjuvant therapy (e.g., chemotherapy). The current clinical consensus is that at least some early-stage, node-negative breast cancer patients should receive adjuvant chemotherapy, but presently there are no widely used assays to risk stratify patients for more aggressive treatment. Since the majority of these early-stage cancer patients enjoy long-term survival following surgery and/or radiation therapy without further treatment, it is likely inappropriate to recommend aggressive adjuvant therapy for all of these patients, particularly in light of the significant side effects associated with cancer chemotherapeutics. Compositions and methods that permit the differentiation of these populations of early-stage breast cancer patients at the time of initial diagnosis into good and bad prognosis groups would assist clinicians in selecting appropriate courses of treatment. Thus, methods for evaluating the prognosis of breast cancer patients, particularly early-stage breast cancer patients, are needed.
Significant research has focused on identifying methods and factors for assessing breast cancer prognosis and predicting therapeutic response. (See generally, Ross and Hortobagyi, eds. (in press) Molecular Oncology of Breast Cancer (Jones and Bartlett Publishers, Boston, Mass.) and the references cited therein, all of which are herein incorporated by reference in their entirety). Prognostic indicators include more conventional factors, such as tumor size, nodal status, and histological grade, as well as molecular markers that provide some information regarding prognosis and likely response to particular treatments. For example, determination of estrogen (ER) and progesterone (PR) steroid hormone receptor status has become a routine procedure in assessment of breast cancer patients. See, for example, Fitzgibbons et al. (2000) Arch. Pathol. Lab. Med. 124:966-978. Tumors that are hormone receptor positive are more likely to respond to hormone therapy and also typically grow less aggressively, thereby resulting in a better prognosis for patients with ER+/PR+tumors.
Overexpression of human epidermal growth factor receptor 2 (HER-2/neu), a transmembrane tyrosine kinase receptor protein, has been correlated with poor breast cancer prognosis. Ross et al. (2003) The Oncologist:307-325. Her2/neu expression levels in breast tumors are currently used to predict response to the anti-Her-2/neu antibody therapeutic trastuzumab (Herceptin®; Genentech). See, for example, Id. and Ross et al., supra. Furthermore, approximately one-third of breast cancers have mutations in the tumor suppressor gene p53, and these mutations have been associated with increased disease aggressiveness and poor prognostic outcome. Fitzgibbons et al., supra. Ki-67 is a non-histone nuclear protein that is expressed during the G1 through M phases of the cell cycle. Studies have shown that overexpression of the cellular proliferation marker Ki-67 also correlates with poor breast cancer prognosis. Id.
Although current prognostic criteria and molecular markers provide some guidance in predicting patient outcome and selecting appropriate course of treatment, a significant need exists for a specific and sensitive method for evaluating breast cancer prognosis, particularly in early-stage, lymph-node negative patients. Such a method should specifically distinguish breast cancer patients with a poor prognosis from those with a good prognosis and permit the identification of high-risk, early-stage breast cancer patients who are likely to need aggressive adjuvant therapy.
SUMMARY OF THE INVENTION
Methods and compositions for evaluating the prognosis of a cancer patient, particularly a breast cancer patient, are provided. The methods comprise detecting expression of at least one, more particularly at least two, biomarker(s) in a body sample, wherein the overexpression of a biomarker or combination of biomarkers is indicative of cancer prognosis. Overexpression of the biomarker or combination of biomarkers of the invention is indicative of either a good prognosis (i.e., disease-free survival) or a bad prognosis (i.e., cancer recurrence, metastasis, or death from the underlying cancer). Thus, the present method permits the differentiation of breast cancer patients with a good prognosis from those patients with a bad prognosis. The methods disclosed herein can be used in combination with assessment of conventional clinical factors (e.g., tumor size, tumor grade, lymph node status, and family history) and/or analysis of the expression level of molecular markers, such as Her2/neu, Ki67, p53, and estrogen and progesterone hormone receptors. In this manner, the methods of the invention permit a more accurate evaluation of breast cancer prognosis.
The biomarkers of the invention are proteins and/or genes whose overexpression is indicative of cancer prognosis, including those biomarkers involved in cell cycle regulation, DNA replication, transcription, signal transduction, cell proliferation, invasion, or metastasis. The detection of overexpression of the biomarker genes or proteins of the invention permits the evaluation of cancer prognosis and facilitates the separation of breast cancer patients into good and bad prognosis risk groups for the purposes of, for example, treatment selection.
Biomarker expression can be assessed at the protein or nucleic acid level. In some embodiments, immunohistochemistry techniques are provided that utilize antibodies to detect the expression of biomarker proteins in breast tumor samples. In this aspect of the invention, at least one antibody directed to a specific biomarker of interest is used. Expression can also be detected by nucleic acid-based techniques, including, for example, hybridization and RT-PCR.
Compositions include monoclonal antibodies capable of binding to biomarker proteins of the invention. Antigen-binding fragments and variants of these monoclonal antibodies, hybridoma cell lines producing these antibodies, and isolated nucleic acid molecules encoding the amino acid sequences of these monoclonal antibodies are also encompassed herein. Kits comprising reagents for practicing the methods of the invention are further provided.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows the distribution of percentage of cells staining with an intensity of 2 as a function of actual breast cancer outcome. Experimental details are provided in Example 4.
FIG. 2 provides the ROC curve obtained using the sequence-based interpretation approach for the SLPI/p21ras/E2F1/PSMB9/src/phospho-p27 combination. Experimental details are provided in Example 5.
FIG. 3 provides the Kaplan-Meier plot for the prognostic performance of the SLPI, src, PSMB9, p21ras, and E2F1 biomarker panel. Details are provided in Example 8.
FIG. 4 provides a graphical representation of the long-term survival data for the general breast cancer patient population, independent of analysis of biomarker overexpression. Details are provided in Example 8.
FIG. 5 provides the Kaplan-Meier plot for the prognostic performance of the SLPI, src, PSMB9, p21ras, E2F1, and MUC-1 biomarker panel. Details are provided in Example 9.
DETAILED DESCRIPTION OF THE INVENTION
The present invention provides methods and compositions for evaluating the prognosis of a cancer patient, particularly a breast cancer patient, more particularly an early-stage breast cancer patient. The methods comprise detecting the expression of biomarkers in a patient tissue or body fluid sample and determining if said biomarkers are overexpressed. Overexpression of a biomarker or combination of biomarkers used in the practice of the invention is indicative of breast cancer prognosis (i.e., bad or good prognosis). Thus, overexpression of a particular biomarker or combination of biomarkers of interest permits the differentiation of breast cancer patients that are likely to experience disease recurrence (i.e., poor prognosis) from those who are more likely to remain cancer-free (i.e., good prognosis). In some aspects of the invention, the methods involve detecting the overexpression of at least one biomarker in a breast tumor sample that is indicative of a poor breast cancer prognosis and thereby identifying patients who are more likely to suffer a recurrence of the underlying cancer. The methods of the invention can also be used to assist in selecting appropriate courses of treatment and to identify patients that would benefit from more aggressive therapy. In particular embodiments, antibodies and immunohistochemistry techniques are used to detect expression of a biomarker of interest and to evaluate the prognosis of a breast cancer patient. Monoclonal antibodies specific for biomarkers of interest and kits for practicing the methods of the invention are further provided.
By "breast cancer" is intended, for example, those conditions classified by biopsy as malignant pathology. The clinical delineation of breast cancer diagnoses is well-known in the medical arts. One of skill in the art will appreciate that breast cancer refers to any malignancy of the breast tissue, including, for example, carcinomas and sarcomas. In particular embodiments, the breast cancer is ductal carcinoma in situ (DCIS), lobular carcinoma in situ (LCIS), or mucinous carcinoma. Breast cancer also refers to infiltrating ductal (IDC) or infiltrating lobular carcinoma (ILC). In most embodiments of the invention, the subject of interest is a human patient suspected of or actually diagnosed with breast cancer.
The American Joint Committee on Cancer (AJCC) has developed a standardized system for breast cancer staging using a "TNM" classification scheme. Patients are assessed for primary tumor size (T), regional lymph node status (N), and the presence/absence of distant metastasis (M) and then classified into stages 0-IV based on this combination of factors. In this system, primary tumor size is categorized on a scale of 0-4 (T0=no evidence of primary tumor; T1=≦2 cm; T2=>2 cm-≦5 cm; T3=>5 cm; T4=tumor of any size with direct spread to chest wall or skin). Lymph node status is classified as N0-N3 (N0=regional lymph nodes are free of metastasis; N1=metastasis to movable, same-side axillary lymph node(s); N2=metastasis to same-side lymph node(s) fixed to one another or to other structures; N3=metastasis to same-side lymph nodes beneath the breastbone). Metastasis is categorized by the absence (M0) or presence of distant metastases (M1). While breast cancer patients at any clinical stage are encompassed by the present invention, breast cancer patients in early-stage breast cancer are of particular interest. By "early-stage breast cancer" is intended stages 0 (in situ breast cancer), I (T1, N0, M0), IIA (T0-1, N1, M0 or T2, N0, M0), and IIB (T2, N1, M0 or T3, N0, M0). Early-stage breast cancer patients exhibit little or no lymph node involvement. As used herein, "lymph node involvement" or "lymph node status" refers to whether the cancer has metastasized to the lymph nodes. Breast cancer patients are classified as "lymph node-positive" or "lymph node-negative" on this basis. Methods of identifying breast cancer patients and staging the disease are well known and may include manual examination, biopsy, review of patient's and/or family history, and imaging techniques, such as mammography, magnetic resonance imaging (MRI), and positron emission tomography (PET).
The term "prognosis" is recognized in the art and encompasses predictions about the likely course of disease or disease progression, particularly with respect to likelihood of disease remission, disease relapse, tumor recurrence, metastasis, and death. "Good prognosis" refers to the likelihood that a patient afflicted with cancer, particularly breast cancer, will remain disease-free (i.e., cancer-free). "Poor prognosis" is intended to mean the likelihood of a relapse or recurrence of the underlying cancer or tumor, metastasis, or death. Cancer patients classified as having a "good outcome" remain free of the underlying cancer or tumor. In contrast, "bad outcome" cancer patients experience disease relapse, tumor recurrence, metastasis, or death. In particular embodiments, the time frame for assessing prognosis and outcome is, for example, less than one year, one, two, three, four, five, six, seven, eight, nine, ten, fifteen, twenty or more years. As used herein, the relevant time for assessing prognosis or disease-free survival time begins with the surgical removal of the tumor or suppression, mitigation, or inhibition of tumor growth. Thus, for example, in particular embodiments, a "good prognosis" refers to the likelihood that a breast cancer patient will remain free of the underlying cancer or tumor for a period of at least five, more particularly, a period of at least ten years. In further aspects of the invention, a "bad prognosis" refers to the likelihood that a breast cancer patient will experience disease relapse, tumor recurrence, metastasis, or death within less than five years, more particularly less than ten years. Time frames for assessing prognosis and outcome provided above are illustrative and are not intended to be limiting.
In some embodiments described herein, prognostic performance of the biomarkers and/or other clinical parameters was assessed utilizing a Cox Proportional Hazards Model Analysis, which is a regression method for survival data that provides an estimate of the hazard ratio and its confidence interval. The Cox model is a well-recognized statistical technique for exploring the relationship between the survival of a patient and particular variables. This statistical method permits estimation of the hazard (i.e., risk) of individuals given their prognostic variables (e.g., overexpression of particular biomarkers, as described herein). Cox model data are commonly presented as Kaplan-Meier curves. The "hazard ratio" is the risk of death at any given time point for patients displaying particular prognostic variables. See generally Spruance et al. (2004) Antimicrob. Agents & Chemo. 48:2787-2792. In particular embodiments, the biomarkers of interest are statistically significant for assessment of the likelihood of breast cancer recurrence or death due to the underlying breast cancer. Methods for assessing statistical significance are well known in the art and include, for example, using a log-rank test Cox analysis and Kaplan-Meier curves. In some aspects of the invention, a p-value of less than 0.05 constitutes statistical significance.
As described herein above, a number of clinical and prognostic breast cancer factors are known in the art and are used to predict treatment outcome and the likelihood of disease recurrence. Such factors include lymph node involvement, tumor size, histologic grade, family history, estrogen and progesterone hormone receptor status, Her 2/neu levels, and tumor ploidy. As used herein, estrogen and progesterone hormone receptor status refers to whether these receptors are expressed in the breast tumor of a particular breast cancer patient. Thus, an "estrogen receptor-positive patient" displays estrogen receptor expression in a breast tumor, whereas an "estrogen receptor-negative patient" does not. Using the methods of the present invention, the prognosis of a breast cancer patient can be determined independent of or in combination with assessment of these or other clinical and prognostic factors. In some embodiments, combining the methods disclosed herein with evaluation of other prognostic factors may permit a more accurate determination of breast cancer prognosis. The methods of the invention may be coupled with analysis of, for example, Her2/neu, Ki67, and/or p53 expression levels. Other factors, such as patient clinical history, family history, and menopausal status, may also be considered when evaluating breast cancer prognosis via the methods of the invention. In some embodiments, patient data obtained via the methods disclosed herein may be coupled with analysis of clinical information and existing tests for breast cancer prognosis to develop a reference laboratory prognostic algorithm. Such algorithms find used in stratifying breast cancer patients, particularly early-stage breast cancer patients, into good and bad prognosis populations. Patients assessed as having a poor prognosis may be upstaged for more aggressive breast cancer treatment.
The methods of the invention permit the superior assessment of breast cancer prognosis in comparison to analysis of other known prognostic indicators (e.g., lymph node involvement, tumor size, histologic grade, estrogen and progesterone receptor levels, Her 2/neu status, tumor ploidy, and family history). In particular aspects of the invention, the sensitivity and specificity is equal to or greater than that of known cancer prognostic evaluation methods. The endpoint for assessing specificity and sensitivity is comparison of the prognosis or outcome predicted using the methods of the invention (i.e., at or near the time of diagnosis) with the actual clinical outcome (i.e., whether the patient remained cancer-free or suffered a recurrence within a specified time period). As used herein, "specificity" refers to the level at which a method of the invention can accurately identify true negatives. In a clinical study, specificity is calculated by dividing the number of true negatives by the sum of true negatives and false positives. By "sensitivity" is intended the level at which a method of the invention can accurately identify samples that are true positives. Sensitivity is calculated in a clinical study by dividing the number of true positives by the sum of true positives and false negatives. In some embodiments, the sensitivity of the disclosed methods for the evaluation of breast cancer is at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more. Furthermore, the specificity of the present methods is preferably at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more. In further embodiments, the combined sensitivity and specificity value for the prognostic methods of the invention is assessed. By "combined sensitivity and specificity value" is intended the sum of the individual specificity and sensitivity values, as defined herein above. The combined sensitivity and specificity value of the present methods is preferably at least about 105%, 110%, 115%, 120%, 130%, 140%, 150%, 160% or more.
As used herein, the definitions of "true" and "false" positives and negatives will be dependent upon whether the biomarker or combination of biomarkers under consideration are good outcome or bad outcome biomarkers. That is, in the case of good outcome biomarkers (i.e., those indicative of a good prognosis), "true positive" refers to those samples exhibiting overexpression of the biomarker of interest, as determined by the methods of the invention (e.g., positive staining by immunohistochemistry), that have a confirmed good actual clinical outcome. In contrast, "false positives" display overexpression of the good outcome biomarker(s) but have a confirmed bad actual clinical outcome. "True negatives" and "false negatives" with respect to good outcome biomarkers do not display biomarker overexpression (e.g., do not stain positive in immunohistochemistry methods) and have confirmed bad and good actual clinical outcomes, respectively.
Similarly, in the case of bad outcome biomarkers, "true positives" refers to those samples exhibiting overexpression of the biomarker or combination of biomarkers of interest that have a confirmed bad actual clinical outcome. That is, "true positive" with respect to both good and bad outcome biomarkers refers to samples in which the actual clinical outcome (i.e., good or bad) is accurately predicted. "False positives" display overexpression of the bad outcome biomarker but have a confirmed good actual clinical outcome. "True negatives" and "false negatives" with respect to bad outcome biomarkers do not display biomarker overexpression and have confirmed good and bad actual clinical outcomes, respectively.
Breast cancer is managed by several alternative strategies that may include, for example, surgery, radiation therapy, hormone therapy, chemotherapy, or some combination thereof. As is known in the art, treatment decisions for individual breast cancer patients can be based on the number of lymph nodes involved, estrogen and progesterone receptor status, size of the primary tumor, and stage of the disease at diagnosis. Analysis of a variety of clinical factors and clinical trials has led to the development of recommendations and treatment guidelines for early-stage breast cancer by the International Consensus Panel of the St. Gallen Conference (2001). See Goldhirsch et al. (2001) J. Clin. Oncol. 19:3817-3827, which is herein incorporated by reference in its entirety. The guidelines indicate that treatment for patients with node-negative breast cancer varies substantially according to the baseline prognosis. More aggressive treatment is recommended for patients with a relative high risk of recurrence when compared to patients with a relatively low risk of recurrence. It has been demonstrated that chemotherapy for the high risk population has resulted in a reduction in the risk of relapse. Women with a low risk category are usually treated with radiation and hormonal therapy. Stratification of patients into poor prognosis or good prognosis risk groups at the time of diagnosis using the methods disclosed herein may provide an additional or alternative treatment decision-making factor. The methods of the invention permit the differentiation of breast cancer patients with a good prognosis from those more likely to suffer a recurrence (i.e., patients who might need or benefit from additional aggressive treatment at the time of diagnosis). The methods of the invention find particular use in choosing appropriate treatment for early-stage breast cancer patients. As discussed above, the majority of breast cancer patients diagnosed at an early-stage of the disease enjoy long-term survival following surgery and/or radiation therapy without further adjuvant therapy. A significant percentage (approximately 20%) of these patients, however, will suffer disease recurrence or death, leading to clinical recommendations that some or all early-stage breast cancer patients should receive adjuvant therapy (e.g., chemotherapy). The methods of the present invention find use in identifying this high-risk, poor prognosis population of early-stage breast cancer patients and thereby determining which patients would benefit from continued and/or more aggressive therapy and close monitoring following treatment. For example, early-stage breast cancer patients assessed as having a poor prognosis by the methods disclosed herein may be selected for more aggressive adjuvant therapy, such as chemotherapy, following surgery and/or radiation treatment. In particular embodiments, the methods of the present invention may be used in conjunction with the treatment guidelines established by the St. Gallens Conference to permit physicians to make more informed breast cancer treatment decisions. The present methods for evaluating breast cancer prognosis can also be combined with other prognostic methods and molecular marker analyses known in the art (e.g., Her2/neu, Ki67, and p53 expression levels) for purposes of selecting an appropriate breast cancer treatment. Furthermore, the methods of the invention can be combined with later-developed prognostic methods and molecular marker analyses not currently known in the art.
The methods disclosed herein also find use in predicting the response of a breast cancer patient to a selected treatment. By "predicting the response of a breast cancer patient to a selected treatment" is intended assessing the likelihood that a patient will experience a positive or negative outcome with a particular treatment. As used herein, "indicative of a positive treatment outcome" refers to an increased likelihood that the patient will experience beneficial results from the selected treatment (e.g., complete or partial remission, reduced tumor size, etc.). By "indicative of a negative treatment outcome" is intended an increased likelihood that the patient will not benefit from the selected treatment with respect to the progression of the underlying breast cancer. In some aspects of the invention, the selected treatment is chemotherapy.
In certain embodiments, methods for predicting the likelihood of survival of a breast cancer patient are provided. In particular, the methods may be used predict the likelihood of long-term, disease-free survival. By "predicting the likelihood of survival of a breast cancer patient" is intended assessing the risk that a patient will die as a result of the underlying breast cancer. "Long-term, disease-free survival" is intended to mean that the patient does not die from or suffer a recurrence of the underlying breast cancer within a period of at least five years, more particularly at least ten or more years, following initial diagnosis or treatment. Such methods for predicting the likelihood of survival of a breast cancer patient comprise detecting expression of multiple biomarkers in a patient sample, wherein the likelihood of survival, particularly long-term, disease-free survival, decreases as the number of biomarkers determined to be overexpressed in the patient sample increases. For example, in one aspect of the invention, the expression of at least five biomarkers is determined, wherein overexpression of none of the biomarkers is indicative of an increased likelihood of survival, and wherein overexpression of two or more biomarkers is indicative of a decreased likelihood of survival. Likelihood of survival may be assessed in comparison to, for example, breast cancer survival statistics available in the art. In other embodiments, methods for predicting the likelihood of survival of breast cancer patient comprise determining the expression of at least six biomarkers and assessing the number of these biomarkers that are overexpressed. Biomarkers useful for these methods may be selected from, for example, E2F1, SLPI, MUC-1, src, p21ras, and PSMB9. See generally examples 8 and 9.
The biomarkers of the invention include genes and proteins. Such biomarkers include DNA comprising the entire or partial sequence of the nucleic acid sequence encoding the biomarker, or the complement of such a sequence. The biomarker nucleic acids also include RNA comprising the entire or partial sequence of any of the nucleic acid sequences of interest. A biomarker protein is a protein encoded by or corresponding to a DNA biomarker of the invention. A biomarker protein comprises the entire or partial amino acid sequence of any of the biomarker proteins or polypeptides. Fragments and variants of biomarker genes and proteins are also encompassed by the present invention. By "fragment" is intended a portion of the polynucleotide or a portion of the amino acid sequence and hence protein encoded thereby. Polynucleotides that are fragments of a biomarker nucleotide sequence generally comprise at least 10, 15, 20, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 800, 900, 1,000, 1,100, 1,200, 1,300, or 1,400 contiguous nucleotides, or up to the number of nucleotides present in a full-length biomarker polynucleotide disclosed herein. A fragment of a biomarker polynucleotide will generally encode at least 15, 25, 30, 50, 100, 150, 200, or 250 contiguous amino acids, or up to the total number of amino acids present in a full-length biomarker protein of the invention. "Variant" is intended to mean substantially similar sequences. Generally, variants of a particular biomarker of the invention will have at least about 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more sequence identity to that biomarker as determined by sequence alignment programs.
A "biomarker" is any gene or protein whose level of expression in a tissue or cell is altered compared to that of a normal or healthy cell or tissue. The biomarkers of the present invention are genes and proteins whose overexpression correlates with cancer, particularly breast cancer, prognosis. In particular embodiments, selective overexpression of a biomarker or combination of biomarkers of interest in a patient sample is indicative of a poor cancer prognosis. By "indicative of a poor prognosis" is intended that overexpression of the particular biomarker or combination of biomarkers is associated with an increased likelihood of relapse or recurrence of the underlying cancer or tumor, metastasis, or death, as defined herein above. For example, "indicative of a poor prognosis" may refer to an increased likelihood of relapse or recurrence of the underlying cancer or tumor, metastasis, or death within five years, more particularly ten years. Biomarkers that are indicative of a poor prognosis may be referred to herein as "bad outcome biomarkers." In other aspects of the invention, the absence of overexpression of a biomarker or combination of biomarkers of interest is indicative of a good prognosis. As used herein, "indicative of a good prognosis" refers to an increased likelihood that the patient will remain cancer-free, as defined herein above. In some embodiments, "indicative of a good prognosis" refers to an increased likelihood that the patient will remain cancer-free for at least five, more particularly at least ten years. Such biomarkers may be referred to as "good outcome biomarkers."
The biomarkers of the present invention include any gene or protein whose overexpression correlates with breast cancer prognosis, as described herein above. Biomarkers include genes and proteins that are indicative of a poor breast cancer prognosis (i.e., bad outcome biomarkers) as well as those that are indicative of a good prognosis (i.e., good outcome biomarkers). Biomarkers of particular interest include genes and proteins that are involved in regulation of cell growth and proliferation, cell cycle control, DNA replication and transcription, apoptosis, signal transduction, angiogenesis/lymphogenesis, or metastasis. In some embodiments, the biomarkers regulate protease systems involved in tissue remodeling, extracellular matrix degradation, and adjacent tissue invasion. Although any biomarker whose overexpression is indicative of breast cancer prognosis can be used to practice the invention, in particular embodiments, biomarkers are selected from the group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, MCM6, and p53. See Table 43. In one embodiment, the biomarkers of interest comprise SLPI, PSMB9, phospho-p27, src, E2F1, p21ras, or p53. In one aspect of the invention, the methods for evaluating breast cancer prognosis comprise detecting the expression of E2F1 and SLPI, wherein overexpression of at least one of these biomarkers is indicative of a poor prognosis. In another embodiment, the methods comprise detecting the expression of E2F1, src, and SLPI, wherein overexpression of at least two of the biomarkers is indicative of a poor breast cancer prognosis. In a further embodiment, the methods of the present invention comprise detecting the expression of E2F1, src, PSMB9, and SLPI, wherein overexpression of at least two of these biomarkers is indicative of a poor breast cancer prognosis. In other aspects of the invention, the expression of E2F1, SLPI, PSMB9, p21ras, and src is detected, and overexpression of at least two of these biomarkers is indicative of a poor prognosis. In yet another embodiment, the methods comprise detecting the expression of SLPI, p21ras, E2F1, PSMB9, phospho-p27, and src in a patient sample, wherein overexpression of at least four of these biomarkers is indicative of a poor prognosis.
In another embodiment, the biomarkers of interest comprise E2F1, SLPI, MUC-1, src, p21ras, and PSMB9. In one aspect of the invention, the methods for evaluating breast cancer prognosis comprise detecting the expression of E2F1 and SLPI, wherein overexpression of at least one of these biomarkers is indicative of a poor prognosis. In another embodiment, the methods comprise detecting the expression of E2F1, SLPI, and PSMB9, wherein overexpression of at least two of the biomarkers is indicative of a poor breast cancer prognosis. In a further embodiment, the methods of the present invention comprise detecting the expression of E2F1, SLPI, MUC-1, and src, wherein overexpression of at least two of these biomarkers is indicative of a poor breast cancer prognosis. In other aspects of the invention, the expression of E2F1, SLPI, MUC-1, src, and p21ras is detected, and overexpression of at least two of these biomarkers is indicative of a poor prognosis. In yet another embodiment, the methods comprise detecting the expression of E2F1, SLPI, MUC-1, src, p21ras, and PSMB9 in a patient sample, wherein overexpression of at least four of these biomarkers is indicative of a poor prognosis.
Secretory Leukocyte Protease Inhibitor (SLPI) is a non-specific inhibitor that can inactivate a number of proteases including leukocyte elastase, trypsin, chymotrypsin and the cathepsins (e.g., cathepsin G). SLPI is known to be involved in inflammation and the inflammatory response in relation to tissue repair. Protease inhibitors have generally been considered to counteract tumor progression and metastasis. However, expression of serine protease inhibitors (SPI's) in tumors is often associated with poor prognosis of cancer patients. Cathepsin G is over expressed in breast cancer and is an indicator of poor prognosis. Its inhibitory effect contributes to the immune response by protecting epithelial surfaces from attack by endogenous proteolytic enzymes. The gene location for SLPI is 20q12, which is a chromosomal region implicated in breast cancer chromosomal alterations and aneuploidy.
PSMB9 is a member of the proteasome B-type family, also known as the T1B family, that is a 20S core beta subunit. This gene is located in the class II region of the MHC (major histocompatibility complex). Expression of this gene is induced by gamma interferon, and this gene product replaces catalytic subunit 1 (proteasome beta 6 subunit) in the immunoproteasome. Proteolytic processing is required to generate a mature subunit.
NDRG-1 (N-Myc downstream regulated) is upregulated during cell differentiation, repressed by N-myc and c-myc in embryonic cells, and suppressed in several tumor cells. Overexpression may be related to hypoxia and the subsequent signaling to induce angiogenesis. Hypoxia causes the accumulation of the transcription factor hypoxia-inducible factor 1 (HIF-1), culminating in the expression of hypoxia-inducible genes such as those for vascular endothelial growth factor (VEGF) and NDRG-1. NDRG-1 is found in some breast cancers as an overexpressed mRNA. NDRG-1 is located on chromosome 8q24 adjacent to the c-myc gene.
MUC1 is a heavily O-glycosylated transmembrane protein expressed on most secretory epithelium, including mammary glands and some hematopoietic cells. It is expressed abundantly in lactating mammary glands and overexpressed in more than 90% of breast carcinomas and metastases. In normal mammary glands, it is expressed on the apical surface of glandular epithelium.
p27 is a key regulator of the cell cycle and participates in the G1-to-S phase progression. It interacts specifically with the cyclin E/cdk2 complex during G1 phase and also with D-type cyclin-cdks. p27 can be phosphorylated on threonine 187 by Cdks. Phosphorylation of p27 at threonine 187 is also cell-cycle dependent, present in proliferating cells but undetectable in G1 cells. Activation of p27 degradation is seen in proliferating cells and in many types of aggressive human carcinomas. Overexpression of p27 may lead to an inhibition of apoptosis and resistance to some chemotherapy.
The Src family of protein tyrosine kinases (including Src, Lyn, Fyn, Yes, Lck, Blk, Hck, etc.) is important in the regulation of growth and differentiation of eukaryotic cells. Src activity is regulated by tyrosine phosphorylation at two sites with opposing effects. Phosphorylation of Tyr416 in the activation loop of the kinase domain upregulates the enzyme. Phosphorylation of Tyr527 in the C-terminal tail by Csk renders the enzyme less active.
E2F1 is a member of a family of transcription factors involved in the regulation of both G1 and S phase cyclins, in particular cyclin D1. These proteins participate in the Rb pathway of cell-cycle regulation and control of DNA synthesis. During the G1 phase of the cell-cycle, the E2F transcription factors are bound in an inactive complex with the Rb tumor suppressor protein. During the G1/S boundary of the cell cycle, the Rb protein is hyperphosphorylated and releases the E2F transcription factor from its inhibitory complex. The E2F transcription factor then activates transcription for those genes responsible for the S-phase of the cell-cycle, predominantly resulting in initiation of DNA synthesis and preparation for mitosis and subsequent cell division. Overexpression of E2F1 has been shown to lead to the induction of apoptosis possibly through the inhibition of cyclinD1-dependent kinase activity coupled with the induction of a p 16 related transcript. In addition, regulation of E2F1 at the level of transcription, E2F1 protein levels are also controlled by the ubiquitin-proteosome dependent degradation pathway. Ubiquitination is blocked by the Rb and E2F1 complex, which directly controls aspects of cell cycle progression.
p21ras is a member of a large group of cytoplasmic proteins involved in signal transduction. Guanine nucleotide binding proteins (G proteins) comprise a large group of cytoplasmic proteins present in eukaryotic cells that are involved in signal transduction. There are two forms, the large heterotrimeric G proteins and the smaller monomers. The 3 ras oncogenes, H-ras, K-ras, and N-ras are members of the smaller monomeric G proteins and are located on chromosomes 11, 12 and 1 respectively. They encode 21-kD proteins called p21s and contain 188 amino acids. p21 ras proteins are involved in normal cell growth, protease activities, and cell adhesion.
Collectively, the three forms of p21ras function by linking ligand-mediated extracellular receptor activation with intracellular tyrosine kinase activation and subsequent initiation of a number of cellular processes relevant to breast cancer progression, including DNA replication, proliferation, and anchorage independent growth. The K- and H-ras genes are most often implicated in breast cancer. In both of these ras genes, mutations at codons 12 and 13 are common. These gain-of-function mutations result in constitutive activation that uncouples the normal ligand-induced signal transduction within the ras signaling pathways. Less common in breast cancer is the involvement of N-ras. Two mechanisms have been reported for N-ras associated changes in breast cancer: mutation at codon 61 resulting in constitutive activation of the oncogene, similar to the mutations mentioned above for K- and H-ras, and chromosomal amplification. Moreover, in addition to activation of intracellular signaling pathways, the ras oncogenes have been reported to induce overexpression of proteases important for tissue remodeling and invasion. H-ras has been implicated in matrix metalloprotease-2 (MMP-2) overexpression, and N-ras has been associated with overexpression of MMP-9. See generally Correll and Zoll (1988) Human Genetics 79:225-259; Tong et al. (1989) Nature 337:90-93; Watson et al. (1991) Breast Cancer Res. Treat. 17:161-169; Dati et al. (1991) Int. J. Cancer 47:833-838; Archer et al. (1995) Br. J. Cancer 72:1259-1266; Bland et al. (1995) Ann. Surg. 221:706-718; Shackney et al. (1998) Clin. Cancer Res. 4:913-928; and Gohring et al. (1999) Tumor Biol. 20:173-183, all of which are herein incorporated by reference in their entirety. Detection of any form (i.e., H-, K-, N-ras) of the p21ras proteins is encompassed by the present invention.
Minichromosome maintenance (MCM) proteins play an essential part in eukaryotic DNA replication. Each of the MCM proteins has DNA-dependent ATPase motifs in their highly conserved central domain. Levels of MCM proteins generally increase in a variable manner as normal cells progress from G0 into the G1/S phase of the cell cycle. In the G0 phase, MCM2 and MCM5 proteins are much less abundant than are the MCM7 and MCM3 proteins. MCM6 forms a complex with MCM2, MCM4, and MCM7, which binds histone H3. In addition, the subcomplex of MCM4, MCM6, and MCM7 has helicase activity, which is mediated by the ATP-binding activity of MCM6 and the DNA-binding activity of MCM4. See, for example, Freeman et al. (1999) Clin. Cancer Res. 5:2121-2132; Lei et al. (2001) J. Cell Sci. 114:1447-1454; Ishimi et al. (2003) Eur. J. Biochem. 270:1089-1101, all of which are herein incorporated by reference in their entirety.
DARPP32 is an inhibitor of protein phosphatase 1 whose biological function and inhibitory activity are modulated through specific amino acid residue phosphorylation within the DARPP32 protein. Threonine 34 (T34) phosphorylation renders the DARPP32 protein a specific protein phosphatase 1 inhibitor. However, threonine 75 (T75) phosphorylation renders the DARPP32 an inhibitor of protein kinase A (PKA). The gene location for DARPP32 is 17q21.2, which is known to be adjacent to the her2/neu (c-erb-B2 receptor tyrosine kinase) gene at 17q12. This region has been implicated in breast cancer chromosomal amplifications and resultant poor outcome within 25-35% of breast cancers. Several publications have demonstrated specific transcriptional activation of this 17q12-21 amplicon in breast cancer, with a number of genes located within this amplicon being overexpressed.
p53 plays multiple roles in cells. Expression of high levels of wild-type, but not mutant, p53 has two outcomes: cell cycle arrest or apoptosis. The observation that DNA-damaging agents induce levels of p53 in cells led to the definition of p53 as a checkpoint factor, akin perhaps to the product of the fad9 gene in yeast. While dispensable for viability, in response to genotoxic stress p53 acts as an "emergency brake" inducing either arrest or apoptosis, protecting the genome from accumulating excess mutations. Consistent with this notion, cells lacking p53 have been shown to be genetically unstable and, thus, more prone to tumors. The p53 protein is located in the nucleus of cells and is very labile. p53 is mutated in roughly 50% of all human tumors, predominantly in the DNA-binding domain codons.
Although the above biomarkers have been discussed in detail, any biomarker whose overexpression is indicative of breast cancer prognosis can be used to practice the invention, including biomarkers not yet identified in the art. Such biomarkers include genes and proteins that are, for example, involved in cell proliferation, cell cycle control, or the generalized mechanisms of cancer motility and invasion. Biomarkers of potential interest include cyclooxygenase-2 (cox-2), rhoC, c-myc, urokinase plasminogen activator receptor (uPAR), Wilms' tumor suppressor, akt kinase, and osteopontin. See, for example, Perou et al. (2000) Nature 406:747-752; Sorlie et al. (2001) Proc. Natl. Acad. Sci. 98:10869-10874; Van't Veer et al. (2002) Nature 415:530-536; Huang et al. (2003) Lancet 361:1590-1596, all of which are herein incorporated by reference in their entirety.
In particular embodiments, the biomarkers are kinases that are involved in signal transduction pathways, such as PI3K regulatory a, LTk, Ser/thr kinase 15, MAPK8IPI, MAPKAPK2, and PK428, PRKR. Growth factors, extracellular signal transduction proteins, and extracellular matrix proteins are also biomarkers of interest. Such proteins include EGFR, TNF receptor associated factor 4, GFR bound protein 7, ErbB2 (her 2), VEGF, GDF1, IGFBP5, EGF8 ras homolog, MMP 9, MMP 7, SLPI, keratin 5, keratin 17, laminin gamma 2 (laminin V), troponin, and tubulin.
In some aspects of the invention, the biomarkers comprise genes and proteins that are involved in chromosome condensation and maintenance, such as, for example, Cc related, HMG non-histone chromosomal 11, MMD5, MCM5, MCM6, and Swi/snf related actin. Biomarkers that are associated with centromere and centrosome function, including CENPA, CENPF, CENPE, Bub 1, polo-like kinase, and HsEg5, MCAK, and HSET, can also be used in the methods described herein. The biomarkers of the invention may also comprise transcription factors, particularly those associated with cell cycle regulation. Transcription factors of interest include but are not limited to E2F1, E2F4, NDRG-1, ORC6L, PCNA, nuclear factor 1, EZH2, and TFAP2A. Cyclins, such as CDC20, CDC 25B, cyclin A2, cyclin E, and cyclin F, may also be used to practice the disclosed methods.
Although the methods of the invention require the detection of at least one, more particularly at least two, biomarker(s) in a patient sample for evaluating breast cancer prognosis, 3, 4, 5, 6, 7, 8, 9, 10 or more biomarkers may be used to practice the present invention. It is recognized that detection of more than one biomarker in a body sample may be used to evaluate cancer, particularly breast cancer, prognosis. Therefore, in some embodiments, two or more biomarkers are used, more preferably, two or more complementary biomarkers. By "complementary" is intended that detection of the combination of biomarkers in a body sample results in the accurate determination of cancer prognosis in a greater percentage of cases than would be identified if only one of the biomarkers was used. Thus, in some cases, a more accurate determination of cancer prognosis can be made by using at least two biomarkers. Accordingly, where at least two biomarker proteins are used, at least two antibodies directed to distinct biomarker proteins will be used to practice the immunohistochemistry methods disclosed herein. The antibodies may be contacted with the body sample simultaneously or successively.
When a combination of two or more biomarkers is used, the biomarkers will typically be substantially statistically independent of one another. By "statistically independent" biomarkers is intended that the prognoses generated therefrom are independent such that one biomarker does not provide substantially repetitive information with regard to the complementary biomarker. This may ensure, for instance, that a biomarker is not used in conjunction with a first biomarker when the two are not substantially statistically independent. The dependence of the two biomarkers may indicate that they are duplicative and that the addition of a second biomarker adds no additional value to the prognostic power of a given pair of biomarkers. In order to optimize the prognostic power of a given panel of biomarkers it is also desirable to reduce the amount of signal "noise" by minimizing the use of biomarkers that provide duplicative prognostic information when compared to another biomarker in the panel. Methods for determining statistical independence are known in the art. Statistical independence of biomarkers of interest can be assessed using any method, including, for example, the methods disclosed in U.S. Application Publication No. 2006/0078926 entitled "Methods and Computer Programs for Analysis and Optimization of Marker Candidates for Cancer Prognosis," filed Sep. 22, 2005 and incorporated by reference in its entirety. Where independent, prognostic biomarkers are used to practice the present methods, the prognostic value is increased by detecting the expression of 2, 3, 4, 5, 6, 7 or more biomarkers. In such cases, any combination of independent biomarkers can be used.
One of skill in the art will also recognize that a panel of biomarkers can be used to evaluate the prognosis of a breast cancer patient in accordance with the methods of the invention. In some embodiments, a panel comprising at least two biomarkers selected from the group consisting of SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, MCM6, and p53 is provided. One particular panel of biomarkers may comprise, for example, all or a subset of E2F1, SLPI, MUC-1, src, p21ras, and PSMB9. A panel of biomarkers may comprise any number or combination of biomarkers of interest. In certain aspects of the invention, a panel comprises at least two statistically independent, prognostic biomarkers.
In particular embodiments, the methods for evaluating breast cancer prognosis comprise collecting a patient body sample, preferably a breast tissue sample, more preferably a primary breast tumor tissue sample, contacting the sample with at least one antibody specific for a biomarker of interest, detecting antibody binding, and determining if the biomarker is overexpressed. That is, samples are incubated with the biomarker antibody for a time sufficient to permit the formation of antibody-antigen complexes, and antibody binding is detected, for example, by a labeled secondary antibody. Samples that exhibit overexpression of at least one bad outcome biomarker, as determined by antibody binding, are classified as having a poor prognosis. Similarly, patient samples that display overexpression of at least one good outcome biomarker are categorized as having a good prognosis. Furthermore, the overexpression of certain combinations of biomarkers of interest is specifically used to distinguish breast cancer patients with a poor prognosis from those with a good prognosis. In some aspects of the invention, the methods comprise detecting the expression of two or more biomarkers in a patient sample and determining if said biomarkers are overexpressed, wherein overexpression of all or some subset of these biomarkers is indicative of breast cancer prognosis. For example, in one embodiment, the methods comprise detecting the expression of SLPI, p21ras, E2F1, PSMB9, phospho-p27, and src, wherein overexpression of at least four of these biomarkers is indicative of a poor prognosis. In another aspect of the invention, the methods comprise detecting the expression of SLPI, E2F1, and src, wherein overexpression of at least two of these biomarkers is indicative of a poor prognosis. In other embodiments, the methods comprise detecting the expression of E2F1, SLPI, MUC-1, src, p21ras, and PSMB9, wherein overexpression of at least four of these biomarkers is indicative of a poor prognosis. In another aspect of the invention, the methods comprise detecting the expression of SLPI, E2F1, and MUC-1, wherein overexpression of at least two of these biomarkers is indicative of a poor prognosis.
By "body sample" is intended any sampling of cells, tissues, or bodily fluids in which expression of a biomarker can be detected. Examples of such body samples include but are not limited to blood, lymph, urine, gynecological fluids, biopsies, and smears. Bodily fluids useful in the present invention include blood, urine, saliva, nipple aspirates, or any other bodily secretion or derivative thereof. Blood can include whole blood, plasma, serum, or any derivative of blood. In preferred embodiments, the body sample comprises breast cells, particularly breast tissue from a biopsy, more particularly a breast tumor tissue sample. Body samples may be obtained from a patient by a variety of techniques including, for example, by scraping or swabbing an area, by using a needle to aspirate bodily fluids, or by removing a tissue sample (i.e., biopsy). Methods for collecting various body samples are well known in the art. In some embodiments, a breast tissue sample is obtained by, for example, fine needle aspiration biopsy, core needle biopsy, or excisional biopsy. Fixative and staining solutions may be applied to the cells or tissues for preserving the specimen and for facilitating examination. Body samples, particularly breast tissue samples, may be transferred to a glass slide for viewing under magnification. In preferred embodiments, the body sample is a formalin-fixed, paraffin-embedded breast tissue sample, particularly a primary breast tumor sample.
Any methods available in the art for detecting expression of biomarkers are encompassed herein. The expression of a biomarker of the invention can be detected on a nucleic acid level or a protein level. By "detecting expression" is intended determining the quantity or presence of a biomarker gene or protein. Thus, "detecting expression" encompasses instances where a biomarker is determined not to be expressed, not to be detectably expressed, expressed at a low level, expressed at a normal level, or overexpressed. In order to determine overexpression, the body sample to be examined may be compared with a corresponding body sample that originates from a healthy person. That is, the "normal" level of expression is the level of expression of the biomarker in, for example, a breast tissue sample from a human subject or patient not afflicted with breast cancer. Such a sample can be present in standardized form. In some embodiments, determination of biomarker overexpression requires no comparison between the body sample and a corresponding body sample that originates from a healthy person. For example, detection of overexpression of a biomarker indicative of a poor prognosis in a breast tumor sample may preclude the need for comparison to a corresponding breast tissue sample that originates from a healthy person. Moreover, in some aspects of the invention, no expression, underexpression, or normal expression (i.e., the absence of overexpression) of a biomarker or combination of biomarkers of interest provides useful information regarding the prognosis of a breast cancer patient.
Methods for detecting expression of the biomarkers of the invention comprise any methods that determine the quantity or the presence of the biomarkers either at the nucleic acid or protein level. Such methods are well known in the art and include but are not limited to western blots, northern blots, southern blots, ELISA, immunoprecipitation, immunofluorescence, flow cytometry, immunohistochemistry, nucleic acid hybridization techniques, nucleic acid reverse transcription methods, and nucleic acid amplification methods. In particular embodiments, expression of a biomarker is detected on a protein level using, for example, antibodies that are directed against specific biomarker proteins. These antibodies can be used in various methods such as Western blot, ELISA, immunoprecipitation, or immunohistochemistry techniques. Likewise, immunostaining of breast tissue, particularly breast tumor tissue, can be combined with assessment of clinical information, conventional prognostic methods, and expression of molecular markers (e.g., Her2/neu, Ki67, p53, and hormone receptor status) known in the art. In this manner, the disclosed methods may permit the more accurate determination of breast cancer prognosis.
In one embodiment, antibodies specific for biomarker proteins are utilized to detect the expression of a biomarker protein in a body sample. The method comprises obtaining a body sample from a patient, contacting the body sample with at least one antibody directed to SLPI, p21ras, MUC-1, DARPP-32, phospho-p27, src, MGC 14832, myc, TGFβ-3, SERHL, E2F1, PDGFRα, NDRG-1, MCM2, PSMB9, or MCM6, and detecting antibody binding to determine if the biomarker is overexpressed in the patient sample. Overexpression of the biomarker protein is indicative of prognosis, more particularly, a bad breast cancer prognosis. In other embodiments, the methods of the invention comprise detecting the expression of at least two biomarkers, wherein overexpression of at least one of the biomarkers is indicative of prognosis. Such methods may comprise the detection of multiple biomarkers in a patient sample wherein it is the overexpression of all or a subset of these biomarkers that is indicative of breast cancer prognosis.
One aspect of the present invention provides an immunohistochemistry technique for evaluating the prognosis of a breast cancer patient. Specifically, this method comprises antibody staining of biomarkers within a breast tissue sample, more particularly a breast tumor sample, that are indicative of prognosis. One of skill in the art will recognize that the immunohistochemistry methods described herein below may be performed manually or in an automated fashion using, for example, the Autostainer Universal Staining System (Dako). One protocol for antibody staining (i.e., immunohistochemistry) of breast tissue samples is provided in Example 1.
In one immunohistochemistry method, a patient breast tissue sample is collected by, for example, biopsy techniques known in the art. Samples may be frozen for later preparation or immediately placed in a fixative solution. Tissue samples may be fixed by treatment with a reagent such as formalin, gluteraldehyde, methanol, or the like and embedded in paraffin. Methods for preparing slides for immunohistochemical analysis from formalin-fixed, paraffin-embedded tissue samples are well known in the art. In some embodiments, particularly the immunohistochemistry methods of the invention, samples may need to be modified in order to make the biomarker antigens accessible to antibody binding. For example, formalin fixation of tissue samples results in extensive cross-linking of proteins that can lead to the masking or destruction of antigen sites and, subsequently, poor antibody staining. As used herein, "antigen retrieval" or "antigen unmaksing" refers to methods for increasing antigen accessibility or recovering antigenicity in, for example, formalin-fixed, paraffin-embedded tissue samples. Any method for making antigens more accessible for antibody binding may be used in the practice of the invention, including those antigen retrieval methods known in the art. See, for example, Hanausek and Walaszek, eds. (1998) Tumor Marker Protocols (Humana Press, Inc., Totowa, N.J.); and Shi et al., eds. (2000) Antigen Retrieval Techniques: Immunohistochemistry and Molecular Morphology (Eaton Publishing, Natick, Mass.), both of which are herein incorporated by reference in their entirety.
Antigen retrieval methods include but are not limited to treatment with proteolytic enzymes (e.g., trypsin, chymoptrypsin, pepsin, pronase, etc.) or antigen retrieval solutions. Antigen retrieval solutions of interest include, for example, citrate buffer, pH 6.0 (Dako), tris buffer, pH 9.5 (Biocare), EDTA, pH 8.0 (Biocare), L.A.B. ("Liberate Antibody Binding Solution;" Polysciences), antigen retrieval Glyca solution (Biogenex), citrate buffer solution, pH 4.0 (Zymed), Dawn® detergent (Proctor & Gamble), deionized water, and 2% glacial acetic acid. In some embodiments, antigen retrieval comprises applying the antigen retrieval solution to a formalin-fixed tissue sample and then heating the sample in an oven (e.g., 60° C.), steamer (e.g., 95° C.), or pressure cooker (e.g., 120° C.) at specified temperatures for defined time periods. In other aspects of the invention, antigen retrieval may be performed at room temperature. Incubation times will vary with the particular antigen retrieval solution selected and with the incubation temperature. For example, an antigen retrieval solution may be applied to a sample for as little as 5, 10, 20, or 30 minutes or up to overnight. The design of assays to determine the appropriate antigen retrieval solution and optimal incubation times and temperatures is standard and well within the routine capabilities of those of ordinary skill in the art.
Following antigen retrieval, samples are blocked using an appropriate blocking agent, e.g., hydrogen peroxide. An antibody directed to a biomarker of interest is then incubated with the sample for a time sufficient to permit antigen-antibody binding. As noted above, one of skill in the art will appreciate that a more accurate breast cancer prognosis may be obtained in some cases by detecting overexpression of more than one biomarker in a patient sample. Therefore, in particular embodiments, at least two antibodies directed to two distinct biomarkers are used to evaluate the prognosis of a breast cancer patient. Where more than one antibody is used, these antibodies may be added to a single sample sequentially as individual antibody reagents or simultaneously as an antibody cocktail. Alternatively, each individual antibody may be added to a separate tissue section from a single patient sample, and the resulting data pooled.
Techniques for detecting antibody binding are well known in the art. Antibody binding to a biomarker of interest may be detected through the use of chemical reagents that generate a detectable signal that corresponds to the level of antibody binding and, accordingly, to the level of biomarker protein expression. For example, antibody binding can be detected through the use of a secondary antibody that is conjugated to a labeled polymer. Examples of labeled polymers include but are not limited to polymer-enzyme conjugates. The enzymes in these complexes are typically used to catalyze the deposition of a chromogen at the antigen-antibody binding site, thereby resulting in cell staining that corresponds to expression level of the biomarker of interest. Enzymes of particular interest include horseradish peroxidase (HRP) and alkaline phosphatase (AP). Commercial antibody detection systems, such as, for example the Dako Envision+ system and Biocare Medical's Mach 3 system, may be used to practice the present invention.
In one immunohistochemistry method of the invention, antibody binding to a biomarker is detected through the use of an HRP-labeled polymer that is conjugated to a secondary antibody. Slides are stained for antibody binding using the chromogen 3,3-diaminobenzidine (DAB) and then counterstained with hematoxylin and, optionally, a bluing agent such as ammonium hydroxide. In some aspects of the invention, slides are reviewed microscopically by a pathologist to assess cell staining (i.e., biomarker overexpression) and to evaluate breast cancer prognosis. Alternatively, samples may be reviewed via automated microscopy or by personnel with the assistance of computer software that facilitates the identification of positive staining cells.
The terms "antibody" and "antibodies" broadly encompass naturally occurring forms of antibodies and recombinant antibodies such as single-chain antibodies, chimeric and humanized antibodies and multi-specific antibodies as well as fragments and derivatives of all of the foregoing, which fragments and derivatives have at least an antigenic binding site. Antibody derivatives may comprise a protein or chemical moiety conjugated to the antibody.
"Antibodies" and "immunoglobulins" (Igs) are glycoproteins having the same structural characteristics. While antibodies exhibit binding specificity to an antigen, immunoglobulins include both antibodies and other antibody-like molecules that lack antigen specificity. Polypeptides of the latter kind are, for example, produced at low levels by the lymph system and at increased levels by myelomas.
The term "antibody" is used in the broadest sense and covers fully assembled antibodies, antibody fragments that can bind antigen (e.g., Fab', F'(ab)2, Fv, single chain antibodies, diabodies), and recombinant peptides comprising the foregoing.
The term "monoclonal antibody" as used herein refers to an antibody obtained from a population of substantially homogeneous antibodies, i.e., the individual antibodies comprising the population are identical except for possible naturally-occurring mutations that may be present in minor amounts.
"Antibody fragments" comprise a portion of an intact antibody, preferably the antigen-binding or variable region of the intact antibody. Examples of antibody fragments include Fab, Fab', F(ab')2, and Fv fragments; diabodies; linear antibodies (Zapata et al. (1995) Protein Eng. 8(10):1057-1062); single-chain antibody molecules; and multispecific antibodies formed from antibody fragments. Papain digestion of antibodies produces two identical antigen-binding fragments, called "Fab" fragments, each with a single antigen-binding site, and a residual "Fc" fragment, whose name reflects its ability to crystallize 35 readily. Pepsin treatment yields an F(ab')2 fragment that has two antigen-combining sites and is still capable of cross-linking antigen.
"Fv" is the minimum antibody fragment that contains a complete antigen recognition and binding site. In a two-chain Fv species, this region consists of a dimer of one heavy- and one light-chain variable domain in tight, non-covalent association. In a single-chain Fv species, one heavy- and one light-chain variable domain can be covalently linked by flexible peptide linker such that the light and heavy chains can associate in a "dimeric" structure analogous to that in a two-chain Fv species. It is in this configuration that the three CDRs of each variable domain interact to define an antigen-binding site on the surface of the VH-VL dimer. Collectively, the six CDRs confer antigen-binding specificity to the antibody. However, even a single variable domain (or half of an Fv comprising only three CDRs specific for an antigen) has the ability to recognize and bind antigen, although at a lower affinity than the entire binding site.
The Fab fragment also contains the constant domain of the light chain and the first constant domain (CH1) of the heavy chain. Fab fragments differ from Fab' fragments by the addition of a few residues at the carboxy terminus of the heavy-chain CH1 domain including one or more cysteines from the antibody hinge region. Fab'-SH is the designation herein for Fab' in which the cysteine residue(s) of the constant domains bear a free thiol group. F(ab')2 antibody fragments originally were produced as pairs of Fab' fragments that have hinge cysteines between them.
Monoclonal antibodies can be prepared using the method of Kohler et al. (1975) Nature 256:495-496, or a modification thereof. Typically, a mouse is immunized with a solution containing an antigen. Immunization can be performed by mixing or emulsifying the antigen-containing solution in saline, preferably in an adjuvant such as Freund's complete adjuvant, and injecting the mixture or emulsion parenterally. Any method of immunization known in the art may be used to obtain the monoclonal antibodies of the invention. After immunization of the animal, the spleen (and optionally, several large lymph nodes) are removed and dissociated into single cells. The spleen cells may be screened by applying a cell suspension to a plate or well coated with the antigen of interest. The B cells expressing membrane bound immunoglobulin specific for the antigen bind to the plate and are not rinsed away. Resulting B cells, or all dissociated spleen cells, are then induced to fuse with myeloma cells to form hybridomas, and are cultured in a selective medium. The resulting cells are plated by serial dilution and are assayed for the production of antibodies that specifically bind the antigen of interest (and that do not bind to unrelated antigens). The selected monoclonal antibody (mAb)-secreting hybridomas are then cultured either in vitro (e.g., in tissue culture bottles or hollow fiber reactors), or in vivo (as ascites in mice).
As an alternative to the use of hybridomas, antibody can be produced in a cell line such as a CHO cell line, as disclosed in U.S. Pat. Nos. 5,545,403; 5,545,405; and 5,998,144; incorporated herein by reference. Briefly the cell line is transfected with vectors capable of expressing a light chain and a heavy chain, respectively. By transfecting the two proteins on separate vectors, chimeric antibodies can be produced. Another advantage is the correct glycosylation of the antibody. A monoclonal antibody can also be identified and isolated by screening a recombinant combinatorial immunoglobulin library (e.g., an antibody phage display library) with a biomarker protein to thereby isolate immunoglobulin library members that bind the biomarker protein. Kits for generating and screening phage display libraries are commercially available (e.g., the Pharmacia Recombinant Phage Antibody System, Catalog No. 27-9400-01; and the Stratagene SurfZAP θ Phage Display Kit, Catalog No. 240612). Additionally, examples of methods and reagents particularly amenable for use in generating and screening antibody display library can be found in, for example, U.S. Pat. No. 5,223,409; PCT Publication Nos. WO 92/18619; WO 91/17271; WO 92/20791; WO 92/15679; 93/01288; WO 92/01047; 92/09690; and 90/02809; Fuchs et al. (1991) Bio/Technology 9:1370-1372; Hay et al. (1992) Hum. Antibod. Hybridomas 3:81-85; Huse et al. (1989) Science 246:1275-1281; Griffiths et al. (1993) EMBO J. 12:725-734.
Polyclonal antibodies can be prepared by immunizing a suitable subject (e.g., rabbit, goat, mouse, or other mammal) with a biomarker protein immunogen. The antibody titer in the immunized subject can be monitored over time by standard techniques, such as with an enzyme linked immunosorbent assay (ELISA) using immobilized biomarker protein. At an appropriate time after immunization, e.g., when the antibody titers are highest, antibody-producing cells can be obtained from the subject and used to prepare monoclonal antibodies by standard techniques, such as the hybridoma technique originally described by Kohler and Milstein (1975) Nature 256:495-497, the human B cell hybridoma technique (Kozbor et al. (1983) Immunol. Today 4:72), the EBV-hybridoma technique (Cole et al. (1985) in Monoclonal Antibodies and Cancer Therapy, ed. Reisfeld and Sell (Alan R. Liss, Inc., New York, N.Y.), pp. 77-96) or trioma techniques. The technology for producing hybridomas is well known (see generally Coligan et al., eds. (1994) Current Protocols in Immunology (John Wiley & Sons, Inc., New York, N.Y.); Galfre et al. (1977) Nature 266:55052; Kenneth (1980) in Monoclonal Antibodies: A New Dimension In Biological Analyses (Plenum Publishing Corp., NY; and Lerner (1981) Yale J. Biol. Med., 54:387-402).
The compositions of the invention further comprise monoclonal antibodies and variants and fragments thereof that specifically bind to biomarker proteins of interest. For example, monoclonal antibodies specific for SLPI (designated clone 5G6.24), DARPP-32 (8G11.20), MGC 14832 (1F3.9 and 2D1.14), NDRG-1 (10A9.34), PSMB9 (3A2.4), and MUC-1 (16E3.3) are provided. The monoclonal antibodies may be labeled with a detectable substance as described below to facilitate biomarker protein detection in the sample. Such antibodies find use in practicing the methods of the invention. Monoclonal antibodies having the binding characteristics of the antibodies disclosed herein are also encompassed by the present invention. Compositions further comprise antigen-binding variants and fragments of the monoclonal antibodies, hybridoma cell lines producing these antibodies, and isolated nucleic acid molecules encoding the amino acid sequences of these monoclonal antibodies.
Antibodies having the binding characteristics of a monoclonal antibody of the invention are also provided. "Binding characteristics" or "binding specificity" when used in reference to an antibody means that the antibody recognizes the same or similar antigenic epitope as a comparison antibody. Examples of such antibodies include, for example, an antibody that competes with a monoclonal antibody of the invention in a competitive binding assay. One of skill in the art could determine whether an antibody competitively interferes with another antibody using standard methods.
By "epitope" is intended the part of an antigenic molecule to which an antibody is produced and to which the antibody will bind. Epitopes can comprise linear amino acid residues (i.e., residues within the epitope are arranged sequentially one after another in a linear fashion), nonlinear amino acid residues (referred to herein as "nonlinear epitopes"; these epitopes are not arranged sequentially), or both linear and nonlinear amino acid residues. Typically epitopes are short amino acid sequences, e.g. about five amino acids in length. Systematic techniques for identifying epitopes are known in the art and are described, for example, in U.S. Pat. No. 4,708,871. Briefly, a set of overlapping oligopeptides derived from the antigen may be synthesized and bound to a solid phase array of pins, with a unique oligopeptide on each pin. The array of pins may comprise a 96-well microtiter plate, permitting one to assay all 96 oligopeptides simultaneously, e.g., for binding to a biomarker-specific monoclonal antibody. Alternatively, phage display peptide library kits (New England BioLabs) are currently commercially available for epitope mapping. Using these methods, the binding affinity for every possible subset of consecutive amino acids may be determined in order to identify the epitope that a given antibody binds. Epitopes may also be identified by inference when epitope length peptide sequences are used to immunize animals from which antibodies are obtained.
Antigen-binding fragments and variants of the monoclonal antibodies disclosed herein are further provided. Such variants will retain the desired binding properties of the parent antibody. Methods for making antibody fragments and variants are generally available in the art. For example, amino acid sequence variants of a monoclonal antibody described herein, can be prepared by mutations in the cloned DNA sequence encoding the antibody of interest. Methods for mutagenesis and nucleotide sequence alterations are well known in the art. See, for example, Walker and Gaastra, eds. (1983) Techniques in Molecular Biology (MacMillan Publishing Company, New York); Kunkel (1985) Proc. Natl. Acad. Sci. USA 82:488-492; Kunkel et al. (1987) Methods Enzymol. 154:367-382; Sambrook et al. (1989) Molecular Cloning: A Laboratory Manual (Cold Spring Harbor, N.Y.); U.S. Pat. No. 4,873,192; and the references cited therein; herein incorporated by reference. Guidance as to appropriate amino acid substitutions that do not affect biological activity of the polypeptide of interest may be found in the model of Dayhoff et al. (1978) in Atlas of Protein Sequence and Structure (Natl. Biomed. Res. Found., Washington, D.C.), herein incorporated by reference. Conservative substitutions, such as exchanging one amino acid with another having similar properties, may be preferred. Examples of conservative substitutions include, but are not limited to, GlyAla, ValIleLeu, AspGlu, LysArg, AsnGln, and PheTrpTyr.
In constructing variants of the antibody polypeptide of interest, modifications are made such that variants continue to possess the desired activity, i.e., similar binding affinity to the biomarker. Obviously, any mutations made in the DNA encoding the variant polypeptide must not place the sequence out of reading frame and preferably will not create complementary regions that could produce secondary mRNA structure. See EP Patent Application Publication No. 75,444.
Preferably, variants of a reference biomarker antibody have amino acid sequences that have at least 70% or 75% sequence identity, preferably at least 80% or 85% sequence identity, more preferably at least 90%, 91%, 92%, 93%, 94% or 95% sequence identity to the amino acid sequence for the reference antibody molecule, or to a shorter portion of the reference antibody molecule. More preferably, the molecules share at least 96%, 97%, 98% or 99% sequence identity. For purposes of the present invention, percent sequence identity is determined using the Smith-Waterman homology search algorithm using an affine gap search with a gap open penalty of 12 and a gap extension penalty of 2, BLOSUM matrix of 62. The Smith-Waterman homology search algorithm is taught in Smith and Waterman (1981) Adv. Appl. Math. 2:482-489. A variant may, for example, differ from the reference antibody by as few as 1 to 15 amino acid residues, as few as 1 to 10 amino acid residues, such as 6-10, as few as 5, as few as 4, 3, 2, or even 1 amino acid residue.
With respect to optimal alignment of two amino acid sequences, the contiguous segment of the variant amino acid sequence may have additional amino acid residues or deleted amino acid residues with respect to the reference amino acid sequence. The contiguous segment used for comparison to the reference amino acid sequence will include at least 20 contiguous amino acid residues, and may be 30, 40, 50, or more amino acid residues. Corrections for sequence identity associated with conservative residue substitutions or gaps can be made (see Smith-Waterman homology search algorithm).
The antibodies used to practice the invention are selected to have specificity for the biomarker proteins of interest. Methods for making antibodies and for selecting appropriate antibodies are known in the art. See, for example, Celis, ed. (in press) Cell Biology & Laboratory Handbook, 3rd edition (Academic Press, New York), which is herein incorporated in its entirety by reference. In some embodiments, commercial antibodies directed to specific biomarker proteins may be used to practice the invention. The antibodies of the invention may be selected on the basis of desirable staining of histological samples. That is, in preferred embodiments the antibodies are selected with the end sample type (e.g., formalin-fixed, paraffin-embedded breast tumor tissue samples) in mind and for binding specificity.
In some aspects of the invention, antibodies directed to specific biomarkers of interest are selected and purified via a multi-step screening process. In particular embodiments, polydomas are screened to identify biomarker-specific antibodies that possess the desired traits of specificity and sensitivity. As used herein, "polydoma" refers to multiple hybridomas. The polydomas of the invention are typically provided in multi-well tissue culture plates. In the initial antibody screening step, a set of individual slides or tumor tissue microarrays comprising normal (i.e., non-cancerous) breast tissue and stage I, II, III, and IV breast tumor samples is used. Methods and equipment, such as the Chemicon® Advanced Tissue Arrayer, for generating arrays of multiple tissues on a single slide are known in the art. See, for example, U.S. Pat. No. 4,820,504. Undiluted supernatants from each well containing a polydoma are assayed for positive staining using standard immunohistochemistry techniques. At this initial screening step, background, non-specific binding is essentially ignored. Polydomas producing positive staining are selected and used in the second phase of antibody screening.
In the second screening step, the positive polydomas are subjected to a limiting dilution process. The resulting unscreened antibodies are assayed via standard immunohistochemistry techniques for positive staining of breast tumor tissue samples with known 5-year outcomes. To do this, tissue microarrays comprising normal breast tissue, early-stage breast tumor samples with known good 5-year outcomes, early-stage breast tumor samples with known bad 5-year outcomes, normal non-breast tissue, and cancerous non-breast tissue are generated. At this stage, background staining is relevant, and the candidate polydomas that stain positive for abnormal cells (i.e., cancer cells) only are selected for further analysis to identify antibodies that differentiate good and bad outcome patient samples.
Positive-staining cultures are prepared as individual clones in order to select individual candidate monoclonal antibodies. Methods for isolating individual clones and for purifying antibodies through affinity adsorption chromatography are well known in the art. Individual clones are further analyzed to determine the optimized antigen retrieval conditions and working dilution.
One of skill in the art will recognize that optimization of staining reagents and conditions, for example, antibody titer and detection chemistry parameters, is needed to maximize the signal to noise ratio for a particular antibody. Antibody concentrations that maximize specific binding to the biomarkers of the invention and minimize non-specific binding (or "background") will be determined. In particular embodiments, appropriate antibody titers are determined by initially testing various antibody dilutions on formalin-fixed, paraffin-embedded normal and cancerous breast tissue samples. The design of assays to optimize antibody titer and detection conditions is standard and well within the routine capabilities of those of ordinary skill in the art. Some antibodies require additional optimization to reduce background staining and/or to increase specificity and sensitivity of staining.
Furthermore, one of skill in the art will recognize that the concentration of a particular antibody used to practice the methods of the invention will vary depending on such factors as time for binding, level of specificity of the antibody for the biomarker protein, and method of body sample preparation. Moreover, when multiple antibodies are used in a single sample, the required concentration may be affected by the order in which the antibodies are applied to the sample, i.e., simultaneously as a cocktail or sequentially as individual antibody reagents. Furthermore, the detection chemistry used to visualize antibody binding to a biomarker of interest must also be optimized to produce the desired signal to noise ratio. One example of optimization of staining reagents and conditions for immunohistochemistry is described in Example 6.
Detection of antibody binding can be facilitated by coupling the antibody to a detectable substance. Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, P-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin; and examples of suitable radioactive material include 125I, 131I, 35S, or 3H.
In regard to detection of antibody staining in the immunohistochemistry methods of the invention, there also exist in the art, video-microscopy and software methods for the quantitative determination of an amount of multiple molecular species (e.g., biomarker proteins) in a biological sample wherein each molecular species present is indicated by a representative dye marker having a specific color. Such methods are also known in the art as a calorimetric analysis methods. In these methods, video-microscopy is used to provide an image of the biological sample after it has been stained to visually indicate the presence of a particular biomarker of interest. Some of these methods, such as those disclosed in U.S. patent application Ser. No. 09/957,446 to Marcelpoil et al. and U.S. patent application Ser. No. 10/057,729 to Marcelpoil et al., incorporated herein by reference, disclose the use of an imaging system and associated software to determine the relative amounts of each molecular species present based on the presence of representative color dye markers as indicated by those color dye markers' optical density or transmittance value, respectively, as determined by an imaging system and associated software. These techniques provide quantitative determinations of the relative amounts of each molecular species in a stained biological sample using a single video image that is "deconstructed" into its component color parts.
The methods of the invention can be used in conjunction with imaging systems and associated imaging software for the detection of biomarker expression. Biomarkers for use in the methods of the invention can be selected based on methods and computer programs such as those disclosed in U.S. Patent Application Publication No. 2006/0078926 entitled "Methods and Computer Programs for Analysis and Optimization of Marker Candidates for Cancer Prognosis," filed Sep. 22, 2005, and incorporated by reference in its entirety. The methods disclosed therein can be used to develop algorithms for evaluating breast cancer prognosis.
In other embodiments, the expression of a biomarker of interest is detected at the nucleic acid level. Nucleic acid-based techniques for assessing expression are well known in the art and include, for example, determining the level of biomarker mRNA in a body sample. Many expression detection methods use isolated RNA. Any RNA isolation technique that does not select against the isolation of mRNA can be utilized for the purification of RNA (see, e.g., Ausubel et al., ed., Current Protocols in Molecular Biology, John Wiley & Sons, New York 1987-1999). Additionally, large numbers of tissue samples can readily be processed using techniques well known to those of skill in the art, such as, for example, the single-step RNA isolation process of Chomczynski (1989, U.S. Pat. No. 4,843,155).
The term "probe" refers to any molecule that is capable of selectively binding to a specifically intended target biomolecule, for example, a nucleotide transcript or a protein encoded by or corresponding to a biomarker. Probes can be synthesized by one of skill in the art, or derived from appropriate biological preparations. Probes may be specifically designed to be labeled. Examples of molecules that can be utilized as probes include, but are not limited to, RNA, DNA, proteins, antibodies, and organic molecules.
Isolated mRNA can be used in hybridization or amplification assays that include, but are not limited to, Southern or Northern analyses, polymerase chain reaction analyses and probe arrays. One method for the detection of mRNA levels involves contacting the isolated mRNA with a nucleic acid molecule (probe) that can hybridize to the mRNA encoded by the gene being detected. The nucleic acid probe can be, for example, a full-length cDNA, or a portion thereof, such as an oligonucleotide of at least 7, 15, 30, 50, 100, 250 or 500 nucleotides in length and sufficient to specifically hybridize under stringent conditions to an mRNA or genomic DNA encoding a biomarker of the present invention. Hybridization of an mRNA with the probe indicates that the biomarker in question is being expressed.
In one embodiment, the mRNA is immobilized on a solid surface and contacted with a probe, for example by running the isolated mRNA on an agarose gel and transferring the mRNA from the gel to a membrane, such as nitrocellulose. In an alternative embodiment, the probe(s) are immobilized on a solid surface and the mRNA is contacted with the probe(s), for example, in an Affymetrix gene chip array. A skilled artisan can readily adapt known mRNA detection methods for use in detecting the level of mRNA encoded by the biomarkers of the present invention.
An alternative method for determining the level of biomarker mRNA in a sample involves the process of nucleic acid amplification, e.g., by RT-PCR (the experimental embodiment set forth in Mullis, 1987, U.S. Pat. No. 4,683,202), ligase chain reaction (Barany, 1991, Proc. Natl. Acad. Sci. USA, 88:189-193), self sustained sequence replication (Guatelli et al., 1990, Proc. Natl. Acad. Sci. USA 87:1874-1878), transcriptional amplification system (Kwoh et al., 1989, Proc. Natl. Acad. Sci. USA 86:1173-1177), Q-Beta Replicase (Lizardi et al., 1988, Bio/Technology 6:1197), rolling circle replication (Lizardi et al., U.S. Pat. No. 5,854,033) or any other nucleic acid amplification method, followed by the detection of the amplified molecules using techniques well known to those of skill in the art. These detection schemes are especially useful for the detection of nucleic acid molecules if such molecules are present in very low numbers. In particular aspects of the invention, biomarker expression is assessed by quantitative fluorogenic RT-PCR (i.e., the TaqMan® System).
Biomarker expression levels of RNA may be monitored using a membrane blot (such as used in hybridization analysis such as Northern, Southern, dot, and the like), or microwells, sample tubes, gels, beads or fibers (or any solid support comprising bound nucleic acids). See U.S. Pat. Nos. 5,770,722, 5,874,219, 5,744,305, 5,677,195 and 5,445,934, which are incorporated herein by reference. The detection of biomarker expression may also comprise using nucleic acid probes in solution.
In one embodiment of the invention, microarrays are used to detect biomarker expression. Microarrays are particularly well suited for this purpose because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the expression levels of large numbers of genes. Each array consists of a reproducible pattern of capture probes attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then detected by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative value representing relative gene expression levels. See, U.S. Pat. Nos. 6,040,138, 5,800,992 and 6,020,135, 6,033,860, and 6,344,316, which are incorporated herein by reference. High-density oligonucleotide arrays are particularly useful for determining the gene expression profile for a large number of RNA's in a sample.
Techniques for the synthesis of these arrays using mechanical synthesis methods are described in, e.g., U.S. Pat. No. 5,384,261, incorporated herein by reference in its entirety for all purposes. Although a planar array surface is preferred, the array may be fabricated on a surface of virtually any shape or even a multiplicity of surfaces. Arrays may be peptides or nucleic acids on beads, gels, polymeric surfaces, fibers such as fiber optics, glass or any other appropriate substrate, see U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992, each of which is hereby incorporated in its entirety for all purposes. Arrays may be packaged in such a manner as to allow for diagnostics or other manipulation of an all-inclusive device. See, for example, U.S. Pat. Nos. 5,856,174 and 5,922,591 herein incorporated by reference.
In one approach, total mRNA isolated from the sample is converted to labeled cRNA and then hybridized to an oligonucleotide array. Each sample is hybridized to a separate array. Relative transcript levels may be calculated by reference to appropriate controls present on the array and in the sample.
Kits for practicing the methods of the invention are further provided. By "kit" is intended any manufacture (e.g., a package or a container) comprising at least one reagent, e.g. an antibody, a nucleic acid probe, etc. for specifically detecting the expression of a biomarker of the invention. The kit may be promoted, distributed, or sold as a unit for performing the methods of the present invention. Additionally, the kits may contain a package insert describing the kit and methods for its use.
In particular embodiments, kits for practicing the immunohistochemistry methods of the invention are provided. Such kits are compatible with both manual and automated immunohistochemistry techniques (e.g., cell staining) as described herein below in Example 1. These kits comprise at least one antibody directed to a biomarker protein of interest. Chemicals for the detection of antibody binding to the biomarker, a counterstain, and a bluing agent to facilitate identification of positive staining cells are optionally provided. Alternatively, the immunochemistry kits of the present invention are used in conjunction with commercial antibody binding detection systems, such as, for example the Dako Envision+system and Biocare Medical's Mach 3 system. Any chemicals that detect antigen-antibody binding may be used in the practice of the invention. In some embodiments, the detection chemicals comprise a labeled polymer conjugated to a secondary antibody. For example, a secondary antibody that is conjugated to an enzyme that catalyzes the deposition of a chromogen at the antigen-antibody binding site may be provided. Such enzymes and techniques for using them in the detection of antibody binding are well known in the art. In one embodiment, the kit comprises a secondary antibody that is conjugated to an HRP-labeled polymer. Chromogens compatible with the conjugated enzyme (e.g., DAB in the case of an HRP-labeled secondary antibody) and solutions, such as hydrogen peroxide, for blocking non-specific staining may be further provided. The kits of the present invention may also comprise a counterstain, such as, for example, hematoxylin. A bluing agent (e.g., ammonium hydroxide) may be further provided in the kit to facilitate detection of positive staining cells.
In another embodiment, the immunohistochemistry kits of the invention comprise at least two reagents, e.g., antibodies, for specifically detecting the expression of at least two distinct biomarkers. Each antibody may be provided in the kit as an individual reagent or, alternatively, as an antibody cocktail comprising all of the antibodies directed to the different biomarkers of interest. Furthermore, any or all of the kit reagents may be provided within containers that protect them from the external environment, such as in sealed containers. Positive and/or negative controls may be included in the kits to validate the activity and correct usage of reagents employed in accordance with the invention. Controls may include samples, such as tissue sections, cells fixed on glass slides, etc., known to be either positive or negative for the presence of the biomarker of interest. The design and use of controls is standard and well within the routine capabilities of those of ordinary skill in the art.
In other embodiments, kits for evaluating the prognosis of a breast cancer patient comprising detecting biomarker overexpression at the nucleic acid level are further provided. Such kits comprise, for example, at least one nucleic acid probe that specifically binds to a biomarker nucleic acid or fragment thereof. In particular embodiments, the kits comprise at least two nucleic acid probes that hybridize with distinct biomarker nucleic acids.
One of skill in the art will appreciate that any or all steps in the methods of the invention could be implemented by personnel or, alternatively, performed in an automated fashion. Thus, the steps of body sample preparation, sample staining, and detection of biomarker expression may be automated. Moreover, in some embodiments, the immunohistochemical methods of the invention are used in conjunction with computerized imaging equipment and software to facilitate the identification of positive-staining cells by a pathologist. The methods disclosed herein can also be combined with other prognostic methods or analyses (e.g., tumor size, lymph node status, expression levels of Her2/neu, Ki67, and p53). In this manner detection of overexpression of the biomarkers of the invention can permit a more accurate determination of the prognosis of a breast cancer patient.
The article "a" and "an" are used herein to refer to one or more than one (i.e., to at least one) of the grammatical object of the article. By way of example, "an element" means one or more element.
Throughout the specification the word "comprising," or variations such as "comprises" or "comprising," will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.
The following examples are offered by way of illustration and not by way of limitation:
Detection of Biomarker Overexpression Using Immunohistochemistry
4 μM sections of formalin-fixed, paraffin-embedded breast tumor tissue samples are cut using a microtome and placed on SuperFrost+ slides (VWR). The slides are baked in a forced air oven for 20 minutes and then contacted with a Histo-Orienter until the paraffin melts. Slides are washed three times with xylene for 5 minutes to remove paraffin and then rinsed three times in absolute alcohol at 2 minutes/rinse.
Pretreatment and Antigen Retrieval
To prevent non-specific background staining, the slides are incubated in a hydrogen peroxide/methanol block for five minutes at room temperature. Slides are then rinsed thoroughly with several changes of dH2O.
In order to make the antigens accessible to antibody binding, slides are incubated in an antigen retrieval solution in a pressure cooker for 5 minutes. Slides are allowed to cool to room temperature for 20 minutes on the bench, and the citrate buffer is gradually replaced with dH2O, tris buffered saline (TBS), or phosphate buffered saline (PBS) by successive dilutions. The slides are then rinsed three times in TBS at 2 minutes per rinse. To break the surface tension, 750 μl/50 ml of 1% BSA/TBS is added to each slide.
To prevent non-specific background staining, slides are not permitted to dry out during the staining procedure. Slides that have been subjected to antigen retrieval are loaded into a humidity chamber filled with water moistened paper towels. A SLPI antibody (clone 5G6.24; 1:100 dilution) is applied to the slide in a volume sufficient to completely cover the tissue section for 1 hour at room temperature. Following incubation with the primary antibody, the slides are rinsed three times in TBS at 2 minutes per wash. 750 μl/50 ml of 1% BSA/TBS is added to the final wash.
The Dako Envision+ HRP-labeled polymer secondary antibody is applied to the slide for 30 minutes at room temperature, followed by a TBS rinse. The HRP substrate chromogen DAB is applied for 10 minutes, and then the slides are rinsed for 5 minutes with water. Each slide is counterstained with hematoxylin for 5 seconds and then rinsed with water until clear. Following counterstaining, the slides are "blued" by soaking in ammonia water for 10 seconds and then rinsed with water for 1 minute.
Samples are dehydrated by immersing the slides in 95% ethanol for 1 minute and then in absolute ethanol for an additional minute. Slides are cleared by rinsing 3 times in xylene for 1 minute per rinse. Slides are then coverslipped with permanent mounting media and incubated at 35° C. to dry. Biomarker staining is visualized using a bright-field microscope. Scoring is performed by a board certified pathologist in a blind manner.
The Dako Autostainer Universal Staining system is programmed according to the manufacturer's instructions, and the necessary staining and counterstaining reagents described above for manual immunohistochemistry are loaded onto the machine. The prepared slides are loaded onto the Autostainer, and the program is run. At the end of the run, the slides are removed and rinsed in water for 5 minutes. The slides are dehydrated, cleared, coverslipped, and analyzed as described above.
Detection of Overexpression of Individual Biomarkers in Clinical Samples
Approximately 130 breast tumor tissue samples from patients at various disease stages were collected. The average patient age was 77. Actual clinical outcome data for each patient was known, and each patient was categorized as having a good or bad outcome. In this study, good outcome was defined as remaining cancer-free for at least 5 years; bad outcome was defined as suffering disease relapse, recurrence, or death within 5 years. The following table indicates the number of samples within each diagnosis group analyzed, as well as actual clinical outcome data.
TABLE-US-00001 TABLE 1 Clinical Samples Analyzed Stage Good Outcome Bad Outcome Total T1N0 50 13 63 T1N1 6 4 10 T2N0 26 19 45 T2N1 9 7 16 T3N0 0 3 3 T3N1 0 1 1 Lymph Node Status Good Outcome Bad Outcome N0 76 35 N1 15 12
The samples were analyzed by the automated immunohistochemistry described in Example 1 to identify biomarkers whose overexpression is indicative of a bad cancer prognosis. That is, the goal of this clinical study was to identify biomarkers that can distinguish good and bad outcome patient samples. Antibodies were used to detect the overexpression of eight biomarkers of interest: SLPI, PSMB9, NDRG-1, E2F1, p21ras, MUC-1, phospho-p27, and src. For quality control purposes, samples were also analyzed for ER, PR, p53, Ki67, and Her2/neu expression.
Commercial antibodies or monoclonal antibodies, identified by polydoma screening as described herein, directed to the biomarkers of interest were diluted as indicated in Table 2 and used to detect biomarker overexpression. The antigen retrieval conditions for each biomarker are also listed below.
TABLE-US-00002 TABLE 2 Antibody Dilutions and Antigen Retrieval Conditions Biomarker Antibody (Dilution) Antigen Retrieval Conditions SLPI Clone 5G6.24 (1:100) Citrate buffer, pH 6.0/pressure cooker PSMB9 Clone 3A2.4 (1:500) Citrate buffer, pH 4.0/steamer NDRG-1 Zymed (1:200) Citrate buffer, pH 4.0/steamer E2F1 Calbiochem (1:50) Tris, pH 9.5/pressure cooker p21ras Dako (1:50) Citrate buffer, pH 4.0/steamer MUC-1 Clone 16E3.3 (1:400) Citrate buffer, pH 4.0/steamer phospho-p27 Zymed (1:100) EDTA, pH 8.0/steamer src Upstate (1:50) Citrate buffer, pH 4.0/steamer
Interpretation of Slides
Each slide was reviewed and scored by a board certified pathologist that was unaware of the actual clinical patient outcomes. Samples were scored for biomarker staining intensity on a scale of 0-3. See, for example, Hanausek and Walaszek, eds. (1998) Tumor Marker Protocols (Humana Press, Inc., Totowa, N.J.); and Shi et al, eds. (2000) Antigen Retrieval Techniques: Immunohistochemistry and Molecular Morphology (Eaton Publishing, Natick, Mass.), both of which are herein incorporated by reference in their entirety. For each biomarker, a threshold staining intensity was established. Samples exhibiting a staining intensity of less than this threshold value for a particular biomarker were deemed negative for that biomarker. The staining intensity threshold values for the biomarkers of interest were as follows:
The staining intensity results were compared with the known actual clinical outcome data available for each patient, and each slide was then given a final result of true positive (TP), true negative (TN), false positive (FP), false negative (FN), according to the parameters described below. Sensitivity and specificity values for each biomarker were calculated.
TABLE-US-00003 TABLE 3 Slide Classification for Bad Outcome Biomarkers Biomarker Staining Actual Clinical Outcome* True Positive Positive Bad outcome True Negative Negative Good outcome False Positive Positive Good outcome False Negative Negative Bad outcome *Good clinical outcome = cancer-free survival for at least 5 years Bad clinical outcome = recurrence or death from the underlying cancer within 5 years
Positive Predictive Power (PPP)=TP/(TP+FP)
Negative Predictive Power (NPP)=TN/(FN+TN)
The results for each biomarker are summarized below.
TABLE-US-00004 TABLE 4 Summary of Results with Individual Biomarkers Src MUC-1 Phospho-p27 PSMB9 NDRG-1 E2F1 p21ras SLPI TP 8 7 7 13 7 3 10 5 FP 8 4 6 15 14 4 11 7 FN 35 37 44 30 31 34 30 39 TN 59 70 76 54 54 57 60 64 Sensitivity 18.60% 15.91% 13.73% 30.23% 18.42% 8.11% 25.00% 11.36% Specificity 88.06% 94.59% 92.68% 78.26% 79.41% 93.44% 84.51% 90.14%
Detection of Biomarker Overexpression in Clinical Samples Combining Biomarkers
In order to determine if the sensitivity and specificity of the methods of the invention could be improved if multiple biomarkers were combined, the data from Example 2 was subjected to further analysis. Thus, various combinations of biomarkers were considered, and samples that stained positive for any of the biomarkers in the combination of interest were deemed positive. These results were compared with the known actual clinical outcome data available for each patient, and each slide was then given a final result of true positive (TP), true negative (TN), false positive (FP), false negative (FN) as before. Sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) for each combination of biomarkers were calculated.
The results for each combination of biomarkers are summarized below.
TABLE-US-00005 TABLE 5 SLPI, PSMB9, MUC-1, and phospho-p27 TP 24 FP 25 FN 23 TN 58 Sensitivity 51.06% Specificity 69.88% NPV 71.60% PPV 48.98%
TABLE-US-00006 TABLE 6 SLPI, PSMB9, MUC-1, phospho-p27, and src TP 28 FP 28 FN 24 TN 60 Sensitivity 53.85% Specificity 68.18% NPV 71.43% PPV 50.00%
TABLE-US-00007 TABLE 7 SLPI, PSMB9, MUC-1, phospho-p27, src, p21ras, E2F1, and NDRG-1 TP 33 FP 41 FN 19 TN 47 Sensitivity 63.46% Specificity 53.41% NPV 71.21% PPV 44.59%
Detection of Overexpression of Individual Biomarkers in Clinical Samples Using Marker Analysis Research System (MARS)
Over 200 patients were analyzed in this study. As summarized in Table 8 this population of patients was quite heterogeneous and exhibited tumors of different stages ranging from T1N0 to T3N0.
TABLE-US-00008 TABLE 8 Patient Population Analyzed Stage Good Bad All T1N0 60 20 80 T1N1 6 7 13 T2N0 59 39 98 T3N0 6 10 16 Totals 131 76 207
The targeted characteristic of the patients was their good outcome or bad outcome status. In this study, good outcome patients were those still disease-free after five years; bad outcome patients were defined as patients with recurrence, relapse, or death within five years.
The paradigm used for biomarker selection was that biomarker overexpression would capture some of the bad outcome patients and show a very high specificity. Combining different markers would therefore ensure high specificity and gain sensitivity to reach, for example, an 80% sensitivity and 80% specificity. After a multi-step selection process, nine biomarkers were selected for the current study. These markers are shown in Table 9, along with their respective subcellular localization.
TABLE-US-00009 TABLE 9 Biomarkers Analyzed Marker Name Localization E2F1 Nucleus MUC-1 (IF3.9) Membrane NDRG-1 (ZYMED CAP43) Cytoplasm (Nucleus + Membrane) p21ras Cytoplasm p53 Nucleus Phospho p27 Cytoplasm (Nucleus) PSMB9 (3A2.4) Cytoplasm SLPI (5G6.24) Cytoplasm src Cytoplasm
The patient samples were analyzed by automated immunohistochemistry, essentially as described in Example 1, to identify biomarkers whose overexpression is indicative of a bad cancer prognosis. That is, the goal of this clinical study was to identify biomarkers that can distinguish good and bad outcome patient samples. Antibodies were used to detect the overexpression of the nine biomarkers of interest: SLPI, PSMB9, NDRG-1, E2F1, p21ras, p53, MUC-1, phospho-p27, and src. Samples were also analyzed for ER, PR, Ki67, and Her2/neu (CerbB2) expression.
Slides were prepared as described in Example 1 and subjected to antigen retrieval. Specifically, prepared slides were immersed in an antigen retrieval solution and then placed in a pressure cooker (120-125° C. at 17-23 psi) for 5 minutes. The antigen retrieval solutions for each biomarker are listed below in Table 10.
TABLE-US-00010 TABLE 10 Antigen Retrieval Solutions Biomarker Antigen Retrieval Solution SLPI Citrate pH 6.0 (Dako #S1699) PSMB9 EDTA (Biocare #CB917L) NDRG-1 Citrate pH 6.0 (Dako #S1699) E2F1 EDTA (Biocare #CB917L) p21ras citrate buffer pH 6.0 (Dako #S1699 MUC-1 Citrate pH 6.0 (Dako #S1699) phospho-p27 deionized water src Tris pH 9.5 (Biocare CB911M)
Slides were gradually returned to room temperature deionized water. The slides were rinsed 3 times in TBS/tween-20 at 2 minutes per wash. 200 pt of a biomarker-specific antibody was added to each slide and incubated at room temperature for one hour. Commercial antibodies or monoclonal antibodies, identified by polydoma screening as described herein, directed to the biomarkers of interest were used to detect biomarker overexpression.
Following incubation with the primary antibody, slides were rinsed twice with TBS/tween-20. 200 μl of labeled polymer (Dako Envision+HRP-labeled polymer secondary antibody) was then added for 30 minutes at room temperature. Slides were again rinsed 3 times with TBS/tween-20 prior to the addition of 200 μl of DAB solution for five minutes at room temperature. The slides were then rinsed three times with TBS/tween-20 and one time with deionized water. 200 μl of hematoxylin was added for 5 minutes. The slides were then rinsed 3 times with deionized water, one time with TBS/tween-20, and 2 additional times with deionized water. The slides were dehydrated, cleared, and coverslipped as described in Example 1.
A board certified pathologist manually scored the slides. p53 expression was scored for staining intensity using a scale of 0, 0.5, 1, 2, or 3, percentage of labeled cells, and a clinical diagnostic score. SLPI and PSMB9 were scored for staining intensity using a scale of 0, 0.5, 1, 2, or 3 and percentage of labeled cells. The pathologist also denoted on the slide the tumor area (ROI) used in making the determination. Up to ten individual 20× fields of view from within the selected regions for each tumor, organized in a single focus, were obtained using MARS. The actual number of images obtained from each sample was dependant on the size of the individual tumor. An Excel spreadsheet containing all of the above scoring information along with the patient outcome, lymph node status, and tumor size was generated. The data was subjected to further analysis as described below.
Using MARS, the following steps were systematically performed for every file: Chromogen separation was optimized for each biomarker using the available slide that showed the best quality stain. Segmentation set up was customized for each biomarker according to its subcellular localization (nucleus, cytoplasm or membrane). Features were extracted at cell, field of view (FOV), and focus level, within the defined ROI and exported to an output file (XML format).
A specific program named Multi Marker Analyzer was developed in order to integrate new analysis algorithms and meet the heavy computation needs for this analysis. This software provided a means to load all or a portion of either TMAs or tissue section XML files generated with MARS, to merge data contained in these files using XML files describing the TMA keys (in the case of a TMA analysis) or Excel files giving patient clinical status and patient evaluation (in the case of a tissue section analysis), and all the further analyzes. This merge process included the association of the parameters measured by MARS for each core (or patient) with the information kept in the TMA key (or the Excel file) about the patient: identification number and medical status (good or bad outcome) and the pathologist evaluation if not included in the XML formatted MARS file.
Because some of the samples did not go through the complete experimental process, the number of analyzed patients was smaller than the number of patients reported in Table 8 above and varies from one biomarker to another. The number of tissue sections analyzed for each biomarker is listed below in Table 11. The number of tissue samples analyzed for the conventional breast cancer markers (i.e., ER, PR, Ki67, and Her2/neu (CerbB2)) is in Table 12.
TABLE-US-00011 TABLE 11 Number of Tissue Sections Analyzed for Biomarker Overexpression Marker Bad Good Total E2F1 66 106 172 MUC-1 65 108 173 NDRG1 (CAP 43) 75 115 190 p21ras 72 109 181 p53 71 121 192 Phospho-p27 70 115 185 PSMB9 74 118 192 SLPI 75 118 193 src 66 108 174
TABLE-US-00012 TABLE 12 Number of Tissue Sections Analyzed for Conventional Breast Cancer Markers Marker Bad Good Total CerbB2 69 122 191 ER 70 123 193 Ki67 69 124 193 PR 69 123 192
Segmentation and Dispatchers Setup
In order to bring MARS analysis closer to the pathologist manner of characterizing slides, only cells considered as being at least 1+ were selected. Table 13 summarizes the segmentation setup used in MARS for this analysis. This segmentation setup lead to the detection of the most stained cells. Segmentation and dispatchers transmittance thresholds were based upon cytologists input. The segmentation setup was pixel-based using 20× images captured with a Dage camera on the computer TPO-RDLAB5.
TABLE-US-00013 TABLE 13 Main segmentation setup parameters Size (pixels) Cell 68 Nucleus 32 Hematoxylin Contribution Nucleus 80% Cytoplasm 100% Membrane 0% Hematoxylin Max. Transmittance Nucleus 80% Cytoplasm 100% Membrane 100% DAB Contribution Nucleus 30% Cytoplasm 100% Membrane 0% DAB Max. Transmittance Nucleus 90% Cytoplasm 100% Membrane 100%
In order to assign the selected cells to categories based upon the biomarker staining intensity in the targeted cellular compartment, valid cells resulting from segmentation were dispatched into 3 categories: 1 (in MARS: NegRef), 2 (in MARS: Test) and 3 (in MARS: PosRef). Table 14 provides MARS features and their values used to perform this dispatch, as a function of the cellular localization of the marker.
TABLE-US-00014 TABLE 14 Dispatcher Settings Resulting in the Assignment of Selected Cells into Category 1, 2 or 3 Marker Targeted Value Cell Compartment Dispatch Step If MARS Feature Is (Transmittance) Cell(s) Is Nucleus 1 NUCL_DYE2_OD_MEAN > 0.161151 (69%) All (2 or 3) otherwise 1 Cytoplasmic 2 NUCL_DYE2_OD_MEAN > 0.29243 (51%) 2 and 3 3 otherwise 2 1 CYTO_DYE2_OD_MEAN > 0.173925 (67%) All (2 or 3) otherwise 1 Membrane 2 CYTO_DYE2_OD_MEAN > 0.29243 (51%) 2 and 3 3 otherwise 2 CYTO_DYE2_OD_MEAN > 0.06048 (87%) 1 MEMB_DYE2_OD_MEAN > 0.200659 (63%) All (2 or 3) otherwise 1 MEMB_AREA > 150 pix. CYTO_DYE2_OD_MEAN > 0.173925 (67%) 2 MEMB_DYE2_OD_MEAN > 0.29243 (51%) 2 and 3 3 otherwise 2 MEMB_AREA > 150 pix.
An evaluation of category 0 (corresponding to the "expected number of non-stained cells") was performed. The approximate number of these cells was computed using the average tumor cell area (1100 pixels as estimated from the MARS feature called CELL_AREA) obtained from the area of cells with a staining intensity of 1, 2 and 3 cells:
N 1 = N NegRef ##EQU00001## N 2 = N Test ##EQU00001.2## N 3 = N PosRef ##EQU00001.3## N Total = max ( N 1 + N 2 + N 3 FOCUS_AREA 1100 ) ##EQU00001.4## N 0 = max ( 0 , N Total - N 1 - N 2 - N 3 ) ##EQU00001.5##
Using N0, N1, N2 and N3, the percentage of cells staining 0, 1, 2 and 3 cells were computed. Table 15 gives the name of these new features.
TABLE-US-00015 TABLE 15 Percentage Summary Features Percentage of cells from categories Feature Name 0 CELL_PERCENT_0 1 CELL_PERCENT_1 2 CELL_PERCENT_2 3 CELL_PERCENT_3 0 and 1 CELL_PERCENT_01 2 and 3 CELL_PERCENT_23 0, 1 and 2 CELL_PERCENT_012 1, 2 and 3 CELL_PERCENT_123
These features were computed as a simple percentage, e.g. for CELL_PERCENT--0:
CELL_PERCENT _ 0 = N 0 N Total × 100 ##EQU00002##
This study was run with MARS features, these new summary features, and the pathologist scores. USER_TYPE is the name of the MARS feature for pathologist scoring only.
Multiple Biomarker Analysis
In order to obtain an improved sensitivity/specificity couple, data from multiple biomarkers was combined and analyzed. The specificity target for each biomarker was dependent on the number of biomarkers combined. As an example, a combination of 3 biomarkers will reach 80% specificity if each individual marker specificity is at least of 0.81/3=93%. Table 16 provides the list of required specificity values based on the number of biomarkers in the combination, from 1 to 9.
TABLE-US-00016 TABLE 16 Minimum specificity required per biomarker when an overall specificity of 0.8 is targeted for a given combination of up to 9 biomarkers Marker Number Specificity Required in combination Per Marker 1 0.8 2 0.694427 3 0.926318 4 0.945742 5 0.956352 6 0.963492 7 0.968625 8 0.972492 9 0.975511
As used herein, the term "marker performance" encompasses the complete experimental performance that relates to the true biological discriminative power of the marker, as well as to the origin and storage of the biological samples, the staining protocols, the scanning process, the imaging and data mining procedures.
1. Per Biomarker
A. Pathologist Scoring
The threshold giving the best sensitivity/specificity couple was computed when considering only the pathologist scores (USER_TYPE in MARS). The most significant results are summarized in Table 17 when a specificity of 0.75 was targeted.
TABLE-US-00017 TABLE 17 Best Sensitivity and Specificity Couple for Biomarkers (Pathologist Scoring) Marker Threshold Sensitivity Specificity E2F1 1.75 0.30 0.69 MUC-1 0.75 0.21 0.61 NDRG1 2.5 0.28 0.74 p21ras 0.25 0.05 0.98 p53 0.5 0.29 0.74 Phospho-p27 1.25 0.17 0.73 PSMB9 0.75 0.10 0.94 SLPI 2.5 0.18 0.63 src 2.5 0.10 0.67
The threshold giving the best sensitivity/specificity couple was also computed when considering only the pathologist evaluation for conventional markers of the breast panel (i.e., ER, PR, Ki67, and Her2/neu (CerbB2)). The most significant results are summarized in Table 18 when a specificity of 0.75 was targeted.
TABLE-US-00018 TABLE 18 Best Sensitivity and Specificity Couple for Conventional Markers (Pathologist Scoring) Marker Threshold Sensitivity Specificity CerbB2 2.5 0.17 0.85 ER 0.5 0.31 0.72 Ki67 0.25 0.14 0.89 PR 2.5 0.23 0.69
For every biomarker and conventional breast cancer marker (i.e., ER, PR, Ki67, and Her2/neu (CerbB2)), the feature and threshold giving the best sensitivity/specificity couple was computed for the pathologist evaluation alone (USER_TYPE). Corresponding receiver operating characteristics (ROC) curves were prepared (data not shown).
B. Single-Feature Analysis
For every biomarker, the feature and threshold giving the best sensitivity/specificity couple was computed when considering every MARS features defined as being meaningful in respect to the analyzed biomarker. Corresponding ROCs were prepared (data not shown). The feature and threshold giving the best result for each biomarker are summarized in Table 19 when a specificity of 0.75 was targeted.
TABLE-US-00019 TABLE 19 Best Sensitivity and Specificity Couple for Each Biomarker Obtained from MARS Features (Single Feature Algorithm) Marker Feature Threshold Sens. Spec. Rule E2F1 CELL_PERCENT_01 97.20165 0.575758 0.716981 8 MUC-1 CELL_PERCENT_1 21.4664 0.415385 0.685185 1 NDRG1 CELL_PERCENT_1 16.97263 0.386667 0.713043 8 p21ras CELL_PERCENT_123 61.04522 0.402776 0.724771 1 p53 CELL_PERCENT_3 0.08369 0.422535 0.702479 8 phospho-p27 CELL_PERCENT_1 0.442341 0.528571 0.643478 8 PSMB9 CELL_PERCENT_123 30.42549 0.391892 0.711864 1 SLPI CELL_PERCENT_123 0.610623 0.493333 0.694915 1 src CELL_PERCENT_1 36.80664 0.409091 0.731481 1 *A decision rule of 1 means that patients above the threshold are considered as being positive (i.e. TRUE POSITIVE if bad actual clinical outcome), whereas a decision rule of 8 means that patients above the threshold are considered as being negative (i.e. FALSE NEGATIVE if bad actual clinical outcome).
C. Multiple Feature Analysis
Every percent summary feature was combined two-by-two, and thresholds giving the best sensitivity/specificity couple were computed. The most significant results for each biomarker are provided in Table 20 for a target specificity of 0.75.
TABLE-US-00020 TABLE 20 Best Sensitivity and Specificity Couple for Each Biomarker Obtained from MARS features (Multiple Feature Algorithm) Marker Feature 1 Feature 2 Threshold 1 Threshold 2 Sensitivity Specificity Rule E2F1 CELL_PERCENT_2 CELL_PERCENT_3 2.386008 1.275799 0.575758 0.745283 7 MUC-1 CELL_PERCENT_1 CELL_PERCENT_3 21.26747 0.311046 0.507892 0.835135 9 NDRG1 CELL_PERCENT_1 CELL_PERCENT_23 32.96842 0.125389 0.48 0.713043 9 p21ras CELL_PERCENT_3 CELL_PERCENT_01 0.1695 99.97016 0.458333 0.715596 6 p53 CELL_PERCENT_1 CELL_PERCENT_123 1.667596 17.22644 0.492958 0.710744 2 phospho-p27 CELL_PERCENT_1 CELL_PERCENT_01 0.456608 100 0.5 0.695652 8 PSMB9 CELL_PERCENT_1 CELL_PERCENT_123 47.63697 20.25946 0.466486 0.720339 4 SLPI CELL_PERCENT_0 CELL_PERCENT_1 62.11591 0.414484 0.573333 0.728814 1 src CELL_PERCENT_2 CELL_PERCENT_3 16.31145 0.082021 0.545455 0.712963 4 *Decision rules correspond to quadrant affection in the 2 features space.
2. Combinations of Biomarkers
The complete set of possible combinations of 1 to 9 markers was investigated using successively: the pathologist scoring, one MARS feature, and two MARS features per marker. The sensitivity and specificity were computed according to an FDA-like and a sequence-based interpretation method. "FDA-like" means that any marker ON (1) leads to a bad outcome decision. That is, a combination of markers is considered positive if at least one marker is positive. The sequence-based interpretation relies on sensitivity/specificity of each specific ON/OFF combination. The results obtained with pathologist scoring (Table 21) and percentage features evaluation (Table 22) are presented below.
TABLE-US-00021 TABLE 21 Best Sensitivity/Specificity Couples for Biomarker Combinations Using Different Targeted Specificities (75% and 95%) and Different Interpretation Algorithms (Pathologist Scoring) Target 9 Spec Markers 1 Marker 2 Markers 3 Markers 4 Markers 5 Markers 6 Markers 7 Markers 8 Markers Markers FDA 0.75 spec 0.74 0.52 sens 0.29 0.58 SEQUENCE spec 0.84 0.84 0.80 0.79 0.80 0.82 0.82 0.77 sens 0.24 0.26 0.31 0.34 0.34 0.31 0.32 0.30 FDA 0.95 spec 0.90 0.86 0.88 0.84 sens 0.13 0.23 0.25 0.30 SEQUENCE spec 0.86 0.85 0.85 0.86 0.85 sens 0.30 0.31 0.31 0.30 0.30 *Each patient is characterized by the pathologist score.
TABLE-US-00022 TABLE 22 Best Sensitivity/Specificity Couples for Biomarker Combinations Using Different Targeted Specificities (75% and 95%) and Different Interpretation Algorithms (Percentage Features) All Povs Target 1 2 3 4 5 6 7 8 9 % Features Spec Markers Marker Markers Markers Markers Markers Markers Markers Markers Markers 1 FDA 0.75 spec 0.71 0.53 sens 0.57 0.80 SEQUENCE spec 0.96 0.88 0.80 0.81 0.81 0.81 0.80 0.80 sens 0.33 0.47 0.60 0.58 0.55 0.62 0.58 0.59 FDA 0.95 spec 0.93 0.87 0.83 0.81 sens 0.18 0.34 0.44 0.50 SEQUENCE spec 0.82 0.81 0.81 0.81 0.82 sens 0.48 0.49 0.49 0.49 0.46 2 FDA 0.75 spec 0.74 0.55 sens 0.57 0.80 SEQUENCE spec 0.97 0.85 0.82 0.86 0.84 0.84 0.86 0.83 sens 0.39 0.61 0.66 0.65 0.69 0.71 0.73 0.71 FDA 0.95 spec 0.94 0.90 0.83 0.82 0.81 sens 0.30 0.50 0.63 0.72 0.76 SEQUENCE spec 0.83 0.81 0.80 0.81 0.80 sens 0.73 0.70 0.70 0.69 0.69 *Each patient is characterized by the percentage of 1, 2 and 3 staining cells.
Specific examples for combinations of four and six biomarkers are provided in Examples 5.
Analysis without Data from Infiltrating Lobular Cancer (ILC) Patients
The patient population described in Table 8 was further subdivided based on diagnosis. Specifically, data from patients with infiltrating lobular carcinoma (ILC) was excluded, and the above analysis was performed on the resulting data set. Details of the patient population analyzed in this study are provided in Table 23.
TABLE-US-00023 TABLE 23 Patient Population Analyzed (Without ILC Patients) Stage Good Bad All T1N0 56 19 75 T1N1 6 7 13 T2N0 54 33 87 T3N0 6 7 13 Totals 122 66 188
1. Per Biomarker
A. Pathologist Scoring
TABLE-US-00024 TABLE 24 Best Sensitivity and Specificity Couple for Biomarkers without ILC Patient Data (Pathologist Scoring) Marker Threshold Sensitivity Specificity E2F1 1.75 0.29 0.69 MUC-1 0.75 0.26 0.80 NDRG-1 2.5 0.26 0.72 p21ras 0.25 0.03 0.98 p53 0.5 0.29 0.75 Phospho-p27 1.25 0.16 0.71 PSMB9 0.75 0.12 0.93 SLPI 2.5 0.22 0.81 src 2.5 0.10 0.86
TABLE-US-00025 TABLE 25 Best Sensitivity and Specificity Couple for Conventional Markers without ILC Patient Data (Pathologist Scoring) Marker Threshold Sensitivity Specificity CerbB2 2.5 0.16 0.85 ER 0.5 0.38 0.71 Ki67 0.25 0.14 0.88 PR 2.5 0.23 0.69
B. Single-Feature Analysis
TABLE-US-00026 TABLE 26 Best Sensitivity and Specificity Couple for Each Biomarker Obtained from MARS Features without ILC Patient Data (Single Feature Algorithm) Marker Feature Threshold Sens. Spec. Rule E2F1 CELL_PERCENT_23 3.19079 0.58182 0.73469 1 MUC-1 CELL_PERCENT_23 8.437 0.38462 0.71717 8 NDRG1 CELL_PERCENT_123 26.13234 0.39683 0.69811 8 p21ras CELL_PERCENT_123 61.04522 0.45763 0.72277 1 p53 CELL_PERCENT_3 0.08289 0.41379 0.71171 8 phospho-p27 CELL_PERCENT_123 0.44587 0.49153 0.64486 8 PSMB9 CELL_PERCENT_123 30.42545 0.40323 0.71560 1 SLPI CELL_PERCENT_123 0.57594 0.53226 0.70370 1 src CELL_PERCENT_23 13.08501 0.43636 0.66000 8 *A decision rule of 1 means that patients above the threshold are considered as being positive (i.e., TRUE POSITIVE if bad actual clinical outcome) whereas a decision rule of 8 means that patients above the threshold are considered as being negative (i.e., FALSE NEGATIVE if bad actual clinical outcome).
C. Multiple Feature Analysis
TABLE-US-00027 TABLE 27 Best Sensitivity and Specificity Couple for Each Biomarker Obtained from MARS Features without ILC Patient Data (Multiple Feature Algorithm) Marker Feature 1 Feature 2 Threshold 1 Threshold 2 Sensitivity Specificity Rule E2F1 CELL_PERCENT_2 CELL_PERCENT_3 2.47761 1.2758 0.61818 0.7449 7 MUC-1 CELL_PERCENT_1 CELL_PERCENT_2 9.6658 13.2244 0.51923 0.68687 9 NDRG1 CELL_PERCENT_0 CELL_PERCENT_123 28.32391 16.95268 0.49206 0.70755 6 p21ras CELL_PERCENT_3 CELL_PERCENT_01 0.1695 99.97219 0.49153 0.72277 6 p53 CELL_PERCENT_0 CELL_PERCENT_3 48.61018 0.07805 0.46552 0.71171 6 phospho-p27 CELL_PERCENT_1 CELL_PERCENT_01 0.50369 100 0.49153 0.69159 8 PSMB9 CELL_PERCENT_123 CELL_PERCENT_01 30.42545 99.09092 0.45161 0.7156 11 SLPI CELL_PERCENT_0 CELL_PERCENT_123 62.11591 0.40094 0.58065 0.75 1 src CELL PERCENT 2 CELL PERCENT 3 16.31145 0.08202 0.52727 0.72 4 *Decision rules correspond to quadrant affection in the 2 features space.
D. Variations Between Analyses: All Patients v. Without ILC Patients
Variations in the sensitivity and specificity values obtained on a per biomarker basis with the analysis of the complete patient population (Table 8) and the population without ILC patients (Table 23) was determined. The results are presented below in Table 28. The sum column (d2) gives the difference of quadratic distance on an ROC curve, i.e., the overall gain in sensitivity and specificity.
TABLE-US-00028 TABLE 28 Variations in Sensitivity and Specificity Obtained with the Complete Patient Population and Without ILC Patients (Per Biomarker) Pathologist Scoring Single-Feature Multi-Features Marker Sens. Spec. d1 Sens. Spec. d2 Sens. Spec. d2 E2F1 ↓ -- -0.004 ↑ ↑ 0.018 ↑ ↓ 0.026 MUC-1 ↑ ↓ 0.004 ↓ ↑ 0.013 ↑ ↑ 0.006 NDRG1 ↓ ↓ -0.026 ↑ ↓ -0.006 ↑ ↓ 0.002 p21ras ↓ -- -0.001 ↑ ↓ 0.026 ↑ ↑ 0.024 p53 -- ↑ 0.009 ↓ ↑ 0.003 ↓ ↑ -0.015 phospho-p27 ↓ ↓ -0.022 ↓ ↑ -0.022 ↓ ↓ -0.008 PSMB9 ↑ ↓ -0.008 ↑ ↑ 0.000 ↓ ↓ -0.023 SLPI ↑ ↓ -0.010 ↑ ↑ 0.030 ↑ ↑ 0.021 src -- ↓ -0.010 ↓ ↓ -0.047 ↓ ↑ -0.005
2. Combinations of Biomarkers
A. Pathologist Scoring
TABLE-US-00029 TABLE 29 Best Sensitivity/Specificity Couples for Biomarker Combinations without ILC Patient Data Using Different Targeted Specificities (75% and 95%) and Different Interpretation Algorithms (Pathologist Scoring) Target 9 Spec. Markers 1 Marker 2 Markers 3 Markers 4 Markers 5 Markers 6 Markers 7 Markers 8 Markers Markers FDA 0.75 spec 0.75 0.63 SEQUENCE sens 0.20 0.67 spec 0.88 0.83 0.84 0.84 0.90 0.85 0.83 0.77 sens 0.24 0.35 0.37 0.35 0.36 0.35 0.37 0.27 *Each patient is characterized by the pathologist score.
B. Percentage Features Analysis
TABLE-US-00030 TABLE 30 Best Sensitivity/Specificity Couples for Biomarker Combinations without ILC Patients Using Different Targeted Specificities (75% and 95%) and Different Interpretation Algorithms (Percentage Features) All Povs Target 1 2 3 4 5 6 7 8 9 % Features Spec Markers Marker Markers Markers Markers Markers Markers Markers Markers Markers 1 FDA 0.79 spec 0.73 0.54 SEQUENCE sens 0.58 0.22 spec 0.95 0.86 0.81 0.68 0.85 0.82 0.92 0.78 sens 0.35 0.46 0.56 0.58 0.38 0.82 0.57 0.50 2 FDA 0.35 spec 0.74 0.55 SEQUENCE sens 0.80 0.63 spec 0.36 0.67 0.64 0.71 0.70 0.72 0.85 0.70 sens 0.35 0.67 0.94 0.75 0.70 0.72 0.56 0.70 *Each patient is characterized by the percentage of 1, 2 and 3 staining cells.
Table 30 shows an increase in specificity (0.88 compared to 0.81, see Table 28) when considering a 5 biomarker combination excluding ILC patients with a single percent feature. An increase in sensitivity was observed when using 2 features (0.71 vs. 0.65, see Table 28) for a 5 biomarker sequence analysis when excluding ILC patients from the study.
C. Variations Between Analyses: All Patients v. without ILC Patients
Variations in the sensitivity and specificity values obtained for biomarker combinations with the analysis of the complete patient population and the population without ILC patients was determined. The results are presented below in Table 31. The sum column (d2) gives the difference of quadratic distance on a ROC curve, i.e., the overall gain in sensitivity and specificity. A slight gain in performance for a 5 biomarker sequence analysis using one or two percentage features was observed when ILC patients were excluded from the study.
TABLE-US-00031 TABLE 31 Variations in Sensitivity and Specificity Obtained with Complete Patient Population and Without ILC Patients (Biomarker Combinations) All Povs Target 1 2 3 4 5 6 7 8 9 % Features Spec Markers Marker Markers Markers Markers Markers Markers Markers Markers Markers 1 FDA 0.75 d2 0.02 0.02 SEQUENCE d2 0.00 0.01 0.00 0.06 0.04 0.01 0.01 -0.07 2 FDA 0.75 d2 0.02 0.02 SEQUENCE d2 -0.01 0.00 0.02 0.02 -0.01 -0.01 -0.06 -0.04
Specific Biomarker Combinations
The data obtained in the study described above in example 4 were further analyzed, and specific biomarker combinations were considered. The results obtained with a combination of four (SLPI/p21ras/E2F1/src) and six (SLPI/p21ras/PSMB9/E2F1/src/phospho-p27) biomarkers are presented below.
Four Biomarker Combination: SLPI/p21ras/E2F1/src
Analysis was performed using only one percentage feature for SLPI, p21ras, E2F1, and src with the thresholds and decision rule defined in Table 32. A 60% sensitivity and an 80% specificity was obtained using the rule: if E2F1 was ON (i.e. 1) and not the only biomarker to be ON, then the patient was considered bad outcome; otherwise, considered good outcome. FIG. 1 shows the distribution of the percentage feature as a function of bad and good outcome patients for E2F1. Using a threshold of 2.46% sensitivity and specificity values of 0.54 and 0.75, respectively, were obtained.
TABLE-US-00032 TABLE 32 Percentage Summary Features for Four Biomarker Analysis Marker Feature Threshold Rule (1 if) SLPI CELL_PERCENT_01 99.887874 < p21ras CELL_PERCENT_0 35.642851 < E2F1 CELL_PERCENT_2 2.463659 > src CELL_PERCENT_1 37.624326 >
A sequence-based interpretation approach was used to analyze the four biomarker combination. The sequence-based decision rule used was: if E2F1 was ON (i.e. 1) and not the only biomarker to be ON, then the patient was considered bad outcome; otherwise, considered good outcome. The sensitivity and specificity values for all of the possible combinations of the four biomarkers are provided in Table 33. The ROC curve obtained using the sequence interpretation approach for the SLPI/p21ras/E2F1/src combination was prepared (data not shown).
TABLE-US-00033 TABLE 33 Sensitivity and Specificity Couples Using Sequence-based Interpretation Approach for SLPI, p21ras, E2F1 and SRC Combination SLPI-p21ras-E2F1-src Sequence CumulBad CumulGood Sensitivity Specificity S1111 4 0 0.069 1 S1011 7 0 0.1207 1 S1110 12 0 0.2069 1 S0111 14 8 0.2414 0.9184 S1010 22 12 0.3793 0.8776 S1101 26 14 0.4483 0.8571 S0011 31 16 0.5345 0.8367 S0110 35 19 0.6034 0.8061 S1001 37 24 0.6379 0.7551 S1100 37 26 0.6379 0.7347 S0010 39 37 0.6724 0.6224 S0101 41 40 0.7069 0.5918 S1000 46 56 0.7931 0.4286 S0001 49 63 0.8448 0.3571 S0100 52 71 0.8966 0.2755 S0000 58 98 1 0 *A sequence S0110 is read as follows: SLPI = OFF/p21ras = ON/E2F1 = ON/src = OFF.
An interpretation based on E2F1 alone gave a sensitivity and specificity of 54% and 75%, respectively. A specificity and sensitivity of 60% and 80%, respectively, was obtained using the sequence-based algorithm defined above (i.e., if E2F1 was ON (i.e. 1) and not the only biomarker to be ON, then the patient was considered bad outcome; otherwise, considered good outcome).
Six Biomarker Combination: SLPI/p21ras/E2F1/src/PSMB9/phospho-p27
Analysis was performed using only one percentage feature for a six biomarker combination of SLPI, p21ras, E2F1, src, PSMB9, and phospho-p27 with the thresholds and decision rules defined in Table 34.
TABLE-US-00034 TABLE 34 Percentage Summary Features for Six Biomarker Analysis MarkerName Feature Threshold Sensitivity Specificity Rule (1 if) SLPI CELL_PERCENT_123 0.576 53.2% 70.4% > p21ras CELL_PERCENT_123 61.045 45.8% 72.3% > E2F1 CELL_PERCENT_23 3.191 58.2% 73.5% > PSMB9 CELL_PERCENT_123 30.425 40.3% 71.6% > src CELL_PERCENT_23 13.085 43.6% 66.0% < phospho-p27 CELL_PERCENT_123 0.446 49.2% 64.5% <
A sequence-based interpretation approach was used to analyze the six biomarker combination. The sequence-based decision rule used was: If E2F1 was ON (i.e. 1) and either SLPI or 21ras, or E2F1 and any 2 biomarkers, or SLPI and any 2 biomarkers, or any 4 biomarkers or more were ON, then the patient was considered bad outcome; otherwise considered good outcome. The sensitivity and specificity values for all of the possible combinations of the six biomarkers of interest are provided in Table 35. The ROC curve obtained using the sequence interpretation approach for the SLPI/p21ras/E2F1/PSMB9/src/phospho-p27 combination are shown in FIG. 2.
TABLE-US-00035 TABLE 35 Sensitivity and Specificity Couples Using Sequence-based Interpretation Approach for SLPI, p21ras, E2F1, PSMB9, SRC, and Phospho-p27 Combination SLPI-p21ras-E2F1-PSMB9-src-phospho-p27 Sequence CumulBad CumulGood Sensitivity Specificity S111111 1 0 0.0208 1 S111101 2 0 0.0417 1 S111011 2 0 0.0417 1 S111110 2 0 0.0417 1 S101111 3 0 0.0625 1 S111001 4 0 0.0833 1 S111100 8 0 0.1667 1 S011111 8 0 0.1667 1 S111010 9 0 0.1875 1 S101101 11 0 0.2292 1 S101011 12 0 0.25 1 S110111 12 0 0.25 1 S101110 12 0 0.25 1 S011101 12 0 0.25 1 S111000 12 0 0.25 1 S011011 13 1 0.2708 0.9885 S011110 13 1 0.2708 0.9885 S101001 13 2 0.2708 0.977 S110101 14 2 0.2917 0.977 S101100 15 3 0.3125 0.9655 S001111 17 3 0.3542 0.9655 S110011 19 4 0.3958 0.954 S101010 21 4 0.4375 0.954 S110110 21 4 0.4375 0.954 S011001 21 5 0.4375 0.9425 S011100 22 8 0.4583 0.908 S011010 23 10 0.4792 0.8851 S100111 23 10 0.4792 0.8851 S001101 23 11 0.4792 0.8736 S110001 23 11 0.4792 0.8736 S101000 25 13 0.5208 0.8506 S001011 26 14 0.5417 0.8391 S110100 27 14 0.5625 0.8391 S010111 27 15 0.5625 0.8276 S001110 28 16 0.5833 0.8161 S110010 28 16 0.5833 0.8161 S011000 31 19 0.6458 0.7816 S100101 31 19 0.6458 0.7816 S100011 33 20 0.6875 0.7701 S100110 34 20 0.7083 0.7701 S001001 34 21 0.7083 0.7586 S010101 35 22 0.7292 0.7471 S001100 35 26 0.7292 0.7011 S110000 36 28 0.75 0.6782 S010011 37 29 0.7708 0.6667 S001010 37 30 0.7708 0.6552 S010110 37 30 0.7708 0.6552 S100001 37 34 0.7708 0.6092 S100100 38 38 0.7917 0.5632 S000111 40 39 0.8333 0.5517 S100010 40 45 0.8333 0.4828 S010001 41 46 0.8542 0.4713 S001000 41 46 0.8542 0.4713 S010100 41 47 0.8542 0.4598 S010010 41 48 0.8542 0.4483 S000101 41 51 0.8542 0.4138 S100000 42 54 0.875 0.3793 S000011 42 59 0.875 0.3218 S000110 42 61 0.875 0.2989 S010000 42 65 0.875 0.2529 S000001 43 70 0.8958 0.1954 S000100 43 72 0.8958 0.1724 S000010 44 77 0.9167 0.1149 S000000 48 87 1 0
A specificity and sensitivity of 70% and 77%, respectively, was obtained using the sequence-based algorithm defined above.
Optimization of Reagents and Staining Conditions for Immunohistochemistry
In order to maximize the signal to noise ratio for detection of expression of a particular biomarker using the immunohistochemistry methods disclosed herein, experiments to select the optimal antigen retrieval solution and conditions, antibody concentration and diluent formulation, and detection chemistry parameters were performed. For each set of experiments, biomarker-specific tissue microarrays (TMAs) were constructed by obtaining cylindrical tissue specimens from regular paraffin blocks, assembling them into a single block, and preparing sections containing multiple tissue specimens. TMAs with 2-3 pre-selected known positive and negative tumors for each breast biomarker were used. Slides were prepared and automated immunohistochemistry was performed essentially as described in Example 1. The following control reagents were used during all of the optimization experiments: For the negative control, the application of the primary antibody was replaced with a ready to use universal negative reagent, either non-specific mouse or rabbit IgG. EF1-α was used as a positive control. A positive marker control slide was run following the optimized labeling parameters established during feasibility for each antibody being tested. A biomarker specific TMA containing both positive and negative tumors was used in the testing of each breast marker antibody.
1. Optimization of Antigen Retrieval
A. Antigen Retrieval Solutions
Each antigen retrieval solution listed below was tested using each of the biomarker antibodies of interest. The time and temperatures used here were standard accepted values as defined below.
TABLE-US-00036 TABLE 36 Antigen Retrieval Solutions Tested Solution Time Temperature Device Citrate Buffer 5 minutes 120° C. Pressure Cooker pH 6.0 (Dako) Tris Buffer pH 9.5 5 minutes 120° C. Pressure Cooker (Biocare) EDTA pH 8.0 20 minutes 95° C. Steamer (Biocare) L.A.B. 20 minutes 20° C. and 60° C. None/oven (Polysciences) Antigen Retrieval 5 minutes 120° C. Pressure Cooker Glyca Solution (Biogenex) Citrate Buffer 20 minutes 95° C. Steamer Solution, pH 4.0 (Zymed) diH20 20 minutes 120° C. Pressure Cooker Dawn (Protor & 3 minutes 120° C. Pressure Cooker Gamble) 2% Glacial Acetic 10 minutes 95° C. Steamer Acid
The slides were scored by a pathologist, and the best performing antigen retrieval solution were determined by comparing the labeling specificity and intensity between positive and negative tumors. If the results were essentially negative, alternative antigen retrieval solutions were screened. If results were positive, i.e. labeling more intense than no antigen retrieval, the top (1-3) solutions were identified and used for antigen retrieval time and temperature testing. The activity of the selected antigen retrieval solutions was verified by labeling a representative sample of positive and negative whole tissue sections.
B. Antigen Retrieval Conditions--Time and Temperature
The best-performing antigen retrieval solutions were tested using the following time and temperature criteria:
TABLE-US-00037 TABLE 37 Antigen Retrieval Time and Temperature Conditions Tested 3 5 10 20 30 4 Over- Temp minutes minutes minutes minutes minutes hours night 2-8° C. * * 25° C. * * 37° C. * * 60° C. * * 95° C./ * * * ST 120° C./ * * * PC
The slides were scored by a pathologist, and the best-performing antigen retrieval time and temperature combinations were determined by comparing the labeling specificity and intensity between positive and negative tumors. The activity of the selected antigen retrieval solutions and time and temperature combinations was verified by labeling a representative sample of positive and negative whole tissue sections utilizing the controls listed above.
2. Optimization of Antibody Dilution and Diluent Formulations
A. Antibody Dilution
Each breast cancer biomarker antibody was tested over a range of antibody dilutions. Table 38 provides an example of antibody dilutions tested for the SLPI 5G6.24 antibody. All other breast biomarker antibodies were tested in a similar manner.
TABLE-US-00038 TABLE 38 Antibody Dilutions Tested IgG μg/slide (200 μl/ Antibody concentration slide) Dilution SLPI .sup. 3.5 mg/ml 3.5 1:200 5G6.24 (3.5 μg/ul) 1.75 1:400 1.17 1:600 0.88 1:800 0.7 1:1000 0.47 1:1500
The slides were scored by a pathologist, and the labeling intensities between controls, known positive, and known negative tumors were assessed. The labeling data was analyzed to determine both the upper and lower limits of the antibody dilutions that maintained the desired labeling intensity and the width of the utility range for each antibody. If the initial dilution range tested did not result in the identification of the upper and lower limits, additional antibody dilutions were tested.
B. Antibody Diluent Formulation
Various antibody diluents were tested using each of the breast biomarker antibodies of interest. The table below provides a description of the diluent parameters that were tested.
TABLE-US-00039 TABLE 39 Antibody Diluents Tested PBS pH 7.4 PBS pH 7.4 0.1% tween 20 PBS pH 7.4 1% BSA PBS pH 7.4 0.05% NaN3 PBS pH 7.4 0.1% tween 20 1% BSA PBS pH 7.4 0.1% tween 20 0.05% NaN3 PBS pH 7.4 1% BSA 0.05% NaN3 PBS pH 7.4 0.1% tween 20 1% BSA 0.05% NaN3
The slides were scored by a pathologist for labeling intensity. The effectiveness of the diluent formulation was determined by comparing the labeling grade of the biomarker control slide to the experimental slides. Those that resulted in the most specific and highest signal to noise ratio by comparing the labeling of positive and negative tumors were carried forward. The diluent formulations (approximately one to three) that resulted in the optimal labeling intensity were carried forward into further optimization and stability studies. The activity of the selected diluents was verified by labeling a representative sample of positive and negative whole breast cancer tissue sections.
3. Optimization of Detection Chemistry
Each of the breast biomarker antibodies was tested utilizing the DAKO Envision+ detection kit over the range of times and concentrations listed below.
TABLE-US-00040 TABLE 40 Detection Chemistry Time and Concentration Conditions Tested Time Concentration 10 minutes 30 minutes 60 minutes 1.0X Concentration 0.75X Concentration 0.5X Concentration
The slides were scored by a pathologist, and the labeling intensities between controls, known positive, and known negative tumors were assessed. The activity of the selected detection chemistry time and concentration combinations was verified by labeling a representative sample of positive and negative whole breast cancer tissue sections.
A significantly improved signal to noise ratio was observed with optimized staining reagent conditions (data not shown).
Real-Time PCR Detection of Biomarkers in Clinical Samples
TaqMan® real-time PCR was performed with the ABI Prism 7700 Sequence Detection System (Applied Biosystems, Foster City, Calif.). The primers and probes were designed with the aid of the Primer Express® program, version 1.5 (Applied Biosystems, Foster City, Calif.), for specific amplification of the targeted breast staging markers (e.g., DARPP32 and NDRG-1) in this study. The sequence information on primers and probes is shown below:
TABLE-US-00041 (SEQ ID NO: 33) Forward Primer Name: DARPP32_t1-F Sequence: TACACACCACCTTCGCTGAAAG (SEQ ID NO: 34) Reverse Primer Name: DARPP32_t1-R Sequence: GGCCTGGTTCTCATTCAAATTG (SEQ ID NO: 35) TaqMan Probe Name: DARPP32_t1-Probe Sequence: CGCATTGCTGAGTCTCACCTGCAGTC (SEQ ID NO: 36) Forward Primer Name: DARPP32_t2-F Sequence: CAGCCTTACAGAGACTGGAAAAGAA (SEQ ID NO: 37) Reverse Primer Name: DARPP32_t2-R Sequence: GAGGCTCAGGGACCCAAAG (SEQ ID NO: 38) TaqMan Probe Name: DARPP32_t2-Probe Sequence: CCAAACCAAGGCCCCCAGAGAGGT
TABLE-US-00042 Forward Primer Name: NDRG-1-F Sequence: CCTACCGCCAGCACATTGT (SEQ ID NO: 39) Reverse Primer Name: NDRG-1-R Sequence: GCTGTTGTAGGCATTGATGAACA (SEQ ID NO: 40) TaqMan Probe Name: NDRG-1-Probe Sequence: AATGACATGAACCCCGGCAACCTG (SEQ ID NO: 41)
The probes were labeled with a fluorescent dye FAM (6-carboxyfluorescein) on the 5' base, and a quenching dye TAMRA (6-carboxytetramethylrhodamine) on the 3' base. The sizes of the amplicons were around 100 bp. 18S ribosomal RNA was applied as endogenous control. 18S rRNA probe was labeled with a fluorescent dye VIC. Pre-Developed 18S rRNA primer/probe mixture was purchased from Applied Biosystems (P/N: 4310893E). 20 frozen breast tissues (i.e., 6 tumors with bad outcome, 12 tumors with good outcome, and 2 normal tissues) were analyzed in this study. In this study, good outcome was defined as remaining cancer-free for at least 5 years; bad outcome was defined as suffering disease relapse, recurrence, or death within 5 years. 5 μg of total RNA extracted from the frozen breast tissues was quantitatively converted into the single stranded cDNA form with random hexamers (not with oligo-dT) by using the High-Capacity cDNA Archive Kit (Applied Biosystems, P/N: 4322171). The following reaction reagents were prepared:
TABLE-US-00043 20X Master Mix of Primers/Probe (in 200 μl) 180 μM Forward primer 20 μl 180 μM Reverse primer 20 μl 100 μM TaqMan probe 10 μl H2O 150 μl Final Reaction Mix (25 μl/well) 20X master mix of primers/probe 1.25 μl 2X TaqMan Universal PCR master mix (P/N: 4304437) 12.5 μl cDNA template 5.0 μl H2O 6.25 μl
20× TaqMan Universal PCR Master Mix was purchased from Applied Biosystems (P/N: 430-4437). The final primer and probe concentrations, in a total volume of 25 μl, were 0.9 μM and 0.25 μM, respectively. 10 ng of total RNA was applied to each well of the reaction. The amplification conditions were 2 min at 50° C., 10 min at 95° C., and a two-step cycle of 95° C. for 15 seconds and 60° C. for 60 seconds for a total of 40 cycles. At least three no-template control reaction mixtures were included in each run. All experiments were performed in triplicate.
At the end of each reaction, the recorded fluorescence intensity was used for the following calculations: Rn.sup.+ is the Rn value of a reaction containing all components, Rn.sup.- is the Rn value of an unreacted sample (baseline value or the value detected in NTC). ΔRn is the difference between Rn.sup.+ and Rn.sup.-. It is an indicator of the magnitude of the signal generated by the PCR. Expression level of a target gene was computed by comparative CT method. This method uses no known amount of standard but compares the relative amount of the target sequence to the reference values chosen (18S rRNA was selected as a reference in this study). See the Applied Biosystems' TaqMan Human Endogenous Control Plate Protocol that contains detailed instructions regarding MS Excel based data analysis.
The results obtained with each biomarker and with the specific primers are listed below in tabular form. Results obtained with normal breast tissue samples are designated N; those obtained with breast cancer samples are labeled T.
TABLE-US-00044 TABLE 41 DARPP32 TaqMan ® Results Samples t1 t2 t1t2 2T 0.18 0.5 0.54 7T 5.7 23.5 62.5 12T 73.5 16.9 84.2 13T 1.2 1.1 2.2 21T 5.8 6.1 16.1 24T 4.2 2.9 7.9 26T 0.6 0.3 1.9 1T 0.02 0.2 0.1 3T 0.4 0.04 0.8 4T 2.5 1 4.8 5T 1.2 0.5 3.7 6T 0.9 0.6 2.6 9T 0.3 0.6 0.5 10T 0.1 0.2 0.3 11T 0.7 0.1 0.9 19T 0.8 0.3 1.6 22T 0.6 0.6 1.6 23T 0.5 0.4 1.2 25T 0.2 0.1 0.3 1N 1.1 1.3 2 8N 0.7 0.3 1.3 Bad 15.10 8.50 28.91 Mean: Good 0.69 0.39 1.53 Mean t-test P = 0.046 0.004 0.007
DARPP32 has two transcripts: t1 and t2. TaqMan® data showed that both t1 and t2 were overexpressed in the breast tumors with bad outcomes (in bold) as compared with those with good outcomes.
TABLE-US-00045 TABLE 42 NDRG-1 TaqMan ® Results Samples NDRG-1 2T 2.8 7T 12.8 12T 5.5 13T 6.4 21T 2.4 24T 6.7 26T 2.3 1T 4.1 3T 4.2 4T 2.8 5T 3.2 6T 1.3 9T 3.1 10T 3.7 11T 1.6 19T 3.4 22T 5.5 23T 1.6 25T 3.1 1N 0.9 8N 0.5 Bad 6.10 Mean: Good 3.13 Mean: t-test P = 0.021
NDRG-1 has one transcript. TaqMan data showed that NDRG-1 was overexpressed in the breast tumors with bad outcomes (in bold) as compared with those with good outcomes.
Detection of Biomarker Overexpression in a Chemo-Naive Patient Population with 10-Year Clinical Follow-Up (Five Biomarker Panel)
Breast tumor tissue samples collected at or near the time of initial diagnosis from 255 early-stage breast cancer patients were analyzed for biomarker overexpression in this study. Ten-year clinical follow-up data was available for all patients in the study. None of the patients received cytotoxic chemotherapy at any time during their treatment for breast cancer. The clinical demographics, distribution, and standard histopathological parameters (e.g., ER/PR hormone receptor status, histological grade, etc.) for the patient population are summarized below in Table 43.
TABLE-US-00046 TABLE 43 Clinical Characteristics of Chemo-Naive Patient Population Characteristics Overall Age at diagnosis (years) n = 255 Mean (std) 64.0 (10.6) Range 30-85 Age group distribution <40 6 (2.4%) 40-<50 23 (9.0%) 50-<60 48 (18.8%) 60-<70 87 (34.1%) >=70 91 (35.7%) Tumor size (cm) n = 255 Mean (std) 2.1 (1.19) Range 0.3-11.0 Tumor size group <1.0 16 (6.3%) 1.0-<2.0 104 (40.8%) 2.0-<4.0 122 (47.8%) >=4.0 13 (5.1%) Lymph node status n = 255 Negative 232 (91.0%) Positive 23 (9.0%) Histological Grade n = 244 1 38 (15.6%) 2 135 (55.3% 3 71 (29.1%) ER Status n = 249 Negative 64 (25.7%) Positive 185 (74.3%) Her2/neu status n = 249 Negative 176 (70.7%) Positive 73 (29.3%)
Detection of expression of a five biomarker panel comprising SLPI, src, PSMB9, p21ras, and E2F1 was performed essentially as described above. That is, breast tumor samples were prepared and stained for biomarker expression using the Dako Autostainer, as described above in Example 1. Biomarker overexpression was determined using the imaging analysis described in Example 4.
The prognostic performance of the 5 biomarker panel was assessed utilizing a Cox Proportional Hazards Model analysis. See, for example Spruance et al., supra. The prognostic value of each biomarker and/or histological characteristic to identify the patients who suffered disease recurrence or death within ten years over the patients disease-free after ten years was calculated. In the analysis without the biomarker panel, age and tumor size were found to be independent prognostic factors with a p value<0.05. When the biomarkers were added to this analysis, they exhibited the highest statistically significant independent prognostic utility with a p value of <0.0001. The results of the Cox Proportional Hazard analysis are summarized below in Table 44.
TABLE-US-00047 TABLE 44 Results of Cox Proportional Hazard Analysis with Chemo-Naive Patient Population (SLPI, src, PSMB9, p21ras, and E2F1 Biomarker Panel) Variable P Value Hazard Ratio (95% CI) Analysis (without Biomarkers) Age at Diagnosis 0.0002 1.05 (1.02, 1.08) Tumor Size 0.0066 1.28 (1.07, 1.53) ER 0.2506 1.40 (0.79, 2.50) Total Grade 0.0674 1.39 (0.98, 1.99) Analysis (with Biomarkers)* Age at Diagnosis 0.0004 1.05 (1.02, 1.08) Tumor Size 0.0318 1.21 (1.02, 1.44) ER 0.0134 2.20 (1.18, 4.12) Total Grade 0.0845 1.37 (0.96, 1.96) TPO Marker <0.0001 1.92 (1.47, 2.50) Age at diagnosis was continuous variable and the biomarker was ordinary variable with 0 or 1, 2, 3, 4 (0 = none positive marker, 1 = one positive marker, or 2, 3, 4 positive marker).
The prognostic performance of the SLPI, src, PSMB9, p21ras, and E2F1 biomarker panel is graphically presented in the Kaplan-Meier plot of FIG. 3. The x-axis represents years from initial diagnosis, and the y axis is the percentage of disease-free survival. The corresponding graph for the general breast cancer population independent of biomarker analysis is presented in FIG. 4. These plot demonstrate the ability of this biomarker panel to risk stratify this early stage breast cancer patient population for disease recurrence and/or death due to primary disease. The risk of reoccurrence and/or death due to primary disease increases as the number of biomarkers that are overexpressed in the patient samples increases. The disease-free survival rates of the patient subgroups identified by the number of overexpressed biomarkers are statistically significant from each other with a p value of <0.001, as determined by log-rank test for comparison of 0 positive, 1 positive, 2 positive, 3 or more positive biomarker groups. A biomarker that is classified as overexpressed by the imaging analyses described herein is deemed "positive."
Because one of the most important clinical features of a breast cancer patient's diagnosis relates to estrogen receptor (ER) status, the prognostic performance of the SLPI, src, PSMB9, p21ras, and E2F1 biomarker panel was further assessed using the Cox Proportional Hazard analysis in the ER-positive and -negative patient subgroups. Clinical management and prognosis of these two subgroups is different because ER-positive patients are candidates for tamoxifen therapy whereas ER negative patients are not. The results of the analysis are summarized below in Table 45. The data indicate that the five biomarkers of interest have prognostic utility in both the ER positive and negative breast cancer patient subgroups. Therefore, while the biomakers SLPI, src, PSMB9, p21ras, and E2F1 are indicative of prognosis independent of the patient's ER status, these biomarkers also correlate with ER status.
TABLE-US-00048 TABLE 45 Results of Cox Proportional Hazard Analysis with Chemo-Naive Patient Population (SLPI, src, PSMB9, p21ras, and E2F1 Biomarker Panel in ER Positive and Negative Patient Subgroups) Variable P Value Hazard Ratio (95% CI) ER Positive Analysis without Biomarker Age at Diagnosis 0.0012 1.05 (1.02, 1.09) Tumor Size 0.0237 1.25 (1.03, 1.51) HER2 0.5732 1.18 (0.66, 2.13) Total Grade 0.0566 1.47 (0.99, 2.20) Analysis with Biomarker* Age at Diagnosis 0.0009 1.06 (1.03, 1.10) Tumor Size 0.0753 1.19 (0.98, 1.43) HER2 0.8523 1.06 (0.58, 1.93) Total Grade 0.0440 1.50 (1.01, 2.23) TPO Marker <0.0001 1.98 (1.46, 2.69) ER Analysis without Negative Biomarker Age at Diagnosis 0.0771 1.04 (1.00, 1.09) Tumor Size 0.1527 1.51 (0.86, 2.64) HER2 0.2562 0.55 (0.19, 1.55) Total Grade 0.9883 1.01 (0.45, 2.24) Analysis with Biomarker* Age at Diagnosis 0.3467 1.03 (0.97, 1.08) Tumor Size 0.1854 1.44 (0.84, 2.48) HER2 0.6577 0.78 (0.27, 2.30) Total Grade 0.7327 0.86 (0.38, 1.99) TPO Marker 0.0089 1.91 (1.18, 3.09) Age at diagnosis was continuous variable and the TPO marker was ordinary variable with 0 or 1, 2, 3, 4 (0 = none positive marker, 1 = one positive marker, or 2, 3, 4 positive marker).
Detection of Biomarker Overexpression in a Chemo-Naive Patient Population with 10-Year Clinical Follow-up (Six Biomarker Panel)
Breast tumor tissue samples from 100 patients (50 good outcome; 50 bad outcome patients) from the chemo-naive patient population described in Example 8 were analyzed for biomarker overexpression of six biomarkers of interest (SLPI, src, PSMB9, p21ras, E2F1, and MUC-1). Detection of expression of the six biomarker panel was performed by automated immunohistochemistry essentially as described above except that an alternate staining platform, the Ventana BenchMark XT, was used in place of the Dako Autostainer. A standard manual for operating the Ventana BenchMark XT is readily available from the manufacturer. Additional modifications to the immunohistochemistry parameters used with the Ventana BenchMark XT staining platform are summarized in Table 46 below. Biomarker overexpression was determined as before using the imaging analysis described in Example 4.
TABLE-US-00049 TABLE 46 Immunohistochemistry Parameters for Biomarker Staining with the Ventana BenchMark XT Staining Platform Antibody Antigen Antigen Antibody Antibody Concentration Retrieval Retrieval Incubation Incubation Block and Biomarker (ug/ml) Solution Time Temp Time Amplification SLPI 3.6 CC1 Extended RT 1 hr None E2F1 2.0 CC1 Extended 37° C. 16 min Pro & Biotin Amp SRC 40 CC2 Standard 37° C. 1 hr None p21ras 13.7 CC1 Short 37° C. 12 min None PSMB9 6.5 CC2 Standard RT 1 hr None MUC1 5.0 CC1 Extended 37° C. 1 hr None *CC1 and CC2 refer to cell conditioning reagents commercially available from Ventana. With respect to antigen retrieval times: short = 30 min; standard = 60 min; and extended = 90 min.*
The prognostic performance of the 6 biomarker panel was assessed utilizing a Cox Proportional Hazards Model analysis, as above. The prognostic value of each biomarker and/or histological characteristic to identify the patients who suffered disease recurrence or death within ten years over the patients disease-free after 10 years was calculated. The biomarkers of interest (SLPI, src, PSMB9, p21ras, E2F1, and MUC-1) exhibited statistically significant prognostic utility with a p value of 0.0220. The results of the Cox Proportional Hazard analysis are summarized below in Table 47.
TABLE-US-00050 TABLE 47 Results of Cox Proportional Hazard Analysis with Chemo-Naive Patient Population (SLPI, src, PSMB9, p21ras, E2F1, and MUC-1 Biomarker Panel) 95% Hazard Ratio Hazard Confidence Variable P Value Ratio Limits Age at Diagnosis 0.0523 1.032 1.000 1.066 Tumor Size 0.0180 1.319 1.049 1.658 Her2 0.2619 0.640 0.293 1.396 ER 0.4539 1.359 0.609 3.035 Total Grade 0.7693 1.075 0.661 1.749 Biomarkers (SLPI, src, 0.0220 1.335 1.042 1.709 PSMB9, p21ras, and E2F1 Biomarker Panel)
The prognostic performance of the SLPI, src, PSMB9, p21ras, E2F1, and MUC-1 biomarker panel is graphically presented in the Kaplan-Meier plot of FIG. 5. The x-axis represents years from initial diagnosis, and the y axis is the percentage of disease-free survival. This plot demonstrates the ability of this biomarker panel to risk stratify this early stage breast cancer patient population for disease recurrence and/or death due to primary disease. The risk of reoccurrence and/or death due to primary disease increases as the number of biomarkers that are overexpressed in the patient samples increases. The disease-free survival rates of the patient subgroups identified by the number of overexpressed biomarkers are statistically significant from each other with a p value of <0.0065, as determined by log-rank test for comparison of 0 positive, 1 positive, 2 positive, 3 or more positive biomarker groups. As described above, a biomarker that is classified as overexpressed by the imaging analyses described herein is deemed "positive."
TABLE-US-00051 TABLE 48 Biomarker Nucleotide and Amino Acid Sequence Information Nucleotide Sequence Amino Acid Sequence Biomarker Sequence Sequence Name Accession No. Identifier Accession No. Identifier SLPI NM_003064 SEQ ID NO: 1 NP_003055 SEQ ID NO: 2 DARPP-32 NM_032192 SEQ ID NO: 3 NP_115568 SEQ ID NO: 4 MGC14832 NM_032339 SEQ ID NO: 5 NP_115715 SEQ ID NO: 6 NDRG-1 NM_006096 SEQ ID NO: 7 NP_006087 SEQ ID NO: 8 PSMB9 NM_002800 SEQ ID NO: 9 NP_002791 SEQ ID NO: 10 p27 NM_004064 SEQ ID NO: 11 NP_004055 SEQ ID NO: 12 E2F1 NM_005225 SEQ ID NO: 13 NP_005216 SEQ ID NO: 14 MCM6 NM_005915 SEQ ID NO: 15 NP_005906 SEQ ID NO: 16 MCM2 D83987 SEQ ID NO: 17 BAA12177 SEQ ID NO: 18 MUC-1 NM_182741 SEQ ID NO: 19 NP_877418 SEQ ID NO: 20 p21ras NM_005343 SEQ ID NO: 21 NP_005334 SEQ ID NO: 22 Src NM_005417 SEQ ID NO: 23 NP_005408 SEQ ID NO: 24 TGF-beta3 BC018503 SEQ ID NO: 25 AAH18503 SEQ ID NO: 26 PDGFRalpha M21574 SEQ ID NO: 27 AAA96715 SEQ ID NO: 28 Myc V00568 SEQ ID NO: 29 CAA23831 SEQ ID NO: 30 SERHL NM_014509 SEQ ID NO: 31 NP_055324 SEQ ID NO: 32
All publications and patent applications mentioned in the specification are indicative of the level of those skilled in the art to which this invention pertains. All publications and patent applications are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.
Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it will be obvious that certain changes and modifications may be practiced within the scope of the appended claims.
411598DNAHomo sapiensCDS(23)...(421) 1cagagtcact cctgccttca cc atg aag tcc agc ggc ctc ttc ccc ttc ctg 52Met Lys Ser Ser Gly Leu Phe Pro Phe Leu1 5 10gtg ctg ctt gcc ctg gga act ctg gca cct tgg gct gtg gaa ggc tct 100Val Leu Leu Ala Leu Gly Thr Leu Ala Pro Trp Ala Val Glu Gly Ser15 20 25gga aag tcc ttc aaa gct gga gtc tgt cct cct aag aaa tct gcc cag 148Gly Lys Ser Phe Lys Ala Gly Val Cys Pro Pro Lys Lys Ser Ala Gln30 35 40tgc ctt aga tac aag aaa cct gag tgc cag agt gac tgg cag tgt cca 196Cys Leu Arg Tyr Lys Lys Pro Glu Cys Gln Ser Asp Trp Gln Cys Pro45 50 55ggg aag aag aga tgt tgt cct gac act tgt ggc atc aaa tgc ctg gat 244Gly Lys Lys Arg Cys Cys Pro Asp Thr Cys Gly Ile Lys Cys Leu Asp60 65 70cct gtt gac acc cca aac cca aca agg agg aag cct ggg aag tgc cca 292Pro Val Asp Thr Pro Asn Pro Thr Arg Arg Lys Pro Gly Lys Cys Pro75 80 85 90gtg act tat ggc caa tgt ttg atg ctt aac ccc ccc aat ttc tgt gag 340Val Thr Tyr Gly Gln Cys Leu Met Leu Asn Pro Pro Asn Phe Cys Glu95 100 105atg gat ggc cag tgc aag cgt gac ttg aag tgt tgc atg ggc atg tgt 388Met Asp Gly Gln Cys Lys Arg Asp Leu Lys Cys Cys Met Gly Met Cys110 115 120ggg aaa tcc tgc gtt tcc cct gtg aaa gct tga ttcctgccat atggaggagg 441Gly Lys Ser Cys Val Ser Pro Val Lys Ala *125 130ctctggagtc ctgctctgtg tggtccaggt cctttccacc ctgagacttg gctccaccac 501tgatatcctc ctttggggaa aggcttggca cacagcaggc tttcaagaag tgccagttga 561tcaatgaata aataaacgag cctatttctc tttgcac 5982132PRTHomo sapiens 2Met Lys Ser Ser Gly Leu Phe Pro Phe Leu Val Leu Leu Ala Leu Gly1 5 10 15Thr Leu Ala Pro Trp Ala Val Glu Gly Ser Gly Lys Ser Phe Lys Ala20 25 30Gly Val Cys Pro Pro Lys Lys Ser Ala Gln Cys Leu Arg Tyr Lys Lys35 40 45Pro Glu Cys Gln Ser Asp Trp Gln Cys Pro Gly Lys Lys Arg Cys Cys50 55 60Pro Asp Thr Cys Gly Ile Lys Cys Leu Asp Pro Val Asp Thr Pro Asn65 70 75 80Pro Thr Arg Arg Lys Pro Gly Lys Cys Pro Val Thr Tyr Gly Gln Cys85 90 95Leu Met Leu Asn Pro Pro Asn Phe Cys Glu Met Asp Gly Gln Cys Lys100 105 110Arg Asp Leu Lys Cys Cys Met Gly Met Cys Gly Lys Ser Cys Val Ser115 120 125Pro Val Lys Ala13031513DNAHomo sapiensCDS(236)...(742) 3attcacttct cacaaggact gggtgaagag ttctgcagcc ttacagagac tggaaaagaa 60gcccaaacca aggcccccag agaggtcccc caggcccctt tgggtccctg agcctcagct 120ggaggtgggg ggtgcctgca gtgcgctggc tcagtctcct tctgaaaagc tggatccagc 180ttgtttgaag cccttgagct gatcttagat ccggcgcagg agaccaacgc ctgcc atg 238Met1ctg ttc cgg ctc tca gag cac tcc tca cca gag gag gaa gcc tcc ccc 286Leu Phe Arg Leu Ser Glu His Ser Ser Pro Glu Glu Glu Ala Ser Pro5 10 15cac cag aga gcc tca gga gag ggg cac cat ctc aag tcg aag aga ccc 334His Gln Arg Ala Ser Gly Glu Gly His His Leu Lys Ser Lys Arg Pro20 25 30aac ccc tgt gcc tac aca cca cct tcg ctg aaa gct gtg cag cgc att 382Asn Pro Cys Ala Tyr Thr Pro Pro Ser Leu Lys Ala Val Gln Arg Ile35 40 45gct gag tct cac ctg cag tct atc agc aat ttg aat gag aac cag gcc 430Ala Glu Ser His Leu Gln Ser Ile Ser Asn Leu Asn Glu Asn Gln Ala50 55 60 65tca gag gag gag gat gag ctg ggg gag ctt cgg gag ctg ggt tat cca 478Ser Glu Glu Glu Asp Glu Leu Gly Glu Leu Arg Glu Leu Gly Tyr Pro70 75 80aga gag gaa gat gag gag gaa gag gag gat gat gaa gaa gag gaa gaa 526Arg Glu Glu Asp Glu Glu Glu Glu Glu Asp Asp Glu Glu Glu Glu Glu85 90 95gaa gag gac agc cag gct gaa gtc ctg aag gtc atc agg cag tct gct 574Glu Glu Asp Ser Gln Ala Glu Val Leu Lys Val Ile Arg Gln Ser Ala100 105 110ggg caa aag aca acc tgt ggc cag ggt ctg gaa ggg ccc tgg gag cgc 622Gly Gln Lys Thr Thr Cys Gly Gln Gly Leu Glu Gly Pro Trp Glu Arg115 120 125cca ccc cct ctg gat gag tcc gag aga gat gga ggc tct gag gac caa 670Pro Pro Pro Leu Asp Glu Ser Glu Arg Asp Gly Gly Ser Glu Asp Gln130 135 140 145gtg gaa gac cca gca cta agt gag cct ggg gag gaa cct cag cgc cct 718Val Glu Asp Pro Ala Leu Ser Glu Pro Gly Glu Glu Pro Gln Arg Pro150 155 160tcc ccc tct gag cct ggc aca tag gcacccagcc tgcatctccc aggaggaagt 772Ser Pro Ser Glu Pro Gly Thr *165ggaggggaca tcgctgttcc ccagaaaccc actctatcct caccctgttt tgtgctcttc 832ccctcgcctg ctagggctgc ggcttctgac ttctagaaga ctaaggctgg tctgtgtttg 892cttgtttgcc cacctttggc tgatacccag agaacctggg cacttgctgc ctgatgccca 952cccctgccag tcattcctcc attcacccag cgggaggtgg gatgtgagac agcccacatt 1012ggaaaatcca gaaaaccggg aacagggatt tgcccttcac aattctactc cccagatcct 1072ctcccctgga cacaggagac ccacagggca ggaccctaag atctggggaa aggaggtcct 1132gagaaccttg aggtaccctt agatcctttt ctacccactt tcctatggag gattccaagt 1192caccacttct ctcaccggct tctaccaggg tccaggacta aggcgttttt ctccatagcc 1252tcaacatttt gggaatcttc ccttaatcac ccttgctcct cctgggtgcc tggaagatgg 1312actggcagag acctctttgt tgcgttttgt gctttgatgc caggaatgcc gcctagttta 1372tgtccccggt ggggcacaca gcggggggcg ccaggttttc cttgtccccc agctgctctg 1432cccctttccc cttcttccct gactccaggc ctgaacccct cccgtgctgt aataaatctt 1492tgtaaataac aaaaaaaaaa a 15134168PRTHomo sapiens 4Met Leu Phe Arg Leu Ser Glu His Ser Ser Pro Glu Glu Glu Ala Ser1 5 10 15Pro His Gln Arg Ala Ser Gly Glu Gly His His Leu Lys Ser Lys Arg20 25 30Pro Asn Pro Cys Ala Tyr Thr Pro Pro Ser Leu Lys Ala Val Gln Arg35 40 45Ile Ala Glu Ser His Leu Gln Ser Ile Ser Asn Leu Asn Glu Asn Gln50 55 60Ala Ser Glu Glu Glu Asp Glu Leu Gly Glu Leu Arg Glu Leu Gly Tyr65 70 75 80Pro Arg Glu Glu Asp Glu Glu Glu Glu Glu Asp Asp Glu Glu Glu Glu85 90 95Glu Glu Glu Asp Ser Gln Ala Glu Val Leu Lys Val Ile Arg Gln Ser100 105 110Ala Gly Gln Lys Thr Thr Cys Gly Gln Gly Leu Glu Gly Pro Trp Glu115 120 125Arg Pro Pro Pro Leu Asp Glu Ser Glu Arg Asp Gly Gly Ser Glu Asp130 135 140Gln Val Glu Asp Pro Ala Leu Ser Glu Pro Gly Glu Glu Pro Gln Arg145 150 155 160Pro Ser Pro Ser Glu Pro Gly Thr1655748DNAHomo sapiensCDS(8)...(355) 5ggccgcg atg agc ggg gag ccg ggg cag acg tcc gta gcg ccc cct ccc 49Met Ser Gly Glu Pro Gly Gln Thr Ser Val Ala Pro Pro Pro1 5 10gag gag gtc gag ccg ggc agt ggg gtc cgc atc gtg gtg gag tac tgt 97Glu Glu Val Glu Pro Gly Ser Gly Val Arg Ile Val Val Glu Tyr Cys15 20 25 30gaa ccc tgc ggc ttc gag gcg acc tac ctg gag ctg gcc agt gct gtg 145Glu Pro Cys Gly Phe Glu Ala Thr Tyr Leu Glu Leu Ala Ser Ala Val35 40 45aag gag cag tat ccg ggc atc gag atc gag tcg cgc ctc ggg ggc aca 193Lys Glu Gln Tyr Pro Gly Ile Glu Ile Glu Ser Arg Leu Gly Gly Thr50 55 60ggt gcc ttt gag ata gag ata aat gga cag ctg gtg ttc tcc aag ctg 241Gly Ala Phe Glu Ile Glu Ile Asn Gly Gln Leu Val Phe Ser Lys Leu65 70 75gag aat ggg ggc ttt ccc tat gag aaa gat ctc att gag gcc atc cga 289Glu Asn Gly Gly Phe Pro Tyr Glu Lys Asp Leu Ile Glu Ala Ile Arg80 85 90aga gcc agt aat gga gaa acc cta gaa aag atc acc aac agc cgt cct 337Arg Ala Ser Asn Gly Glu Thr Leu Glu Lys Ile Thr Asn Ser Arg Pro95 100 105 110ccc tgc gtc atc ctg tga ctgcacagga ctctgggttc ctgctctgtt 385Pro Cys Val Ile Leu *115ctggggtcca aaccttggtc tccctttggt cctgctggga gctccccctg cctctttccc 445ctacttagct ccttagcaaa gagaccctgg cctccacttt gccctttggg tacaaagaag 505gaatagaaga ttccgtggcc ttgggggcag gagagagaca ctctccatga acacttctcc 565agccacctca tacccccttc ccagggtaag tgcccacgaa agcccagtcc actcttcgcc 625tcggtaatac ctgtctgatg ccacagattt tatttattct cccctaaccc agggcaatgt 685cagctattgg cagtaaagtg gcgctacaaa cactaaaaaa aaaaaaaaaa aaaaaaaaaa 745aaa 7486115PRTHomo sapiens 6Met Ser Gly Glu Pro Gly Gln Thr Ser Val Ala Pro Pro Pro Glu Glu1 5 10 15Val Glu Pro Gly Ser Gly Val Arg Ile Val Val Glu Tyr Cys Glu Pro20 25 30Cys Gly Phe Glu Ala Thr Tyr Leu Glu Leu Ala Ser Ala Val Lys Glu35 40 45Gln Tyr Pro Gly Ile Glu Ile Glu Ser Arg Leu Gly Gly Thr Gly Ala50 55 60Phe Glu Ile Glu Ile Asn Gly Gln Leu Val Phe Ser Lys Leu Glu Asn65 70 75 80Gly Gly Phe Pro Tyr Glu Lys Asp Leu Ile Glu Ala Ile Arg Arg Ala85 90 95Ser Asn Gly Glu Thr Leu Glu Lys Ile Thr Asn Ser Arg Pro Pro Cys100 105 110Val Ile Leu11573020DNAHomo sapiensCDS(111)...(1295) 7tgaagctcgt cagttcacca tccgccctcg gcttccgcgg ggcgctgggc cgccagcctc 60ggcaccgtcc tttcctttct ccctcgcgtt aggcaggtga cagcagggac atg tct 116Met Ser1cgg gag atg cag gat gta gac ctc gct gag gtg aag cct ttg gtg gag 164Arg Glu Met Gln Asp Val Asp Leu Ala Glu Val Lys Pro Leu Val Glu5 10 15aaa ggg gag acc atc acc ggc ctc ctg caa gag ttt gat gtc cag gag 212Lys Gly Glu Thr Ile Thr Gly Leu Leu Gln Glu Phe Asp Val Gln Glu20 25 30cag gac atc gag act tta cat ggc tct gtt cac gtc acg ctg tgt ggg 260Gln Asp Ile Glu Thr Leu His Gly Ser Val His Val Thr Leu Cys Gly35 40 45 50act ccc aag gga aac cgg cct gtc atc ctc acc tac cat gac atc ggc 308Thr Pro Lys Gly Asn Arg Pro Val Ile Leu Thr Tyr His Asp Ile Gly55 60 65atg aac cac aaa acc tgc tac aac ccc ctc ttc aac tac gag gac atg 356Met Asn His Lys Thr Cys Tyr Asn Pro Leu Phe Asn Tyr Glu Asp Met70 75 80cag gag atc acc cag cac ttt gcc gtc tgc cac gtg gac gcc cct ggc 404Gln Glu Ile Thr Gln His Phe Ala Val Cys His Val Asp Ala Pro Gly85 90 95cag cag gac ggc gca gcc tcc ttc ccc gca ggg tac atg tac ccc tcc 452Gln Gln Asp Gly Ala Ala Ser Phe Pro Ala Gly Tyr Met Tyr Pro Ser100 105 110atg gat cag ctg gct gaa atg ctt cct gga gtc ctt caa cag ttt ggg 500Met Asp Gln Leu Ala Glu Met Leu Pro Gly Val Leu Gln Gln Phe Gly115 120 125 130ctg aaa agc att att ggc atg gga aca gga gca ggc gcc tac acc cta 548Leu Lys Ser Ile Ile Gly Met Gly Thr Gly Ala Gly Ala Tyr Thr Leu135 140 145act cga ttt gct cta aac aac cct gag atg gtg gag ggc ctt gtc ctt 596Thr Arg Phe Ala Leu Asn Asn Pro Glu Met Val Glu Gly Leu Val Leu150 155 160atc aac gtg aac cct tgt gcg gaa ggc tgg atg gac tgg gcc gcc tcc 644Ile Asn Val Asn Pro Cys Ala Glu Gly Trp Met Asp Trp Ala Ala Ser165 170 175aag atc tca gga tgg acc caa gct ctg ccg gac atg gtg gtg tcc cac 692Lys Ile Ser Gly Trp Thr Gln Ala Leu Pro Asp Met Val Val Ser His180 185 190ctt ttt ggg aag gaa gaa atg cag agt aac gtg gaa gtg gtc cac acc 740Leu Phe Gly Lys Glu Glu Met Gln Ser Asn Val Glu Val Val His Thr195 200 205 210tac cgc cag cac att gtg aat gac atg aac ccc ggc aac ctg cac ctg 788Tyr Arg Gln His Ile Val Asn Asp Met Asn Pro Gly Asn Leu His Leu215 220 225ttc atc aat gcc tac aac agc cgg cgc gac ctg gag att gag cga cca 836Phe Ile Asn Ala Tyr Asn Ser Arg Arg Asp Leu Glu Ile Glu Arg Pro230 235 240atg ccg gga acc cac aca gtc acc ctg cag tgc cct gct ctg ttg gtg 884Met Pro Gly Thr His Thr Val Thr Leu Gln Cys Pro Ala Leu Leu Val245 250 255gtt ggg gac agc tcg cct gca gtg gat gcc gtg gtg gag tgc aac tca 932Val Gly Asp Ser Ser Pro Ala Val Asp Ala Val Val Glu Cys Asn Ser260 265 270aaa ttg gac cca aca aag acc act ctc ctc aag atg gcg gac tgt ggc 980Lys Leu Asp Pro Thr Lys Thr Thr Leu Leu Lys Met Ala Asp Cys Gly275 280 285 290ggc ctc ccg cag atc tcc cag ccg gcc aag ctc gct gag gcc ttc aag 1028Gly Leu Pro Gln Ile Ser Gln Pro Ala Lys Leu Ala Glu Ala Phe Lys295 300 305tac ttc gtg cag ggc atg gga tac atg ccc tcg gct agc atg acc cgc 1076Tyr Phe Val Gln Gly Met Gly Tyr Met Pro Ser Ala Ser Met Thr Arg310 315 320ctg atg cgg tcc cgc aca gcc tct ggt tcc agc gtc act tct ctg gat 1124Leu Met Arg Ser Arg Thr Ala Ser Gly Ser Ser Val Thr Ser Leu Asp325 330 335ggc acc cgc agc cgc tcc cac acc agc gag ggc acc cga agc cgc tcc 1172Gly Thr Arg Ser Arg Ser His Thr Ser Glu Gly Thr Arg Ser Arg Ser340 345 350cac acc agc gag ggc acc cgc agc cgc tcg cac acc agc gag ggg gcc 1220His Thr Ser Glu Gly Thr Arg Ser Arg Ser His Thr Ser Glu Gly Ala355 360 365 370cac ctg gac atc acc ccc aac tcg ggt gct gct ggg aac agc gcc ggg 1268His Leu Asp Ile Thr Pro Asn Ser Gly Ala Ala Gly Asn Ser Ala Gly375 380 385ccc aag tcc atg gag gtc tcc tgc tag gcggcctgcc cagctgccgc 1315Pro Lys Ser Met Glu Val Ser Cys *390ccccggactc tgatctctgt agtggccccc tcctccccgg ccccttttcg ccccctgcct 1375gccatactgc gcctaactcg gtattaatcc aaagcttatt ttgtaagagt gagctctggt 1435ggagacaaat gaggtctatt acgtgggtgc cctctccaaa ggcggggtgg cggtggacca 1495aaggaaggaa gcaagcatct ccgcatcgca tcctcttcca ttaaccagtg gccggttgcc 1555actctcctcc cctccctcag agacaccaaa ctgccaaaaa caagacgcgt agcagcacac 1615acttcacaaa gccaagccta ggccgccctg agcatcctgg ttcaaacggg tgcctggtca 1675gaaggccagc cgcccacttc ccgtttcctc tttaactgag gagaagctga tccagctttc 1735cggaaacaaa atccttttct tcatttgggg aggggggtaa tagtgacatg caggcacctc 1795ttttaaacag gcaaaacagg aagggggaaa aggtgggatt catgtcgagg ctagaggcat 1855ttggaacaac aaatctacgt agttaacttg aagaaaccga tttttaaagt tggtgcatct 1915agaaagcttt gaatgcagaa gcaaacaagc ttgatttttc tagcatcctc ttaatgtgca 1975gcaaaagcag gcaacaaaat ctcctggctt tacagacaaa aatatttcag caaacgttgg 2035gcatcatggt ttttgaaggc tttagttctg ctttctgcct ctcctccaca gccccaacct 2095cccacccctg atacatgagc cagtgattat tcttgttcag ggagaagatc atttagattt 2155gttttgcatt ccttagaatg gagggcaaca ttccacagct gccctggctg tgatgagtgt 2215ccttgcaggg gccggagtag gagcactggg gtgggggcgg aattggggtt actcgatgta 2275agggattcct tgttgttgtg ttgagatcca gtgcagttgt gatttctgtg gatcccagct 2335tggtccagga attttgagag attggcttaa atccagtttt caatcttcga cagctgggct 2395ggaacgtgaa ctcagtagct gaacctgtct gacccggtca cgttcttgga tcctcagaac 2455tctttgctct tgtcggggtg ggggtgggaa ctcacgtggg gagcggtggc tgagaaaatg 2515taaggattct ggaatacata ttccatggac tttccttccc tctcctgctt cctcttttcc 2575tgctccctaa cctttcgccg aatggggcag acaaacactg acgtttctgg gtggccagtg 2635cggctgccag gttcctgtac tactgccttg tacttttcat tttggctcac cgtggatttt 2695ctcataggaa gtttggtcag agtgaattga atattgtaag tcagccactg ggacccgagg 2755atttctggga ccccgcagtt gggaggagga agtagtccag ccttccaggt gggcgtgaga 2815ggcaatgact cgttacctgc cgcccatcac cttggaggcc ttccctggcc ttgagtagaa 2875aagtcgggga tcggggcaag agaggctgag tacggatggg aaactattgt gcacaagtct 2935ttccagagga gtttcttaat gagatatttg tatttatttc cagaccaata aatttgtaac 2995tttgcaaaaa aaaaaaaaaa aaaaa 30208394PRTHomo sapiens 8Met Ser Arg Glu Met Gln Asp Val Asp Leu Ala Glu Val Lys Pro Leu1 5 10 15Val Glu Lys Gly Glu Thr Ile Thr Gly Leu Leu Gln Glu Phe Asp Val20 25 30Gln Glu Gln Asp Ile Glu Thr Leu His Gly Ser Val His Val Thr Leu35 40 45Cys Gly Thr Pro Lys Gly Asn Arg Pro Val Ile Leu Thr Tyr His Asp50 55 60Ile Gly Met Asn His Lys Thr Cys Tyr Asn Pro Leu Phe Asn Tyr Glu65 70 75 80Asp Met Gln Glu Ile Thr Gln His Phe Ala Val Cys His Val Asp Ala85 90 95Pro Gly Gln Gln Asp Gly Ala Ala Ser Phe Pro Ala Gly Tyr Met Tyr100 105 110Pro Ser Met Asp Gln Leu Ala Glu Met Leu Pro Gly Val Leu Gln Gln115 120 125Phe Gly Leu Lys Ser Ile Ile Gly Met Gly Thr Gly Ala Gly Ala Tyr130 135 140Thr Leu Thr Arg Phe Ala Leu Asn Asn Pro Glu Met Val Glu Gly Leu145 150 155 160Val Leu Ile Asn Val Asn Pro Cys Ala Glu Gly Trp Met Asp Trp Ala165 170 175Ala Ser Lys Ile Ser Gly Trp Thr Gln Ala Leu Pro Asp Met Val Val180 185 190Ser His Leu Phe Gly Lys Glu Glu Met Gln Ser Asn Val Glu Val Val195 200 205His Thr Tyr Arg Gln His Ile Val Asn Asp Met Asn Pro Gly Asn Leu210 215 220His Leu Phe Ile Asn Ala Tyr Asn Ser Arg Arg Asp Leu Glu Ile Glu225
230 235 240Arg Pro Met Pro Gly Thr His Thr Val Thr Leu Gln Cys Pro Ala Leu245 250 255Leu Val Val Gly Asp Ser Ser Pro Ala Val Asp Ala Val Val Glu Cys260 265 270Asn Ser Lys Leu Asp Pro Thr Lys Thr Thr Leu Leu Lys Met Ala Asp275 280 285Cys Gly Gly Leu Pro Gln Ile Ser Gln Pro Ala Lys Leu Ala Glu Ala290 295 300Phe Lys Tyr Phe Val Gln Gly Met Gly Tyr Met Pro Ser Ala Ser Met305 310 315 320Thr Arg Leu Met Arg Ser Arg Thr Ala Ser Gly Ser Ser Val Thr Ser325 330 335Leu Asp Gly Thr Arg Ser Arg Ser His Thr Ser Glu Gly Thr Arg Ser340 345 350Arg Ser His Thr Ser Glu Gly Thr Arg Ser Arg Ser His Thr Ser Glu355 360 365Gly Ala His Leu Asp Ile Thr Pro Asn Ser Gly Ala Ala Gly Asn Ser370 375 380Ala Gly Pro Lys Ser Met Glu Val Ser Cys385 3909778DNAHomo sapiensCDS(52)...(711) 9caggttggaa accagtgccc caggcggcga ggagagcggt gccttgcagg g atg ctg 57Met Leu1cgg gcg gga gca cca acc ggg gac tta ccc cgg gcg gga gaa gtc cac 105Arg Ala Gly Ala Pro Thr Gly Asp Leu Pro Arg Ala Gly Glu Val His5 10 15acc ggg acc acc atc atg gca gtg gag ttt gac ggg ggc gtt gtg atg 153Thr Gly Thr Thr Ile Met Ala Val Glu Phe Asp Gly Gly Val Val Met20 25 30ggt tct gat tcc cga gtg tct gca ggc gag gcg gtg gtg aac cga gtg 201Gly Ser Asp Ser Arg Val Ser Ala Gly Glu Ala Val Val Asn Arg Val35 40 45 50ttt gac aag ctg tcc ccg ctg cac gag cgc atc tac tgt gca ctc tct 249Phe Asp Lys Leu Ser Pro Leu His Glu Arg Ile Tyr Cys Ala Leu Ser55 60 65ggt tca gct gct gat gcc caa gcc gtg gcc gac atg gcc gcc tac cag 297Gly Ser Ala Ala Asp Ala Gln Ala Val Ala Asp Met Ala Ala Tyr Gln70 75 80ctg gag ctc cat ggg ata gaa ctg gag gaa cct cca ctt gtt ttg gct 345Leu Glu Leu His Gly Ile Glu Leu Glu Glu Pro Pro Leu Val Leu Ala85 90 95gct gca aat gtg gtg aga aat atc agc tat aaa tat cga gag gac ttg 393Ala Ala Asn Val Val Arg Asn Ile Ser Tyr Lys Tyr Arg Glu Asp Leu100 105 110tct gca cat ctc atg gta gct ggc tgg gac caa cgt gaa gga ggt cag 441Ser Ala His Leu Met Val Ala Gly Trp Asp Gln Arg Glu Gly Gly Gln115 120 125 130gta tat gga acc ctg gga gga atg ctg act cga cag cct ttt gcc att 489Val Tyr Gly Thr Leu Gly Gly Met Leu Thr Arg Gln Pro Phe Ala Ile135 140 145ggt ggc tcc ggc agc acc ttt atc tat ggt tat gtg gat gca gca tat 537Gly Gly Ser Gly Ser Thr Phe Ile Tyr Gly Tyr Val Asp Ala Ala Tyr150 155 160aag cca ggc atg tct ccc gag gag tgc agg cgc ttc acc aca gac gct 585Lys Pro Gly Met Ser Pro Glu Glu Cys Arg Arg Phe Thr Thr Asp Ala165 170 175att gct ctg gcc atg agc cgg gat ggc tca agc ggg ggt gtc atc tac 633Ile Ala Leu Ala Met Ser Arg Asp Gly Ser Ser Gly Gly Val Ile Tyr180 185 190ctg gtc act att aca gct gcc ggt gtg gac cat cga gtc atc ttg ggc 681Leu Val Thr Ile Thr Ala Ala Gly Val Asp His Arg Val Ile Leu Gly195 200 205 210aat gaa ctg cca aaa ttc tat gat gag tga accttcccca gacttctctt 731Asn Glu Leu Pro Lys Phe Tyr Asp Glu *215tcttattttg taataaactc tctagggcca aaaaaaaaaa aaaaaaa 77810219PRTHomo sapiens 10Met Leu Arg Ala Gly Ala Pro Thr Gly Asp Leu Pro Arg Ala Gly Glu1 5 10 15Val His Thr Gly Thr Thr Ile Met Ala Val Glu Phe Asp Gly Gly Val20 25 30Val Met Gly Ser Asp Ser Arg Val Ser Ala Gly Glu Ala Val Val Asn35 40 45Arg Val Phe Asp Lys Leu Ser Pro Leu His Glu Arg Ile Tyr Cys Ala50 55 60Leu Ser Gly Ser Ala Ala Asp Ala Gln Ala Val Ala Asp Met Ala Ala65 70 75 80Tyr Gln Leu Glu Leu His Gly Ile Glu Leu Glu Glu Pro Pro Leu Val85 90 95Leu Ala Ala Ala Asn Val Val Arg Asn Ile Ser Tyr Lys Tyr Arg Glu100 105 110Asp Leu Ser Ala His Leu Met Val Ala Gly Trp Asp Gln Arg Glu Gly115 120 125Gly Gln Val Tyr Gly Thr Leu Gly Gly Met Leu Thr Arg Gln Pro Phe130 135 140Ala Ile Gly Gly Ser Gly Ser Thr Phe Ile Tyr Gly Tyr Val Asp Ala145 150 155 160Ala Tyr Lys Pro Gly Met Ser Pro Glu Glu Cys Arg Arg Phe Thr Thr165 170 175Asp Ala Ile Ala Leu Ala Met Ser Arg Asp Gly Ser Ser Gly Gly Val180 185 190Ile Tyr Leu Val Thr Ile Thr Ala Ala Gly Val Asp His Arg Val Ile195 200 205Leu Gly Asn Glu Leu Pro Lys Phe Tyr Asp Glu210 215112422DNAHomo sapiensCDS(466)...(1062) 11gtcagcctcc cttccaccgc catattgggc cactaaaaaa agggggctcg tcttttcggg 60gtgtttttct ccccctcccc tgtccccgct tgctcacggc tctgcgactc cgacgccggc 120aaggtttgga gagcggctgg gttcgcggga cccgcgggct tgcacccgcc cagactcgga 180cgggctttgc caccctctcc gcttgcctgg tcccctctcc tctccgccct cccgctcgcc 240agtccatttg atcagcggag actcggcggc cgggccgggg cttccccgca gcccctgcgc 300gctcctagag ctcgggccgt ggctcgtcgg ggtctgtgtc ttttggctcc gagggcagtc 360gctgggcttc cgagaggggt tcgggccgcg taggggcgct ttgttttgtt cggttttgtt 420tttttgagag tgcgagagag gcggtcgtgc agacccggga gaaag atg tca aac gtg 477Met Ser Asn Val1cga gtg tct aac ggg agc cct agc ctg gag cgg atg gac gcc agg cag 525Arg Val Ser Asn Gly Ser Pro Ser Leu Glu Arg Met Asp Ala Arg Gln5 10 15 20gcg gag cac ccc aag ccc tcg gcc tgc agg aac ctc ttc ggc ccg gtg 573Ala Glu His Pro Lys Pro Ser Ala Cys Arg Asn Leu Phe Gly Pro Val25 30 35gac cac gaa gag tta acc cgg gac ttg gag aag cac tgc aga gac atg 621Asp His Glu Glu Leu Thr Arg Asp Leu Glu Lys His Cys Arg Asp Met40 45 50gaa gag gcg agc cag cgc aag tgg aat ttc gat ttt cag aat cac aaa 669Glu Glu Ala Ser Gln Arg Lys Trp Asn Phe Asp Phe Gln Asn His Lys55 60 65ccc cta gag ggc aag tac gag tgg caa gag gtg gag aag ggc agc ttg 717Pro Leu Glu Gly Lys Tyr Glu Trp Gln Glu Val Glu Lys Gly Ser Leu70 75 80ccc gag ttc tac tac aga ccc ccg cgg ccc ccc aaa ggt gcc tgc aag 765Pro Glu Phe Tyr Tyr Arg Pro Pro Arg Pro Pro Lys Gly Ala Cys Lys85 90 95 100gtg ccg gcg cag gag agc cag gat gtc agc ggg agc cgc ccg gcg gcg 813Val Pro Ala Gln Glu Ser Gln Asp Val Ser Gly Ser Arg Pro Ala Ala105 110 115cct tta att ggg gct ccg gct aac tct gag gac acg cat ttg gtg gac 861Pro Leu Ile Gly Ala Pro Ala Asn Ser Glu Asp Thr His Leu Val Asp120 125 130cca aag act gat ccg tcg gac agc cag acg ggg tta gcg gag caa tgc 909Pro Lys Thr Asp Pro Ser Asp Ser Gln Thr Gly Leu Ala Glu Gln Cys135 140 145gca gga ata agg aag cga cct gca acc gac gat tct tct act caa aac 957Ala Gly Ile Arg Lys Arg Pro Ala Thr Asp Asp Ser Ser Thr Gln Asn150 155 160aaa aga gcc aac aga aca gaa gaa aat gtt tca gac ggt tcc cca aat 1005Lys Arg Ala Asn Arg Thr Glu Glu Asn Val Ser Asp Gly Ser Pro Asn165 170 175 180gcc ggt tct gtg gag cag acg ccc aag aag cct ggc ctc aga aga cgt 1053Ala Gly Ser Val Glu Gln Thr Pro Lys Lys Pro Gly Leu Arg Arg Arg185 190 195caa acg taa acagctcgaa ttaagaatat gtttccttgt ttatcagata 1102Gln Thr *catcactgct tgatgaagca aggaagatat acatgaaaat tttaaaaata catatcgctg 1162acttcatgga atggacatcc tgtataagca ctgaaaaaca acaacacaat aacactaaaa 1222ttttaggcac tcttaaatga tctgcctcta aaagcgttgg atgtagcatt atgcaattag 1282gtttttcctt atttgcttca ttgtactacc tgtgtatata gtttttacct tttatgtagc 1342acataaactt tggggaaggg agggcagggt ggggctgagg aactgacgtg gagcggggta 1402tgaagagctt gctttgattt acagcaagta gataaatatt tgacttgcat gaagagaagc 1462aattttgggg aagggtttga attgttttct ttaaagatgt aatgtccctt tcagagacag 1522ctgatacttc atttaaaaaa atcacaaaaa tttgaacact ggctaaagat aattgctatt 1582tatttttaca agaagtttat tctcatttgg gagatctggt gatctcccaa gctatctaaa 1642gtttgttaga tagctgcatg tggctttttt aaaaaagcaa cagaaaccta tcctcactgc 1702cctccccagt ctctcttaaa gttggaattt accagttaat tactcagcag aatggtgatc 1762actccaggta gtttggggca aaaatccgag gtgcttggga gttttgaatg ttaagaattg 1822accatctgct tttattaaat ttgttgacaa aattttctca ttttcttttc acttcgggct 1882gtgtaaacac agtcaaaata attctaaatc cctcgatatt tttaaagatc tgtaagtaac 1942ttcacattaa aaaatgaaat attttttaat ttaaagctta ctctgtccat ttatccacag 2002gaaagtgtta tttttaaagg aaggttcatg tagagaaaag cacacttgta ggataagtga 2062aatggatact acatctttaa acagtatttc attgcctgtg tatggaaaaa ccatttgaag 2122tgtacctgtg tacataactc tgtaaaaaca ctgaaaaatt atactaactt atttatgtta 2182aaagattttt tttaatctag acaatataca agccaaagtg gcatgttttg tgcatttgta 2242aatgctgtgt tgggtagaat aggttttccc ctcttttgtt aaataatatg gctatgctta 2302aaaggttgca tactgagcca agtataattt tttgtaatgt gtgaaaaaga tgccaattat 2362tgttacacat taagtaatca ataaagaaaa cttccatagc taaaaaaaaa aaaaaaaaaa 242212198PRTHomo sapiens 12Met Ser Asn Val Arg Val Ser Asn Gly Ser Pro Ser Leu Glu Arg Met1 5 10 15Asp Ala Arg Gln Ala Glu His Pro Lys Pro Ser Ala Cys Arg Asn Leu20 25 30Phe Gly Pro Val Asp His Glu Glu Leu Thr Arg Asp Leu Glu Lys His35 40 45Cys Arg Asp Met Glu Glu Ala Ser Gln Arg Lys Trp Asn Phe Asp Phe50 55 60Gln Asn His Lys Pro Leu Glu Gly Lys Tyr Glu Trp Gln Glu Val Glu65 70 75 80Lys Gly Ser Leu Pro Glu Phe Tyr Tyr Arg Pro Pro Arg Pro Pro Lys85 90 95Gly Ala Cys Lys Val Pro Ala Gln Glu Ser Gln Asp Val Ser Gly Ser100 105 110Arg Pro Ala Ala Pro Leu Ile Gly Ala Pro Ala Asn Ser Glu Asp Thr115 120 125His Leu Val Asp Pro Lys Thr Asp Pro Ser Asp Ser Gln Thr Gly Leu130 135 140Ala Glu Gln Cys Ala Gly Ile Arg Lys Arg Pro Ala Thr Asp Asp Ser145 150 155 160Ser Thr Gln Asn Lys Arg Ala Asn Arg Thr Glu Glu Asn Val Ser Asp165 170 175Gly Ser Pro Asn Ala Gly Ser Val Glu Gln Thr Pro Lys Lys Pro Gly180 185 190Leu Arg Arg Arg Gln Thr195132486DNAHomo sapiensCDS(124)...(1437) 13ccgggacttt gcaggcagcg gcggccgggg gcggagcggg atcgagccct cgccgaggcc 60tgccgccatg ggcccgcgcc gccgccgccg cctgtcaccc gggccgcgcg ggccgtgagc 120gtc atg gcc ttg gcc ggg gcc cct gcg ggc ggc cca tgc gcg ccg gcg 168Met Ala Leu Ala Gly Ala Pro Ala Gly Gly Pro Cys Ala Pro Ala1 5 10 15ctg gag gcc ctg ctc ggg gcc ggc gcg ctg cgg ctg ctc gac tcc tcg 216Leu Glu Ala Leu Leu Gly Ala Gly Ala Leu Arg Leu Leu Asp Ser Ser20 25 30cag atc gtc atc atc tcc gcc gcg cag gac gcc agc gcc ccg ccg gct 264Gln Ile Val Ile Ile Ser Ala Ala Gln Asp Ala Ser Ala Pro Pro Ala35 40 45ccc acc ggc ccc gcg gcg ccc gcc gcc ggc ccc tgc gac cct gac ctg 312Pro Thr Gly Pro Ala Ala Pro Ala Ala Gly Pro Cys Asp Pro Asp Leu50 55 60ctg ctc ttc gcc aca ccg cag gcg ccc cgg ccc aca ccc agt gcg ccg 360Leu Leu Phe Ala Thr Pro Gln Ala Pro Arg Pro Thr Pro Ser Ala Pro65 70 75cgg ccc gcg ctc ggc cgc ccg ccg gtg aag cgg agg ctg gac ctg gaa 408Arg Pro Ala Leu Gly Arg Pro Pro Val Lys Arg Arg Leu Asp Leu Glu80 85 90 95act gac cat cag tac ctg gcc gag agc agt ggg cca gct cgg ggc aga 456Thr Asp His Gln Tyr Leu Ala Glu Ser Ser Gly Pro Ala Arg Gly Arg100 105 110ggc cgc cat cca gga aaa ggt gtg aaa tcc ccg ggg gag aag tca cgc 504Gly Arg His Pro Gly Lys Gly Val Lys Ser Pro Gly Glu Lys Ser Arg115 120 125tat gag acc tca ctg aat ctg acc acc aag cgc ttc ctg gag ctg ctg 552Tyr Glu Thr Ser Leu Asn Leu Thr Thr Lys Arg Phe Leu Glu Leu Leu130 135 140agc cac tcg gct gac ggt gtc gtc gac ctg aac tgg gct gcc gag gtg 600Ser His Ser Ala Asp Gly Val Val Asp Leu Asn Trp Ala Ala Glu Val145 150 155ctg aag gtg cag aag cgg cgc atc tat gac atc acc aac gtc ctt gag 648Leu Lys Val Gln Lys Arg Arg Ile Tyr Asp Ile Thr Asn Val Leu Glu160 165 170 175ggc atc cag ctc att gcc aag aag tcc aag aac cac atc cag tgg ctg 696Gly Ile Gln Leu Ile Ala Lys Lys Ser Lys Asn His Ile Gln Trp Leu180 185 190ggc agc cac acc aca gtg ggc gtc ggc gga cgg ctt gag ggg ttg acc 744Gly Ser His Thr Thr Val Gly Val Gly Gly Arg Leu Glu Gly Leu Thr195 200 205cag gac ctc cga cag ctg cag gag agc gag cag cag ctg gac cac ctg 792Gln Asp Leu Arg Gln Leu Gln Glu Ser Glu Gln Gln Leu Asp His Leu210 215 220atg aat atc tgt act acg cag ctg cgc ctg ctc tcc gag gac act gac 840Met Asn Ile Cys Thr Thr Gln Leu Arg Leu Leu Ser Glu Asp Thr Asp225 230 235agc cag cgc ctg gcc tac gtg acg tgt cag gac ctt cgt agc att gca 888Ser Gln Arg Leu Ala Tyr Val Thr Cys Gln Asp Leu Arg Ser Ile Ala240 245 250 255gac cct gca gag cag atg gtt atg gtg atc aaa gcc cct cct gag acc 936Asp Pro Ala Glu Gln Met Val Met Val Ile Lys Ala Pro Pro Glu Thr260 265 270cag ctc caa gcc gtg gac tct tcg gag aac ttt cag atc tcc ctt aag 984Gln Leu Gln Ala Val Asp Ser Ser Glu Asn Phe Gln Ile Ser Leu Lys275 280 285agc aaa caa ggc ccg atc gat gtt ttc ctg tgc cct gag gag acc gta 1032Ser Lys Gln Gly Pro Ile Asp Val Phe Leu Cys Pro Glu Glu Thr Val290 295 300ggt ggg atc agc cct ggg aag acc cca tcc cag gag gtc act tct gag 1080Gly Gly Ile Ser Pro Gly Lys Thr Pro Ser Gln Glu Val Thr Ser Glu305 310 315gag gag aac agg gcc act gac tct gcc acc ata gtg tca cca cca cca 1128Glu Glu Asn Arg Ala Thr Asp Ser Ala Thr Ile Val Ser Pro Pro Pro320 325 330 335tca tct ccc ccc tca tcc ctc acc aca gat ccc agc cag tct cta ctc 1176Ser Ser Pro Pro Ser Ser Leu Thr Thr Asp Pro Ser Gln Ser Leu Leu340 345 350agc ctg gag caa gaa ccg ctg ttg tcc cgg atg ggc agc ctg cgg gct 1224Ser Leu Glu Gln Glu Pro Leu Leu Ser Arg Met Gly Ser Leu Arg Ala355 360 365ccc gtg gac gag gac cgc ctg tcc ccg ctg gtg gcg gcc gac tcg ctc 1272Pro Val Asp Glu Asp Arg Leu Ser Pro Leu Val Ala Ala Asp Ser Leu370 375 380ctg gag cat gtg cgg gag gac ttc tcc ggc ctc ctc cct gag gag ttc 1320Leu Glu His Val Arg Glu Asp Phe Ser Gly Leu Leu Pro Glu Glu Phe385 390 395atc agc ctt tcc cca ccc cac gag gcc ctc gac tac cac ttc ggc ctc 1368Ile Ser Leu Ser Pro Pro His Glu Ala Leu Asp Tyr His Phe Gly Leu400 405 410 415gag gag ggc gag ggc atc aga gac ctc ttc gac tgt gac ttt ggg gac 1416Glu Glu Gly Glu Gly Ile Arg Asp Leu Phe Asp Cys Asp Phe Gly Asp420 425 430ctc acc ccc ctg gat ttc tga cagggcttgg agggaccagg gtttccagag 1467Leu Thr Pro Leu Asp Phe *435tagctcacct tgtctctgca gccctggagc cccctgtccc tggccgtcct cccagcctgt 1527ttggaaacat ttaatttata cccctctcct ctgtctccag aagcttctag ctctggggtc 1587tggctaccgc taggaggctg agcaagccag gaagggaagg agtctgtgtg gtgtgtatgt 1647gcatgcagcc tacacccaca cgtgtgtacc gggggtgaat gtgtgtgagc atgtgtgtgt 1707gcatgtaccg gggaatgaag gtgaacatac acctctgtgt gtgcactgca gacacgcccc 1767agtgtgtcca catgtgtgtg catgagtcca tctctgcgcg tgggggggct ctaactgcac 1827tttcggccct tttgctcgtg gggtcccaca aggcccaggg cagtgcctgc tcccagaatc 1887tggtgctctg accaggccag gtggggaggc tttggctggc tgggcgtgta ggacggtgag 1947agcacttctg tcttaaaggt tttttctgat tgaagcttta atggagcgtt atttatttat 2007cgaggcctct ttggtgagcc tggggaatca gcaaaagggg aggaggggtg tggggttgat 2067accccaactc cctctaccct tgagcaaggg caggggtccc tgagctgttc ttctgcccca 2127tactgaagga actgaggcct gggtgattta tttattggga aagtgaggga gggagacaga 2187ctgactgaca gccatgggtg gtcagatggt ggggtgggcc ctctccaggg ggccagttca 2247gggcccagct gccccccagg atggatatga gatgggagag gtgagtgggg gaccttcact 2307gatgtgggca ggaggggtgg tgaaggcctc ccccagccca gaccctgtgg tccctcctgc 2367agtgtctgaa gcgcctgcct ccccactgct ctgccccacc ctccaatctg cactttgatt 2427tgcttcctaa cagctctgtt ccctcctgct ttggttttaa taaatatttt gatgacgtt 248614437PRTHomo sapiens 14Met Ala Leu Ala Gly Ala Pro Ala Gly Gly Pro Cys Ala Pro Ala Leu1 5 10 15Glu Ala Leu Leu Gly Ala Gly Ala Leu Arg Leu Leu Asp Ser Ser Gln20 25 30Ile Val Ile Ile Ser Ala Ala Gln Asp Ala Ser Ala Pro Pro Ala Pro35 40 45Thr Gly Pro Ala Ala Pro Ala Ala Gly Pro Cys Asp Pro Asp Leu Leu50 55 60Leu Phe Ala Thr Pro Gln Ala Pro Arg Pro Thr Pro Ser Ala Pro Arg65 70 75 80Pro Ala Leu Gly Arg Pro Pro Val
Lys Arg Arg Leu Asp Leu Glu Thr85 90 95Asp His Gln Tyr Leu Ala Glu Ser Ser Gly Pro Ala Arg Gly Arg Gly100 105 110Arg His Pro Gly Lys Gly Val Lys Ser Pro Gly Glu Lys Ser Arg Tyr115 120 125Glu Thr Ser Leu Asn Leu Thr Thr Lys Arg Phe Leu Glu Leu Leu Ser130 135 140His Ser Ala Asp Gly Val Val Asp Leu Asn Trp Ala Ala Glu Val Leu145 150 155 160Lys Val Gln Lys Arg Arg Ile Tyr Asp Ile Thr Asn Val Leu Glu Gly165 170 175Ile Gln Leu Ile Ala Lys Lys Ser Lys Asn His Ile Gln Trp Leu Gly180 185 190Ser His Thr Thr Val Gly Val Gly Gly Arg Leu Glu Gly Leu Thr Gln195 200 205Asp Leu Arg Gln Leu Gln Glu Ser Glu Gln Gln Leu Asp His Leu Met210 215 220Asn Ile Cys Thr Thr Gln Leu Arg Leu Leu Ser Glu Asp Thr Asp Ser225 230 235 240Gln Arg Leu Ala Tyr Val Thr Cys Gln Asp Leu Arg Ser Ile Ala Asp245 250 255Pro Ala Glu Gln Met Val Met Val Ile Lys Ala Pro Pro Glu Thr Gln260 265 270Leu Gln Ala Val Asp Ser Ser Glu Asn Phe Gln Ile Ser Leu Lys Ser275 280 285Lys Gln Gly Pro Ile Asp Val Phe Leu Cys Pro Glu Glu Thr Val Gly290 295 300Gly Ile Ser Pro Gly Lys Thr Pro Ser Gln Glu Val Thr Ser Glu Glu305 310 315 320Glu Asn Arg Ala Thr Asp Ser Ala Thr Ile Val Ser Pro Pro Pro Ser325 330 335Ser Pro Pro Ser Ser Leu Thr Thr Asp Pro Ser Gln Ser Leu Leu Ser340 345 350Leu Glu Gln Glu Pro Leu Leu Ser Arg Met Gly Ser Leu Arg Ala Pro355 360 365Val Asp Glu Asp Arg Leu Ser Pro Leu Val Ala Ala Asp Ser Leu Leu370 375 380Glu His Val Arg Glu Asp Phe Ser Gly Leu Leu Pro Glu Glu Phe Ile385 390 395 400Ser Leu Ser Pro Pro His Glu Ala Leu Asp Tyr His Phe Gly Leu Glu405 410 415Glu Gly Glu Gly Ile Arg Asp Leu Phe Asp Cys Asp Phe Gly Asp Leu420 425 430Thr Pro Leu Asp Phe435153744DNAHomo sapiensCDS(56)...(2521) 15ccacgcgtcc ggtggcggtc gagcgtggcg taggcgaatc ctcggcacta agcat atg 58Met1gac ctc gcg gcg gca gcg gag ccg ggc gcc ggc agc cag cac ctg gag 106Asp Leu Ala Ala Ala Ala Glu Pro Gly Ala Gly Ser Gln His Leu Glu5 10 15gtc cgc gac gag gtg gcc gag aag tgc cag aaa ctg ttc ctg gac ttc 154Val Arg Asp Glu Val Ala Glu Lys Cys Gln Lys Leu Phe Leu Asp Phe20 25 30ttg gag gag ttt cag agc agc gat gga gaa att aaa tac ttg caa tta 202Leu Glu Glu Phe Gln Ser Ser Asp Gly Glu Ile Lys Tyr Leu Gln Leu35 40 45gca gag gaa ctg att cgt cct gag aga aac aca ttg gtt gtg agt ttt 250Ala Glu Glu Leu Ile Arg Pro Glu Arg Asn Thr Leu Val Val Ser Phe50 55 60 65gtg gac ctg gaa caa ttt aac cag caa ctt tcc acc acc att caa gag 298Val Asp Leu Glu Gln Phe Asn Gln Gln Leu Ser Thr Thr Ile Gln Glu70 75 80gag ttc tat aga gtt tac cct tac ctg tgt cgg gcc ttg aaa aca ttc 346Glu Phe Tyr Arg Val Tyr Pro Tyr Leu Cys Arg Ala Leu Lys Thr Phe85 90 95gtc aaa gac cgt aaa gag atc cct ctt gcc aag gat ttt tat gtt gca 394Val Lys Asp Arg Lys Glu Ile Pro Leu Ala Lys Asp Phe Tyr Val Ala100 105 110ttc caa gac ctg cct acc aga cac aag att cga gag ctc acc tca tcc 442Phe Gln Asp Leu Pro Thr Arg His Lys Ile Arg Glu Leu Thr Ser Ser115 120 125aga att ggt ttg ctc act cgc atc agt ggg cag gtg gtg cgg act cac 490Arg Ile Gly Leu Leu Thr Arg Ile Ser Gly Gln Val Val Arg Thr His130 135 140 145cca gtt cac cca gag ctt gtg agc gga act ttt ctg tgc ttg gac tgt 538Pro Val His Pro Glu Leu Val Ser Gly Thr Phe Leu Cys Leu Asp Cys150 155 160cag aca gtg atc agg gat gta gaa cag cag ttc aaa tac aca cag cca 586Gln Thr Val Ile Arg Asp Val Glu Gln Gln Phe Lys Tyr Thr Gln Pro165 170 175aac atc tgc cga aat cca gtt tgt gcc aac agg agg aga ttc tta ctg 634Asn Ile Cys Arg Asn Pro Val Cys Ala Asn Arg Arg Arg Phe Leu Leu180 185 190gat aca aat aaa tca aga ttt gtt gat ttt caa aag gtt cgt att caa 682Asp Thr Asn Lys Ser Arg Phe Val Asp Phe Gln Lys Val Arg Ile Gln195 200 205gag acc caa gct gag ctt cct cga ggg agt atc ccc cgc agt tta gaa 730Glu Thr Gln Ala Glu Leu Pro Arg Gly Ser Ile Pro Arg Ser Leu Glu210 215 220 225gta att tta agg gct gaa gct gtg gaa tca gct caa gct ggt gac aag 778Val Ile Leu Arg Ala Glu Ala Val Glu Ser Ala Gln Ala Gly Asp Lys230 235 240tgt gac ttt aca ggg aca ctg att gtt gtg cct gac gtc tcc aag ctt 826Cys Asp Phe Thr Gly Thr Leu Ile Val Val Pro Asp Val Ser Lys Leu245 250 255agc aca cca gga gca cgt gca gaa act aat tcc cgt gtc agt ggt gtt 874Ser Thr Pro Gly Ala Arg Ala Glu Thr Asn Ser Arg Val Ser Gly Val260 265 270gat gga tat gag aca gaa ggc att cga gga ctc cgg gcc ctt ggt gtt 922Asp Gly Tyr Glu Thr Glu Gly Ile Arg Gly Leu Arg Ala Leu Gly Val275 280 285agg gac ctt tct tat agg ctg gtc ttt ctt gcc tgc tgt gtt gcg cca 970Arg Asp Leu Ser Tyr Arg Leu Val Phe Leu Ala Cys Cys Val Ala Pro290 295 300 305acc aac cca agg ttt ggg ggg aaa gag ctc aga gat gag gaa cag aca 1018Thr Asn Pro Arg Phe Gly Gly Lys Glu Leu Arg Asp Glu Glu Gln Thr310 315 320gct gag agc att aag aac caa atg act gtg aaa gaa tgg gag aaa gtg 1066Ala Glu Ser Ile Lys Asn Gln Met Thr Val Lys Glu Trp Glu Lys Val325 330 335ttt gag atg agt caa gat aaa aat cta tac cac aat ctt tgt acc agc 1114Phe Glu Met Ser Gln Asp Lys Asn Leu Tyr His Asn Leu Cys Thr Ser340 345 350ctg ttc cct act ata cat ggc aat gat gaa gta aaa cgg ggt gtc ctg 1162Leu Phe Pro Thr Ile His Gly Asn Asp Glu Val Lys Arg Gly Val Leu355 360 365ctg atg ctc ttt ggt ggc gtt cca aag aca aca gga gaa ggg acc tct 1210Leu Met Leu Phe Gly Gly Val Pro Lys Thr Thr Gly Glu Gly Thr Ser370 375 380 385ctt cga ggg gac ata aat gtt tgc att gtt ggt gac cca agt aca gct 1258Leu Arg Gly Asp Ile Asn Val Cys Ile Val Gly Asp Pro Ser Thr Ala390 395 400aag agc caa ttt ctc aag cac gtg gag gag ttc agc ccc aga gct gtc 1306Lys Ser Gln Phe Leu Lys His Val Glu Glu Phe Ser Pro Arg Ala Val405 410 415tac acc agt ggt aaa gcg tcc agt gct gct ggc tta aca gca gct gtt 1354Tyr Thr Ser Gly Lys Ala Ser Ser Ala Ala Gly Leu Thr Ala Ala Val420 425 430gtg aga gat gaa gaa tct cat gag ttt gtc att gag gct gga gct ttg 1402Val Arg Asp Glu Glu Ser His Glu Phe Val Ile Glu Ala Gly Ala Leu435 440 445atg ttg gct gat aat ggt gtg tgt tgt att gat gaa ttt gat aag atg 1450Met Leu Ala Asp Asn Gly Val Cys Cys Ile Asp Glu Phe Asp Lys Met450 455 460 465gac gtg cgg gat caa gtt gct att cat gaa gct atg gaa cag cag acc 1498Asp Val Arg Asp Gln Val Ala Ile His Glu Ala Met Glu Gln Gln Thr470 475 480ata tcc atc act aaa gca gga gtg aag gct act ctg aac gcc cgg acg 1546Ile Ser Ile Thr Lys Ala Gly Val Lys Ala Thr Leu Asn Ala Arg Thr485 490 495tcc att ttg gca gca gca aac cca atc agt gga cac tat gac aga tca 1594Ser Ile Leu Ala Ala Ala Asn Pro Ile Ser Gly His Tyr Asp Arg Ser500 505 510aaa tca ttg aaa cag aat ata aat ttg tca gct ccc atc atg tcc cga 1642Lys Ser Leu Lys Gln Asn Ile Asn Leu Ser Ala Pro Ile Met Ser Arg515 520 525ttc gat ctc ttc ttt atc ctt gtg gat gaa tgt aat gag gtt aca gat 1690Phe Asp Leu Phe Phe Ile Leu Val Asp Glu Cys Asn Glu Val Thr Asp530 535 540 545tat gcc att gcc agg cgc ata gta gat ttg cat tca aga att gag gaa 1738Tyr Ala Ile Ala Arg Arg Ile Val Asp Leu His Ser Arg Ile Glu Glu550 555 560tca att gat cgt gtc tat tcc ctc gat gat atc aga aga tat ctt ctc 1786Ser Ile Asp Arg Val Tyr Ser Leu Asp Asp Ile Arg Arg Tyr Leu Leu565 570 575ttt gca aga cag ttt aaa ccc aag att tcc aaa gag tca gag gac ttc 1834Phe Ala Arg Gln Phe Lys Pro Lys Ile Ser Lys Glu Ser Glu Asp Phe580 585 590att gtg gag caa tat aaa cat ctc cgc cag aga gat ggt tct gga gtg 1882Ile Val Glu Gln Tyr Lys His Leu Arg Gln Arg Asp Gly Ser Gly Val595 600 605acc aag tct tca tgg agg att aca gtg cga cag ctt gag agc atg att 1930Thr Lys Ser Ser Trp Arg Ile Thr Val Arg Gln Leu Glu Ser Met Ile610 615 620 625cgt ctc tct gaa gct atg gct cgg atg cac tgc tgt gat gag gtc caa 1978Arg Leu Ser Glu Ala Met Ala Arg Met His Cys Cys Asp Glu Val Gln630 635 640cct aaa cat gtg aag gaa gct ttc cgg tta ctg aat aaa tca atc atc 2026Pro Lys His Val Lys Glu Ala Phe Arg Leu Leu Asn Lys Ser Ile Ile645 650 655cgt gtg gaa aca cct gat gtc aat cta gat caa gag gaa gag atc cag 2074Arg Val Glu Thr Pro Asp Val Asn Leu Asp Gln Glu Glu Glu Ile Gln660 665 670atg gag gta gat gag ggt gcc ggt ggc atc aat ggt cat gct gac agc 2122Met Glu Val Asp Glu Gly Ala Gly Gly Ile Asn Gly His Ala Asp Ser675 680 685cct gct cct gtg aac ggg atc aat ggc tac aat gaa gac ata aat caa 2170Pro Ala Pro Val Asn Gly Ile Asn Gly Tyr Asn Glu Asp Ile Asn Gln690 695 700 705gag tct gct ccc aaa gcc tcc tta agg ctg ggc ttc tct gag tac tgc 2218Glu Ser Ala Pro Lys Ala Ser Leu Arg Leu Gly Phe Ser Glu Tyr Cys710 715 720cga atc tct aac ctt att gtg ctt cac ctc aga aag gtg gaa gaa gaa 2266Arg Ile Ser Asn Leu Ile Val Leu His Leu Arg Lys Val Glu Glu Glu725 730 735gag gac gag tca gca tta aag agg agc gag ctt gtt aac tgg tac ttg 2314Glu Asp Glu Ser Ala Leu Lys Arg Ser Glu Leu Val Asn Trp Tyr Leu740 745 750aag gaa atc gaa tca gag ata gac tct gaa gaa gaa ctt ata aat aaa 2362Lys Glu Ile Glu Ser Glu Ile Asp Ser Glu Glu Glu Leu Ile Asn Lys755 760 765aaa aga atc ata gag aaa gtt att cat cga ctc aca cac tat gat cat 2410Lys Arg Ile Ile Glu Lys Val Ile His Arg Leu Thr His Tyr Asp His770 775 780 785gtt cta att gag ctc acc cag gct gga ttg aaa ggc tcc aca gag gga 2458Val Leu Ile Glu Leu Thr Gln Ala Gly Leu Lys Gly Ser Thr Glu Gly790 795 800agt gag agc tat gaa gaa gat ccc tac ttg gta gtt aac cct aac tac 2506Ser Glu Ser Tyr Glu Glu Asp Pro Tyr Leu Val Val Asn Pro Asn Tyr805 810 815ttg ctc gaa gat tga gatagtgaaa gtaactgacc agagctgagg aactgtggca 2561Leu Leu Glu Asp *820cagcacctcg tggcctggag cctggctgga gctctgctag ggacagaagt gtttctggaa 2621gtgatgcttc caggatttgt tttcagaaac aagaattgag ttgatggtcc tatgtgtcac 2681attcatcaca ggtttcatac caacacaggc ttcagcactt cctttggtgt gtttcctgtc 2741ccagtgaagt tggaaccaaa taatgtgtag tctctataac caataccttt gttttcatgt 2801gtaagaaaag gcccattact tttaaggtat gtgctgtcct attgagcaaa taactttttt 2861tcaattgcca gctactgctt ttattcatca aaataaaata acttgttctg aagttgtcta 2921ttggatttct ttctactgta ccctgattat tacttccatc tacttctgaa tgtgagactt 2981tccctttttg cttaacctgg agtgaagagg tagaactgtg gtattatgga tgaggtttct 3041atgagaagga gtcattagag aactcatatg aaagctagag gccttagaga tgactttcca 3101aggttaattc cagttttttt tttttttaag tttataaaag tttattatac ttttttaaaa 3161ttactcttta gtaatttatt ttacttctgt gtcctaaggg taatttctca ggattgtttt 3221caaattgctt ttttagggga aataggtcat ttgctatatt acaagcaatc cccaaatttt 3281atggtcttcc aggaaaagtt attaccgttt atgatactaa cagttcctga gacttagcta 3341tgatcagtat gttcatgagg tggagcagtt cctgtgttgc agcttttaac aacagatggc 3401attcattaaa tcacaaagta tgttaaaggt cacaaaagca aaataactgt ctgaggctaa 3461ggcccacgtg ggacagtcta atacccatga gtactcaact tgccttgatg tctgagcttt 3521ccagtgcaat gtgaatttga gcagccagaa atctattagt agaaagcaag acagattaat 3581ataggttaaa acaatgattt aaatatgttt ctcccaataa ttatctcttt ccctggaatc 3641aacttgtatg aaaccttgtc aaaatgtact ccacaagtat gtacaattaa gtattttaaa 3701aataaatggc aaacattaaa aaaaaaaaaa aaaaaaaaaa aaa 374416821PRTHomo sapiens 16Met Asp Leu Ala Ala Ala Ala Glu Pro Gly Ala Gly Ser Gln His Leu1 5 10 15Glu Val Arg Asp Glu Val Ala Glu Lys Cys Gln Lys Leu Phe Leu Asp20 25 30Phe Leu Glu Glu Phe Gln Ser Ser Asp Gly Glu Ile Lys Tyr Leu Gln35 40 45Leu Ala Glu Glu Leu Ile Arg Pro Glu Arg Asn Thr Leu Val Val Ser50 55 60Phe Val Asp Leu Glu Gln Phe Asn Gln Gln Leu Ser Thr Thr Ile Gln65 70 75 80Glu Glu Phe Tyr Arg Val Tyr Pro Tyr Leu Cys Arg Ala Leu Lys Thr85 90 95Phe Val Lys Asp Arg Lys Glu Ile Pro Leu Ala Lys Asp Phe Tyr Val100 105 110Ala Phe Gln Asp Leu Pro Thr Arg His Lys Ile Arg Glu Leu Thr Ser115 120 125Ser Arg Ile Gly Leu Leu Thr Arg Ile Ser Gly Gln Val Val Arg Thr130 135 140His Pro Val His Pro Glu Leu Val Ser Gly Thr Phe Leu Cys Leu Asp145 150 155 160Cys Gln Thr Val Ile Arg Asp Val Glu Gln Gln Phe Lys Tyr Thr Gln165 170 175Pro Asn Ile Cys Arg Asn Pro Val Cys Ala Asn Arg Arg Arg Phe Leu180 185 190Leu Asp Thr Asn Lys Ser Arg Phe Val Asp Phe Gln Lys Val Arg Ile195 200 205Gln Glu Thr Gln Ala Glu Leu Pro Arg Gly Ser Ile Pro Arg Ser Leu210 215 220Glu Val Ile Leu Arg Ala Glu Ala Val Glu Ser Ala Gln Ala Gly Asp225 230 235 240Lys Cys Asp Phe Thr Gly Thr Leu Ile Val Val Pro Asp Val Ser Lys245 250 255Leu Ser Thr Pro Gly Ala Arg Ala Glu Thr Asn Ser Arg Val Ser Gly260 265 270Val Asp Gly Tyr Glu Thr Glu Gly Ile Arg Gly Leu Arg Ala Leu Gly275 280 285Val Arg Asp Leu Ser Tyr Arg Leu Val Phe Leu Ala Cys Cys Val Ala290 295 300Pro Thr Asn Pro Arg Phe Gly Gly Lys Glu Leu Arg Asp Glu Glu Gln305 310 315 320Thr Ala Glu Ser Ile Lys Asn Gln Met Thr Val Lys Glu Trp Glu Lys325 330 335Val Phe Glu Met Ser Gln Asp Lys Asn Leu Tyr His Asn Leu Cys Thr340 345 350Ser Leu Phe Pro Thr Ile His Gly Asn Asp Glu Val Lys Arg Gly Val355 360 365Leu Leu Met Leu Phe Gly Gly Val Pro Lys Thr Thr Gly Glu Gly Thr370 375 380Ser Leu Arg Gly Asp Ile Asn Val Cys Ile Val Gly Asp Pro Ser Thr385 390 395 400Ala Lys Ser Gln Phe Leu Lys His Val Glu Glu Phe Ser Pro Arg Ala405 410 415Val Tyr Thr Ser Gly Lys Ala Ser Ser Ala Ala Gly Leu Thr Ala Ala420 425 430Val Val Arg Asp Glu Glu Ser His Glu Phe Val Ile Glu Ala Gly Ala435 440 445Leu Met Leu Ala Asp Asn Gly Val Cys Cys Ile Asp Glu Phe Asp Lys450 455 460Met Asp Val Arg Asp Gln Val Ala Ile His Glu Ala Met Glu Gln Gln465 470 475 480Thr Ile Ser Ile Thr Lys Ala Gly Val Lys Ala Thr Leu Asn Ala Arg485 490 495Thr Ser Ile Leu Ala Ala Ala Asn Pro Ile Ser Gly His Tyr Asp Arg500 505 510Ser Lys Ser Leu Lys Gln Asn Ile Asn Leu Ser Ala Pro Ile Met Ser515 520 525Arg Phe Asp Leu Phe Phe Ile Leu Val Asp Glu Cys Asn Glu Val Thr530 535 540Asp Tyr Ala Ile Ala Arg Arg Ile Val Asp Leu His Ser Arg Ile Glu545 550 555 560Glu Ser Ile Asp Arg Val Tyr Ser Leu Asp Asp Ile Arg Arg Tyr Leu565 570 575Leu Phe Ala Arg Gln Phe Lys Pro Lys Ile Ser Lys Glu Ser Glu Asp580 585 590Phe Ile Val Glu Gln Tyr Lys His Leu Arg Gln Arg Asp Gly Ser Gly595 600 605Val Thr Lys Ser Ser Trp Arg Ile Thr Val Arg Gln Leu Glu Ser Met610 615 620Ile Arg Leu Ser Glu Ala Met Ala Arg Met His Cys Cys Asp Glu Val625 630 635 640Gln Pro Lys His Val Lys Glu Ala Phe Arg Leu Leu Asn Lys Ser Ile645 650 655Ile Arg Val Glu Thr Pro Asp Val Asn Leu Asp Gln Glu Glu Glu Ile660 665 670Gln Met Glu Val Asp Glu Gly Ala Gly Gly Ile Asn Gly His Ala Asp675 680 685Ser Pro Ala Pro Val Asn Gly Ile Asn Gly Tyr Asn Glu Asp Ile Asn690 695 700Gln Glu Ser Ala Pro Lys Ala Ser Leu Arg Leu Gly Phe Ser Glu Tyr705 710
715 720Cys Arg Ile Ser Asn Leu Ile Val Leu His Leu Arg Lys Val Glu Glu725 730 735Glu Glu Asp Glu Ser Ala Leu Lys Arg Ser Glu Leu Val Asn Trp Tyr740 745 750Leu Lys Glu Ile Glu Ser Glu Ile Asp Ser Glu Glu Glu Leu Ile Asn755 760 765Lys Lys Arg Ile Ile Glu Lys Val Ile His Arg Leu Thr His Tyr Asp770 775 780His Val Leu Ile Glu Leu Thr Gln Ala Gly Leu Lys Gly Ser Thr Glu785 790 795 800Gly Ser Glu Ser Tyr Glu Glu Asp Pro Tyr Leu Val Val Asn Pro Asn805 810 815Tyr Leu Leu Glu Asp820173371DNAHomo sapiensCDS(25)...(2712) 17gcggaatcat cggaatcctt cacc atg gca tcc agc ccg gcc cag cgt cgg 51Met Ala Ser Ser Pro Ala Gln Arg Arg1 5cga ggc aat gat cct ctc acc tcc agc cct ggc cga agc tcc cgg cgt 99Arg Gly Asn Asp Pro Leu Thr Ser Ser Pro Gly Arg Ser Ser Arg Arg10 15 20 25act gat gcc ctc acc tcc agc cct ggc cgt gac ctt cca cca ttt gag 147Thr Asp Ala Leu Thr Ser Ser Pro Gly Arg Asp Leu Pro Pro Phe Glu30 35 40gat gag tcc gag ggg ctc cta ggc aca gag ggg ccc ctg gag gaa gaa 195Asp Glu Ser Glu Gly Leu Leu Gly Thr Glu Gly Pro Leu Glu Glu Glu45 50 55gag gat gga gag gag ctc att gga gat ggc atg gaa agg gac tac cgc 243Glu Asp Gly Glu Glu Leu Ile Gly Asp Gly Met Glu Arg Asp Tyr Arg60 65 70gcc atc cca gag ctg gac gcc tat gag gcc gag gga ctg gct ctg gat 291Ala Ile Pro Glu Leu Asp Ala Tyr Glu Ala Glu Gly Leu Ala Leu Asp75 80 85gat gag gac gta gag gag ctg acg gcc agt cag agg gag gca gca gag 339Asp Glu Asp Val Glu Glu Leu Thr Ala Ser Gln Arg Glu Ala Ala Glu90 95 100 105cgg gcc atg cgg cag cgt gac cgg gag gct ggc cgg ggc ctg ggc cgc 387Arg Ala Met Arg Gln Arg Asp Arg Glu Ala Gly Arg Gly Leu Gly Arg110 115 120atg cgc cgt ggg ctc ctg tat gac agc gat gag gag gac gag gag cgc 435Met Arg Arg Gly Leu Leu Tyr Asp Ser Asp Glu Glu Asp Glu Glu Arg125 130 135cct gcc cgc aag cgc cgc cag gtg gag cgg gcc acg gag gac ggc gag 483Pro Ala Arg Lys Arg Arg Gln Val Glu Arg Ala Thr Glu Asp Gly Glu140 145 150gag gac gag gag atg att gag agc atc gag aac ctg gag gat ctc aaa 531Glu Asp Glu Glu Met Ile Glu Ser Ile Glu Asn Leu Glu Asp Leu Lys155 160 165ggc cac tct gtg cgc gag tgg gtg agc atg gcg ggc ccc cgg ctg gag 579Gly His Ser Val Arg Glu Trp Val Ser Met Ala Gly Pro Arg Leu Glu170 175 180 185atc cac cac cgc ttc aag aac ttc ctg cgc act cac gtc gac agc cac 627Ile His His Arg Phe Lys Asn Phe Leu Arg Thr His Val Asp Ser His190 195 200ggc cac aac gtc ttc aag gag cgc atc agc gac atg tgc aaa gag aac 675Gly His Asn Val Phe Lys Glu Arg Ile Ser Asp Met Cys Lys Glu Asn205 210 215cgt gag agc ctg gtg gtg aac tat gag gac ttg gca gcc agg gag cac 723Arg Glu Ser Leu Val Val Asn Tyr Glu Asp Leu Ala Ala Arg Glu His220 225 230gtg ctg gcc tac ttc ctg cct gag gca ccg gcg gag ctg ctg cag atc 771Val Leu Ala Tyr Phe Leu Pro Glu Ala Pro Ala Glu Leu Leu Gln Ile235 240 245ttt gat gag gct gcc ctg gag gtg gta ctg gcc atg tac ccc aag tac 819Phe Asp Glu Ala Ala Leu Glu Val Val Leu Ala Met Tyr Pro Lys Tyr250 255 260 265gac cgc atc acc aac cac atc cat gtc cgc atc tcc cac ctg cct ctg 867Asp Arg Ile Thr Asn His Ile His Val Arg Ile Ser His Leu Pro Leu270 275 280gtg gag gag ctg cgc tcg ctg agg cag ctg cat ctg aac cag ctg atc 915Val Glu Glu Leu Arg Ser Leu Arg Gln Leu His Leu Asn Gln Leu Ile285 290 295cgc acc agt ggg gtg gtg acc agc tgc act ggc gtc ctg ccc cag ctc 963Arg Thr Ser Gly Val Val Thr Ser Cys Thr Gly Val Leu Pro Gln Leu300 305 310agc atg gtc aag tac aac tgc aac aag tgc aat ttc gtc ctg ggt cct 1011Ser Met Val Lys Tyr Asn Cys Asn Lys Cys Asn Phe Val Leu Gly Pro315 320 325ttc tgc cag tcc cag aac cag gag gtg aaa cca ggc tcc tgt cct gag 1059Phe Cys Gln Ser Gln Asn Gln Glu Val Lys Pro Gly Ser Cys Pro Glu330 335 340 345tgc cag tcg gcc ggc ccc ttt gag gtc aac atg gag gag acc atc tat 1107Cys Gln Ser Ala Gly Pro Phe Glu Val Asn Met Glu Glu Thr Ile Tyr350 355 360cag aac tac cag cgt atc cga atc cag gag agt cca ggc aaa gtg gcg 1155Gln Asn Tyr Gln Arg Ile Arg Ile Gln Glu Ser Pro Gly Lys Val Ala365 370 375gct ggc cgg ctg ccc cgc tcc aag gac gcc att ctc ctc gca gat ctg 1203Ala Gly Arg Leu Pro Arg Ser Lys Asp Ala Ile Leu Leu Ala Asp Leu380 385 390gtg gac agc tgc aac gca gga gac gag ata gag ctg act ggc atc tat 1251Val Asp Ser Cys Asn Ala Gly Asp Glu Ile Glu Leu Thr Gly Ile Tyr395 400 405cac aac aac tat gat ggc tcc ctc aac act gcc aat ggc ttc cct gtc 1299His Asn Asn Tyr Asp Gly Ser Leu Asn Thr Ala Asn Gly Phe Pro Val410 415 420 425ttt gcc act gtc atc cta gcc aac cac gtg gcc aag aag gac aac aag 1347Phe Ala Thr Val Ile Leu Ala Asn His Val Ala Lys Lys Asp Asn Lys430 435 440gtt gct gta ggg gaa ctg acc gat gaa gat gtg aag atg atc act agc 1395Val Ala Val Gly Glu Leu Thr Asp Glu Asp Val Lys Met Ile Thr Ser445 450 455ctc tcc aag gat cag cag atc gga gag aag atc ttt gcc agc att gct 1443Leu Ser Lys Asp Gln Gln Ile Gly Glu Lys Ile Phe Ala Ser Ile Ala460 465 470cct tcc atc tat ggt cat gaa gac atc aag aga ggc ctg gct ctg gcc 1491Pro Ser Ile Tyr Gly His Glu Asp Ile Lys Arg Gly Leu Ala Leu Ala475 480 485ctg ttc gga ggg gag ccc aaa aac cca ggt ggc aag cac aag gta cgt 1539Leu Phe Gly Gly Glu Pro Lys Asn Pro Gly Gly Lys His Lys Val Arg490 495 500 505ggt gat atc aac gtg ctc ttg tgc gga gac cct ggc aca gcg aag tcg 1587Gly Asp Ile Asn Val Leu Leu Cys Gly Asp Pro Gly Thr Ala Lys Ser510 515 520cag ttt ctc aag tat att gag aaa gtg tcc agc cga gcc atc ttc acc 1635Gln Phe Leu Lys Tyr Ile Glu Lys Val Ser Ser Arg Ala Ile Phe Thr525 530 535act ggc cag ggg gcg tcg gct gtg ggc ctc acg gcg tat gtc cag cgg 1683Thr Gly Gln Gly Ala Ser Ala Val Gly Leu Thr Ala Tyr Val Gln Arg540 545 550cac cct gtc agc agg gag tgg acc ttg gag gct ggg gcc ctg gtt ctg 1731His Pro Val Ser Arg Glu Trp Thr Leu Glu Ala Gly Ala Leu Val Leu555 560 565gct gac cga gga gtg tgt ctc att gat gaa ttt gac aag atg aat gac 1779Ala Asp Arg Gly Val Cys Leu Ile Asp Glu Phe Asp Lys Met Asn Asp570 575 580 585cag gac aga acc agc atc cat gag gcc atg gag caa cag agc atc tcc 1827Gln Asp Arg Thr Ser Ile His Glu Ala Met Glu Gln Gln Ser Ile Ser590 595 600atc tcg aag gct ggc atc gtc acc tcc ctg cag gct cgc tgc acg gtc 1875Ile Ser Lys Ala Gly Ile Val Thr Ser Leu Gln Ala Arg Cys Thr Val605 610 615att gct gcc gcc aac ccc ata gga ggg cgc tac gac ccc tcg ctg act 1923Ile Ala Ala Ala Asn Pro Ile Gly Gly Arg Tyr Asp Pro Ser Leu Thr620 625 630ttc tct gag aac gtg gac ctc aca gag ccc atc atc tca cgc ttt gac 1971Phe Ser Glu Asn Val Asp Leu Thr Glu Pro Ile Ile Ser Arg Phe Asp635 640 645atc ctg tgt gtg gtg agg gac acc gtg gac cca gtc cag gac gag atg 2019Ile Leu Cys Val Val Arg Asp Thr Val Asp Pro Val Gln Asp Glu Met650 655 660 665ctg gcc cgc ttc gtg gtg ggc agc cac gtc aga cac cac ccc agc aac 2067Leu Ala Arg Phe Val Val Gly Ser His Val Arg His His Pro Ser Asn670 675 680aag gag gag gag ggg ctg gcc aat ggc agc gct gct gag ccc gcc atg 2115Lys Glu Glu Glu Gly Leu Ala Asn Gly Ser Ala Ala Glu Pro Ala Met685 690 695ccc aac acg tat ggc gtg gag ccc ctg ccc cag gag gtc ctg aag aag 2163Pro Asn Thr Tyr Gly Val Glu Pro Leu Pro Gln Glu Val Leu Lys Lys700 705 710tac atc atc tac gcc aag gag agg gtc cac ccg aag ctc aac cag atg 2211Tyr Ile Ile Tyr Ala Lys Glu Arg Val His Pro Lys Leu Asn Gln Met715 720 725gac cag gac aag gtg gcc aag atg tac agt gac ctg agg aaa gaa tct 2259Asp Gln Asp Lys Val Ala Lys Met Tyr Ser Asp Leu Arg Lys Glu Ser730 735 740 745atg gcg aca ggc agc atc ccc att acg gtg cgg cac atc gag tcc atg 2307Met Ala Thr Gly Ser Ile Pro Ile Thr Val Arg His Ile Glu Ser Met750 755 760atc cgc atg gcg gag gcc cac gcg cgc atc cat ctg cgg gac tat gtg 2355Ile Arg Met Ala Glu Ala His Ala Arg Ile His Leu Arg Asp Tyr Val765 770 775atc gaa gac gac gtc aac atg gcc atc cgc gtg atg ctg gag agc ttc 2403Ile Glu Asp Asp Val Asn Met Ala Ile Arg Val Met Leu Glu Ser Phe780 785 790ata gac aca cag aag ttc agc gtc atg cgc agc atg cgc aag act ttt 2451Ile Asp Thr Gln Lys Phe Ser Val Met Arg Ser Met Arg Lys Thr Phe795 800 805gcc cgc tac ctt tca ttc cgg cgt gac aac aat gag ctg ttg ctc ttc 2499Ala Arg Tyr Leu Ser Phe Arg Arg Asp Asn Asn Glu Leu Leu Leu Phe810 815 820 825ata ctg aag cag tta gtg gca gag cag gtg aca tat cag cgc aac cgc 2547Ile Leu Lys Gln Leu Val Ala Glu Gln Val Thr Tyr Gln Arg Asn Arg830 835 840ttt ggg gcc cag cag gac act att gag gtc cct gag aag gac ttg gtg 2595Phe Gly Ala Gln Gln Asp Thr Ile Glu Val Pro Glu Lys Asp Leu Val845 850 855gat aag gct cgt cag atc aac atc cac aac ctc tct gca ttt tat gac 2643Asp Lys Ala Arg Gln Ile Asn Ile His Asn Leu Ser Ala Phe Tyr Asp860 865 870agt gag ctc ttc agg atg aac aag ttc agc cac gac ctg aaa agg aaa 2691Ser Glu Leu Phe Arg Met Asn Lys Phe Ser His Asp Leu Lys Arg Lys875 880 885atg atc ctg cag cag ttc tga ggccctatgc catccataag gattccttgg 2742Met Ile Leu Gln Gln Phe *890 895gattctggtt tggggtggtc agtgccctct gtgctttatg gacacaaaac cagagcactt 2802gatgaactcg gggtactagg gtcagggctt atagcaggat gtctggctgc acctggcatg 2862actgtttgtt tctccaagcc tgctttgtgc ttctcacctt tgggtgggat gccttgccag 2922tgtgtcttac ttggttgctg aacatcttgc cacctccgag tgctttgtct ccactcagta 2982ccttggatca gagctgctga gttcaggatg cctgcgtgtg gtttaggtgt tagccttctt 3042acatggatgt caggagagct gctgccctct tggcgtgagt tgcgtattca ggctgctttt 3102gctgcctttg gccagagagc tggttgaaga tgtttgtaat cgttttcagt ctcctgcagg 3162tttctgtgcc cctgtggtgg aagaggcacg acagtgccag cgcagcgttc tgggctcctc 3222agtcgcaggg gtgggatgtg agtcatgcgg attatccact cgccacagtt atcagctgcc 3282attgctccct gtctgtttcc ccactctctt atttgtgcat tcggtttggt ttctgtagtt 3342ttaattttta ataaagttga ataaaatat 337118895PRTHomo sapiens 18Met Ala Ser Ser Pro Ala Gln Arg Arg Arg Gly Asn Asp Pro Leu Thr1 5 10 15Ser Ser Pro Gly Arg Ser Ser Arg Arg Thr Asp Ala Leu Thr Ser Ser20 25 30Pro Gly Arg Asp Leu Pro Pro Phe Glu Asp Glu Ser Glu Gly Leu Leu35 40 45Gly Thr Glu Gly Pro Leu Glu Glu Glu Glu Asp Gly Glu Glu Leu Ile50 55 60Gly Asp Gly Met Glu Arg Asp Tyr Arg Ala Ile Pro Glu Leu Asp Ala65 70 75 80Tyr Glu Ala Glu Gly Leu Ala Leu Asp Asp Glu Asp Val Glu Glu Leu85 90 95Thr Ala Ser Gln Arg Glu Ala Ala Glu Arg Ala Met Arg Gln Arg Asp100 105 110Arg Glu Ala Gly Arg Gly Leu Gly Arg Met Arg Arg Gly Leu Leu Tyr115 120 125Asp Ser Asp Glu Glu Asp Glu Glu Arg Pro Ala Arg Lys Arg Arg Gln130 135 140Val Glu Arg Ala Thr Glu Asp Gly Glu Glu Asp Glu Glu Met Ile Glu145 150 155 160Ser Ile Glu Asn Leu Glu Asp Leu Lys Gly His Ser Val Arg Glu Trp165 170 175Val Ser Met Ala Gly Pro Arg Leu Glu Ile His His Arg Phe Lys Asn180 185 190Phe Leu Arg Thr His Val Asp Ser His Gly His Asn Val Phe Lys Glu195 200 205Arg Ile Ser Asp Met Cys Lys Glu Asn Arg Glu Ser Leu Val Val Asn210 215 220Tyr Glu Asp Leu Ala Ala Arg Glu His Val Leu Ala Tyr Phe Leu Pro225 230 235 240Glu Ala Pro Ala Glu Leu Leu Gln Ile Phe Asp Glu Ala Ala Leu Glu245 250 255Val Val Leu Ala Met Tyr Pro Lys Tyr Asp Arg Ile Thr Asn His Ile260 265 270His Val Arg Ile Ser His Leu Pro Leu Val Glu Glu Leu Arg Ser Leu275 280 285Arg Gln Leu His Leu Asn Gln Leu Ile Arg Thr Ser Gly Val Val Thr290 295 300Ser Cys Thr Gly Val Leu Pro Gln Leu Ser Met Val Lys Tyr Asn Cys305 310 315 320Asn Lys Cys Asn Phe Val Leu Gly Pro Phe Cys Gln Ser Gln Asn Gln325 330 335Glu Val Lys Pro Gly Ser Cys Pro Glu Cys Gln Ser Ala Gly Pro Phe340 345 350Glu Val Asn Met Glu Glu Thr Ile Tyr Gln Asn Tyr Gln Arg Ile Arg355 360 365Ile Gln Glu Ser Pro Gly Lys Val Ala Ala Gly Arg Leu Pro Arg Ser370 375 380Lys Asp Ala Ile Leu Leu Ala Asp Leu Val Asp Ser Cys Asn Ala Gly385 390 395 400Asp Glu Ile Glu Leu Thr Gly Ile Tyr His Asn Asn Tyr Asp Gly Ser405 410 415Leu Asn Thr Ala Asn Gly Phe Pro Val Phe Ala Thr Val Ile Leu Ala420 425 430Asn His Val Ala Lys Lys Asp Asn Lys Val Ala Val Gly Glu Leu Thr435 440 445Asp Glu Asp Val Lys Met Ile Thr Ser Leu Ser Lys Asp Gln Gln Ile450 455 460Gly Glu Lys Ile Phe Ala Ser Ile Ala Pro Ser Ile Tyr Gly His Glu465 470 475 480Asp Ile Lys Arg Gly Leu Ala Leu Ala Leu Phe Gly Gly Glu Pro Lys485 490 495Asn Pro Gly Gly Lys His Lys Val Arg Gly Asp Ile Asn Val Leu Leu500 505 510Cys Gly Asp Pro Gly Thr Ala Lys Ser Gln Phe Leu Lys Tyr Ile Glu515 520 525Lys Val Ser Ser Arg Ala Ile Phe Thr Thr Gly Gln Gly Ala Ser Ala530 535 540Val Gly Leu Thr Ala Tyr Val Gln Arg His Pro Val Ser Arg Glu Trp545 550 555 560Thr Leu Glu Ala Gly Ala Leu Val Leu Ala Asp Arg Gly Val Cys Leu565 570 575Ile Asp Glu Phe Asp Lys Met Asn Asp Gln Asp Arg Thr Ser Ile His580 585 590Glu Ala Met Glu Gln Gln Ser Ile Ser Ile Ser Lys Ala Gly Ile Val595 600 605Thr Ser Leu Gln Ala Arg Cys Thr Val Ile Ala Ala Ala Asn Pro Ile610 615 620Gly Gly Arg Tyr Asp Pro Ser Leu Thr Phe Ser Glu Asn Val Asp Leu625 630 635 640Thr Glu Pro Ile Ile Ser Arg Phe Asp Ile Leu Cys Val Val Arg Asp645 650 655Thr Val Asp Pro Val Gln Asp Glu Met Leu Ala Arg Phe Val Val Gly660 665 670Ser His Val Arg His His Pro Ser Asn Lys Glu Glu Glu Gly Leu Ala675 680 685Asn Gly Ser Ala Ala Glu Pro Ala Met Pro Asn Thr Tyr Gly Val Glu690 695 700Pro Leu Pro Gln Glu Val Leu Lys Lys Tyr Ile Ile Tyr Ala Lys Glu705 710 715 720Arg Val His Pro Lys Leu Asn Gln Met Asp Gln Asp Lys Val Ala Lys725 730 735Met Tyr Ser Asp Leu Arg Lys Glu Ser Met Ala Thr Gly Ser Ile Pro740 745 750Ile Thr Val Arg His Ile Glu Ser Met Ile Arg Met Ala Glu Ala His755 760 765Ala Arg Ile His Leu Arg Asp Tyr Val Ile Glu Asp Asp Val Asn Met770 775 780Ala Ile Arg Val Met Leu Glu Ser Phe Ile Asp Thr Gln Lys Phe Ser785 790 795 800Val Met Arg Ser Met Arg Lys Thr Phe Ala Arg Tyr Leu Ser Phe Arg805 810 815Arg Asp Asn Asn Glu Leu Leu Leu Phe Ile Leu Lys Gln Leu Val Ala820 825 830Glu Gln Val Thr Tyr Gln Arg Asn Arg Phe Gly Ala Gln Gln Asp Thr835 840 845Ile Glu Val Pro Glu Lys Asp Leu Val Asp Lys Ala Arg Gln Ile Asn850 855 860Ile His Asn Leu Ser Ala Phe Tyr Asp Ser Glu Leu Phe Arg Met Asn865 870 875 880Lys Phe Ser His Asp Leu Lys Arg Lys Met Ile Leu Gln Gln Phe885 890 895191721DNAHomo sapiensCDS(58)...(1605) 19gaattccctg gctgcttgaa tctgttctgc cccctcccca cccatttcac caccacc atg 60Met1aca ccg ggc acc cag tct cct ttc ttc ctg ctg ctg ctc ctc aca gtg 108Thr Pro Gly Thr Gln Ser Pro Phe Phe Leu Leu Leu Leu Leu Thr Val5 10 15ctt aca
gtt gtt aca ggt tct ggt cat gca agc tct acc cca ggt gga 156Leu Thr Val Val Thr Gly Ser Gly His Ala Ser Ser Thr Pro Gly Gly20 25 30gaa aag gag act tcg gct acc cag aga agt tca gtg ccc agc tct act 204Glu Lys Glu Thr Ser Ala Thr Gln Arg Ser Ser Val Pro Ser Ser Thr35 40 45gag aag aat gct gtg agt atg acc agc agc gta ctc tcc agc cac agc 252Glu Lys Asn Ala Val Ser Met Thr Ser Ser Val Leu Ser Ser His Ser50 55 60 65ccc ggt tca ggc tcc tcc acc act cag gga cag gat gtc act ctg gcc 300Pro Gly Ser Gly Ser Ser Thr Thr Gln Gly Gln Asp Val Thr Leu Ala70 75 80ccg gcc acg gaa cca gct tca ggt tca gct gcc acc tgg gga cag gat 348Pro Ala Thr Glu Pro Ala Ser Gly Ser Ala Ala Thr Trp Gly Gln Asp85 90 95gtc acc tcg gtc cca gtc acc agg cca gcc ctg ggc tcc acc acc ccg 396Val Thr Ser Val Pro Val Thr Arg Pro Ala Leu Gly Ser Thr Thr Pro100 105 110cca gcc cac gat gtc acc tca gcc ccg gac aac aag cca gcc ccg ggc 444Pro Ala His Asp Val Thr Ser Ala Pro Asp Asn Lys Pro Ala Pro Gly115 120 125tcc acc gcc ccc cca gcc cac ggt gtc acc tcg gcc ccg gac acc agg 492Ser Thr Ala Pro Pro Ala His Gly Val Thr Ser Ala Pro Asp Thr Arg130 135 140 145ccg ccc ccg ggc tcc acc gcc ccc cca gcc cac ggt gtc acc tcg gcc 540Pro Pro Pro Gly Ser Thr Ala Pro Pro Ala His Gly Val Thr Ser Ala150 155 160ccg gac acc agg ccg ccc ccg ggc tcc acc gcg ccc gca gcc cac ggt 588Pro Asp Thr Arg Pro Pro Pro Gly Ser Thr Ala Pro Ala Ala His Gly165 170 175gtc acc tcg gcc ccg gac acc agg ccg gcc ccg ggc tcc acc gcc ccc 636Val Thr Ser Ala Pro Asp Thr Arg Pro Ala Pro Gly Ser Thr Ala Pro180 185 190cca gcc cat ggt gtc acc tcg gcc ccg gac aac agg ccc gcc ttg gcg 684Pro Ala His Gly Val Thr Ser Ala Pro Asp Asn Arg Pro Ala Leu Ala195 200 205tcc acc gcc cct cca gtc cac aat gtc acc tcg gcc tca ggc tct gca 732Ser Thr Ala Pro Pro Val His Asn Val Thr Ser Ala Ser Gly Ser Ala210 215 220 225tca ggc tca gct tct act ctg gtg cac aac ggc acc tct gcc agg gct 780Ser Gly Ser Ala Ser Thr Leu Val His Asn Gly Thr Ser Ala Arg Ala230 235 240acc aca acc cca gcc agc aag agc act cca ttc tca att ccc agc cac 828Thr Thr Thr Pro Ala Ser Lys Ser Thr Pro Phe Ser Ile Pro Ser His245 250 255cac tct gat act cct acc acc ctt gcc agc cat agc acc aag act gat 876His Ser Asp Thr Pro Thr Thr Leu Ala Ser His Ser Thr Lys Thr Asp260 265 270gcc agt agc act cac cat agc acg gta cct cct ctc acc tcc tcc aat 924Ala Ser Ser Thr His His Ser Thr Val Pro Pro Leu Thr Ser Ser Asn275 280 285cac agc act tct ccc cag ttg tct act ggg gtc tct ttc ttt ttc ctg 972His Ser Thr Ser Pro Gln Leu Ser Thr Gly Val Ser Phe Phe Phe Leu290 295 300 305tct ttt cac att tca aac ctc cag ttt aat tcc tct ctg gaa gat ccc 1020Ser Phe His Ile Ser Asn Leu Gln Phe Asn Ser Ser Leu Glu Asp Pro310 315 320agc acc gac tac tac caa gag ctg cag aga gac att tct gaa atg ttt 1068Ser Thr Asp Tyr Tyr Gln Glu Leu Gln Arg Asp Ile Ser Glu Met Phe325 330 335ttg cag att tat aaa caa ggg ggt ttt ctg ggc ctc tcc aat att aag 1116Leu Gln Ile Tyr Lys Gln Gly Gly Phe Leu Gly Leu Ser Asn Ile Lys340 345 350ttc agg cca gga tct gtg gtg gta caa ttg act ctg gcc ttc cga gaa 1164Phe Arg Pro Gly Ser Val Val Val Gln Leu Thr Leu Ala Phe Arg Glu355 360 365ggt acc atc aat gtc cac gac gtg gag aca cag ttc aat cag tat aaa 1212Gly Thr Ile Asn Val His Asp Val Glu Thr Gln Phe Asn Gln Tyr Lys370 375 380 385acg gaa gca gcc tct cga tat aac ctg acg atc tca gac gtc agc gtg 1260Thr Glu Ala Ala Ser Arg Tyr Asn Leu Thr Ile Ser Asp Val Ser Val390 395 400agt gat gtg cca ttt cct ttc tct gcc cag tct ggg gct ggg gtg cca 1308Ser Asp Val Pro Phe Pro Phe Ser Ala Gln Ser Gly Ala Gly Val Pro405 410 415ggc tgg ggc atc gcg ctg ctg gtg ctg gtc tgt gtt ctg gtt gcg ctg 1356Gly Trp Gly Ile Ala Leu Leu Val Leu Val Cys Val Leu Val Ala Leu420 425 430gcc att gtc tat ctc att gcc ttg gct gtc tgt cag tgc cgc cga aag 1404Ala Ile Val Tyr Leu Ile Ala Leu Ala Val Cys Gln Cys Arg Arg Lys435 440 445aac tac ggg cag ctg gac atc ttt cca gcc cgg gat acc tac cat cct 1452Asn Tyr Gly Gln Leu Asp Ile Phe Pro Ala Arg Asp Thr Tyr His Pro450 455 460 465atg agc gag tac ccc acc tac cac acc cat ggg cgc tat gtg ccc cct 1500Met Ser Glu Tyr Pro Thr Tyr His Thr His Gly Arg Tyr Val Pro Pro470 475 480agc agt acc gat cgt agc ccc tat gag aag gtt tct gca ggt aat ggt 1548Ser Ser Thr Asp Arg Ser Pro Tyr Glu Lys Val Ser Ala Gly Asn Gly485 490 495ggc agc agc ctc tct tac aca aac cca gca gtg gca gcc act tct gcc 1596Gly Ser Ser Leu Ser Tyr Thr Asn Pro Ala Val Ala Ala Thr Ser Ala500 505 510aac ttg tag gggcacgtcg ccctctgagc tgagtggcca gccagtgcca 1645Asn Leu *515ttccactcca ctcagggctc tctgggccag tcctcctggg agcccccacc acaacacttc 1705ccaggcatgg aattcc 172120515PRTHomo sapiens 20Met Thr Pro Gly Thr Gln Ser Pro Phe Phe Leu Leu Leu Leu Leu Thr1 5 10 15Val Leu Thr Val Val Thr Gly Ser Gly His Ala Ser Ser Thr Pro Gly20 25 30Gly Glu Lys Glu Thr Ser Ala Thr Gln Arg Ser Ser Val Pro Ser Ser35 40 45Thr Glu Lys Asn Ala Val Ser Met Thr Ser Ser Val Leu Ser Ser His50 55 60Ser Pro Gly Ser Gly Ser Ser Thr Thr Gln Gly Gln Asp Val Thr Leu65 70 75 80Ala Pro Ala Thr Glu Pro Ala Ser Gly Ser Ala Ala Thr Trp Gly Gln85 90 95Asp Val Thr Ser Val Pro Val Thr Arg Pro Ala Leu Gly Ser Thr Thr100 105 110Pro Pro Ala His Asp Val Thr Ser Ala Pro Asp Asn Lys Pro Ala Pro115 120 125Gly Ser Thr Ala Pro Pro Ala His Gly Val Thr Ser Ala Pro Asp Thr130 135 140Arg Pro Pro Pro Gly Ser Thr Ala Pro Pro Ala His Gly Val Thr Ser145 150 155 160Ala Pro Asp Thr Arg Pro Pro Pro Gly Ser Thr Ala Pro Ala Ala His165 170 175Gly Val Thr Ser Ala Pro Asp Thr Arg Pro Ala Pro Gly Ser Thr Ala180 185 190Pro Pro Ala His Gly Val Thr Ser Ala Pro Asp Asn Arg Pro Ala Leu195 200 205Ala Ser Thr Ala Pro Pro Val His Asn Val Thr Ser Ala Ser Gly Ser210 215 220Ala Ser Gly Ser Ala Ser Thr Leu Val His Asn Gly Thr Ser Ala Arg225 230 235 240Ala Thr Thr Thr Pro Ala Ser Lys Ser Thr Pro Phe Ser Ile Pro Ser245 250 255His His Ser Asp Thr Pro Thr Thr Leu Ala Ser His Ser Thr Lys Thr260 265 270Asp Ala Ser Ser Thr His His Ser Thr Val Pro Pro Leu Thr Ser Ser275 280 285Asn His Ser Thr Ser Pro Gln Leu Ser Thr Gly Val Ser Phe Phe Phe290 295 300Leu Ser Phe His Ile Ser Asn Leu Gln Phe Asn Ser Ser Leu Glu Asp305 310 315 320Pro Ser Thr Asp Tyr Tyr Gln Glu Leu Gln Arg Asp Ile Ser Glu Met325 330 335Phe Leu Gln Ile Tyr Lys Gln Gly Gly Phe Leu Gly Leu Ser Asn Ile340 345 350Lys Phe Arg Pro Gly Ser Val Val Val Gln Leu Thr Leu Ala Phe Arg355 360 365Glu Gly Thr Ile Asn Val His Asp Val Glu Thr Gln Phe Asn Gln Tyr370 375 380Lys Thr Glu Ala Ala Ser Arg Tyr Asn Leu Thr Ile Ser Asp Val Ser385 390 395 400Val Ser Asp Val Pro Phe Pro Phe Ser Ala Gln Ser Gly Ala Gly Val405 410 415Pro Gly Trp Gly Ile Ala Leu Leu Val Leu Val Cys Val Leu Val Ala420 425 430Leu Ala Ile Val Tyr Leu Ile Ala Leu Ala Val Cys Gln Cys Arg Arg435 440 445Lys Asn Tyr Gly Gln Leu Asp Ile Phe Pro Ala Arg Asp Thr Tyr His450 455 460Pro Met Ser Glu Tyr Pro Thr Tyr His Thr His Gly Arg Tyr Val Pro465 470 475 480Pro Ser Ser Thr Asp Arg Ser Pro Tyr Glu Lys Val Ser Ala Gly Asn485 490 495Gly Gly Ser Ser Leu Ser Tyr Thr Asn Pro Ala Val Ala Ala Thr Ser500 505 510Ala Asn Leu515211061DNAHomo sapiensCDS(189)...(758) 21tgccctgcgc ccgcaacccg agccgcaccc gccgcggacg gagcccatgc gcggggcgaa 60ccgcgcgccc ccgcccccgc cccgccccgg cctcggcccc ggccctggcc ccgggggcag 120tcgcgcctgt gaacggtggg gcaggagacc ctgtaggagg accccgggcc gcaggcccct 180gaggagcg atg acg gaa tat aag ctg gtg gtg gtg ggc gcc ggc ggt gtg 230Met Thr Glu Tyr Lys Leu Val Val Val Gly Ala Gly Gly Val1 5 10ggc aag agt gcg ctg acc atc cag ctg atc cag aac cat ttt gtg gac 278Gly Lys Ser Ala Leu Thr Ile Gln Leu Ile Gln Asn His Phe Val Asp15 20 25 30gaa tac gac ccc act ata gag gat tcc tac cgg aag cag gtg gtc att 326Glu Tyr Asp Pro Thr Ile Glu Asp Ser Tyr Arg Lys Gln Val Val Ile35 40 45gat ggg gag acg tgc ctg ttg gac atc ctg gat acc gcc ggc cag gag 374Asp Gly Glu Thr Cys Leu Leu Asp Ile Leu Asp Thr Ala Gly Gln Glu50 55 60gag tac agc gcc atg cgg gac cag tac atg cgc acc ggg gag ggc ttc 422Glu Tyr Ser Ala Met Arg Asp Gln Tyr Met Arg Thr Gly Glu Gly Phe65 70 75ctg tgt gtg ttt gcc atc aac aac acc aag tct ttt gag gac atc cac 470Leu Cys Val Phe Ala Ile Asn Asn Thr Lys Ser Phe Glu Asp Ile His80 85 90cag tac agg gag cag atc aaa cgg gtg aag gac tcg gat gac gtg ccc 518Gln Tyr Arg Glu Gln Ile Lys Arg Val Lys Asp Ser Asp Asp Val Pro95 100 105 110atg gtg ctg gtg ggg aac aag tgt gac ctg gct gca cgc act gtg gaa 566Met Val Leu Val Gly Asn Lys Cys Asp Leu Ala Ala Arg Thr Val Glu115 120 125tct cgg cag gct cag gac ctc gcc cga agc tac ggc atc ccc tac atc 614Ser Arg Gln Ala Gln Asp Leu Ala Arg Ser Tyr Gly Ile Pro Tyr Ile130 135 140gag acc tcg gcc aag acc cgg cag gga gtg gag gat gcc ttc tac acg 662Glu Thr Ser Ala Lys Thr Arg Gln Gly Val Glu Asp Ala Phe Tyr Thr145 150 155ttg gtg cgt gag atc cgg cag cac aag ctg cgg aag ctg aac cct cct 710Leu Val Arg Glu Ile Arg Gln His Lys Leu Arg Lys Leu Asn Pro Pro160 165 170gat gag agt ggc ccc ggc tgc atg agc tgc aag tgt gtg ctc tcc tga 758Asp Glu Ser Gly Pro Gly Cys Met Ser Cys Lys Cys Val Leu Ser *175 180 185cgcagcacaa gctcaggaca tggaggtgcc ggatgcagga aggaggtgca gacggaagga 818ggaggaagga aggacggaag caaggaagga aggaagggct gctggagccc agtcaccccg 878ggaccgtggg ccgaggtgac tgcagaccct cccagggagg ctgtgcacag actgtcttga 938acatcccaaa tgccaccgga accccagccc ttagctcccc tcccaggcct ctgtgggccc 998ttgtcgggca cagatgggat cacagtaaat tattggatgg tcttgaaaaa aaaaaaaaaa 1058aaa 106122189PRTHomo sapiens 22Met Thr Glu Tyr Lys Leu Val Val Val Gly Ala Gly Gly Val Gly Lys1 5 10 15Ser Ala Leu Thr Ile Gln Leu Ile Gln Asn His Phe Val Asp Glu Tyr20 25 30Asp Pro Thr Ile Glu Asp Ser Tyr Arg Lys Gln Val Val Ile Asp Gly35 40 45Glu Thr Cys Leu Leu Asp Ile Leu Asp Thr Ala Gly Gln Glu Glu Tyr50 55 60Ser Ala Met Arg Asp Gln Tyr Met Arg Thr Gly Glu Gly Phe Leu Cys65 70 75 80Val Phe Ala Ile Asn Asn Thr Lys Ser Phe Glu Asp Ile His Gln Tyr85 90 95Arg Glu Gln Ile Lys Arg Val Lys Asp Ser Asp Asp Val Pro Met Val100 105 110Leu Val Gly Asn Lys Cys Asp Leu Ala Ala Arg Thr Val Glu Ser Arg115 120 125Gln Ala Gln Asp Leu Ala Arg Ser Tyr Gly Ile Pro Tyr Ile Glu Thr130 135 140Ser Ala Lys Thr Arg Gln Gly Val Glu Asp Ala Phe Tyr Thr Leu Val145 150 155 160Arg Glu Ile Arg Gln His Lys Leu Arg Lys Leu Asn Pro Pro Asp Glu165 170 175Ser Gly Pro Gly Cys Met Ser Cys Lys Cys Val Leu Ser180 185234145DNAHomo sapiensCDS(450)...(2060) 23caaacaagtg cggccatttc accagcccag gctggcttct gctgttgact ggctgtggca 60cctcaagcag cccctttccc ctctagcctc agtttatcac cgcaagagct accattcatc 120tagcacaacc tgaccatcct cacactggtc agttccaacc ttcccaggaa tcttctgtgg 180ccatgttcac tccggtttta cagaacagag aacagaagct cagagaagtg aagcaacttg 240cccagctatg agagacagag ccaggatttg aaaccagatg aggacgctga ggcccagaga 300gggaaagcca cttgcctagg gacacacagc ggggagaggt ggagcagggc ctctatttcg 360agacccctga ctccacacct ggtgtttgtg ccaagacccc aggctgcctc ccaggtcctc 420tgggacagcc cctgccttct accaggacc atg ggt agc aac aag agc aag ccc 473Met Gly Ser Asn Lys Ser Lys Pro1 5aag gat gcc agc cag cgg cgc cgc agc ctg gag ccc gcc gag aac gtg 521Lys Asp Ala Ser Gln Arg Arg Arg Ser Leu Glu Pro Ala Glu Asn Val10 15 20cac ggc gct ggc ggg ggc gct ttc ccc gcc tcg cag acc ccc agc aag 569His Gly Ala Gly Gly Gly Ala Phe Pro Ala Ser Gln Thr Pro Ser Lys25 30 35 40cca gcc tcg gcc gac ggc cac cgc ggc ccc agc gcg gcc ttc gcc ccc 617Pro Ala Ser Ala Asp Gly His Arg Gly Pro Ser Ala Ala Phe Ala Pro45 50 55gcg gcc gcc gag ccc aag ctg ttc gga ggc ttc aac tcc tcg gac acc 665Ala Ala Ala Glu Pro Lys Leu Phe Gly Gly Phe Asn Ser Ser Asp Thr60 65 70gtc acc tcc ccg cag agg gcg ggc ccg ctg gcc ggt gga gtg acc acc 713Val Thr Ser Pro Gln Arg Ala Gly Pro Leu Ala Gly Gly Val Thr Thr75 80 85ttt gtg gcc ctc tat gac tat gag tct agg acg gag aca gac ctg tcc 761Phe Val Ala Leu Tyr Asp Tyr Glu Ser Arg Thr Glu Thr Asp Leu Ser90 95 100ttc aag aaa ggc gag cgg ctc cag att gtc aac aac aca gag gga gac 809Phe Lys Lys Gly Glu Arg Leu Gln Ile Val Asn Asn Thr Glu Gly Asp105 110 115 120tgg tgg ctg gcc cac tcg ctc agc aca gga cag aca ggc tac atc ccc 857Trp Trp Leu Ala His Ser Leu Ser Thr Gly Gln Thr Gly Tyr Ile Pro125 130 135agc aac tac gtg gcg ccc tcc gac tcc atc cag gct gag gag tgg tat 905Ser Asn Tyr Val Ala Pro Ser Asp Ser Ile Gln Ala Glu Glu Trp Tyr140 145 150ttt ggc aag atc acc aga cgg gag tca gag cgg tta ctg ctc aat gca 953Phe Gly Lys Ile Thr Arg Arg Glu Ser Glu Arg Leu Leu Leu Asn Ala155 160 165gag aac ccg aga ggg acc ttc ctc gtg cga gaa agt gag acc acg aaa 1001Glu Asn Pro Arg Gly Thr Phe Leu Val Arg Glu Ser Glu Thr Thr Lys170 175 180ggt gcc tac tgc ctc tca gtg tct gac ttc gac aac gcc aag ggc ctc 1049Gly Ala Tyr Cys Leu Ser Val Ser Asp Phe Asp Asn Ala Lys Gly Leu185 190 195 200aac gtg aag cac tac aag atc cgc aag ctg gac agc ggc ggc ttc tac 1097Asn Val Lys His Tyr Lys Ile Arg Lys Leu Asp Ser Gly Gly Phe Tyr205 210 215atc acc tcc cgc acc cag ttc aac agc ctg cag cag ctg gtg gcc tac 1145Ile Thr Ser Arg Thr Gln Phe Asn Ser Leu Gln Gln Leu Val Ala Tyr220 225 230tac tcc aaa cac gcc gat ggc ctg tgc cac cgc ctc acc acc gtg tgc 1193Tyr Ser Lys His Ala Asp Gly Leu Cys His Arg Leu Thr Thr Val Cys235 240 245ccc acg tcc aag ccg cag act cag ggc ctg gcc aag gat gcc tgg gag 1241Pro Thr Ser Lys Pro Gln Thr Gln Gly Leu Ala Lys Asp Ala Trp Glu250 255 260atc cct cgg gag tcg ctg cgg ctg gag gtc aag ctg ggc cag ggc tgc 1289Ile Pro Arg Glu Ser Leu Arg Leu Glu Val Lys Leu Gly Gln Gly Cys265 270 275 280ttt ggc gag gtg tgg atg ggg acc tgg aac ggt acc acc agg gtg gcc 1337Phe Gly Glu Val Trp Met Gly Thr Trp Asn Gly Thr Thr Arg Val Ala285 290 295atc aaa acc ctg aag cct ggc acg atg tct cca gag gcc ttc ctg cag 1385Ile Lys Thr Leu Lys Pro Gly Thr Met Ser Pro Glu Ala Phe Leu Gln300 305 310gag gcc cag gtc atg aag aag ctg agg cat gag aag ctg gtg cag ttg 1433Glu Ala Gln Val Met Lys Lys Leu Arg His Glu Lys Leu Val Gln Leu315 320 325tat gct gtg gtt tca gag gag ccc att tac atc gtc acg gag tac atg 1481Tyr Ala Val Val Ser Glu Glu Pro Ile Tyr Ile Val Thr Glu Tyr Met330 335 340agc aag ggg agt ttg ctg gac ttt ctc aag ggg gag aca ggc aag tac 1529Ser Lys Gly Ser Leu Leu Asp Phe Leu Lys Gly Glu Thr Gly Lys Tyr345 350 355
360ctg cgg ctg cct cag ctg gtg gac atg gct gct cag atc gcc tca ggc 1577Leu Arg Leu Pro Gln Leu Val Asp Met Ala Ala Gln Ile Ala Ser Gly365 370 375atg gcg tac gtg gag cgg atg aac tac gtc cac cgg gac ctt cgt gca 1625Met Ala Tyr Val Glu Arg Met Asn Tyr Val His Arg Asp Leu Arg Ala380 385 390gcc aac atc ctg gtg gga gag aac ctg gtg tgc aaa gtg gcc gac ttt 1673Ala Asn Ile Leu Val Gly Glu Asn Leu Val Cys Lys Val Ala Asp Phe395 400 405ggg ctg gct cgg ctc att gaa gac aat gag tac acg gcg cgg caa ggt 1721Gly Leu Ala Arg Leu Ile Glu Asp Asn Glu Tyr Thr Ala Arg Gln Gly410 415 420gcc aaa ttc ccc atc aag tgg acg gct cca gaa gct gcc ctc tat ggc 1769Ala Lys Phe Pro Ile Lys Trp Thr Ala Pro Glu Ala Ala Leu Tyr Gly425 430 435 440cgc ttc acc atc aag tcg gac gtg tgg tcc ttc ggg atc ctg ctg act 1817Arg Phe Thr Ile Lys Ser Asp Val Trp Ser Phe Gly Ile Leu Leu Thr445 450 455gag ctc acc aca aag gga cgg gtg ccc tac cct ggg atg gtg aac cgc 1865Glu Leu Thr Thr Lys Gly Arg Val Pro Tyr Pro Gly Met Val Asn Arg460 465 470gag gtg ctg gac cag gtg gag cgg ggc tac cgg atg ccc tgc ccg ccg 1913Glu Val Leu Asp Gln Val Glu Arg Gly Tyr Arg Met Pro Cys Pro Pro475 480 485gag tgt ccc gag tcc ctg cac gac ctc atg tgc cag tgc tgg cgg aag 1961Glu Cys Pro Glu Ser Leu His Asp Leu Met Cys Gln Cys Trp Arg Lys490 495 500gag cct gag gag cgg ccc acc ttc gag tac ctg cag gcc ttc ctg gag 2009Glu Pro Glu Glu Arg Pro Thr Phe Glu Tyr Leu Gln Ala Phe Leu Glu505 510 515 520gac tac ttc acg tcc acc gag ccc cag tac cag ccc ggg gag aac ctc 2057Asp Tyr Phe Thr Ser Thr Glu Pro Gln Tyr Gln Pro Gly Glu Asn Leu525 530 535tag gcacaggcgg gcccagaccg gcttctcggc ttggatcctg ggctgggtgg 2110*cccctgtctc ggggcttgcc ccactctgcc tgcctgctgt tggtcctctc tctgtggggc 2170tgaattgcca ggggcgaggc ccttcctctt tggtggcatg gaaggggctt ctggacctag 2230ggtggcctga gagggcggtg ggtatgcgag accagcacgg tgactctgtc cagctcccgc 2290tgtggccgca cgcctctccc tgcactccct cctggagctc tgtgggtctc tggaagagga 2350accaggagaa gggctggggc cggggctgag ggtgcccttt tccagcctca gcctactccg 2410ctcactgaac tccttcccca cttctgtgcc acccccggtc tatgtcgaga gctggccaaa 2470gagcctttcc aaagaggagc gatgggcccc tggccccgcc tgcctgccac cctgcccctt 2530gccatccatt ctggaaacac ctgtaggcag aggctgccga gacagaccct ctgccgctgc 2590ttccaggctg ggcagcacaa ggccttgcct ggcctgatga tggtgggtgg gtgggatgag 2650taccccctca aaccctgccc tccttagacc tgagggaccc ttcgagatca tcacttcctt 2710gcccccattt cacccatggg gagacagttg agagcgggga tgtgacatgc ccaaggccac 2770ggagcagttc agagtggagg cgggcttgga acccggtgct ccctctgtca tcctcaggaa 2830ccaacaattc gtcggaggca tcatggaaag actgggacag cccaggaaac aaggggtctg 2890aggatgcatt cgagatggca gattcccact gccgctgccc gctcagccca gctgttggga 2950acagcatgga ggcagatgtg gggctgagct ggggaatcag ggtaaaaggt gcaggtgtgg 3010agagagaggc ttcaatcggc ttgtgggtga tgtttgacct tcagagccag ccggctatga 3070aagggagcga gcccctcggc tctggaggca atcaagcaga catagaagag ccaagagtcc 3130aggaggccct ggtcctggcc tccttccccg tactttgtcc cgtggcattt caattcctgg 3190ccctgttctc ctccccaagt cggcaccctt taactcatga ggagggaaaa gagtgcctaa 3250gcgggggtga aagaggacgt gttacccact gccatgcacc aggactggct gtgtaacctt 3310gggtggcccc tgctgtctct ctgggctgca gagtctgccc cacatgtggc catggcctct 3370gcaactgctc agctctggtc caggccctgt ggcaggacac acatggtgag cctagccctg 3430ggacatcagg agactgggct ctggctctgt tcggcctttg ggtgtgtggt ggattctccc 3490tgggcctcag tgtgcccatc tgtaaagggg cagctgacag tttgtggcat cttgccaagg 3550gtccctgtgt gtgtgtatgt gtgtgcatgt gtgcgtgtct ccatgtgcgt ccatatttaa 3610catgtaaaaa tgtccccccc gctccgtccc ccaaacatgt tgtacatttc accatggccc 3670cctcatcata gcaataacat tcccactgcc aggggttctt gagccagcca ggccctgcca 3730gtggggaagg aggccaagca gtgcctgcct atgaaatttc aacttttcct ttcatacgtc 3790tttattaccc aagtcttctc ccgtccattc cagtcaaatc tgggctcact caccccagcg 3850agctctcaaa tccctctcca actgcctaag gccctttgtg taaggtgtct taatactgtc 3910cttttttttt ttttaacagt gttttgtaga tttcagatga ctatgcagag gcctggggga 3970cccctggctc tgggccgggc ctggggctcc gaaattccaa ggcccagact tgcggggggt 4030gggggggtat ccagaattgg ttgtaaatac tttgcatatt gtctgattaa acacaaacag 4090acctcagaaa aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa aaaaa 414524536PRTHomo sapiens 24Met Gly Ser Asn Lys Ser Lys Pro Lys Asp Ala Ser Gln Arg Arg Arg1 5 10 15Ser Leu Glu Pro Ala Glu Asn Val His Gly Ala Gly Gly Gly Ala Phe20 25 30Pro Ala Ser Gln Thr Pro Ser Lys Pro Ala Ser Ala Asp Gly His Arg35 40 45Gly Pro Ser Ala Ala Phe Ala Pro Ala Ala Ala Glu Pro Lys Leu Phe50 55 60Gly Gly Phe Asn Ser Ser Asp Thr Val Thr Ser Pro Gln Arg Ala Gly65 70 75 80Pro Leu Ala Gly Gly Val Thr Thr Phe Val Ala Leu Tyr Asp Tyr Glu85 90 95Ser Arg Thr Glu Thr Asp Leu Ser Phe Lys Lys Gly Glu Arg Leu Gln100 105 110Ile Val Asn Asn Thr Glu Gly Asp Trp Trp Leu Ala His Ser Leu Ser115 120 125Thr Gly Gln Thr Gly Tyr Ile Pro Ser Asn Tyr Val Ala Pro Ser Asp130 135 140Ser Ile Gln Ala Glu Glu Trp Tyr Phe Gly Lys Ile Thr Arg Arg Glu145 150 155 160Ser Glu Arg Leu Leu Leu Asn Ala Glu Asn Pro Arg Gly Thr Phe Leu165 170 175Val Arg Glu Ser Glu Thr Thr Lys Gly Ala Tyr Cys Leu Ser Val Ser180 185 190Asp Phe Asp Asn Ala Lys Gly Leu Asn Val Lys His Tyr Lys Ile Arg195 200 205Lys Leu Asp Ser Gly Gly Phe Tyr Ile Thr Ser Arg Thr Gln Phe Asn210 215 220Ser Leu Gln Gln Leu Val Ala Tyr Tyr Ser Lys His Ala Asp Gly Leu225 230 235 240Cys His Arg Leu Thr Thr Val Cys Pro Thr Ser Lys Pro Gln Thr Gln245 250 255Gly Leu Ala Lys Asp Ala Trp Glu Ile Pro Arg Glu Ser Leu Arg Leu260 265 270Glu Val Lys Leu Gly Gln Gly Cys Phe Gly Glu Val Trp Met Gly Thr275 280 285Trp Asn Gly Thr Thr Arg Val Ala Ile Lys Thr Leu Lys Pro Gly Thr290 295 300Met Ser Pro Glu Ala Phe Leu Gln Glu Ala Gln Val Met Lys Lys Leu305 310 315 320Arg His Glu Lys Leu Val Gln Leu Tyr Ala Val Val Ser Glu Glu Pro325 330 335Ile Tyr Ile Val Thr Glu Tyr Met Ser Lys Gly Ser Leu Leu Asp Phe340 345 350Leu Lys Gly Glu Thr Gly Lys Tyr Leu Arg Leu Pro Gln Leu Val Asp355 360 365Met Ala Ala Gln Ile Ala Ser Gly Met Ala Tyr Val Glu Arg Met Asn370 375 380Tyr Val His Arg Asp Leu Arg Ala Ala Asn Ile Leu Val Gly Glu Asn385 390 395 400Leu Val Cys Lys Val Ala Asp Phe Gly Leu Ala Arg Leu Ile Glu Asp405 410 415Asn Glu Tyr Thr Ala Arg Gln Gly Ala Lys Phe Pro Ile Lys Trp Thr420 425 430Ala Pro Glu Ala Ala Leu Tyr Gly Arg Phe Thr Ile Lys Ser Asp Val435 440 445Trp Ser Phe Gly Ile Leu Leu Thr Glu Leu Thr Thr Lys Gly Arg Val450 455 460Pro Tyr Pro Gly Met Val Asn Arg Glu Val Leu Asp Gln Val Glu Arg465 470 475 480Gly Tyr Arg Met Pro Cys Pro Pro Glu Cys Pro Glu Ser Leu His Asp485 490 495Leu Met Cys Gln Cys Trp Arg Lys Glu Pro Glu Glu Arg Pro Thr Phe500 505 510Glu Tyr Leu Gln Ala Phe Leu Glu Asp Tyr Phe Thr Ser Thr Glu Pro515 520 525Gln Tyr Gln Pro Gly Glu Asn Leu530 535251333DNAHomo sapiensCDS(101)...(1030) 25ggggaggccg cctggttttc ctccctcctt ctgcacgtct gctggggtct cttcctctcc 60aggccttgcc gtccccctgg cctctcttcc cagctcacac atg aag atg cac ttg 115Met Lys Met His Leu1 5caa agg gct ctg gtg gtc ctg gcc ctg ctg aac ttt gcc acg gtc agc 163Gln Arg Ala Leu Val Val Leu Ala Leu Leu Asn Phe Ala Thr Val Ser10 15 20ctc tct ctg tcc act tgc acc acc ttg gac ttc ggc cac atc aag aag 211Leu Ser Leu Ser Thr Cys Thr Thr Leu Asp Phe Gly His Ile Lys Lys25 30 35aag agg gtg gaa gcc att agg gga cag atc ttg agc aag ctc agg ctc 259Lys Arg Val Glu Ala Ile Arg Gly Gln Ile Leu Ser Lys Leu Arg Leu40 45 50acc agc ccc cct gag cca acg gtg atg acc cac gtc ccc tat cag gtc 307Thr Ser Pro Pro Glu Pro Thr Val Met Thr His Val Pro Tyr Gln Val55 60 65ctg gcc ctt tac aac agc acc cgg gag ctg ctg gag gag atg cat ggg 355Leu Ala Leu Tyr Asn Ser Thr Arg Glu Leu Leu Glu Glu Met His Gly70 75 80 85gag agg gag gaa ggc tgc acc cag gaa aac acc gag tcg gaa tac tat 403Glu Arg Glu Glu Gly Cys Thr Gln Glu Asn Thr Glu Ser Glu Tyr Tyr90 95 100gcc aaa gaa atc cat aaa ttc gac atg atc cag ggg ctg gcg gag cac 451Ala Lys Glu Ile His Lys Phe Asp Met Ile Gln Gly Leu Ala Glu His105 110 115aac gaa ctg gct gtc tgc cct aaa gga att acc tcc aag gtt ttc cgc 499Asn Glu Leu Ala Val Cys Pro Lys Gly Ile Thr Ser Lys Val Phe Arg120 125 130ttc aat gtg tcc tca gtg gag aaa aat aga acc aac cta ttc cga gca 547Phe Asn Val Ser Ser Val Glu Lys Asn Arg Thr Asn Leu Phe Arg Ala135 140 145gaa ttc cgg gtc ttg cgg gtg ccc aac ccc agc tct aag cgg aat gag 595Glu Phe Arg Val Leu Arg Val Pro Asn Pro Ser Ser Lys Arg Asn Glu150 155 160 165cag agg atc gag ctc ttc cag atc ctt cgg cca gat gag cac att gcc 643Gln Arg Ile Glu Leu Phe Gln Ile Leu Arg Pro Asp Glu His Ile Ala170 175 180aaa cag cgc tat atc ggt ggc aag aat ctg ccc aca cgg ggc act gcc 691Lys Gln Arg Tyr Ile Gly Gly Lys Asn Leu Pro Thr Arg Gly Thr Ala185 190 195gag tgg ctg tcc ttt gat gtc act gac act gtg cgt gag tgg ctg ttg 739Glu Trp Leu Ser Phe Asp Val Thr Asp Thr Val Arg Glu Trp Leu Leu200 205 210aga aga gag tcc aac tta ggt cta gaa atc agc att cac tgt cca tgt 787Arg Arg Glu Ser Asn Leu Gly Leu Glu Ile Ser Ile His Cys Pro Cys215 220 225cac acc ttt cag ccc aat gga gat atc ctg gaa aac att cac gag gtg 835His Thr Phe Gln Pro Asn Gly Asp Ile Leu Glu Asn Ile His Glu Val230 235 240 245atg gaa atc aaa ttc aaa ggc gtg gac aat gag gat gac cat ggc cgt 883Met Glu Ile Lys Phe Lys Gly Val Asp Asn Glu Asp Asp His Gly Arg250 255 260gga gat ctg ggg cgc ctc aag aag cag aag gat cac cac aac cct cat 931Gly Asp Leu Gly Arg Leu Lys Lys Gln Lys Asp His His Asn Pro His265 270 275cta atc ctc atg atg att ccc cca cac cgg ctc gac aac ccg ggc cag 979Leu Ile Leu Met Met Ile Pro Pro His Arg Leu Asp Asn Pro Gly Gln280 285 290ggg ggt cag agg aag aag cgg gct ttg gac acc aat tac tgc ttc cgg 1027Gly Gly Gln Arg Lys Lys Arg Ala Leu Asp Thr Asn Tyr Cys Phe Arg295 300 305tga gactgggccc acatgggaac caacatctac tgcctgccta ctgcccaatg 1080*gctaggtcag gccccagagc caagccacac tcaacagagg gtccctgata ctattcacaa 1140acatctccag gaagaagact gaaaatctct cacagagatt ttctctgtga aatctctttc 1200tgttttcctg ggagtcccac tgtttttcca taggctaact ctggaaggag ctggctgaag 1260taaatgagga aaactctgtg aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa 1320aaaaaaaaaa aaa 133326309PRTHomo sapiens 26Met Lys Met His Leu Gln Arg Ala Leu Val Val Leu Ala Leu Leu Asn1 5 10 15Phe Ala Thr Val Ser Leu Ser Leu Ser Thr Cys Thr Thr Leu Asp Phe20 25 30Gly His Ile Lys Lys Lys Arg Val Glu Ala Ile Arg Gly Gln Ile Leu35 40 45Ser Lys Leu Arg Leu Thr Ser Pro Pro Glu Pro Thr Val Met Thr His50 55 60Val Pro Tyr Gln Val Leu Ala Leu Tyr Asn Ser Thr Arg Glu Leu Leu65 70 75 80Glu Glu Met His Gly Glu Arg Glu Glu Gly Cys Thr Gln Glu Asn Thr85 90 95Glu Ser Glu Tyr Tyr Ala Lys Glu Ile His Lys Phe Asp Met Ile Gln100 105 110Gly Leu Ala Glu His Asn Glu Leu Ala Val Cys Pro Lys Gly Ile Thr115 120 125Ser Lys Val Phe Arg Phe Asn Val Ser Ser Val Glu Lys Asn Arg Thr130 135 140Asn Leu Phe Arg Ala Glu Phe Arg Val Leu Arg Val Pro Asn Pro Ser145 150 155 160Ser Lys Arg Asn Glu Gln Arg Ile Glu Leu Phe Gln Ile Leu Arg Pro165 170 175Asp Glu His Ile Ala Lys Gln Arg Tyr Ile Gly Gly Lys Asn Leu Pro180 185 190Thr Arg Gly Thr Ala Glu Trp Leu Ser Phe Asp Val Thr Asp Thr Val195 200 205Arg Glu Trp Leu Leu Arg Arg Glu Ser Asn Leu Gly Leu Glu Ile Ser210 215 220Ile His Cys Pro Cys His Thr Phe Gln Pro Asn Gly Asp Ile Leu Glu225 230 235 240Asn Ile His Glu Val Met Glu Ile Lys Phe Lys Gly Val Asp Asn Glu245 250 255Asp Asp His Gly Arg Gly Asp Leu Gly Arg Leu Lys Lys Gln Lys Asp260 265 270His His Asn Pro His Leu Ile Leu Met Met Ile Pro Pro His Arg Leu275 280 285Asp Asn Pro Gly Gln Gly Gly Gln Arg Lys Lys Arg Ala Leu Asp Thr290 295 300Asn Tyr Cys Phe Arg305276378DNAHomo sapiensCDS(140)...(3409) 27cccattactg ttggagctac agggagagaa acaggaggag actgcaagag atcatttggg 60aaggccgtgg gcacgctctt tactccatgt gtgggacatt cattgcggaa taacatcgga 120ggagaagttt cccagagct atg ggg act tcc cat ccg gcg ttc ctg gtc tta 172Met Gly Thr Ser His Pro Ala Phe Leu Val Leu1 5 10ggc tgt ctt ctc aca ggg ctg agc cta atc ctc tgc cag ctt tca tta 220Gly Cys Leu Leu Thr Gly Leu Ser Leu Ile Leu Cys Gln Leu Ser Leu15 20 25ccc tct atc ctt cca aat gaa aat gaa aag gtt gtg cag ctg aat tca 268Pro Ser Ile Leu Pro Asn Glu Asn Glu Lys Val Val Gln Leu Asn Ser30 35 40tcc ttt tct ctg aga tgc ttt ggg gag agt gaa gtg agc tgg cag tac 316Ser Phe Ser Leu Arg Cys Phe Gly Glu Ser Glu Val Ser Trp Gln Tyr45 50 55ccc atg tct gaa gaa gag agc tcc gat gtg gaa atc aga aat gaa gaa 364Pro Met Ser Glu Glu Glu Ser Ser Asp Val Glu Ile Arg Asn Glu Glu60 65 70 75aac aac agc ggc ctt ttt gtg acg gtc ttg gaa gtg agc agt gcc tcg 412Asn Asn Ser Gly Leu Phe Val Thr Val Leu Glu Val Ser Ser Ala Ser80 85 90gcg gcc cac aca ggg ttg tac act tgc tat tac aac cac act cag aca 460Ala Ala His Thr Gly Leu Tyr Thr Cys Tyr Tyr Asn His Thr Gln Thr95 100 105gaa gag aat gag ctt gaa ggc agg cac att tac atc tat gtg cca gac 508Glu Glu Asn Glu Leu Glu Gly Arg His Ile Tyr Ile Tyr Val Pro Asp110 115 120cca gat gta gcc ttt gta cct cta gga atg acg gat tat tta gtc atc 556Pro Asp Val Ala Phe Val Pro Leu Gly Met Thr Asp Tyr Leu Val Ile125 130 135gtg gag gat gat gat tct gcc att ata cct tgt cgc aca act gat ccc 604Val Glu Asp Asp Asp Ser Ala Ile Ile Pro Cys Arg Thr Thr Asp Pro140 145 150 155gag act cct gta acc tta cac aac agt gag ggg gtg gta cct gcc tcc 652Glu Thr Pro Val Thr Leu His Asn Ser Glu Gly Val Val Pro Ala Ser160 165 170tac gac agc aga cag ggc ttt aat ggg acc ttc act gta ggg ccc tat 700Tyr Asp Ser Arg Gln Gly Phe Asn Gly Thr Phe Thr Val Gly Pro Tyr175 180 185atc tgt gag gcc acc gtc aaa gga aag aag ttc cag acc atc cca ttt 748Ile Cys Glu Ala Thr Val Lys Gly Lys Lys Phe Gln Thr Ile Pro Phe190 195 200aat gtt tat gct tta aaa gca aca tca gag ctg gat cta gaa atg gaa 796Asn Val Tyr Ala Leu Lys Ala Thr Ser Glu Leu Asp Leu Glu Met Glu205 210 215gct ctt aaa acc gtg tat aag tca ggg gaa acg att gtg gtc acc tgt 844Ala Leu Lys Thr Val Tyr Lys Ser Gly Glu Thr Ile Val Val Thr Cys220 225 230 235gct gtt ttt aac aat gag gtg gtt gac ctt caa tgg act tac cct gga 892Ala Val Phe Asn Asn Glu Val Val Asp Leu Gln Trp Thr Tyr Pro Gly240 245 250gaa gtg aaa ggc aaa ggc atc aca atg ctg gaa gaa atc aaa gtc cca 940Glu Val Lys Gly Lys Gly Ile Thr Met Leu Glu Glu Ile Lys Val Pro255 260 265tcc atc aaa ttg gtg tac act ttg acg gtc ccc gag gcc acg gtg aaa 988Ser Ile Lys Leu Val Tyr Thr Leu Thr Val Pro Glu Ala Thr Val Lys270 275 280gac agt gga gat tac gaa tgt gct gcc cgc cag gct acc agg gag gtc 1036Asp Ser Gly Asp Tyr Glu Cys Ala Ala Arg Gln Ala Thr Arg Glu Val285 290 295aaa gaa atg aag aaa gtc act att tct gtc cat gag aaa ggt ttc att 1084Lys Glu Met Lys Lys Val Thr Ile Ser Val His
Glu Lys Gly Phe Ile300 305 310 315gaa atc aaa ccc acc ttc agc cag ttg gaa gct gtc aac ctg cat gaa 1132Glu Ile Lys Pro Thr Phe Ser Gln Leu Glu Ala Val Asn Leu His Glu320 325 330gtc aaa cat ttt gtt gta gag gtg cgg gcc tac cca cct ccc agg ata 1180Val Lys His Phe Val Val Glu Val Arg Ala Tyr Pro Pro Pro Arg Ile335 340 345tcc tgg ctg aaa aac aat ctg act ctg att gaa aat ctc act gag atc 1228Ser Trp Leu Lys Asn Asn Leu Thr Leu Ile Glu Asn Leu Thr Glu Ile350 355 360acc act gat gtg gaa aag att cag gaa ata agg tat cga agc aaa tta 1276Thr Thr Asp Val Glu Lys Ile Gln Glu Ile Arg Tyr Arg Ser Lys Leu365 370 375aag ctg atc cgt gct aag gaa gaa gac agt ggc cat tat act att gta 1324Lys Leu Ile Arg Ala Lys Glu Glu Asp Ser Gly His Tyr Thr Ile Val380 385 390 395gct caa aat gaa gat gct gtg aag agc tat act ttt gaa ctg tta act 1372Ala Gln Asn Glu Asp Ala Val Lys Ser Tyr Thr Phe Glu Leu Leu Thr400 405 410caa gtt cct tca tcc att ctg gac ttg gtc gat gat cac cat ggc tca 1420Gln Val Pro Ser Ser Ile Leu Asp Leu Val Asp Asp His His Gly Ser415 420 425act ggg gga cag acg gtg agg tgc aca gct gaa ggc acg ccg ctt cct 1468Thr Gly Gly Gln Thr Val Arg Cys Thr Ala Glu Gly Thr Pro Leu Pro430 435 440gat att gag tgg atg ata tgc aaa gat att aag aaa tgt aat aat gaa 1516Asp Ile Glu Trp Met Ile Cys Lys Asp Ile Lys Lys Cys Asn Asn Glu445 450 455act tcc tgg act att ttg gcc aac aat gtc tca aac atc atc acg gag 1564Thr Ser Trp Thr Ile Leu Ala Asn Asn Val Ser Asn Ile Ile Thr Glu460 465 470 475atc cac tcc cga gac agg agt acc gtg gag ggc cgt gtg act ttc gcc 1612Ile His Ser Arg Asp Arg Ser Thr Val Glu Gly Arg Val Thr Phe Ala480 485 490aaa gtg gag gag acc atc gcc gtg cga tgc ctg gct aag aat ctc ctt 1660Lys Val Glu Glu Thr Ile Ala Val Arg Cys Leu Ala Lys Asn Leu Leu495 500 505gga gct gag aac cga gag ctg aag ctg gtg gct ccc acc ctg cgt tct 1708Gly Ala Glu Asn Arg Glu Leu Lys Leu Val Ala Pro Thr Leu Arg Ser510 515 520gaa ctc acg gtg gct gct gca gtc ctg gtg ctg ttg gtg att gtg atc 1756Glu Leu Thr Val Ala Ala Ala Val Leu Val Leu Leu Val Ile Val Ile525 530 535atc tca ctt att gtc ctg gtt gtc att tgg aaa cag aaa ccg agg tat 1804Ile Ser Leu Ile Val Leu Val Val Ile Trp Lys Gln Lys Pro Arg Tyr540 545 550 555gaa att cgc tgg agg gtc att gaa tca atc agc ccg gat gga cat gaa 1852Glu Ile Arg Trp Arg Val Ile Glu Ser Ile Ser Pro Asp Gly His Glu560 565 570tat att tat gtg gac ccg atg cag ctg cct tat gac tca aga tgg gag 1900Tyr Ile Tyr Val Asp Pro Met Gln Leu Pro Tyr Asp Ser Arg Trp Glu575 580 585ttt cca aga gat gga cta gtg ctt ggt cgg gtc ttg ggg tct gga gcg 1948Phe Pro Arg Asp Gly Leu Val Leu Gly Arg Val Leu Gly Ser Gly Ala590 595 600ttt ggg aag gtg gtt gaa gga aca gcc tat gga tta agc cgg tcc caa 1996Phe Gly Lys Val Val Glu Gly Thr Ala Tyr Gly Leu Ser Arg Ser Gln605 610 615cct gtc atg aaa gtt gca gtg aag atg cta aaa ccc acg gcc aga tcc 2044Pro Val Met Lys Val Ala Val Lys Met Leu Lys Pro Thr Ala Arg Ser620 625 630 635agt gaa aaa caa gct ctc atg tct gaa ctg aag ata atg act cac ctg 2092Ser Glu Lys Gln Ala Leu Met Ser Glu Leu Lys Ile Met Thr His Leu640 645 650ggg cca cat ttg aac att gta aac ttg ctg gga gcc tgc acc aag tca 2140Gly Pro His Leu Asn Ile Val Asn Leu Leu Gly Ala Cys Thr Lys Ser655 660 665ggc ccc att tac atc atc aca gag tat tgc ttc tat gga gat ttg gtc 2188Gly Pro Ile Tyr Ile Ile Thr Glu Tyr Cys Phe Tyr Gly Asp Leu Val670 675 680aac tat ttg cat aag aat agg gat agc ttc ctg agc cac cac cca gag 2236Asn Tyr Leu His Lys Asn Arg Asp Ser Phe Leu Ser His His Pro Glu685 690 695aag cca aag aaa gag ctg gat atc ttt gga ttg aac cct gct gat gaa 2284Lys Pro Lys Lys Glu Leu Asp Ile Phe Gly Leu Asn Pro Ala Asp Glu700 705 710 715agc aca cgg agc tat gtt att tta tct ttt gaa aac aat ggt gac tac 2332Ser Thr Arg Ser Tyr Val Ile Leu Ser Phe Glu Asn Asn Gly Asp Tyr720 725 730atg gac atg aag cag gct gat act aca cag tat gtc ccc atg cta gaa 2380Met Asp Met Lys Gln Ala Asp Thr Thr Gln Tyr Val Pro Met Leu Glu735 740 745agg aaa gag gtt tct aaa tat tcc gac atc cag aga tca ctc tat gat 2428Arg Lys Glu Val Ser Lys Tyr Ser Asp Ile Gln Arg Ser Leu Tyr Asp750 755 760cgt cca gcc tca tat aag aag aaa tct atg tta gac tca gaa gtc aaa 2476Arg Pro Ala Ser Tyr Lys Lys Lys Ser Met Leu Asp Ser Glu Val Lys765 770 775aac ctc ctt tca gat gat aac tca gaa ggc ctt act tta ttg gat ttg 2524Asn Leu Leu Ser Asp Asp Asn Ser Glu Gly Leu Thr Leu Leu Asp Leu780 785 790 795ttg agc ttc acc tat caa gtt gcc cga gga atg gag ttt ttg gct tca 2572Leu Ser Phe Thr Tyr Gln Val Ala Arg Gly Met Glu Phe Leu Ala Ser800 805 810aaa aat tgt gtc cac cgt gat ctg gct gct cgc aac gtc ctc ctg gca 2620Lys Asn Cys Val His Arg Asp Leu Ala Ala Arg Asn Val Leu Leu Ala815 820 825caa gga aaa att gtg aag atc tgt gac ttt ggc ctg gcc aga gac atc 2668Gln Gly Lys Ile Val Lys Ile Cys Asp Phe Gly Leu Ala Arg Asp Ile830 835 840atg cat gat tcg aac tat gtg tcg aaa ggc agt acc ttt ctg ccc gtg 2716Met His Asp Ser Asn Tyr Val Ser Lys Gly Ser Thr Phe Leu Pro Val845 850 855aag tgg atg gct cct gag agc atc ttt gac aac ctc tac acc aca ctg 2764Lys Trp Met Ala Pro Glu Ser Ile Phe Asp Asn Leu Tyr Thr Thr Leu860 865 870 875agt gat gtc tgg tct tat ggc att ctg ctc tgg gag atc ttt tcc ctt 2812Ser Asp Val Trp Ser Tyr Gly Ile Leu Leu Trp Glu Ile Phe Ser Leu880 885 890ggt ggc acc cct tac ccc ggc atg atg gtg gat tct act ttc tac aat 2860Gly Gly Thr Pro Tyr Pro Gly Met Met Val Asp Ser Thr Phe Tyr Asn895 900 905aag atc aag agt ggg tac cgg atg gcc aag cct gac cac gct acc agt 2908Lys Ile Lys Ser Gly Tyr Arg Met Ala Lys Pro Asp His Ala Thr Ser910 915 920gaa gtc tac gag atc atg gtg aaa tgc tgg aac agt gag ccg gag aag 2956Glu Val Tyr Glu Ile Met Val Lys Cys Trp Asn Ser Glu Pro Glu Lys925 930 935aga ccc tcc ttt tac cac ctg agt gag att gtg gag aat ctg ctg cct 3004Arg Pro Ser Phe Tyr His Leu Ser Glu Ile Val Glu Asn Leu Leu Pro940 945 950 955gga caa tat aaa aag agt tat gaa aaa att cac ctg gac ttc ctg aag 3052Gly Gln Tyr Lys Lys Ser Tyr Glu Lys Ile His Leu Asp Phe Leu Lys960 965 970agt gac cat cct gct gtg gca cgc atg cgt gtg gac tca gac aat gca 3100Ser Asp His Pro Ala Val Ala Arg Met Arg Val Asp Ser Asp Asn Ala975 980 985tac att ggt gtc acc tac aaa aac gag gaa gac aag ctg aag gac tgg 3148Tyr Ile Gly Val Thr Tyr Lys Asn Glu Glu Asp Lys Leu Lys Asp Trp990 995 1000gag ggt ggt ctg gat gag cag aga ctg agc gct gac agt ggc tac atc 3196Glu Gly Gly Leu Asp Glu Gln Arg Leu Ser Ala Asp Ser Gly Tyr Ile1005 1010 1015att cct ctg cct gac att gac cct gtc cct gag gag gag gac ctg ggc 3244Ile Pro Leu Pro Asp Ile Asp Pro Val Pro Glu Glu Glu Asp Leu Gly1020 1025 1030 1035aag agg aac aga cac agc tcg cag acc tct gaa gag agt gcc att gag 3292Lys Arg Asn Arg His Ser Ser Gln Thr Ser Glu Glu Ser Ala Ile Glu1040 1045 1050acg ggt tcc agc agt tcc acc ttc atc aag aga gag gac gag acc att 3340Thr Gly Ser Ser Ser Ser Thr Phe Ile Lys Arg Glu Asp Glu Thr Ile1055 1060 1065gaa gac atc gac atg atg gac gac atc ggc ata gac tct tca gac ctg 3388Glu Asp Ile Asp Met Met Asp Asp Ile Gly Ile Asp Ser Ser Asp Leu1070 1075 1080gtg gaa gac agc ttc ctg taa ctggcggatt cgaggggttc cttccacttc 3439Val Glu Asp Ser Phe Leu *1085tggggccacc tctggatccc gttcagaaaa ccactttatt gcaatgcgga ggttgagagg 3499aggacttggt tgatgtttaa agagaagttc ccagccaagg gcctcgggga gcgttctaaa 3559tatgaatgaa tgggatattt tgaaatgaac tttgtcagtg ttgcctctcg caatgcctca 3619gtagcatctc agtggtgtgt gaagtttgga gatagatgga taagggaata ataggccaca 3679gaaggtgaac tttgtgcttc aaggacattg gtgagagtcc aacagacaca atttatactg 3739cgacagaact tcagcattgt aattatgtaa ataactctaa ccaaggctgt gtttagattg 3799tattaactat cttctttgga cttctgaaga gaccactcaa tccatccatg tacttccctc 3859ttgaaacctg atgtcagctg ctgttgaact ttttaaagaa gtgcatgaaa aaccattttt 3919gaaccttaaa aggtactggt actatagcat tttgctatct tttttagtgt taagagataa 3979agaataataa ttaaccaacc ttgtttaata gatttgggtc atttagaagc ctgacaactc 4039attttcatat tgtaatctat gtttataata ctactactgt tatcagtaat gctaaatgtg 4099taataatgta acatgatttc cctccagaga aagcacaatt taaaacaatc cttactaagt 4159aggtgatgag tttgacagtt tttgacattt atattaaata acatgtttct ctataaagta 4219tggtaatagc tttagtgaat taaatttagt tgagcataga gaacaaagta aaagtagtgt 4279tgtccaggaa gtcagaattt ttaactgtac tgaataggtt ccccaatcca tcgtattaaa 4339aaacaattaa ctgccctctg aaataatggg attagaaaca aacaaaactc ttaagtccta 4399aaagttctca atgtagaggc ataaacctgt gctgaacata acttctcatg tatattaccc 4459aatggaaaat ataatgatca gcaaaaagac tggatttgca gaagtttttt ttttttttct 4519tcatgcctga tgaaagcttt ggcaacccca atatatgtat tttttgaatc tatgaacctg 4579aaaagggtca gaaggatgcc cagacatcag cctccttctt tcacccctta ccccaaagag 4639aaagagtttg aaactcgaga ccataaagat attctttagt ggaggctgga tgtgcattag 4699cctggatcct cagttctcaa atgtgtgtgg cagccaggat gactagatcc tgggtttcca 4759tccttgagat tctgaagtat gaagtctgag ggaaaccaga gtctgtattt ttctaaactc 4819cctggctgtt ctgatcggcc agttttcgga aacactgact taggtttcag gaagttgcca 4879tgggaaacaa ataatttgaa ctttggaaca gggttggaat tcaaccacgc aggaagccta 4939ctatttaaat ccttggcttc aggttagtga catttaatgc catctagcta gcaattgcga 4999ccttaattta actttccagt cttagctgag gctgagaaag ctaaagtttg gttttgacag 5059gttttccaaa agtaaagatg ctacttccca ctgtatgggg gagattgaac tttccccgtc 5119tcccgtcttc tgcctcccac tccatacccc gccaaggaaa ggcatgtaca aaaattatgc 5179aattcagtgt tccaagtctc tgtgtaacca gctcagtgtt ttggtggaaa aaacatttta 5239agttttactg ataatttgag gttagatggg aggatgaatt gtcacatcta tccacactgt 5299caaacaggtt ggtgtgggtt cattggcatt ctttgcaata ctgcttaatt gctgatacca 5359tatgaatgaa acatgggctg tgattactgc aatcactgtg ctatcggcag atgatgcttt 5419ggaagatgca gaagcaataa taaagtactt gactacctac tggtgtaatc tcaatgcaag 5479ccccaacttt cttatccaac tttttcatag taagtgcgaa gactgagcca gattggccaa 5539ttaaaaacga aaacctgact aggttctgta gagccaatta gacttgaaat acgtttgtgt 5599ttctagaatc acagctcaag cattctgttt atcgctcact ctcccttgta cagccttatt 5659ttgttggtgc tttgcatttt gatattgctg tgagccttgc atgacatcat gaggccggat 5719gaaacttctc agtccagcag tttccagtcc taacaaatgc tcccacctga atttgtatat 5779gactgcattt gtgggtgtgt gtgtgttttc agcaaattcc agatttgttt ccttttggcc 5839tcctgcaaag tctccagaag aaaatttgcc aatctttcct actttctatt tttatgatga 5899caatcaaagc cggcctgaga aacactattt gtgacttttt aaacgattag tgatgtcctt 5959aaaatgtggt ctgccaatct gtacaaaatg gtcctatttt tgtgaagagg gacataagat 6019aaaatgatgt tatacatcaa tatgtatata tgtatttcta tatagacttg gagaatactg 6079ccaaaacatt tatgacaagc tgtatcactg ccttcgttta tattttttta actgtgataa 6139tccccacagg cacattaact gttgcacttt tgaatgtcca aaatttatat tttagaaata 6199ataaaaagaa agatacttac atgttcccaa aacaatggtg tggtgaatgt gtgagaaaaa 6259ctaacttgat agggtctacc aatacaaaat gtattacgaa tgcccctgtt catgtttttg 6319ttttaaaacg tgtaaatgaa gatctttata tttcaataaa tgatatataa tttaaagtt 6378281089PRTHomo sapiens 28Met Gly Thr Ser His Pro Ala Phe Leu Val Leu Gly Cys Leu Leu Thr1 5 10 15Gly Leu Ser Leu Ile Leu Cys Gln Leu Ser Leu Pro Ser Ile Leu Pro20 25 30Asn Glu Asn Glu Lys Val Val Gln Leu Asn Ser Ser Phe Ser Leu Arg35 40 45Cys Phe Gly Glu Ser Glu Val Ser Trp Gln Tyr Pro Met Ser Glu Glu50 55 60Glu Ser Ser Asp Val Glu Ile Arg Asn Glu Glu Asn Asn Ser Gly Leu65 70 75 80Phe Val Thr Val Leu Glu Val Ser Ser Ala Ser Ala Ala His Thr Gly85 90 95Leu Tyr Thr Cys Tyr Tyr Asn His Thr Gln Thr Glu Glu Asn Glu Leu100 105 110Glu Gly Arg His Ile Tyr Ile Tyr Val Pro Asp Pro Asp Val Ala Phe115 120 125Val Pro Leu Gly Met Thr Asp Tyr Leu Val Ile Val Glu Asp Asp Asp130 135 140Ser Ala Ile Ile Pro Cys Arg Thr Thr Asp Pro Glu Thr Pro Val Thr145 150 155 160Leu His Asn Ser Glu Gly Val Val Pro Ala Ser Tyr Asp Ser Arg Gln165 170 175Gly Phe Asn Gly Thr Phe Thr Val Gly Pro Tyr Ile Cys Glu Ala Thr180 185 190Val Lys Gly Lys Lys Phe Gln Thr Ile Pro Phe Asn Val Tyr Ala Leu195 200 205Lys Ala Thr Ser Glu Leu Asp Leu Glu Met Glu Ala Leu Lys Thr Val210 215 220Tyr Lys Ser Gly Glu Thr Ile Val Val Thr Cys Ala Val Phe Asn Asn225 230 235 240Glu Val Val Asp Leu Gln Trp Thr Tyr Pro Gly Glu Val Lys Gly Lys245 250 255Gly Ile Thr Met Leu Glu Glu Ile Lys Val Pro Ser Ile Lys Leu Val260 265 270Tyr Thr Leu Thr Val Pro Glu Ala Thr Val Lys Asp Ser Gly Asp Tyr275 280 285Glu Cys Ala Ala Arg Gln Ala Thr Arg Glu Val Lys Glu Met Lys Lys290 295 300Val Thr Ile Ser Val His Glu Lys Gly Phe Ile Glu Ile Lys Pro Thr305 310 315 320Phe Ser Gln Leu Glu Ala Val Asn Leu His Glu Val Lys His Phe Val325 330 335Val Glu Val Arg Ala Tyr Pro Pro Pro Arg Ile Ser Trp Leu Lys Asn340 345 350Asn Leu Thr Leu Ile Glu Asn Leu Thr Glu Ile Thr Thr Asp Val Glu355 360 365Lys Ile Gln Glu Ile Arg Tyr Arg Ser Lys Leu Lys Leu Ile Arg Ala370 375 380Lys Glu Glu Asp Ser Gly His Tyr Thr Ile Val Ala Gln Asn Glu Asp385 390 395 400Ala Val Lys Ser Tyr Thr Phe Glu Leu Leu Thr Gln Val Pro Ser Ser405 410 415Ile Leu Asp Leu Val Asp Asp His His Gly Ser Thr Gly Gly Gln Thr420 425 430Val Arg Cys Thr Ala Glu Gly Thr Pro Leu Pro Asp Ile Glu Trp Met435 440 445Ile Cys Lys Asp Ile Lys Lys Cys Asn Asn Glu Thr Ser Trp Thr Ile450 455 460Leu Ala Asn Asn Val Ser Asn Ile Ile Thr Glu Ile His Ser Arg Asp465 470 475 480Arg Ser Thr Val Glu Gly Arg Val Thr Phe Ala Lys Val Glu Glu Thr485 490 495Ile Ala Val Arg Cys Leu Ala Lys Asn Leu Leu Gly Ala Glu Asn Arg500 505 510Glu Leu Lys Leu Val Ala Pro Thr Leu Arg Ser Glu Leu Thr Val Ala515 520 525Ala Ala Val Leu Val Leu Leu Val Ile Val Ile Ile Ser Leu Ile Val530 535 540Leu Val Val Ile Trp Lys Gln Lys Pro Arg Tyr Glu Ile Arg Trp Arg545 550 555 560Val Ile Glu Ser Ile Ser Pro Asp Gly His Glu Tyr Ile Tyr Val Asp565 570 575Pro Met Gln Leu Pro Tyr Asp Ser Arg Trp Glu Phe Pro Arg Asp Gly580 585 590Leu Val Leu Gly Arg Val Leu Gly Ser Gly Ala Phe Gly Lys Val Val595 600 605Glu Gly Thr Ala Tyr Gly Leu Ser Arg Ser Gln Pro Val Met Lys Val610 615 620Ala Val Lys Met Leu Lys Pro Thr Ala Arg Ser Ser Glu Lys Gln Ala625 630 635 640Leu Met Ser Glu Leu Lys Ile Met Thr His Leu Gly Pro His Leu Asn645 650 655Ile Val Asn Leu Leu Gly Ala Cys Thr Lys Ser Gly Pro Ile Tyr Ile660 665 670Ile Thr Glu Tyr Cys Phe Tyr Gly Asp Leu Val Asn Tyr Leu His Lys675 680 685Asn Arg Asp Ser Phe Leu Ser His His Pro Glu Lys Pro Lys Lys Glu690 695 700Leu Asp Ile Phe Gly Leu Asn Pro Ala Asp Glu Ser Thr Arg Ser Tyr705 710 715 720Val Ile Leu Ser Phe Glu Asn Asn Gly Asp Tyr Met Asp Met Lys Gln725 730 735Ala Asp Thr Thr Gln Tyr Val Pro Met Leu Glu Arg Lys Glu Val Ser740 745 750Lys Tyr Ser Asp Ile Gln Arg Ser Leu Tyr Asp Arg Pro Ala Ser Tyr755 760 765Lys Lys Lys Ser Met Leu Asp Ser Glu Val Lys Asn Leu Leu Ser Asp770 775 780Asp Asn Ser Glu Gly Leu Thr Leu Leu Asp Leu Leu Ser Phe Thr Tyr785 790 795 800Gln Val Ala Arg Gly Met Glu Phe Leu Ala Ser Lys Asn Cys Val His805 810 815Arg Asp Leu Ala Ala Arg Asn Val Leu Leu Ala Gln Gly Lys Ile Val820 825 830Lys Ile Cys Asp Phe Gly Leu Ala Arg Asp Ile
Met His Asp Ser Asn835 840 845Tyr Val Ser Lys Gly Ser Thr Phe Leu Pro Val Lys Trp Met Ala Pro850 855 860Glu Ser Ile Phe Asp Asn Leu Tyr Thr Thr Leu Ser Asp Val Trp Ser865 870 875 880Tyr Gly Ile Leu Leu Trp Glu Ile Phe Ser Leu Gly Gly Thr Pro Tyr885 890 895Pro Gly Met Met Val Asp Ser Thr Phe Tyr Asn Lys Ile Lys Ser Gly900 905 910Tyr Arg Met Ala Lys Pro Asp His Ala Thr Ser Glu Val Tyr Glu Ile915 920 925Met Val Lys Cys Trp Asn Ser Glu Pro Glu Lys Arg Pro Ser Phe Tyr930 935 940His Leu Ser Glu Ile Val Glu Asn Leu Leu Pro Gly Gln Tyr Lys Lys945 950 955 960Ser Tyr Glu Lys Ile His Leu Asp Phe Leu Lys Ser Asp His Pro Ala965 970 975Val Ala Arg Met Arg Val Asp Ser Asp Asn Ala Tyr Ile Gly Val Thr980 985 990Tyr Lys Asn Glu Glu Asp Lys Leu Lys Asp Trp Glu Gly Gly Leu Asp995 1000 1005Glu Gln Arg Leu Ser Ala Asp Ser Gly Tyr Ile Ile Pro Leu Pro Asp1010 1015 1020Ile Asp Pro Val Pro Glu Glu Glu Asp Leu Gly Lys Arg Asn Arg His1025 1030 1035 1040Ser Ser Gln Thr Ser Glu Glu Ser Ala Ile Glu Thr Gly Ser Ser Ser1045 1050 1055Ser Thr Phe Ile Lys Arg Glu Asp Glu Thr Ile Glu Asp Ile Asp Met1060 1065 1070Met Asp Asp Ile Gly Ile Asp Ser Ser Asp Leu Val Glu Asp Ser Phe1075 1080 1085Leu292121DNAHomo sapiensCDS(559)...(1878) 29ctgctcgcgg ccgccaccgc cgggccccgg ccgtccctgg ctcccctcct gcctcgagaa 60gggcagggct tctcagaggc ttggcgggaa aaaagaacgg agggagggat cgcgctgagt 120ataaaagccg gttttcgggg ctttatctaa ctcgctgtag taattccagc gagaggcaga 180gggagcgagc gggcggccgg ctagggtgga agagccgggc gagcagagct gcgctgcggg 240cgtcctggga agggagatcc ggagcgaata gggggcttcg cctctggccc agccctcccg 300cttgatcccc caggccagcg gtccgcaacc cttgccgcat ccacgaaact ttgcccatag 360cagcgggcgg gcactttgca ctggaactta caacacccga gcaaggacgc gactctcccg 420acgcggggag gctattctgc ccatttgggg acacttcccc gccgctgcca ggacccgctt 480ctctgaaagg ctctccttgc agctgcttag acgctggatt tttttcgggt agtggaaaac 540cagcagcctc ccgcgacg atg ccc ctc aac gtt agc ttc acc aac agg aac 591Met Pro Leu Asn Val Ser Phe Thr Asn Arg Asn1 5 10tat gac ctc gac tac gac tcg gtg cag ccg tat ttc tac tgc gac gag 639Tyr Asp Leu Asp Tyr Asp Ser Val Gln Pro Tyr Phe Tyr Cys Asp Glu15 20 25gag gag aac ttc tac cag cag cag cag cag agc gag ctg cag ccc ccg 687Glu Glu Asn Phe Tyr Gln Gln Gln Gln Gln Ser Glu Leu Gln Pro Pro30 35 40gcg ccc agc gag gat atc tgg aag aaa ttc gag ctg ctg ccc acc ccg 735Ala Pro Ser Glu Asp Ile Trp Lys Lys Phe Glu Leu Leu Pro Thr Pro45 50 55ccc ctg tcc cct agc cgc cgc tcc ggg ctc tgc tcg ccc tcc tac gtt 783Pro Leu Ser Pro Ser Arg Arg Ser Gly Leu Cys Ser Pro Ser Tyr Val60 65 70 75gcg gtc aca ccc ttc tcc ctt cgg gga gac aac gac ggc ggt ggc ggg 831Ala Val Thr Pro Phe Ser Leu Arg Gly Asp Asn Asp Gly Gly Gly Gly80 85 90agc ttc tcc acg gcc gac cag ctg gag atg gtg acc gag ctg ctg gga 879Ser Phe Ser Thr Ala Asp Gln Leu Glu Met Val Thr Glu Leu Leu Gly95 100 105gga gac atg gtg aac cag agt ttc atc tgc gac ccg gac gac gag acc 927Gly Asp Met Val Asn Gln Ser Phe Ile Cys Asp Pro Asp Asp Glu Thr110 115 120ttc atc aaa aac atc atc atc cag gac tgt atg tgg agc ggc ttc tcg 975Phe Ile Lys Asn Ile Ile Ile Gln Asp Cys Met Trp Ser Gly Phe Ser125 130 135gcc gcc gcc aag ctc gtc tca gag aag ctg gcc tcc tac cag gct gcg 1023Ala Ala Ala Lys Leu Val Ser Glu Lys Leu Ala Ser Tyr Gln Ala Ala140 145 150 155cgc aaa gac agc ggc agc ccg aac ccc gcc cgc ggc cac agc gtc tgc 1071Arg Lys Asp Ser Gly Ser Pro Asn Pro Ala Arg Gly His Ser Val Cys160 165 170tcc acc tcc agc ttg tac ctg cag gat ctg agc gcc gcc gcc tca gag 1119Ser Thr Ser Ser Leu Tyr Leu Gln Asp Leu Ser Ala Ala Ala Ser Glu175 180 185tgc atc gac ccc tcg gtg gtc ttc ccc tac cct ctc aac gac agc agc 1167Cys Ile Asp Pro Ser Val Val Phe Pro Tyr Pro Leu Asn Asp Ser Ser190 195 200tcg ccc aag tcc tgc gcc tcg caa gac tcc agc gcc ttc tct ccg tcc 1215Ser Pro Lys Ser Cys Ala Ser Gln Asp Ser Ser Ala Phe Ser Pro Ser205 210 215tcg gat tct ctg ctc tcc tcg acg gag tcc tcc ccg cag ggc agc ccc 1263Ser Asp Ser Leu Leu Ser Ser Thr Glu Ser Ser Pro Gln Gly Ser Pro220 225 230 235gag ccc ctg gtg ctc cat gag gag aca ccg ccc acc acc agc agc gac 1311Glu Pro Leu Val Leu His Glu Glu Thr Pro Pro Thr Thr Ser Ser Asp240 245 250tct gag gag gaa caa gaa gat gag gaa gaa atc gat gtt gtt tct gtg 1359Ser Glu Glu Glu Gln Glu Asp Glu Glu Glu Ile Asp Val Val Ser Val255 260 265gaa aag agg cag gct cct ggc aaa agg tca gag tct gga tca cct tct 1407Glu Lys Arg Gln Ala Pro Gly Lys Arg Ser Glu Ser Gly Ser Pro Ser270 275 280gct gga ggc cac agc aaa cct cct cac agc cca ctg gtc ctc aag agg 1455Ala Gly Gly His Ser Lys Pro Pro His Ser Pro Leu Val Leu Lys Arg285 290 295tgc cac gtc tcc aca cat cag cac aac tac gca gcg cct ccc tcc act 1503Cys His Val Ser Thr His Gln His Asn Tyr Ala Ala Pro Pro Ser Thr300 305 310 315cgg aag gac tat cct gct gcc aag agg gtc aag ttg gac agt gtc aga 1551Arg Lys Asp Tyr Pro Ala Ala Lys Arg Val Lys Leu Asp Ser Val Arg320 325 330gtc ctg aga cag atc agc aac aac cga aaa tgc acc agc ccc agg tcc 1599Val Leu Arg Gln Ile Ser Asn Asn Arg Lys Cys Thr Ser Pro Arg Ser335 340 345tcg gac acc gag gag aat gtc aag agg cga aca cac aac gtc ttg gag 1647Ser Asp Thr Glu Glu Asn Val Lys Arg Arg Thr His Asn Val Leu Glu350 355 360cgc cag agg agg aac gag cta aaa cgg agc ttt ttt gcc ctg cgt gac 1695Arg Gln Arg Arg Asn Glu Leu Lys Arg Ser Phe Phe Ala Leu Arg Asp365 370 375cag atc ccg gag ttg gaa aac aat gaa aag gcc ccc aag gta gtt atc 1743Gln Ile Pro Glu Leu Glu Asn Asn Glu Lys Ala Pro Lys Val Val Ile380 385 390 395ctt aaa aaa gcc aca gca tac atc ctg tcc gtc caa gca gag gag caa 1791Leu Lys Lys Ala Thr Ala Tyr Ile Leu Ser Val Gln Ala Glu Glu Gln400 405 410aag ctc att tct gaa gag gac ttg ttg cgg aaa cga cga gaa cag ttg 1839Lys Leu Ile Ser Glu Glu Asp Leu Leu Arg Lys Arg Arg Glu Gln Leu415 420 425aaa cac aaa ctt gaa cag cta cgg aac tct tgt gcg taa ggaaaagtaa 1888Lys His Lys Leu Glu Gln Leu Arg Asn Ser Cys Ala *430 435ggaaaacgat tccttctaac agaaatgtcc tgagcaatca cctatgaact tgtttcaaat 1948gcatgatcaa atgcaacctc acaaccttgg ctgagtcttg agactgaaag atttagccat 2008aatgtaaact gcctcaaatt ggactttggg cataaaagaa cttttttatg cttaccatct 2068tttttttttc tttaacagat ttgtatttaa gaattgtttt taaaaaattt taa 212130439PRTHomo sapiens 30Met Pro Leu Asn Val Ser Phe Thr Asn Arg Asn Tyr Asp Leu Asp Tyr1 5 10 15Asp Ser Val Gln Pro Tyr Phe Tyr Cys Asp Glu Glu Glu Asn Phe Tyr20 25 30Gln Gln Gln Gln Gln Ser Glu Leu Gln Pro Pro Ala Pro Ser Glu Asp35 40 45Ile Trp Lys Lys Phe Glu Leu Leu Pro Thr Pro Pro Leu Ser Pro Ser50 55 60Arg Arg Ser Gly Leu Cys Ser Pro Ser Tyr Val Ala Val Thr Pro Phe65 70 75 80Ser Leu Arg Gly Asp Asn Asp Gly Gly Gly Gly Ser Phe Ser Thr Ala85 90 95Asp Gln Leu Glu Met Val Thr Glu Leu Leu Gly Gly Asp Met Val Asn100 105 110Gln Ser Phe Ile Cys Asp Pro Asp Asp Glu Thr Phe Ile Lys Asn Ile115 120 125Ile Ile Gln Asp Cys Met Trp Ser Gly Phe Ser Ala Ala Ala Lys Leu130 135 140Val Ser Glu Lys Leu Ala Ser Tyr Gln Ala Ala Arg Lys Asp Ser Gly145 150 155 160Ser Pro Asn Pro Ala Arg Gly His Ser Val Cys Ser Thr Ser Ser Leu165 170 175Tyr Leu Gln Asp Leu Ser Ala Ala Ala Ser Glu Cys Ile Asp Pro Ser180 185 190Val Val Phe Pro Tyr Pro Leu Asn Asp Ser Ser Ser Pro Lys Ser Cys195 200 205Ala Ser Gln Asp Ser Ser Ala Phe Ser Pro Ser Ser Asp Ser Leu Leu210 215 220Ser Ser Thr Glu Ser Ser Pro Gln Gly Ser Pro Glu Pro Leu Val Leu225 230 235 240His Glu Glu Thr Pro Pro Thr Thr Ser Ser Asp Ser Glu Glu Glu Gln245 250 255Glu Asp Glu Glu Glu Ile Asp Val Val Ser Val Glu Lys Arg Gln Ala260 265 270Pro Gly Lys Arg Ser Glu Ser Gly Ser Pro Ser Ala Gly Gly His Ser275 280 285Lys Pro Pro His Ser Pro Leu Val Leu Lys Arg Cys His Val Ser Thr290 295 300His Gln His Asn Tyr Ala Ala Pro Pro Ser Thr Arg Lys Asp Tyr Pro305 310 315 320Ala Ala Lys Arg Val Lys Leu Asp Ser Val Arg Val Leu Arg Gln Ile325 330 335Ser Asn Asn Arg Lys Cys Thr Ser Pro Arg Ser Ser Asp Thr Glu Glu340 345 350Asn Val Lys Arg Arg Thr His Asn Val Leu Glu Arg Gln Arg Arg Asn355 360 365Glu Leu Lys Arg Ser Phe Phe Ala Leu Arg Asp Gln Ile Pro Glu Leu370 375 380Glu Asn Asn Glu Lys Ala Pro Lys Val Val Ile Leu Lys Lys Ala Thr385 390 395 400Ala Tyr Ile Leu Ser Val Gln Ala Glu Glu Gln Lys Leu Ile Ser Glu405 410 415Glu Asp Leu Leu Arg Lys Arg Arg Glu Gln Leu Lys His Lys Leu Glu420 425 430Gln Leu Arg Asn Ser Cys Ala435311374DNAHomo sapiensCDS(103)...(1047) 31ggacagcttg gagatagggc ccggaattgc gggcgtcact ctgctcctgc gacctagcca 60ggcgtgaggg agtgacagca gcgcattcgc gggacgagag cg atg agt gag aac 114Met Ser Glu Asn1gcc gca cca ggt ctg atc tca gag ctg aag ctg gct gtg ccc tgg ggc 162Ala Ala Pro Gly Leu Ile Ser Glu Leu Lys Leu Ala Val Pro Trp Gly5 10 15 20cac atc gca gcc aaa gcc tgg ggc tcc ctg cag ggc cct cca gtt ctc 210His Ile Ala Ala Lys Ala Trp Gly Ser Leu Gln Gly Pro Pro Val Leu25 30 35tgc ctg cac ggc tgg ctg gac aat gcc agc tcc ttc gac aga ctc atc 258Cys Leu His Gly Trp Leu Asp Asn Ala Ser Ser Phe Asp Arg Leu Ile40 45 50cct ctt ctc ccg caa gac ttt tat tac gtt gcc atg gat ttc gga ggt 306Pro Leu Leu Pro Gln Asp Phe Tyr Tyr Val Ala Met Asp Phe Gly Gly55 60 65cat ggg ctc tcg tcc cat tac agc cca ggt gtc cca tat tac ctc cag 354His Gly Leu Ser Ser His Tyr Ser Pro Gly Val Pro Tyr Tyr Leu Gln70 75 80act ttt gtg agt gag atc cga aga gtt gtg gca gcc ttg aaa tgg aat 402Thr Phe Val Ser Glu Ile Arg Arg Val Val Ala Ala Leu Lys Trp Asn85 90 95 100cga ttc tcc att ctg ggc cac agc ttc ggt ggc gtc gtg ggc gga atg 450Arg Phe Ser Ile Leu Gly His Ser Phe Gly Gly Val Val Gly Gly Met105 110 115ttt ttc tgt acc ttc ccc gag atg gtg gat aaa ctt atc ttg ctg gac 498Phe Phe Cys Thr Phe Pro Glu Met Val Asp Lys Leu Ile Leu Leu Asp120 125 130acg ccg ctc ttt ctc ctg gaa tca gat gaa atg gag aac ttg ctg acc 546Thr Pro Leu Phe Leu Leu Glu Ser Asp Glu Met Glu Asn Leu Leu Thr135 140 145tac aag cgg aga gcc ata gag cac gtg ctg cag gta gag gcc tcc cag 594Tyr Lys Arg Arg Ala Ile Glu His Val Leu Gln Val Glu Ala Ser Gln150 155 160gag ccc tcg cac gtg ttc agc ctg aag cag ctg ctg cag agg tta ctg 642Glu Pro Ser His Val Phe Ser Leu Lys Gln Leu Leu Gln Arg Leu Leu165 170 175 180aag agc aat agc cac ttg agt gag gag tgc ggg gag ctt ctc ctg caa 690Lys Ser Asn Ser His Leu Ser Glu Glu Cys Gly Glu Leu Leu Leu Gln185 190 195aga gga acc acg aag gtg gcc aca ggt ctg gtt ctg aac aga gac cag 738Arg Gly Thr Thr Lys Val Ala Thr Gly Leu Val Leu Asn Arg Asp Gln200 205 210agg ctc gcc tgg gca gag aac agc att gac ttc atc agc agg gag ctg 786Arg Leu Ala Trp Ala Glu Asn Ser Ile Asp Phe Ile Ser Arg Glu Leu215 220 225tgt gcg cat tcc atc agg aag ctg cag gcc cat gtc ctg ttg atc aaa 834Cys Ala His Ser Ile Arg Lys Leu Gln Ala His Val Leu Leu Ile Lys230 235 240gca gtc cac gga tat ttt gat tca aga cag aat tac tct gag aag gag 882Ala Val His Gly Tyr Phe Asp Ser Arg Gln Asn Tyr Ser Glu Lys Glu245 250 255 260tcc ctg tcg ttc atg ata gac acg atg aaa tcc acc ctc aaa gag cag 930Ser Leu Ser Phe Met Ile Asp Thr Met Lys Ser Thr Leu Lys Glu Gln265 270 275ttc cag ttt gtg gaa gtc cca ggc aat cac tgt gtc cac atg agc gaa 978Phe Gln Phe Val Glu Val Pro Gly Asn His Cys Val His Met Ser Glu280 285 290ccc cag cac gtg gcc agt atc atc agc tcc ttc tta cag tgc aca cac 1026Pro Gln His Val Ala Ser Ile Ile Ser Ser Phe Leu Gln Cys Thr His295 300 305atg ctc cca gcc cag ctg tag ctctgggcct ggaactatga agacctagtg 1077Met Leu Pro Ala Gln Leu *310ctcccagact caacactggg actctgagtt cctgagcccc acaacaaggc cagggatggt 1137ggggacaggc ctcactagtc ttgaggccca gcctaggatg gtagtcaggg gaaggagcga 1197gattccaact tcaacatctg tgacctcaag ggggagacag agtctgggtt ccagggctgc 1257tttctcctgg ctaataataa atatccagcc agctggagga aggaagggca ggctgggccc 1317acctagcctt tccctgctgc ccaactggat ggaaaataaa aggttcttgt attctca 137432314PRTHomo sapiens 32Met Ser Glu Asn Ala Ala Pro Gly Leu Ile Ser Glu Leu Lys Leu Ala1 5 10 15Val Pro Trp Gly His Ile Ala Ala Lys Ala Trp Gly Ser Leu Gln Gly20 25 30Pro Pro Val Leu Cys Leu His Gly Trp Leu Asp Asn Ala Ser Ser Phe35 40 45Asp Arg Leu Ile Pro Leu Leu Pro Gln Asp Phe Tyr Tyr Val Ala Met50 55 60Asp Phe Gly Gly His Gly Leu Ser Ser His Tyr Ser Pro Gly Val Pro65 70 75 80Tyr Tyr Leu Gln Thr Phe Val Ser Glu Ile Arg Arg Val Val Ala Ala85 90 95Leu Lys Trp Asn Arg Phe Ser Ile Leu Gly His Ser Phe Gly Gly Val100 105 110Val Gly Gly Met Phe Phe Cys Thr Phe Pro Glu Met Val Asp Lys Leu115 120 125Ile Leu Leu Asp Thr Pro Leu Phe Leu Leu Glu Ser Asp Glu Met Glu130 135 140Asn Leu Leu Thr Tyr Lys Arg Arg Ala Ile Glu His Val Leu Gln Val145 150 155 160Glu Ala Ser Gln Glu Pro Ser His Val Phe Ser Leu Lys Gln Leu Leu165 170 175Gln Arg Leu Leu Lys Ser Asn Ser His Leu Ser Glu Glu Cys Gly Glu180 185 190Leu Leu Leu Gln Arg Gly Thr Thr Lys Val Ala Thr Gly Leu Val Leu195 200 205Asn Arg Asp Gln Arg Leu Ala Trp Ala Glu Asn Ser Ile Asp Phe Ile210 215 220Ser Arg Glu Leu Cys Ala His Ser Ile Arg Lys Leu Gln Ala His Val225 230 235 240Leu Leu Ile Lys Ala Val His Gly Tyr Phe Asp Ser Arg Gln Asn Tyr245 250 255Ser Glu Lys Glu Ser Leu Ser Phe Met Ile Asp Thr Met Lys Ser Thr260 265 270Leu Lys Glu Gln Phe Gln Phe Val Glu Val Pro Gly Asn His Cys Val275 280 285His Met Ser Glu Pro Gln His Val Ala Ser Ile Ile Ser Ser Phe Leu290 295 300Gln Cys Thr His Met Leu Pro Ala Gln Leu305 3103322DNAArtificial SequenceTaqMan primer 33tacacaccac cttcgctgaa ag 223422DNAArtificial SequenceTaqMan primer 34ggcctggttc tcattcaaat tg 223526DNAArtificial SequenceTaqMan primer 35cgcattgctg agtctcacct gcagtc 263625DNAArtificial SequenceTaqMan primer 36cagccttaca gagactggaa aagaa 253719DNAArtificial SequenceTaqMan primer 37gaggctcagg gacccaaag 193824DNAArtificial SequenceTaqMan primer 38ccaaaccaag gcccccagag aggt 243919DNAArtificial SequenceTaqMan primer 39cctaccgcca gcacattgt 194023DNAArtificial SequenceTaqMan primer 40gctgttgtag gcattgatga aca 234124DNAArtificial SequenceTaqMan primer 41aatgacatga accccggcaa cctg 24
Patent applications by Clark M. Whitehead, Apex, NC US
Patent applications by Didier Morel, Grenoble FR
Patent applications by Douglas P. Malinowski, Hillsborough, NC US
Patent applications by Raphaël Marcelpoil, Grenoble FR
Patent applications by Timothy J. Fischer, Raleigh, NC US
Patent applications by TriPath Imaging, Inc
Patent applications in class BIOSPECIFIC LIGAND BINDING ASSAY
Patent applications in all subclasses BIOSPECIFIC LIGAND BINDING ASSAY