Abstract:
Methods are provided for predicting the presence, subtype and stage of ovarian cancer, as well as for assessing the therapeutic efficacy of a cancer treatment and determining whether a subject potentially is developing cancer. Associated test kits, computer and analytical systems as well as software and diagnostic models are also provided.

Description:
RELATED APPLICATIONS 
       [0001]    This application is a Continuation of U.S. application Ser. No. 14/000,597 filed Aug. 20, 2013, which is the U.S. national phase of PCT International Application No. PCT/US2012/024997, filed Feb. 14, 2012, which published as International Publication No. WO 2012/115820 A2, which claims the benefit of and priority to U.S. Provisional Application No. 61/463,870, filed Feb. 24, 2011, the entire contents of which are incorporated herein by reference. 
     
    
     STATEMENT OF GOVERNMENT SUPPORT 
       [0002]    The subject matter of the present application includes work supported by SBIR Award No. HHSN261200800045C entitled “Improvement of a Promising MAP for Ovarian Cancer” from the National Cancer Institute. 
     
    
     FIELD OF THE INVENTION 
       [0003]    This invention provides methods for predicting and diagnosing ovarian cancer, particularly epithelial ovarian cancer, and it further provides associated analytical reagents, diagnostic models, test kits and clinical reports. 
       BACKGROUND 
       [0004]    The American Cancer Society estimates that ovarian cancer will strike 22,430 women and take the lives of 15,280 women in 2007 in the United States. Ovarian cancer is not a single disease, however, and there are actually more than 30 types and subtypes of ovarian malignancies, each with its own pathology and clinical behavior. Most experts therefore group ovarian cancers within three major categories, according to the kind of cells from which they were formed: epithelial tumors arise from cells that line or cover the ovaries; germ cell tumors originate from cells that are destined to form eggs within the ovaries; and sex cord-stromal cell tumors begin in the connective cells that hold the ovaries together and produce female hormones. 
         [0005]    Common epithelial tumors begin in the surface epithelium of the ovaries and account for about 90 percent of all ovarian cancers in the U.S. (and the following percentages reflect U.S. prevalence of these cancers). They are further divided into a number of subtypes—including serous, endometrioid, mucinous, and clear cell tumors—that can be further subclassified as benign or malignant tumors. Serous tumors are the most widespread forms of ovarian cancer. They account for 40 percent of common epithelial tumors. About 50 percent of these serous tumors are malignant, 33 percent are benign, and 17 percent are of borderline malignancy. Serous tumors occur most often in women who are between 40 and 60 years of age. 
         [0006]    Endometrioid tumors represent approximately 20 percent of common epithelial tumors. In about 20 percent of individuals, these cancers are associated with endometrial carcinoma (cancer of the womb lining) In 5 percent of cases, they also are linked with endometriosis, an abnormal occurrence of endometrium (womb lining tissue) within the pelvic cavity. The majority (about 80 percent) of these tumors are malignant, and the remainder (roughly 20 percent) usually is borderline malignancies. Endometrioid tumors occur primarily in women who are between 50 and 70 years of age. 
         [0007]    Clear cell tumors account for about 6 percent of common epithelial tumors. Nearly all of these tumors are malignant. Approximately one-half of all clear cell tumors are associated with endometriosis. Most patients with clear cell tumors are between 40 and 80 years of age. 
         [0008]    Mucinous tumors make up about 1 percent of all common epithelial tumors. Most (approximately 80 percent) of these tumors are benign, 15 percent are of borderline malignancy, and only 5 percent are malignant. Mucinous tumors appear most often in women between 30 to 50 years of age. 
         [0009]    Ovarian cancer is by far the most deadly of gynecologic cancers, accounting for more than 55 percent of all gynecologic cancer deaths. But ovarian cancer is also among the most treatable—if it is caught early. When ovarian cancer is caught early and appropriately treated, the 5-year survival rate is 93 percent. See, for example, Luce et al, “Early Diagnosis Key to Epithelial Ovarian Cancer Detection,” The Nurse Practitioner, December 2003 at p. 41. Extensive background information about ovarian cancer is readily available on the internet, for example, from the “Overview: Ovarian Cancer” of the Cancer Reference Information provided by the American Cancer Society and the NCCN Clinical Practice Guidelines in Oncology™ Ovarian Cancer V.1.2007. 
         [0010]    The current reality for the diagnosis of ovarian cancer is that most cases—81 percent of all cases of ovarian cancer—are not caught in earliest stage. This is because early stage ovarian cancer is very difficult to diagnose. Its symptoms may not appear or be noticed at this point. Or, symptoms—such as bloating, indigestion, diarrhea, constipation and others—may be vague and associated with many common and less serious conditions. Most importantly, there has been no effective test for early detection. An effective tool for early and accurate detection of ovarian cancer is a critical unmet medical need. 
         [0011]    What has been urgently needed in the field of gynecologic oncology is a minimally invasive (preferably serum-based) clinical test for assessing and predicting the presence of ovarian cancer that is based on a robust set of biomarkers and sample features identified from a large and diverse set of samples, together with methods and associated computer systems and software tools to predict, diagnose and monitor ovarian cancer with high accuracy at its various stages. 
       SUMMARY OF THE INVENTION 
       [0012]    The present invention generally relates to cancer biomarkers and particularly to biomarkers associated with ovarian cancer. It provides methods to predict, evaluate diagnose, and monitor cancer, particularly ovarian cancer, by measuring certain biomarkers, and further provides a set or array of reagents to evaluate the expression levels of biomarkers that are associated with ovarian cancer. A preferred set of biomarkers provides a detectable molecular signature of ovarian cancer in a subject. The invention provides a predictive or diagnostic test for ovarian cancer, particularly for epithelial ovarian cancer and more particularly for early-stage ovarian cancer (that is Stage I, Stage II or Stage I and II together). 
         [0013]    In one aspect, the present disclosure generally features a method of predicting the ovarian cancer status of a subject, involving the steps of measuring the level of CA-125 and HE4 and measuring the level of one or more biomarkers selected from the group consisting of IL-2 receptor alpha (IL-2Rα), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, IL-6, Vascular Endothelial Growth Factor B (VEGF-B), Matrix Metalloproteinase-7 (MMP-7), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1 in a sample of a biological fluid obtained from the subject; and correlating the measurements with ovarian cancer status. 
         [0014]    In another aspect, the present disclosure features a kit containing a panel of affinity reagents that each selectively binds to CA-125 and HE4 and one or more biomarkers selected from the group consisting of Interleukin-2 receptor alpha (IL-2 receptor alpha), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), Cancer Antigen 72-4 (CA-72-4), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, Matrix Metalloproteinase-7 (MMP-7), IL-6, Vascular Endothelial Growth Factor B (VEGF-B), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1; and a panel of containers each comprising CA-125 and HE4 and a one or more biomarkers selected from the group consisting of Interleukin-2 receptor alpha (IL-2 receptor alpha), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), Cancer Antigen 72-4 (CA-72-4), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, Matrix Metalloproteinase-7 (MMP-7), IL-6, Vascular Endothelial Growth Factor B (VEGF-B), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1. 
         [0015]    In a further aspect, the present disclosure features a panel of purified peptides containing CA-125 and HE4 and one or more biomarkers selected from the group consisting of Interleukin-2 receptor alpha (IL-2 receptor alpha), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), Cancer Antigen 72-4 (CA-72-4), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, Matrix Metalloproteinase-7 (MMP-7), IL-6, Vascular Endothelial Growth Factor B (VEGF-B), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1. 
         [0016]    In various embodiments of any of the above aspects or any other aspect of the disclosure delineated herein, the methods involve measuring the level of Cancer Antigen 72-4 (CA-72-4). In another embodiment the ovarian cancer status is presence of ovarian cancer. In additional embodiments the ovarian cancer is stage I ovarian cancer. In yet another embodiment the ovarian cancer is stage II ovarian cancer. In other embodiments the ovarian cancer is stage III ovarian cancer. In yet another embodiment the ovarian cancer is stage IV ovarian cancer. In further embodiments the ovarian cancer is stage I, II, III, or IV ovarian cancer. In other embodiments the method further involves managing subject treatment based on the status. In yet another embodiment managing subject treatment is selected from the group consisting of ordering more tests, performing surgery, and taking no further action. In yet another embodiment the method includes measuring the level of CA-125 and HE4 and measuring the level of one or more biomarkers selected from the group consisting of Interleukin-2 receptor alpha (IL-2 receptor alpha), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), Cancer Antigen 72-4 (CA-72-4), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, Matrix Metalloproteinase-7 (MMP-7), IL-6, Vascular Endothelial Growth Factor B (VEGF-B), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1 in a sample of a biological fluid obtained from the subject after subject management; correlating the measurements with ovarian cancer status; and determining if subject management resulted in a change in ovarian cancer status. In other embodiments measuring is selected from detecting the presence or absence of the biomarkers, quantifying the amount of biomarkers, and qualifying the type of biomarker. In certain embodiments the biomarkers are measured by an immunoassay. In further embodiments the correlating is performed by a software classification algorithm. In yet another embodiment the sample is selected from blood, serum, and plasma. In some embodiments the affinity reagent is an antibody. In yet another embodiment the kits further include written instructions for using the affinity reagent to measure the levels of the biomarkers in a sample from a subject. In yet another embodiment the kits include written instructions for use of the kit for determining a subjects ovarian cancer status. In certain embodiments one or more of the peptides have a detectable label. 
         [0017]    In a preferred embodiment of the present invention, a method of predicting the ovarian cancer status of a subject is provided, which comprises the steps of: determining the concentration of CA-125 and HE4 in a sample of a biological fluid from the subject and the age of the subject (collectively, the “biomarkers”); and evaluating the biomarkers, wherein a change in the level or evaluation of the biomarkers, as compared with a control group of patients who do not have ovarian cancer, predicts that the subject has ovarian cancer. In a more preferred embodiment, the foregoing method further comprises the evaluation of a subject&#39;s menopausal status of the subject as being either post-menopausal or not post-menopausal, and the concentrations of CA15-3 and CA72-4 in a sample of a biological fluid from the subject. 
         [0018]    A variety of additional biomarkers also are evaluated with the foregoing biomarkers in additional embodiments of the present invention. These include: Vascular Endothelial Growth Factor (VEGF), Interleukin-2 receptor alpha (IL-2 receptor alpha), Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Haptoglobin, Ferritin (FRTN), Prostasin, Interleukin-8 (IL-8), Maspin, Osteopontin, Serum Amyloid P-Component (SAP), Platelet-Derived Growth Factor BB (PDGF-BB) and B cell-activating factor (BAFF). Optionally, certain additional biomarkers are also evaluated: Calprotectin, von Willebrand Factor (vWF), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), Interleukin-6 (IL-6), Leptin, Transthyretin (TTR), Carcinoembryonic Antigen (CEA), Insulin-like Growth Factor-Binding Protein 1 (IGFBP-1) and Thyroxine-Binding Globulin (TBG). 
         [0019]    In preferred embodiments, the evaluation is made by a method selected from the group consisting of: logistic regression, look-up tables, decision tree, support vector machine, cluster analysis, neighbor analysis, genetic algorithm, Bayesian and non-Bayesian approaches, and the like. Additionally, the sample preferably is selected from the group of fluids and tissues drawn from a patient that include blood, serum, plasma, lymph, cerebrospinal fluid, ascites, urine and tissue biopsy. 
         [0020]    In other preferred embodiments, the methods of the present invention also include the step of providing a written or electronic report of the prediction of ovarian cancer and, optionally, the report includes a prediction as to the presence or absence or likelihood of ovarian cancer in the subject or the stratified risk of ovarian cancer for the subject, optionally by stage of cancer. 
         [0021]    Other preferred embodiments provide a method in which the a) the sum of sensitivity and specificity for the method is greater than about 150%, when the sensitivity is above about 95%; or b) the sum of sensitivity and specificity for the method is greater than about 170%, when the specificity is above 95%; and c) the foregoing sum of sensitivity and specificity is supported by analysis of a set of samples comprising at least about 50 cancer samples and 150 benign samples. 
         [0022]    Sets of reagents, test kits and multianalyte and ELISA panels and kits are provided to accomplish the foregoing methods. 
         [0023]    Other biomarkers useful in the methods of the present invention include the following, which may be determined as one or more additional markers in the methods of claims  1  through  4  appended below: Prostatic Acid Phosphatase (PAP), Epidermal Growth Factor Receptor (EGFR), Cathepsin D, YKL-40, Matrix Metalloproteinase-7 (MMP-7), Vascular Endothelial Growth Factor D (VEGF-D), Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), Mesothelin (MSLN), Sortilin, Cellular Fibronectin (cFib), Osteoprotegerin (OPG), EN-RAGE, CD 40 antigen (CD40), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), Neuropilin-1, Fetuin-A, Resistin, Matrix Metalloproteinase-2 (MMP-2), Peroxiredoxin 4 (Prx-IV), Phosphoserine Aminotransferase (PSAT), Alpha-1-Microglobulin (AlMicro), Heparin-Binding EGF-Like Growth Factor (HB-EGF), Hepatocyte Growth Factor (HGF), Trefoil Factor 3 (TFF3), Complement Factor 11, Clusterin (CLU), Aldose Reductase, Macrophage Migration Inhibitory Factor (MW), Amphiregulin (AR), Macrophage Inflammatory Protein-1 alpha (MIP-1 alpha), FASLG Receptor (FAS), Vascular Endothelial Growth Factor Receptor 1 (VEGFR-1), Matrix Metalloproteinase-1 (MMP-1), Monocyte Chemotactic Protein 2 (MCP-2) and Vascular Endothelial Growth Factor B (VEGF-B). 
         [0024]    In yet other embodiments of the present invention, any three or more of the following biomarkers are determined and evaluated: HE4, CA-125, IL-2 receptor alpha, AAT, CRP, YKL-40, fibronectin and CA-72-4. 
         [0025]    In another embodiment of the invention, the levels of the following biomarkers, optionally including HE4, are determined and evaluated, in some cases with a determination of age: CA-125, CA72-4, VEGF-B, Maspin, VEGF-D and YKL-40; CA-125, CA72-4, VEGF-B, Maspin, VEGF-D, YKL-40, OSP, Age and CRP; CA-125, CA72-4, VEGF-B, Maspin, and OSP; CA-125, CA72-4, VEGF-B, Maspin, YKL-40 and Age; CA-125, Maspin and Age; CA-125, CA72-4, VEGF-B, Maspin, OSP and Age; CA-125, VEGF-B and Age. 
         [0026]    In an additional embodiment of the invention, the levels of the following biomarkers, optionally including HE4, are determined and evaluated: HE4, Cancer Antigen 125 (CA-125), Cancer Antigen 72-4 (CA-72-4), Cancer Antigen 15-3 (CA-15-3), Age, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Interleukin-2 receptor alpha (IL-2 receptor alpha); HE4, Cancer Antigen 125 (CA-125) and YKL-40, optionally also including Age; HE4, Cancer Antigen 72-4(CA-72-4), Cancer Antigen 15-3 (CA-15-3), Age, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), and Interleukin-2 receptor alpha (IL-2 receptor alpha); CA-125, CA-72-4, Prostasin, CA-15-3, Age, IL-2 receptor alpha, IL-8, optionally also including HE4; and CA-125, CA-72-4, Prostasin, CA-15-3, Age, IL-2 receptor alpha, IL-8, FRTN. VEGF, Osteopontin, Maspin, and Haptoglobin, optionally also including Age. 
         [0027]    More specifically, predictive tests and associated methods and products also provide useful clinical information regarding the stage of ovarian cancer progression, that is: Stage I, Stage II, Stage III and Stage IV and an advanced stage which reflects relatively advanced tumors that cannot readily be classified as either Stage III or Stage IV. Overall, the invention also relates to newly discovered correlations between the relative levels of expression of certain groups of markers in bodily fluids, preferably blood serum and plasma, and a subject&#39;s ovarian cancer status. 
         [0028]    In one embodiment, the invention provides a set of reagents to measure the expression levels of a panel or set of biomarkers in a fluid sample drawn from a patient, such as blood, serum, plasma, lymph, cerebrospinal fluid, ascites or urine. The reagents in a further embodiment are a multianalyte panel assay comprising reagents to evaluate the expression levels of these biomarker panels. 
         [0029]    In embodiments of the invention, a subject&#39;s sample is prepared from tissue samples such a tissue biopsy or from primary cell cultures or culture fluid. In a further embodiment, the expression of the biomarkers is determined at the polypeptide level. Related embodiments utilize immunoassays, enzyme-linked immunosorbent assays and multiplexed immunoassays for this purpose. 
         [0030]    Preferred panels of biomarkers are selected from the group consisting of the following sets of molecules and their measurable fragments: (a) myoglobin, CRP (C reactive protein), FGF basic protein and CA 19-9; (b) Hepatitis C NS4, Ribosomal P Antibody and CRP; (c) CA 19-9, TGF alpha, EN-RAGE, EGF and HSP 90 alpha antibody, (d) EN-RAGE, EGF, CA 125, Fibrinogen, Apolipoprotein CIII, EGF, Cholera Toxin and CA 19-9; (e) Proteinase 3 (cANCA) antibody, Fibrinogen, CA 125, EGF, CD40, TSH, Leptin, CA 19-9 and lymphotactin; (f) CA125, EGFR, CRP, IL-18, Apolipoprotein CIII, Tenascin C and Apolipoprotein A1; (g) CA125, Beta-2 Microglobulin, CRP, Ferritin, TIMP-1, Creatine Kinase-MB and IL-8; (h) CA125, EGFR, IL-10, Haptoglobin, CRP, Insulin, TIMP-1, Ferritin, Alpha-2 Macroglobulin, Leptin, IL-8, CTGF, EN-RAGE, Lymphotactin, TNF-alpha, IGF-1, TNF RII, von Willebrand Factor and MDC; (i) CA-125, CRP, EGF-R, CA-19-9, Apo-AI, Apo-CIII, IL-6, IL-18, MIP-1a, Tenascin C and Myoglobin; (j) CA-125, CRP, EGF-R, CA-19-9, Apo-AI, Apo-CIII, IL-6, MIP-1a, Tenascin C and Myoglobin; and (k) any of the biomarker panels presented in Table II and Table III. 
         [0031]    In another embodiment, the reagents that measure such biomarkers may measure other molecular species that are found upstream or downstream in a biochemical pathway or measure fragments of such biomarkers and molecular species. In some instances, the same reagent may accurately measure a biomarker and its fragments. 
         [0032]    Another embodiment of the present invention relates to binding molecules (or binding reagents) to measure the biomarkers and related molecules and fragments. Contemplated binding molecules includes antibodies, both monoclonal and polyclonal, aptamers and the like. 
         [0033]    Other embodiments include such binding reagents provided in the form of a test kit, optionally together with written instructions for performing an evaluation of biomarkers to predict the likelihood of ovarian cancer in a subject. 
         [0034]    In other of its embodiments, the present invention provides methods of predicting the likelihood of ovarian cancer in a subject based on detecting or measuring the levels in a specimen or biological sample from the subject of the foregoing biomarkers. As described in this specification, a change in the expression levels of these biomarkers, particularly their relative expression levels, as compared with a control group of patients who do not have ovarian cancer, is predictive of ovarian cancer in that subject. 
         [0035]    In other of its aspects, the type of ovarian cancer that is predicted is serous, endometrioid, mucinous, and clear cell tumors. And prediction of ovarian cancer includes the prediction of a specific stage of the disease such as Stage I (IA, IB or IC), II, III and IV tumors. 
         [0036]    In yet another embodiment, the invention relates to creating a report for a physician of the relative levels of the biomarkers and to transmitting such a report by mail, fax, email or otherwise. In an embodiment, a data stream is transmitted via the internet that contains the reports of the biomarker evaluations. In a further embodiment, the report includes the prediction as to the presence or absence of ovarian cancer in the subject or the stratified risk of ovarian cancer for the subject, optionally by subtype or stage of cancer. 
         [0037]    According to another aspect of the invention, the foregoing evaluation of biomarker expression levels is combined for diagnostic purposes with other diagnostic procedures such as gastrointestinal tract evaluation, chest x-ray, HE4 test, CA-125 test, complete blood count, ultrasound or abdominal/pelvic computerized tomography, blood chemistry profile and liver function tests. 
         [0038]    Yet other embodiments of the invention relate to the evaluation of samples drawn from a subject who is symptomatic for ovarian cancer or is at high risk for ovarian cancer. Other embodiments relate to subjects who are asymptomatic of ovarian cancer. Symptomatic subjects have one or more of the following: pelvic mass; ascites; abdominal distention; general abdominal discomfort and/or pain (gas, indigestion, pressure, swelling, bloating, cramps); nausea, diarrhea, constipation, or frequent urination; loss of appetite; feeling of fullness even after a light meal; weight gain or loss with no known reason; and abnormal bleeding from the vagina. The levels of biomarkers may be combined with the findings of such symptoms for a diagnosis of ovarian cancer. 
         [0039]    Embodiments of the invention are highly accurate for determining the presence of ovarian cancer. By “highly accurate” is meant a sensitivity and a specificity each at least about 85 percent or higher, more preferably at least about 90 percent or 92 percent and most preferably at least about 95 percent or 97 percent accurate Embodiments of the invention further include methods having a sensitivity of at least about 85 percent, 90 percent or 95 percent and a specificity of at least about 55 percent, 65 percent, 75 percent, 85 percent or 90 percent or higher. Other embodiments include methods having a specificity of at least about 85 percent, 90 percent or 95 percent, and a sensitivity of at least about 55 percent, 65 percent, 75 percent, 85 percent or 90 percent or higher. 
         [0040]    Embodiments of the invention relating sensitivity and specificity are determined for a population of subjects who are symptomatic for ovarian cancer and have ovarian cancer as compared with a control group of subjects who are symptomatic for ovarian cancer but who do not have ovarian cancer. In another embodiment, sensitivity and specificity are determined for a population of subjects who are at increased risk for ovarian cancer and have ovarian cancer as compared with a control group of subjects who are at increased risk for ovarian cancer but who do not have ovarian cancer. And in another embodiment, sensitivity and specificity are determined for a population of subjects who are symptomatic for ovarian cancer and have ovarian cancer as compared with a control group of subjects who are not symptomatic for ovarian cancer but who do not have ovarian cancer. 
         [0041]    In other aspects, the levels of the biomarkers are evaluated by applying a statistical method such as knowledge discovery engine (KDE™), regression analysis, discriminant analysis, classification tree analysis, random forests, ProteomeQuest®, support vector machine, One R, kNN and heuristic naive Bayes analysis, neural nets and variants thereof. 
         [0042]    In another embodiment, a predictive or diagnostic model based on the expression levels of the biomarkers is provided. The model may be in the form of software code, computer readable format or in the form of written instructions for evaluating the relative expression of the biomarkers. 
         [0043]    A patient&#39;s physician can utilize a report of the biomarker evaluation, in a broader diagnostic context, in order to develop a relatively more complete assessment of the risk that a given patient has ovarian cancer. In making this assessment, a physician will consider the clinical presentation of a patient, which includes symptoms such as a suspicious pelvic mass and/or ascites, abdominal distention and other symptoms without another obvious source of malignancy. The general lab workup for symptomatic patients currently includes a GI evaluation if clinically indicated, chest x-ray, CA-125 test, CBC, ultrasound or abdominal/pelvic CT if clinically indicated, chemistry profile with LFTs and may include a family history evaluation along with genetic marker tests such as BRCA-1 and BRCA-2. (See, generally, the NCCN Clinical Practice Guidelines in Oncology™ for Ovarian Cancer, V.I.2007.) 
         [0044]    The present invention provides a novel and important additional source of information to assist a physician in stratifying a patient&#39;s risk of having ovarian cancer and in planning the next diagnostic steps to take. The present invention is also similarly useful in assessing the risk of ovarian cancer in non-symptomatic, high-risk subjects as well as for the general population as a screening tool. It is contemplated that the methods of the present invention may be used by clinicians as part of an overall assessment of other predictive and diagnostic indicators. 
         [0045]    The present invention also provides methods to assess the therapeutic efficacy of existing and candidate chemotherapeutic agents and other types of cancer treatments. As will be appreciated by persons skilled in the art, the relative expression levels of the biomarker panels—or biomarker profiles—are determined as described above, in specimens taken from a subject prior to and again after treatment or, optionally, at progressive stages during treatment. A change in the relative expression of these biomarkers to a non-cancer profile of expression levels (or to a more nearly non-cancer expression profile) or to a stable, non-changing profile of relative biomarker expression levels is interpreted as therapeutic efficacy. Persons skilled in the art will readily understand that a profile of such expressions levels may become diagnostic for cancer or a pre-cancer, pre-malignant condition or simply move toward such a diagnostic profile as the relative ratios of the biomarkers become more like a cancer-related profile than previously. 
         [0046]    In another embodiment, the invention provides a method for determining whether a subject potentially is developing cancer. The relative levels of expression of the biomarkers are determined in specimens taken from a subject over time, whereby a change in the biomarker expression profile toward a cancer profile is interpreted as a progression toward developing cancer. 
         [0047]    The expression levels of the biomarkers of a specimen may be stored electronically once a subject&#39;s analysis is completed and recalled for such comparison purposes at a future time. 
         [0048]    The present invention further provides methods, software products, computer systems and networks, and associated instruments that provide a highly accurate test for ovarian cancer. 
         [0049]    The combinations of markers described in this specification provide sensitive, specific and accurate methods for predicting the presence of or detecting ovarian cancer at various stages of its progression. The evaluation of samples as described may also correlate with the presence of a pre-malignant or a pre-clinical condition in a patient. Thus, it is contemplated that the disclosed methods are useful for predicting or detecting the presence of ovarian cancer in a sample, the absence of ovarian cancer in a sample drawn from a subject, the stage of an ovarian cancer, the grade of an ovarian cancer, the benign or malignant nature of an ovarian cancer, the metastatic potential of an ovarian cancer, the histological type of neoplasm associated with the ovarian cancer, the indolence or aggressiveness of the cancer, and other characteristics of ovarian cancer that are relevant to prevention, diagnosis, characterization, and therapy of ovarian cancer in a patient. 
         [0050]    It is further contemplated that the methods disclosed are also useful for assessing the efficacy of one or more test agents for inhibiting ovarian cancer, assessing the efficacy of a therapy for ovarian cancer, monitoring the progression of ovarian cancer, selecting an agent or therapy for inhibiting ovarian cancer, monitoring the treatment of a patient afflicted with ovarian cancer, monitoring the inhibition of ovarian cancer in a patient, and assessing the carcinogenic potential of a test compound by evaluating biomarkers of test animals following exposure. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0051]      FIG. 1  is a table showing the demographics of the study subjects. 
           [0052]      FIG. 2 , comprising  FIGS. 2A-2C , is a table showing the biomarkers assayed in the study. 
           [0053]      FIG. 3  is a table showing the Area Underneath the Curve (AUC) values from Receiver Operating Characteristic (ROC) curve analysis of the top 20 markers. 
           [0054]      FIGS. 4 , comprising  FIGS. 4A-4E , is a table listing the informative biomarkers identified with Area Underneath the Curve (AUC) values statistically greater than 0.5. 
           [0055]      FIG. 5  is a set of graphs showing the Receiver Operating Characteristic curves for the nine most informative biomarkers with area under the curve values greater than 0.800. 
           [0056]      FIG. 6 , comprising  FIGS. 6A and 6B , is a set of graphs showing the serum level distributions broken out by International Federation of Gynecology and Obstetrics (FIGO) ovarian cancer stage for the nine most informative biomarkers with area underneath the curve values greater than 0.800. 
           [0057]      FIG. 7 , comprising  FIGS. 7A and 7B , is a set of graphs showing the serum level distributions broken out by subtype of ovarian cancer stage for the nine most informative biomarkers with area underneath the curve values greater than 0.800. 
           [0058]      FIG. 8  is a correlation matrix for biomarkers with area underneath the curve values greater than 0.600. 
           [0059]      FIG. 9  is a table listing the identities of markers in clusters A through D. 
           [0060]      FIG. 10  is a table showing the correlation data of the markers in cluster A. 
           [0061]      FIG. 11  is a table showing the correlation data of the markers in cluster B. 
           [0062]      FIG. 12  is a table showing the correlation data of the markers in cluster C. 
           [0063]      FIG. 13 , comprising  FIGS. 13A-13D , is a table showing the correlation data of the markers in cluster D. 
           [0064]      FIG. 14  is a table showing the sensitivity at landmark threshold specificity values of logistic regression models using the nine most informative markers and the OVA1 biomarkers. 
           [0065]      FIG. 15  is a table showing the specificity at landmark threshold sensitivity values of logistic regression models using the nine most informative markers and the OVA1 biomarkers. 
           [0066]      FIG. 16  is a table showing the Area Underneath the Curve (AUC) values from Receiver Operating Characteristic (ROC) curve analysis of the top 20 markers broken out by menopausal status. 
       
    
    
     DEFINITIONS 
       [0067]    Unless defined otherwise, all technical and scientific terms used herein have the meaning commonly understood by a person skilled in the art to which this invention belongs. The following references provide one of skill with a general definition of many of the terms used in this invention: Singleton et al.,  Dictionary of Microbiology and Molecular Biology  (2nd ed. 1994);  The Cambridge Dictionary of Science and Technology  (Walker ed., 1988);  The Glossary of Genetics , 5th Ed., R. Rieger et al. (eds.), Springer Verlag (1991); and Hale &amp; Marham,  The Harper Collins Dictionary of Biology  (1991). As used herein, the following terms have the meanings ascribed to them unless specified otherwise. 
         [0068]    “Biomarker panel” refers to one of the biomarker panels set forth herein. A preferred biomarker panel comprises CA-125 and HE4 and one or more biomarkers selected from the group consisting of Interleukin-2 receptor alpha (IL-2 receptor alpha), Alpha-1-Antitrypsin (AAT), C-Reactive Protein (CRP), YKL-40, Cellular Fibronectin (cFib), Cancer Antigen 72-4 (CA-72-4), prostasin, Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), IL-8, Matrix Metalloproteinase-7 (MMP-7), IL-6, Vascular Endothelial Growth Factor B (VEGF-B), calprotectin, Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2), Lectin-Like Oxidized LDL Receptor 1 (LOX-1), neuropilin-1, TNFR2, and MPIF-1. 
         [0069]    “Eluant” or “wash solution” refers to an agent, typically a solution, which is used to affect or modify adsorption of an analyte to an affinity reagent and/or remove unbound materials from the reagent. The elution characteristics of an eluant can depend, for example, on pH, ionic strength, hydrophobicity, degree of chaotropism, detergent strength and temperature. 
         [0070]    “Analyte” refers to any component of a sample that is desired to be detected. The term can refer to a single component or a plurality of components in the sample. 
         [0071]    “Molecular binding partners” and “specific binding partners” refer to pairs of molecules, typically pairs of biomolecules that exhibit specific binding. Molecular binding partners include, without limitation, receptor and ligand, antibody and antigen, biotin and avidin, and biotin and streptavidin. 
         [0072]    “Monitoring” refers to recording changes in a continuously varying parameter. 
         [0073]    “Marker” in the context of the present invention refers to a polypeptide (of a particular apparent molecular weight), which is differentially present in a sample taken from patients having human cancer as compared to a comparable sample taken from control subjects (e.g., a person with a negative diagnosis or undetectable cancer, normal or healthy subject). The term “biomarker” is used interchangeably with the term “marker.” 
         [0074]    The term “measuring” means methods which include detecting the presence or absence of marker(s) in the sample, quantifying the amount of marker(s) in the sample, and/or qualifying the type of biomarker. Measuring can be accomplished by methods known in the art and those further described herein, including but not limited to SELDI and immunoassay. Any suitable methods can be used to detect and measure one or more of the markers described herein. These methods include, without limitation, mass spectrometry (e.g., laser desorption/ionization mass spectrometry), fluorescence (e.g. sandwich immunoassay), surface plasmon resonance, ellipsometry and atomic force microscopy. 
         [0075]    The phrase “differentially present” refers to differences in the quantity and/or the frequency of a marker present in a sample taken from patients having human cancer as compared to a control subject. Furthermore, a marker can be a polypeptide, which is detected at a higher frequency or at a lower frequency in samples of human cancer patients compared to samples of control subjects. A marker can be differentially present in terms of quantity, frequency or both. 
         [0076]    A polypeptide is differentially present between two samples if the amount of the polypeptide in one sample is statistically significantly different from the amount of the polypeptide in the other sample. For example, a polypeptide is differentially present between the two samples if it is present at least about 120%, at least about 130%, at least about 150%, at least about 180%, at least about 200%, at least about 300%, at least about 500%, at least about 700%, at least about 900%, or at least about 1000% greater than it is present in the other sample, or if it is detectable in one sample and not detectable in the other. 
         [0077]    Alternatively or additionally, a polypeptide is differentially present between two sets of samples if the frequency of detecting the polypeptide in the ovarian cancer patients&#39; samples is statistically significantly higher or lower than in the control samples. For example, a polypeptide is differentially present between the two sets of samples if it is detected at least about 120%, at least about 130%, at least about 150%, at least about 180%, at least about 200%, at least about 300%, at least about 500%, at least about 700%, at least about 900%, or at least about 1000% more frequently or less frequently observed in one set of samples than the other set of samples. 
         [0078]    “Diagnostic” means identifying the presence or nature of a pathologic condition, i.e., ovarian cancer. Diagnostic methods differ in their sensitivity and specificity. The “sensitivity” of a diagnostic assay is the percentage of diseased individuals who test positive (percent of “true positives”). Diseased individuals not detected by the assay are “false negatives.” Subjects who are not diseased and who test negative in the assay, are termed “true negatives.” The “specificity” of a diagnostic assay is 1 minus the false positive rate, where the “false positive” rate is defined as the proportion of those without the disease who test positive. While a particular diagnostic method may not provide a definitive diagnosis of a condition, it suffices if the method provides a positive indication that aids in diagnosis. 
         [0079]    A “test amount” of a marker refers to an amount of a marker present in a sample being tested. A test amount can be either in absolute amount (e.g., μg/m) or a relative amount (e.g., relative intensity of signals). 
         [0080]    A “diagnostic amount” of a marker refers to an amount of a marker in a subject&#39;s sample that is consistent with a diagnosis of ovarian cancer. A diagnostic amount can be either in absolute amount (e.g., μg/m) or a relative amount (e.g., relative intensity of signals). 
         [0081]    A “control amount” of a marker can be any amount or a range of amount, which is to be compared against a test amount of a marker. For example, a control amount of a marker can be the amount of a marker in a person without ovarian cancer. A control amount can be either in absolute amount (e.g., μg/m) or a relative amount (e.g., relative intensity of signals). 
         [0082]    “Antibody” refers to a polypeptide ligand substantially encoded by an immunoglobulin gene or immunoglobulin genes, or fragments thereof, which specifically binds and recognizes an epitope (e.g., an antigen). The recognized immunoglobulin genes include the kappa and lambda light chain constant region genes, the alpha, gamma, delta, epsilon and mu heavy chain constant region genes, and the myriad immunoglobulin variable region genes. Antibodies exist, e.g., as intact immunoglobulins or as a number of well-characterized fragments produced by digestion with various peptidases. This includes, e.g., Fab′ and F(ab)′ 2  fragments. The term “antibody,” as used herein, also includes antibody fragments either produced by the modification of whole antibodies or those synthesized de novo using recombinant DNA methodologies. It also includes polyclonal antibodies, monoclonal antibodies, chimeric antibodies, humanized antibodies, or single chain antibodies. “Fc” portion of an antibody refers to that portion of an immunoglobulin heavy chain that comprises one or more heavy chain constant region domains, CH 1 , CH 2  and CH 3 , but does not include the heavy chain variable region. 
         [0083]    As used herein by the term a “sample” is meant material which can be specifically related to a patient and from which specific information about the patient can be determined, calculated or inferred. A sample can be composed in whole or in part of biological material from of the patient. A sample can also be material that has contacted the patient in a way that allows tests to be conducted on the sample which provides information about the patient. A sample may also be material that has contacted other material that is not of the patient but allows the first material to then be tested to determine information about the patient. A sample can contact sources of biologic material other than the patient provided that one skilled in the art can nevertheless determine information about the patient from the sample. It is also understood that extraneous material or information that is not the sample could be utilized to conclusively link the patient to the sample. For a non-limiting example, a double blind test requires a chart or database to match a sample with a patient. 
         [0084]    As used herein the term “body fluid” it is meant a material obtained from a patient that is substantially fluid in consistency, but may have solid or particulate matter associated with it. A body fluid can also contain material and portions that are not from the patient. For instance a body fluid can be diluted with water, or can contain preservative, such as EDTA. Non-limiting examples of body fluids blood, serum, serosal fluids, plasma, lymph, urine, cerebrospinal fluid, saliva, mucosal secretions of the secretory tissues and organs, vaginal secretions, breast milk, tears, and ascites fluids such as those associated with non-solid tumors. Additional examples include fluids of the pleural, pericardial, peritoneal, abdominal and other body cavities, and the like. Biological fluids may further include liquid solutions contacted with a subject or biological source, for example, cell and organ culture medium including cell or organ conditioned medium, lavage fluids and the like. 
         [0085]    “Managing subject treatment” refers to the behavior of the clinician or physician subsequent to the determination of ovarian cancer status. For example, if the result of the methods of the present invention is inconclusive or there is reason that confirmation of status is necessary, the physician may order more tests. Alternatively, if the status indicates that surgery is appropriate, the physician may schedule the patient for surgery. Likewise, if the status is negative, e.g., late stage ovarian cancer or if the status is acute, no further action may be warranted. Furthermore, if the results show that treatment has been successful, no further management may be necessary. 
         [0086]    The term “stage” or “cancer stage” is intended to mean a classification of ovarian cancer that is based on the size, invasiveness, progression, migration, etc. of cancer in a subject. The stages of ovarian cancer are well defined. Stage I refers to ovarian cancer wherein the cancer is still contained within the ovary (or ovaries). Specifically, stage IA cancer has developed in one ovary, and the tumor is confined to the inside of the ovary. There is no cancer on the outer surface of the ovary. Laboratory examination of washings from the abdomen and pelvis did not find any cancer cells. Stage IB cancer has developed within both ovaries without any tumor on their outer surfaces. Laboratory examination of washings from the abdomen and pelvis did not find any cancer cells. Stage IC cancer is present in one or both ovaries and 1 or more of the following are present: cancer on the outer surface of at least one of the ovaries; in the case of cystic tumors (fluid-filled tumors), the capsule (outer wall of the tumor) has ruptured (burst); or laboratory examination found cancer cells in fluid or washings from the abdomen. 
         [0087]    Stage II cancer is in one or both ovaries and has involved other organs (such as the uterus, fallopian tubes, bladder, the sigmoid colon, or the rectum) within the pelvis. Specifically, stage IIA cancer has spread to or has actually invaded the uterus or the fallopian tubes, or both. Laboratory examination of washings from the abdomen did not find any cancer cells. Stage IIB cancer has spread to other nearby pelvic organs such as the bladder, the sigmoid colon, or the rectum. Laboratory examination of fluid from the abdomen did not find any cancer cells. Stage IIC cancer has spread to pelvic organs as in stages IIA or IIB and laboratory examination of the washings from the abdomen found evidence of cancer cells. 
         [0088]    Stage III cancer involves 1 or both ovaries, and 1 or both of the following are present: (1) cancer has spread beyond the pelvis to the lining of the abdomen; (2) cancer has spread to lymph nodes. The cancer is Stage IIIA if, during the staging operation, the surgeon can see cancer involving the ovary or ovaries, but no cancer is grossly visible (can be seen without using a microscope) in the abdomen and the cancer has not spread to lymph nodes. However, when biopsies are checked under a microscope, tiny deposits of cancer are found in the lining of the upper abdomen. Stage BIB cancer is in one or both ovaries, and deposits of cancer large enough for the surgeon to see, but smaller than 2 cm (about ¾ inch) across, are present in the abdomen. Cancer has not spread to the lymph nodes. For a cancer to be stage IIIC the cancer is in one or both ovaries, and one or both of the following are present: cancer has spread to lymph nodes and/or deposits of cancer larger than 2 cm (about ¾ inch) across are seen in the abdomen. 
         [0089]    Stage IV cancer is the most advanced stage of ovarian cancer. The cancer is in one or both ovaries. Distant metastasis (spread of the cancer to the inside of the liver, the lungs, or other organs located outside of the peritoneal cavity) has occurred. Finding ovarian cancer cells in pleural fluid (from the cavity that surrounds the lungs) is also evidence of stage IV disease. 
         [0090]    As used herein, the term “recurrent ovarian cancer” is intended to mean that the disease has come back (recurred) after completion of treatment. 
       Biomarkers 
       [0091]    By “CA-125” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers NP — 078966.2 or AAL65133 or a fragment thereof. An exemplary sequence of CA-125 is: 
         [0000]    
       
         
               
               
               
             
           
               
                 1 
                 mlkpsglpgs ssptrslmtg srstkatpem dsgltgatls pktstgaivv 
                   
               
               
                   
                 tehtlpftsp 
               
               
                   
               
               
                 61 
                 dktlasptss vvgrttqslg vmssalpest srgmthseqr tspslspqvn 
               
               
                   
                 gtpsrnypat 
               
               
                   
               
               
                 121 
                 smvsglsspr trtsstegnf tkeastytlt vettsgpvte kytvptetst 
               
               
                   
                 tegdstetpw 
               
               
                   
               
               
                 181 
                 dtryipvkit spmktfadst askenapvsm tpaettvtds htpgrtnpsf 
               
               
                   
                 gtlyssfldl 
               
               
                   
               
               
                 241 
                 spkgtpnsrg etslelilst tgypfsspep gsaghsrist saplsssasv 
               
               
                   
                 ldnkisetsi 
               
               
                   
               
               
                 301 
                 fsgqsltspl spgvpearas tmpnsaipfs mtlsnaetsa ervrstissl 
               
               
                   
                 gtpsistkqt 
               
               
                   
               
               
                 361 
                 aetiltfhaf aetmdipsth iaktlasewl gspgtlggts tsaltttsps 
               
               
                   
                 ttlvseetnt 
               
               
                   
               
               
                 421 
                 hhstsgkete gtlntsmtpl etsapgeese mtatlvptlg fttldskirs 
               
               
                   
                 psqvssshpt 
               
               
                   
               
               
                 481 
                 relrttgsts grqssstaah gssdilratt sstskasswt sestaqqfse 
               
               
                   
                 pqhtqwvets 
               
               
                   
               
               
                 541 
                 psmkterppa stsvaapitt svpsvvsgft tlktsstkgi wleetsadtl 
               
               
                   
                 igestagptt 
               
               
                   
               
               
                 601 
                 hqfavptgis mtggsstrgs qgtthlltra tassetsadl tlatngvpvs 
               
               
                   
                 vspavsktaa 
               
               
                   
               
               
                 661 
                 gssppggtkp sytmvssvip etsslqssaf regtslgltp lntrhpfssp 
               
               
                   
                 epdsaghtki 
               
               
                   
               
               
                 721 
                 stsipllssa svledkvsat stfshhkats sittgtpeis tktkpssavl 
               
               
                   
                 ssmtlsnaat 
               
               
                   
               
               
                 781 
                 spervrnats plthpspsge etagsvltls tsaettdspn ihptgtltse 
               
               
                   
                 ssespstlsl 
               
               
                   
               
               
                 841 
                 psvsgvkttf ssstpsthlf tsgeeteets npsvsqpets vsrvrttlas 
               
               
                   
                 tsvptpvfpt 
               
               
                   
               
               
                 901 
                 mdtwptrsaq fssshlvsel ratsstsvtn stgsalpkis hltgtatmsq 
               
               
                   
                 tnrdtfndsa 
               
               
                   
               
               
                 961 
                 apqsttwpet sprfktglps atttvstsat slsatvmvsk ftspatssme 
               
               
                   
                 atsirepstt 
               
               
                   
               
               
                 1021 
                 ilttettngp gsmavastni pigkgyiteg rldtshlpig ttassetsmd 
               
               
                   
                 ftmakesvsm 
               
               
                   
               
               
                 1081 
                 svspsqsmda agsstpgrts qfvdtfsddv yhltsreiti prdgtssalt 
               
               
                   
                 pqmtathpps 
               
               
                   
               
               
                 1141 
                 pdpgsarstw lgilssspss ptpkvtmsst fstqrvttsm imdtvetsrw 
               
               
                   
                 nmpnlpstts 
               
               
                   
               
               
                 1201 
                 ltpsniptsg aigkstlvpl dtpspatsle asegglptls typestntps 
               
               
                   
                 ihlgahasse 
               
               
                   
               
               
                 1261 
                 spstikltma svvkpgsytp ltfpsiethi hvstarmays sgsspemtap 
               
               
                   
                 getntgstwd 
               
               
                   
               
               
                 1321 
                 pttyitttdp kdtssaqvst phsvrtlrtt enhpktesat paaysgspki 
               
               
                   
                 ssspnltspa 
               
               
                   
               
               
                 1381 
                 tkawtitdtt ehstqlhytk laekssgfet qsapgpvsvv iptsptigss 
               
               
                   
                 tleltsdvpg 
               
               
                   
               
               
                 1441 
                 eplvlapseq ttitlpmatw lstslteema stdldissps spmstfaifp 
               
               
                   
                 pmstpshels 
               
               
                   
               
               
                 1501 
                 kseadtsair ntdsttldqh lgirslgrtg dlttvpitpl tttwtsvieh 
               
               
                   
                 stqaqdtlsa 
               
               
                   
               
               
                 1561 
                 tmspthvtqs lkdqtsipas aspshltevy pelgtqgrss seattfwkps 
               
               
                   
                 tdtlsreiet 
               
               
                   
               
               
                 1621 
                 gptniqstpp mdntttgsss sgvtlgiahl pigtsspaet stnmalerrs 
               
               
                   
                 statvsmagt 
               
               
                   
               
               
                 1681 
                 mgllvtsapg rsisqslgrv ssvlsestte gvtdsskgss prlntqgnta 
               
               
                   
                 lssslepsya 
               
               
                   
               
               
                 1741 
                 egsqmstsip ltsspttpdv efiggstfwt kevttvmtsd iskssartes 
               
               
                   
                 ssatlmstal 
               
               
                   
               
               
                 1801 
                 gstentgkek lrtasmdlps ptpsmevtpw isltlsnapn ttdsldlshg 
               
               
                   
                 vhtssagtla 
               
               
                   
               
               
                 1861 
                 tdrslntgvt rasrlengsd tsskslsmgn sthtsmtyte ksevsssihp 
               
               
                   
                 rpetsapgae 
               
               
                   
               
               
                 1921 
                 ttltstpgnr aisltlpfss ipveevistg itsgpdinsa pmthspitpp 
               
               
                   
                 tivwtstgti 
               
               
                   
               
               
                 1981 
                 eqstqplhav ssekvsvqtq stpyvnsvav saspthensv ssgsstsspy 
               
               
                   
                 ssasleslds 
               
               
                   
               
               
                 2041 
                 tisrrnaits wlwdlttslp tttwpstsls ealssghsgv snpsstttef 
               
               
                   
                 plfsaastsa 
               
               
                   
               
               
                 2101 
                 akqrnpetet hgpqntaast lntdassvtg lsetpvgasi ssevplpmai 
               
               
                   
                 tsrsdvsglt 
               
               
                   
               
               
                 2161 
                 sestanpslg tassagtklt rtislptses lvsfrmnkdp wtvsiplgsh 
               
               
                   
                 pttntetsip 
               
               
                   
               
               
                 2221 
                 vnsagppgls tvasdvidtp sdgaesiptv sfspspdtev ttishfpekt 
               
               
                   
                 thsfrtissl 
               
               
                   
               
               
                 2281 
                 theltsrvtp ipgdwmssam stkptgasps itlgerrtit saapttspiv 
               
               
                   
                 ltasftetst 
               
               
                   
               
               
                 2341 
                 vsldnettvk tsdildarkt nelpsdssss sdlintsias stmdvtktas 
               
               
                   
                 isptsisgmt 
               
               
                   
               
               
                 2401 
                 assspslfss drpqvptstt etntatspsv ssntysldgg snvggtpstl 
               
               
                   
                 ppftithpve 
               
               
                   
               
               
                 2461 
                 tssallawsr pvrtfstmvs tdtasgenpt ssnsvvtsvp apgtwtsvgs 
               
               
                   
                 ttdlpamgfl 
               
               
                   
               
               
                 2521 
                 ktspageahs llastiepat aftphlsaav vtgssatsea sllttseska 
               
               
                   
                 ihsspqtptt 
               
               
                   
               
               
                 2581 
                 ptsganwets atpesllvvt etsdttltsk ilvtdtilfs tvstppskfp 
               
               
                   
                 stgtlsgasf 
               
               
                   
               
               
                 2641 
                 ptllpdtpai pltateptss latsfdstpl vtiasdslgt vpettltmse 
               
               
                   
                 tsngdalvlk 
               
               
                   
               
               
                 2701 
                 tvsnpdrsip gitiqgvtes plhpsstsps kivaprntty egsitvalst 
               
               
                   
                 lpagttgslv 
               
               
                   
               
               
                 2761 
                 fsqssenset talvdssagl erasvmpltt gsqgmassgg irsgsthstg 
               
               
                   
                 tktfsslplt 
               
               
                   
               
               
                 2821 
                 mnpgevtams eittnrltat qstapkgipv kptsaesgll tpvsasssps 
               
               
                   
                 kafaslttap 
               
               
                   
               
               
                 2881 
                 ptwgipqstl tfefsevpsl dtksaslptp gqslntipds dastasssls 
               
               
                   
                 kspeknprar 
               
               
                   
               
               
                 2941 
                 mmtstkaisa ssfqstgfte tpegsaspsm agheprvpts gtgdpryase 
               
               
                   
                 smsypdpska 
               
               
                   
               
               
                 3001 
                 ssamtstsla sklttlfstg qaarsgssss pislsteket sflsptasts 
               
               
                   
                 rktslflgps 
               
               
                   
               
               
                 3061 
                 marqpnilvh lqtsaltlsp tstlnmsqee ppeltssqti aeeegttaet 
               
               
                   
                 qtltftpset 
               
               
                   
               
               
                 3121 
                 ptsllpvssp teptarrkss petwassisv paktslvett dgtlvttikm 
               
               
                   
                 ssqaaqgnst 
               
               
                   
               
               
                 3181 
                 wpapaeetgs spagtspgsp emsttlkims skepsispei rstvrnspwk 
               
               
                   
                 tpettvpmet 
               
               
                   
               
               
                 3241 
                 tvepvtlqst algsgstsis hlptgttspt ksptenmlat ervslspspp 
               
               
                   
                 eawtnlysgt 
               
               
                   
               
               
                 3301 
                 pggtrqslat mssvslespt arsitgtgqq sspelvsktt gmefsmwhgs 
               
               
                   
                 tggttgdthv 
               
               
                   
               
               
                 3361 
                 slstssnile dpvtspnsvs sltdkskhkt etwvsttaip stvlnnkima 
               
               
                   
                 aeqqtsrsvd 
               
               
                   
               
               
                 3421 
                 eaysstssws dqtsgsditl gaspdvtntl yitstaqtts lvslpsgdqg 
               
               
                   
                 itsltnpsgg 
               
               
                   
               
               
                 3481 
                 ktssassvts psigletlra nvsavksdia ptaghlsqts spaevsildv 
               
               
                   
                 ttaptpgist 
               
               
                   
               
               
                 3541 
                 tittmgtnsi stttpnpevg mstmdstpat errttstehp stwsstaasd 
               
               
                   
                 swtvtdmtsn 
               
               
                   
               
               
                 3601 
                 lkvarspgti stmhttsfla ssteldsmst phgritvigt slvtpssdas 
               
               
                   
                 avktetstse 
               
               
                   
               
               
                 3661 
                 rtlspsdtta stpistfsrv qrmsisvpdi lstswtpsst eaedvpvsmv 
               
               
                   
                 stdhastktd 
               
               
                   
               
               
                 3721 
                 pntplstflf dslstldwdt grslssatat tsapqgattp qeltletmis 
               
               
                   
                 patsqlpfsi 
               
               
                   
               
               
                 3781 
                 ghitsavtpa amarssgvtf srpdptskka eqtstqlptt tsahpgqvpr 
               
               
                   
                 saattldvip 
               
               
                   
               
               
                 3841 
                 htaktpdatf qrqgqtaltt earatsdswn ekekstpsap witemmnsvs 
               
               
                   
                 edtikevtss 
               
               
                   
               
               
                 3901 
                 ssvlrtlntl dinlesgtts spswksspye riapsesttd keaihpstnt 
               
               
                   
                 vettgwvtss 
               
               
                   
               
               
                 3961 
                 ehashstipa hsasskltsp vvttstreqa ivsmstttwp estrartepn 
               
               
                   
                 sfltielrdv 
               
               
                   
               
               
                 4021 
                 spymdtsstt qtsiisspgs taitkgprte itsskrisss flaqsmrssd 
               
               
                   
                 spseaitrls 
               
               
                   
               
               
                 4081 
                 nfpamtesgg milamqtspp gatslsaptl dtsataswtg tplattqrft 
               
               
                   
                 ysekttlfsk 
               
               
                   
               
               
                 4141 
                 gpedtsqpsp psveetssss slvpihatts psnilltsqg hspsstppvt 
               
               
                   
                 svflsetsgl 
               
               
                   
               
               
                 4201 
                 gkttdmsris lepgtslppn lsstageals tyeasrdtka ihhsadtavt 
               
               
                   
                 nmeatsseys 
               
               
                   
               
               
                 4261 
                 pipghtkpsk atsplvtshi mgditsstsv fgssetteie tvssvnqglq 
               
               
                   
                 erstsqvass 
               
               
                   
               
               
                 4321 
                 atetstvith vssgdatthv tktqatfssg tsissphqfi tstntftdvs 
               
               
                   
                 tnpstslimt 
               
               
                   
               
               
                 4381 
                 essgvtittq tgptgaatqg pylldtstmp yltetplavt pdfmqsektt 
               
               
                   
                 liskgpkdvs 
               
               
                   
               
               
                 4441 
                 wtsppsvaet sypssltpfl vttippatst lqgqhtsspv satsvltsgl 
               
               
                   
                 vkttdmlnts 
               
               
                   
               
               
                 4501 
                 mepvtnspqn lnnpsneila tlaattdiet ihpsinkavt nmgtassahv 
               
               
                   
                 lhstlpvsse 
               
               
                   
               
               
                 4561 
                 pstatspmvp assmgdalas isipgsettd iegeptsslt agrkenstlq 
               
               
                   
                 emnsttesni 
               
               
                   
               
               
                 4621 
                 ilsnvsvgai teatkmevps fdatfiptpa qstkfpdifs vassrlsnsp 
               
               
                   
                 pmtisthmtt 
               
               
                   
               
               
                 4681 
                 tqtgssgats kiplaldtst letsagtpsv vtegfahski ttamnndvkd 
               
               
                   
                 vsqtnppfqd 
               
               
                   
               
               
                 4741 
                 easspssqap vlvttlpssv aftpqwhsts spvsmssvlt sslvktagkv 
               
               
                   
                 dtsletvtss 
               
               
                   
               
               
                 4801 
                 pqsmsntldd isvtsaattd ietthpsint vvtnvgttgs afeshstvsa 
               
               
                   
                 ypepskvtsp 
               
               
                   
               
               
                 4861 
                 nvttstmedt tisrsipkss kttrtetett ssltpklret sisqeitsst 
               
               
                   
                 etstvpykel 
               
               
                   
               
               
                 4921 
                 tgattevsrt dvtsssstsf pgpdqstvsl distetntrl stspimtesa 
               
               
                   
                 eitittqtgp 
               
               
                   
               
               
                 4981 
                 hgatsqdtft mdpsnttpqa gihsamthgf sqldvttlms ripqdvswts 
               
               
                   
                 ppsvdktssp 
               
               
                   
               
               
                 5041 
                 ssflsspamt tpslisstlp edklsspmts lltsglvkit dilrtrlepv 
               
               
                   
                 tsslpnfsst 
               
               
                   
               
               
                 5101 
                 sdkilatskd skdtkeifps inteetnvka nnsgheshsp aladsetpka 
               
               
                   
                 ttqmvitttv 
               
               
                   
               
               
                 5161 
                 gdpapstsmp vhgssettni kreptyfltp rlretstsqe ssfptdtsfl 
               
               
                   
                 lskvptgtit 
               
               
                   
               
               
                 5221 
                 evsstgvnss skistpdhdk stvppdtftg eiprvftssi ktksaemtit 
               
               
                   
                 tqasppesas 
               
               
                   
               
               
                 5281 
                 hstlpldtst tlsqggthst vtqgfpysev ttlmgmgpgn vswmttppve 
               
               
                   
                 etssvsslms 
               
               
                   
               
               
                 5341 
                 spamtspspv sstspqsips splpvtalpt svlvtttdvl gttspesvts 
               
               
                   
                 sppnlssith 
               
               
                   
               
               
                 5401 
                 erpatykdta hteaamhhst ntavtnvgts gsghksqssv ladsetskat 
               
               
                   
                 plmsttstlg 
               
               
                   
               
               
                 5461 
                 dtsvststpn isqtnqiqte ptaslsprlr esstsektss ttetntafsy 
               
               
                   
                 vptgaitqas 
               
               
                   
               
               
                 5521 
                 rteisssrts isdldrptia pdistgmitr lftspimtks aemtvttqtt 
               
               
                   
                 tpgatsqgil 
               
               
                   
               
               
                 5581 
                 pwdtsttlfq ggthstvsqg fphseittlr srtpgdvswm ttppveetss 
               
               
                   
                 gfslmspsmt 
               
               
                   
               
               
                 5641 
                 spspvsstsp esipssplpv talltsvlvt ttnvlgttsp epvtssppnl 
               
               
                   
                 ssptqerltt 
               
               
                   
               
               
                 5701 
                 ykdtahteam hasmhtntav anvgtsisgh esqssvpads htskatspmg 
               
               
                   
                 itfamgdtsv 
               
               
                   
               
               
                 5761 
                 ststpaffet riqtestssl ipglrdtrts eeintvtets tvlsevpttt 
               
               
                   
                 ttevsrtevi 
               
               
                   
               
               
                 5821 
                 tssrttisgp dhskmspyis tetitrlstf pfvtgstema itnqtgpigt 
               
               
                   
                 isqatltldt 
               
               
                   
               
               
                 5881 
                 sstaswegth spvtqrfphs eetttmsrst kgvswqspps veetsspssp 
               
               
                   
                 vplpaitshs 
               
               
                   
               
               
                 5941 
                 slysavsgss ptsalpvtsl ltsgrrktid mldthselvt sslpsassfs 
               
               
                   
                 geiltseast 
               
               
                   
               
               
                 6001 
                 ntetihfsen taetnmgttn smhklhssvs ihsqpsghtp pkvtgsmmed 
               
               
                   
                 aivststpgs 
               
               
                   
               
               
                 6061 
                 petknvdrds tspltpelke dstalvmnst tesntvfssv sldaatevsr 
               
               
                   
                 aevtyydptf 
               
               
                   
               
               
                 6121 
                 mpasaqstks pdispeasss hsnsppltis thktiatqtg psgvtslgql 
               
               
                   
                 tldtstiats 
               
               
                   
               
               
                 6181 
                 agtpsartqd fvdsettsvm nndlndvlkt spfsaeeans lssqapllvt 
               
               
                   
                 tspspvtstl 
               
               
                   
               
               
                 6241 
                 qehstsslvs vtsvptptla kitdmdtnle pvtrspqnlr ntlatseatt 
               
               
                   
                 dthtmhpsin 
               
               
                   
               
               
                 6301 
                 tavanvgtts spnefyftvs pdsdpykats avvitstsgd sivstsmprs 
               
               
                   
                 samkkieset 
               
               
                   
               
               
                 6361 
                 tfslifrlre tstsqkigss sdtstvfdka ftaattevsr teltsssrts 
               
               
                   
                 iqgtekptms 
               
               
                   
               
               
                 6421 
                 pdtstrsvtm lstfagltks eertiatqtg phratsqgtl twdtsittsq 
               
               
                   
                 agthsamthg 
               
               
                   
               
               
                 6481 
                 fsqldlstlt srvpeyisgt sppsvektss sssllslpai tspspvpttl 
               
               
                   
                 pesrpsspvh 
               
               
                   
               
               
                 6541 
                 ltslptsglv kttdmlasva slppnlgsts hkipttsedi kdtekmypst 
               
               
                   
                 niavtnvgtt 
               
               
                   
               
               
                 6601 
                 tsekesyssv payseppkvt spmvtsfnir dtivstsmpg sseitrieme 
               
               
                   
                 stfslahglk 
               
               
                   
               
               
                 6661 
                 gtstsqdpiv steksavlhk lttgatetsr tevassrrts ipgpdhstes 
               
               
                   
                 pdistevips 
               
               
                   
               
               
                 6721 
                 lpislgites snmtiitrtg pplgstsqgt ftldtpttss ragthsmatq 
               
               
                   
                 efphsemttv 
               
               
                   
               
               
                 6781 
                 mnkdpeilsw tippsiekts fssslmpspa mtsppvsstl pktihttpsp 
               
               
                   
                 mtslltpslv 
               
               
                   
               
               
                 6841 
                 mttdtlgtsp epttssppnl sstsheiltt dedttaieam hpststaatn 
               
               
                   
                 vettssghgs 
               
               
                   
               
               
                 6901 
                 qssvladsek tkatapmdtt stmghttvst smsvssettk ikrestyslt 
               
               
                   
                 pglretsisq 
               
               
                   
               
               
                 6961 
                 nasfstdtsi vlsevptgtt aevsrtevts sgrtsipgps qstvlpeist 
               
               
                   
                 rtmtrlfasp 
               
               
                   
               
               
                 7021 
                 tmtesaemti ptqtgpsgst sqdtltldts ttksqakths tltqrfphse 
               
               
                   
                 mttlmsrgpg 
               
               
                   
               
               
                 7081 
                 dmswqsspsl enpsslpsll slpattsppp isstlpvtis ssplpvtsll 
               
               
                   
                 tsspvtttdm 
               
               
                   
               
               
                 7141 
                 lhtspelvts sppklshtsd erlttgkdtt nteavhpstn taasnveips 
               
               
                   
                 sghespssal 
               
               
                   
               
               
                 7201 
                 adsetskats pmfitstqed ttvaistphf letsriqkes isslspklre 
               
               
                   
                 tgssvetssa 
               
               
                   
               
               
                 7261 
                 ietsavlsev sigatteisr tevtsssrts isgsaestml peisttrkii 
               
               
                   
                 kfptspilae 
               
               
                   
               
               
                 7321 
                 ssemtiktqt sppgstsest ftldtsttps lvithstmtq rlphseittl 
               
               
                   
                 vsrgagdvpr 
               
               
                   
               
               
                 7381 
                 psslpveets ppssqlslsa mispspvsst lpasshsssa svtslltpgq 
               
               
                   
                 vkttevldas 
               
               
                   
               
               
                 7441 
                 aepetsspps lsstsveila tsevttdtek ihpfsntavt kvgtsssghe 
               
               
                   
                 spssvlpdse 
               
               
                   
               
               
                 7501 
                 ttkatsamgt isimgdtsvs tltpalsntr kiqsepassl ttrlretsts 
               
               
                   
                 eetslatean 
               
               
                   
               
               
                 7561 
                 tvlskvstga ttevsrteai sfsrtsmsgp eqstmsqdis igtiprisas 
               
               
                   
                 svltesakmt 
               
               
                   
               
               
                 7621 
                 ittqtgpses tlestlnlnt attpswveth siviqgfphp emttsmgrgp 
               
               
                   
                 ggvswpsppf 
               
               
                   
               
               
                 7681 
                 vketsppssp lslpavtsph pvsttflahi ppsplpvtsl ltsgpatttd 
               
               
                   
                 ilgtstepgt 
               
               
                   
               
               
                 7741 
                 ssssslstts herlttykdt ahteavhpst ntggtnvatt ssgyksqssv 
               
               
                   
                 ladsspmctt 
               
               
                   
               
               
                 7801 
                 stmgdtsvlt stpafletrr iqtelasslt pglressgse gtssgtkmst 
               
               
                   
                 vlskvptgat 
               
               
                   
               
               
                 7861 
                 teiskedvts ipgpaqstis pdistrtvsw fstspvmtes aeitmnthts 
               
               
                   
                 plgattqgts 
               
               
                   
               
               
                 7921 
                 tldtssttsl tmthstisqg fshsqmstlm rrgpedvswm sppllektrp 
               
               
                   
                 sfslmsspat 
               
               
                   
               
               
                 7981 
                 tspspvsstl pesisssplp vtslltsgla kttdmlhkss epvtnspanl 
               
               
                   
                 sstsveilat 
               
               
                   
               
               
                 8041 
                 sevttdtekt hpssnrtvtd vgtsssghes tsfvladsqt skvtspmvit 
               
               
                   
                 stmedtsvst 
               
               
                   
               
               
                 8101 
                 stpgffetsr iqteptsslt lglrktssse gtslatemst vlsgvptgat 
               
               
                   
                 aevsrtevts 
               
               
                   
               
               
                 8161 
                 ssrtsisgfa qltvspetst etitrlptss imtesaemmi ktqtdppgst 
               
               
                   
                 pesthtvdis 
               
               
                   
               
               
                 8221 
                 ttpnwveths tvtqrfshse mttlvsrspg dmlwpsqssv eetssassll 
               
               
                   
                 slpattspsp 
               
               
                   
               
               
                 8281 
                 vsstlvedfp saslpvtsll npglvittdr mgisrepgts stsnlsstsh 
               
               
                   
                 erlttledtv 
               
               
                   
               
               
                 8341 
                 dtedmqpsth tavtnvrtsi sghesqssvl sdsetpkats pmgttytmge 
               
               
                   
                 tsvsistsdf 
               
               
                   
               
               
                 8401 
                 fetsriqiep tssltsglre tssserissa tegstvlsev psgattevsr 
               
               
                   
                 tevissrgts 
               
               
                   
               
               
                 8461 
                 msgpdqftis pdisteaitr lstspimtes aesaitietg spgatsegtl 
               
               
                   
                 tldtstttfw 
               
               
                   
               
               
                 8521 
                 sgthstaspg fshsemttlm srtpgdvpwp slpsveeass vssslsspam 
               
               
                   
                 tstsffstlp 
               
               
                   
               
               
                 8581 
                 esisssphpv talltlgpvk ttdmlrtsse petssppnls stsaeilats 
               
               
                   
                 evtkdrekih 
               
               
                   
               
               
                 8641 
                 pssntpvvnv gtviykhlsp ssvladlvtt kptspmatts tlgntsvsts 
               
               
                   
                 tpafpetmmt 
               
               
                   
               
               
                 8701 
                 qptssltsgl reistsqets satersasls gmptgattkv srtealslgr 
               
               
                   
                 tstpgpaqst 
               
               
                   
               
               
                 8761 
                 ispeisteti tristplttt gsaemtitpk tghsgassqg tftldtssra 
               
               
                   
                 swpgthsaat 
               
               
                   
               
               
                 8821 
                 hrsphsgmtt pmsrgpedvs wpsrpsvekt sppsslvsls avtspsplys 
               
               
                   
                 tpsesshssp 
               
               
                   
               
               
                 8881 
                 lrvtslftpv mmkttdmldt slepvttspp smnitsdesl atskatmete 
               
               
                   
                 aiqlsentav 
               
               
                   
               
               
                 8941 
                 tqmgtisarq efyssypglp epskvtspvv tsstikdivs ttipasseit 
               
               
                   
                 riemeststl 
               
               
                   
               
               
                 9001 
                 tptpretsts qeihsatkps tvpykaltsa tiedsmtqvm sssrgpspdq 
               
               
                   
                 stmsqdiste 
               
               
                   
               
               
                 9061 
                 vitrlstspi ktestemtit tqtgspgats rgtltldtst tfmsgthsta 
               
               
                   
                 sqgfshsqmt 
               
               
                   
               
               
                 9121 
                 almsrtpgdv pwlshpsvee assasfslss pvmtssspvs stlpdsihss 
               
               
                   
                 slpvtsllts 
               
               
                   
               
               
                 9181 
                 glvkttellg tssepetssp pnlsstsaei laitevttdt eklemtnvvt 
               
               
                   
                 sgythespss 
               
               
                   
               
               
                 9241 
                 vladsvttka tssmgitypt gdtnvltstp afsdtsriqt ksklsltpgl 
               
               
                   
                 metsiseets 
               
               
                   
               
               
                 9301 
                 satekstvls svptgattev srteaisssr tsipgpaqst mssdtsmeti 
               
               
                   
                 tristpltrk 
               
               
                   
               
               
                 9361 
                 estdmaitpk tgpsgatsqg tftldsssta swpgthsatt qrfpqsvvtt 
               
               
                   
                 pmsrgpedvs 
               
               
                   
               
               
                 9421 
                 wpsplsvekn sppsslvsss svtspsplys tpsgsshssp vpvtslftsi 
               
               
                   
                 mmkatdmlda 
               
               
                   
               
               
                 9481 
                 slepettsap nmnitsdesl aaskattete aihvfentaa shvettsate 
               
               
                   
                 elyssspgfs 
               
               
                   
               
               
                 9541 
                 eptkvispvv tsssirdnmv sttmpgssgi trieiesmss ltpglretrt 
               
               
                   
                 sqditsstet 
               
               
                   
               
               
                 9601 
                 stvlykmpsg atpevsrtev mpssrtsipg paqstmsldi sdevvtrlst 
               
               
                   
                 spimtesaei 
               
               
                   
               
               
                 9661 
                 tittqtgysl atsqvtlplg tsmtflsgth stmsqglshs emtnlmsrgp 
               
               
                   
                 eslswtsprf 
               
               
                   
               
               
                 9721 
                 vettrssssl tslplttsls pvsstlldss pssplpvtsl ilpglvktte 
               
               
                   
                 vldtssepkt 
               
               
                   
               
               
                 9781 
                 ssspnlssts veipatseim tdtekihpss ntavakvrts ssvheshssv 
               
               
                   
                 ladsettiti 
               
               
                   
               
               
                 9841 
                 psmgitsavd dttvftsnpa fsetrripte ptfsltpgfr etstseetts 
               
               
                   
                 itetsavlyg 
               
               
                   
               
               
                 9901 
                 vptsattevs mteimssnri hipdsdqstm spdiitevit rlssssmmse 
               
               
                   
                 stqmtittqk 
               
               
                   
               
               
                 9961 
                 sspgataqst ltlatttapl arthstvppr flhsemttlm srspenpswk 
               
               
                   
                 sslfvektss 
               
               
                   
               
               
                 10021 
                 sssllslpvt tspsvsstlp qsipsssfsv tslltpgmvk ttdtstepgt 
               
               
                   
                 slspnlsgts 
               
               
                   
               
               
                 10081 
                 veilaasevt tdtekihpss smavtnvgtt ssghelyssv sihsepskat 
               
               
                   
                 ypvgtpssma 
               
               
                   
               
               
                 10141 
                 etsistsmpa nfettgfeae pfshltsgfr ktnmsldtss vtptntpssp 
               
               
                   
                 gsthllqssk 
               
               
                   
               
               
                 10201 
                 tdftssakts spdwppasqy teipvdiitp fnaspsites tgitsfpesr 
               
               
                   
                 ftmsvtesth 
               
               
                   
               
               
                 10261 
                 hlstdllpsa etistgtvmp slseamtsfa ttgvpraisg sgspfsrtes 
               
               
                   
                 gpgdatlsti 
               
               
                   
               
               
                 10321 
                 aeslpsstpv pfssstfttt dsstipalhe itsssatpyr vdtslgtess 
               
               
                   
                 ttegrlvmvs 
               
               
                   
               
               
                 10381 
                 tldtssqpgr tssspildtr mtesvelgtv tsayqvpsls trltrtdgim 
               
               
                   
                 ehitkipnea 
               
               
                   
               
               
                 10441 
                 ahrgtirpvk gpqtstspas pkglhtggtk rmettttalk ttttalktts 
               
               
                   
                 ratlttsvyt 
               
               
                   
               
               
                 10501 
                 ptlgtltpln asmqmastip temmittpyv fpdvpettss latslgaets 
               
               
                   
                 talprttpsv 
               
               
                   
               
               
                 10561 
                 fnresettas lvsrsgaers pviqtldvss sepdttaswv ihpaetiptv 
               
               
                   
                 skttpnffhs 
               
               
                   
               
               
                 10621 
                 eldtvsstat shgadvssai ptnispseld altplvtisg tdtsttfptl 
               
               
                   
                 tksphetetr 
               
               
                   
               
               
                 10681 
                 ttwlthpaet sstiprtipn fshhesdatp siatspgaet ssaipimtvs 
               
               
                   
                 pgaedlvtsq 
               
               
                   
               
               
                 10741 
                 vtssgtdrnm tiptltlspg epktiaslvt hpeaqtssai ptstispavs 
               
               
                   
                 rlvtsmvtsl 
               
               
                   
               
               
                 10801 
                 aaktsttnra ltnspgepat tvslvthpaq tsptvpwtts iffhsksdtt 
               
               
                   
                 psmttshgae 
               
               
                   
               
               
                 10861 
                 sssavptptv stevpgvvtp lvtssravis ttipiltlsp gepettpsma 
               
               
                   
                 tshgeeassa 
               
               
                   
               
               
                 10921 
                 iptptvspgv pgvvtslvts sravtsttip iltfslgepe ttpsmatshg 
               
               
                   
                 teagsavptv 
               
               
                   
               
               
                 10981 
                 lpevpgmvts lvassravts ttlptltlsp gepettpsma tshgaeasst 
               
               
                   
                 vptvspevpg 
               
               
                   
               
               
                 11041 
                 vvtslvtsss gvnstsiptl ilspgelett psmatshgae assavptptv 
               
               
                   
                 spgvsgvvtp 
               
               
                   
               
               
                 11101 
                 lvtssravts ttipiltlss sepettpsma tshgveassa vltvspevpg 
               
               
                   
                 mvtslvtssr 
               
               
                   
               
               
                 11161 
                 avtsttiptl tissdepett tslvthseak misaiptlav sptvqglvts 
               
               
                   
                 lvtssgsets 
               
               
                   
               
               
                 11221 
                 afsnltvass qpetidswva hpgteassvv ptltvstgep ftnislvthp 
               
               
                   
                 aessstlprt 
               
               
                   
               
               
                 11281 
                 tsrfshseld tmpstvtspe aesssaistt ispgipgvlt slvtssgrdi 
               
               
                   
                 satfptvpes 
               
               
                   
               
               
                 11341 
                 pheseatasw vthpavtstt vprttpnysh sepdttpsia tspgaeatsd 
               
               
                   
                 fptitvspdv 
               
               
                   
               
               
                 11401 
                 pdmvtsqvts sgtdtsitip tltlssgepe tttsfityse thtssaiptl 
               
               
                   
                 pvspgaskml 
               
               
                   
               
               
                 11461 
                 tslvissgtd stttfptlte tpyepettai qlihpaetnt mvprttpkfs 
               
               
                   
                 hsksdttlpv 
               
               
                   
               
               
                 11521 
                 aitspgpeas savstttisp dmsdlvtslv pssgtdtstt fptlsetpye 
               
               
                   
                 pettatwlth 
               
               
                   
               
               
                 11581 
                 paetsttvsg tipnfshrgs dtapsmvtsp gvdtrsgvpt ttippsipgv 
               
               
                   
                 vtsqvtssat 
               
               
                   
               
               
                 11641 
                 dtstaiptlt pspgepetta ssathpgtqt gftvpirtvp ssepdtmasw 
               
               
                   
                 vthppqtstp 
               
               
                   
               
               
                 11701 
                 vsrttssfsh sspdatpvma tsprteassa vlttispgap emvtsqitss 
               
               
                   
                 gaatsttvpt 
               
               
                   
               
               
                 11761 
                 lthspgmpet tallsthprt etsktfpast vfpqvsetta sltirpgaet 
               
               
                   
                 stalptqtts 
               
               
                   
               
               
                 11821 
                 slftllvtgt srvdlsptas pgvsaktapl sthpgtetst miptstlslg 
               
               
                   
                 llettgllat 
               
               
                   
               
               
                 11881 
                 sssaetstst ltltvspavs glssasittd kpqtvtswnt etspsvtsvg 
               
               
                   
                 ppefsrtvtg 
               
               
                   
               
               
                 11941 
                 ttmtlipsem ptppktshge gvspttilrt tmveatnlat tgssptvakt 
               
               
                   
                 tttfntlags 
               
               
                   
               
               
                 12001 
                 lftplttpgm stlasesvts rtsynhrswi sttssynrry wtpatstpvt 
               
               
                   
                 stfspgists 
               
               
                   
               
               
                 12061 
                 sipsstaatv pfmvpftlnf titnlqyeed mrhpgsrkfn aterelqgll 
               
               
                   
                 kplfrnssle 
               
               
                   
               
               
                 12121 
                 ylysgcrlas lrpekdssat avdaicthrp dpedlgldre rlywelsnlt 
               
               
                   
                 ngiqelgpyt 
               
               
                   
               
               
                 12181 
                 ldrnslyvng fthrssmptt stpgtstvdv gtsgtpsssp spttagpllm 
               
               
                   
                 pftlnftitn 
               
               
                   
               
               
                 12241 
                 lqyeedmrrt gsrkfntmes vlqgllkplf kntsvgplys gcrltllrpe 
               
               
                   
                 kdgaatgvda 
               
               
                   
               
               
                 12301 
                 icthrldpks pglnreqlyw elskltndie elgpytldrn slyvngfthq 
               
               
                   
                 ssvsttstpg 
               
               
                   
               
               
                 12361 
                 tstvdlrtsg tpsslsspti maagpllvpf tlnftitnlq ygedmghpgs 
               
               
                   
                 rkfnttervl 
               
               
                   
               
               
                 12421 
                 qgllgpifkn tsvgplysgc rltslrsekd gaatgvdaic ihhldpkspg 
               
               
                   
                 lnrerlywel 
               
               
                   
               
               
                 12481 
                 sqltngikel gpytldrnsl yvngfthrts vptsstpgts tvdlgtsgtp 
               
               
                   
                 fslpspatag 
               
               
                   
               
               
                 12541 
                 pllvlftlnf titnlkyeed mhrpgsrkfn ttervlqtll gpmfkntsvg 
               
               
                   
                 llysgcrltl 
               
               
                   
               
               
                 12601 
                 lrsekdgaat gvdaicthrl dpkspgvdre qlywelsqlt ngikelgpyt 
               
               
                   
                 ldrnslyvng 
               
               
                   
               
               
                 12661 
                 fthwipvpts stpgtstvdl gsgtpsslps pttagpllvp ftlnftitnl 
               
               
                   
                 kyeedmhcpg 
               
               
                   
               
               
                 12721 
                 srkfntterv lqsllgpmfk ntsvgplysg crltllrsek dgaatgvdai 
               
               
                   
                 cthrldpksp 
               
               
                   
               
               
                 12781 
                 gvdreqlywe lsqltngike lgpytldrns lyvngfthqt sapntstpgt 
               
               
                   
                 stvdlgtsgt 
               
               
                   
               
               
                 12841 
                 psslpsptsa gpllvpftln ftitnlqyee dmhhpgsrkf nttervlqgl 
               
               
                   
                 lgpmfkntsv 
               
               
                   
               
               
                 12901 
                 gllysgcrlt llrpekngaa tgmdaicshr ldpkspglnr eqlywelsql 
               
               
                   
                 thgikelgpy 
               
               
                   
               
               
                 12961 
                 tldrnslyvn gfthrssvap tstpgtstvd lgtsgtpssl pspttavpll 
               
               
                   
                 vpftlnftit 
               
               
                   
               
               
                 13021 
                 nlqygedmrh pgsrkfntte rvlqgllgpl fknssvgply sgcrlislrs 
               
               
                   
                 ekdgaatgvd 
               
               
                   
               
               
                 13081 
                 aicthhlnpq spgldreqly wqlsqmtngi kelgpytldr nslyvngfth 
               
               
                   
                 rssglttstp 
               
               
                   
               
               
                 13141 
                 wtstvdlgts gtpspvpspt ttgpllvpft lnftitnlqy eenmghpgsr 
               
               
                   
                 kfnitesvlq 
               
               
                   
               
               
                 13201 
                 gllkplfkst svgplysgcr ltllrpekdg vatrvdaict hrpdpkipgl 
               
               
                   
                 drqqlywels 
               
               
                   
               
               
                 13261 
                 qlthsitelg pytldrdsly vngftqrssv pttstpgtft vqpetsetps 
               
               
                   
                 slpgptatgp 
               
               
                   
               
               
                 13321 
                 vllpftlnft itnlqyeedm rrpgsrkfnt tervlqgllm plfkntsvss 
               
               
                   
                 lysgcrltll 
               
               
                   
               
               
                 13381 
                 rpekdgaatr vdavcthrpd pkspgldrer lywklsqlth gitelgpytl 
               
               
                   
                 drhslyvngf 
               
               
                   
               
               
                 13441 
                 thqssmtttr tpdtstmhla tsrtpaslsg pmtaspllvl ftinftitnl 
               
               
                   
                 ryeenmhhpg 
               
               
                   
               
               
                 13501 
                 srkfntterv lqgllrpvfk ntsvgplysg crltllrpkk dgaatkvdai 
               
               
                   
                 ctyrpdpksp 
               
               
                   
               
               
                 13561 
                 gldreqlywe lsqlthsite lgpytldrds lyvngftqrs svpttsipgt 
               
               
                   
                 ptvdlgtsgt 
               
               
                   
               
               
                 13621 
                 pvskpgpsaa spllvlftln ftitnlryee nmqhpgsrkf nttervlqgl 
               
               
                   
                 lrslfkstsv 
               
               
                   
               
               
                 13681 
                 gplysgcrlt llrpekdgta tgvdaicthh pdpksprldr eqlywelsql 
               
               
                   
                 thnitelgpy 
               
               
                   
               
               
                 13741 
                 aldndslfvn gfthrssvst tstpgtptvy lgasktpasi fgpsaashll 
               
               
                   
                 ilftlnftit 
               
               
                   
               
               
                 13801 
                 nlryeenmwp gsrkfntter vlqgllrplf kntsvgplys gcrltllrpe 
               
               
                   
                 kdgeatgvda 
               
               
                   
               
               
                 13861 
                 icthrpdptg pgldreqlyl elsqlthsit elgpytldrd slyvngfthr 
               
               
                   
                 ssvpttstgv 
               
               
                   
               
               
                 13921 
                 vseepftlnf tinnlrymad mgqpgslkfn itdnvmqhll splfqrsslg 
               
               
                   
                 arytgcrvia 
               
               
                   
               
               
                 13981 
                 lrsvkngaet rvdllctylq plsgpglpik qvfhelsqqt hgitrlgpys 
               
               
                   
                 ldkdslylng 
               
               
                   
               
               
                 14041 
                 ynepgpdepp ttpkpattfl pplseattam gyhlktltln ftisnlqysp 
               
               
                   
                 dmgkgsatfn 
               
               
                   
               
               
                 14101 
                 stegvlqhll rplfqkssmg pfylgcqlis lrpekdgaat gvdttctyhp 
               
               
                   
                 dpvgpgldiq 
               
               
                   
               
               
                 14161 
                 qlywelsqlt hgvtqlgfyv ldrdslfing yapqnlsirg eyqinfhivn 
               
               
                   
                 wnlsnpdpts 
               
               
                   
               
               
                 14221 
                 seyitllrdi qdkvttlykg sqlhdtfrfc lvtnltmdsv lvtvkalfss 
               
               
                   
                 nldpslveqv 
               
               
                   
               
               
                 14281 
                 fldktlnasf hwlgstyqlv dihvtemess vyqptsssst qhfylnftit 
               
               
                   
                 nlpysqdkaq 
               
               
                   
               
               
                 14341 
                 pgttnyqrnk rniedalnql frnssiksyf sdcqvstfrs vpnrhhtgvd 
               
               
                   
                 slcnfsplar 
               
               
                   
               
               
                 14401 
                 rvdrvaiyee flrmtrngtq lqnftldrss vlvdgyspnr nepltgnsdl 
               
               
                   
                 pfwaviligl 
               
               
                   
               
               
                 14461 
                 agllgvitcl icgvlvttrr rkkegeynvq qqcpgyyqsh ldledlq 
               
             
          
         
       
     
         [0092]    By “HE4” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AA052683 or CAA44869 or a fragment thereof. An exemplary sequence of HE4 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mpacrlgpla aalllslllf gftlvsgtga ektgvcpelq 
               
               
                   
                 adqnctqecv sdsecadnlk 
               
               
                   
               
               
                 61 
                 ccsagcatfc slpndkegsc pqvninfpql 
               
               
                   
                 glcrdqcqvd sqcpgqmkcc rngcgkvscv 
               
               
                   
               
               
                 121 
                 tpnf 
               
             
          
         
       
     
         [0093]    By “IL-2 receptor alpha (IL-2Rα)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers CAK26553 or NP — 000408 or a fragment thereof. An exemplary sequence of IL-2Rα is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mdsyllmwgl ltfimvpgcq aelcdddppe iphatfkama 
               
               
                   
                 ykegtmlnce ckrgfrriks 
               
               
                   
               
               
                 61 
                 gslymlctgn sshsswdnqc qctssatrnt tkqvtpqpee 
               
               
                   
                 qkerkttemq spmqpvdqas 
               
               
                   
               
               
                 121 
                 lpghcreppp weneateriy hfvvgqmvyy qcvqgyralh 
               
               
                   
                 rgpaesvckm thgktrwtqp 
               
               
                   
               
               
                 181 
                 qlictgemet sqfpgeekpq aspegrpese tsclvtttdf 
               
               
                   
                 qiqtemaatm etsiftteyq 
               
               
                   
               
               
                 241 
                 vavagcvfll isvlllsglt wqrrqrksrr ti 
               
             
          
         
       
     
         [0094]    By “Alpha-1-Antitrypsin (AAT)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAB59495 or CAJ15161 or a fragment thereof. An exemplary sequence of ATT is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mpssvswgil llaglcclvp vslaedpqgd aaqktdtshh 
               
               
                   
                 dqdhptfnki tpnlaefafs 
               
               
                   
               
               
                 61 
                 lyrqlahqsn stniffspvs iatafamlsl gtkadthdei 
               
               
                   
                 leglnfnlte ipeaqihegf 
               
               
                   
               
               
                 121 
                 qellrtlnqp dsqlqlttgn glflseglkl vdkfledvkk 
               
               
                   
                 lyhseaftvn fgdteeakkq 
               
               
                   
               
               
                 181 
                 indyvekgtq gkivdlvkel drdtvfalvn yiffkgkwer 
               
               
                   
                 pfevkdteee dfhvdqvttv 
               
               
                   
               
               
                 241 
                 kvpmmkrlgm fniqhckkls swvllmkylg nataifflpd 
               
               
                   
                 egklqhlvne lthdiitkfl 
               
               
                   
               
               
                 301 
                 enedrrsasl hlpklsitgt ydlksvlgql gitkvfsnga 
               
               
                   
                 dlsgvteeap lklskavhka 
               
               
                   
               
               
                 361 
                 vltidekgte aagamfleai pmsippevkf nkpfvflmie 
               
               
                   
                 qntksplfmg kvvnptqk 
               
             
          
         
       
     
         [0095]    By “C-Reactive Protein (CRP)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers CAA39671 or P02741 or a fragment thereof. An exemplary sequence of CRP is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mekllcflvl tslshafgqt dmsrkafvfp kesdtsyvsl 
               
               
                   
                 kapltkplka ftvclhfyte 
               
               
                   
               
               
                 61 
                 lsstrgtvfs rmpprdktmr ffifwskdig ysftvggsei 
               
               
                   
                 lfevpevtva pvhictswes 
               
               
                   
               
               
                 121 
                 asgivefwvd gkprvrkslk kgytvgaeas iilgqeqdsf 
               
               
                   
                 ggnfegsqsl vgdignvnmw 
               
               
                   
               
               
                 181 
                 dfvlspdein tiylggpfsp nvlnwralky evqgevftkp 
               
               
                   
                 qlwp 
               
             
          
         
       
     
         [0096]    By “YKL-40” also know as “chitinase-3-like protein” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P36222 or NP — 001267 or a fragment thereof. An exemplary sequence of YKL-40 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mgvkasqtgf vvlvllqccs ayklvcyyts wsqyregdgs 
               
               
                   
                 cfpdaldrfl cthiiysfan 
               
               
                   
               
               
                 61 
                 isndhidtwe wndvtlygml ntlknrnpnl ktllsvggwn 
               
               
                   
                 fgsqrfskia sntqsrrtfi 
               
               
                   
               
               
                 121 
                 ksvppflrth gfdgldlawl ypgrrdkqhf ttlikemkae 
               
               
                   
                 fikeaqpgkk qlllsaalsa 
               
               
                   
               
               
                 181 
                 gkvtidssyd iakisqhldf isimtydfhg awrgttghhs 
               
               
                   
                 plfrgqedas pdrfsntdya 
               
               
                   
               
               
                 241 
                 vgymlrlgap asklvmgipt fgrsftlass etgvgapisg 
               
               
                   
                 pgipgrftke agtlayyeic 
               
               
                   
               
               
                 301 
                 dflrgatvhr ilgqqvpyat kgnqwvgydd qesvkskvqy 
               
               
                   
                 lkdrqlagam vwaldlddfq 
               
               
                   
               
               
                 361 
                 gsfcgqdlrf pltnaikdal aat 
               
             
          
         
       
     
         [0097]    By “Cellular Fibronectin (cFib)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P02751 or a fragment thereof. An exemplary sequence of cFib is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mlrgpgpgll llavqclgta vpstgasksk rqaqqmvqpq 
               
               
                   
                 spvavsqskp gcydngkhyq 
               
               
                   
               
               
                 61 
                 inqqwertyl gnalvctcyg gsrgfncesk peaeetcfdk 
               
               
                   
                 ytgntyrvgd tyerpkdsmi 
               
               
                   
               
               
                 121 
                 wdctcigagr grisctianr cheggqsyki gdtwrrphet 
               
               
                   
                 ggymlecvcl gngkgewtck 
               
               
                   
               
               
                 181 
                 piaekcfdha agtsyvvget wekpyqgwmm vdctclgegs 
               
               
                   
                 gritctsrnr cndqdtrtsy 
               
               
                   
               
               
                 241 
                 rigdtwskkd nrgnllqcic tgngrgewkc erhtsvqtts 
               
               
                   
                 sgsgpftdvr aavyqpqphp 
               
               
                   
               
               
                 301 
                 qpppyghcvt dsgvvysvgm qwlktqgnkq mlctclgngv 
               
               
                   
                 scqetavtqt yggnsngepc 
               
               
                   
               
               
                 361 
                 vlpftyngrt fyscttegrq dghlwcstts nyeqdqkysf 
               
               
                   
                 ctdhtvlvqt rggnsngalc 
               
               
                   
               
               
                 421 
                 hfpflynnhn ytdctsegrr dnmkwcgttq nydadqkfgf 
               
               
                   
                 cpmaaheeic ttnegvmyri 
               
               
                   
               
               
                 481 
                 gdqwdkqhdm ghmmrctcvg ngrgewtcia ysqlrdqciv 
               
               
                   
                 dditynvndt fhkrheeghm 
               
               
                   
               
               
                 541 
                 lnctcfgqgr grwkcdpvdq cqdsetgtfy qigdswekyv 
               
               
                   
                 hgvryqcycy grgigewhcq 
               
               
                   
               
               
                 601 
                 plqtypsssg pvevfitetp sqpnshpiqw napqpshisk 
               
               
                   
                 yilrwrpkns vgrwkeatip 
               
               
                   
               
               
                 661 
                 ghlnsytikg lkpgvvyegq lisiqqyghq evtrfdfttt 
               
               
                   
                 ststpvtsnt vtgettpfsp 
               
               
                   
               
               
                 721 
                 lvatsesvte itassfvvsw vsasdtvsgf rveyelseeg 
               
               
                   
                 depqyldlps tatsvnipdl 
               
               
                   
               
               
                 781 
                 lpgrkyivnv yqisedgeqs lilstsqtta pdappdttvd 
               
               
                   
                 qvddtsivvr wsrpqapitg 
               
               
                   
               
               
                 841 
                 yrivyspsve gsstelnlpe tansvtlsdl qpgvqyniti 
               
               
                   
                 yaveenqest pvviqqettg 
               
               
                   
               
               
                 901 
                 tprsdtvpsp rdlqfvevtd vkvtimwtpp esavtgyrvd 
               
               
                   
                 vipvnlpgeh gqrlpisrnt 
               
               
                   
               
               
                 961 
                 faevtglspg vtyyfkvfav shgreskplt aqqttkldap 
               
               
                   
                 tnlqfvnetd stvlvrwtpp 
               
               
                   
               
               
                 1021 
                 raqitgyrlt vgltrrgqpr qynvgpsvsk yplrnlqpas 
               
               
                   
                 eytvslvaik gnqespkatg 
               
               
                   
               
               
                 1081 
                 vfttlqpgss ippyntevte ttivitwtpa prigfklgvr 
               
               
                   
                 psqggeapre vtsdsgsivv 
               
               
                   
               
               
                 1141 
                 sgltpgveyv ytiqvlrdgq erdapivnkv vtplspptnl 
               
               
                   
                 hleanpdtgv ltvswerstt 
               
               
                   
               
               
                 1201 
                 pditgyritt tptngqqgns leevvhadqs sctfdnlspg 
               
               
                   
                 leynvsvytv kddkesvpis 
               
               
                   
               
               
                 1261 
                 dtiipavppp tdlrftnigp dtmrvtwapp psidltnflv 
               
               
                   
                 ryspvkneed vaelsispsd 
               
               
                   
               
               
                 1321 
                 navvltnllp gteyvvsvss vyeqhestpl rgrqktglds 
               
               
                   
                 ptgidfsdit ansftvhwia 
               
               
                   
               
               
                 1381 
                 pratitgyri rhhpehfsgr predrvphsr nsitltnltp 
               
               
                   
                 gteyvvsiva lngreespll 
               
               
                   
               
               
                 1441 
                 igqqstvsdv prdlevvaat ptslliswda pavtvryyri 
               
               
                   
                 tygetggnsp vqeftvpgsk 
               
               
                   
               
               
                 1501 
                 statisglkp gvdytitvya vtgrgdspas skpisinyrt 
               
               
                   
                 eidkpsqmqv tdvqdnsisv 
               
               
                   
               
               
                 1561 
                 kwlpssspvt gyrvtttpkn gpgptktkta gpdqtemtie 
               
               
                   
                 glqptveyvv svyaqnpsge 
               
               
                   
               
               
                 1621 
                 sqplvqtavt nidrpkglaf tdvdvdsiki awespqgqvs 
               
               
                   
                 ryrvtysspe dgihelfpap 
               
               
                   
               
               
                 1681 
                 dgeedtaelq glrpgseytv svvalhddme sqpligtqst 
               
               
                   
                 aipaptdlkf tqvtptslsa 
               
               
                   
               
               
                 1741 
                 qwtppnvqlt gyrvrvtpke ktgpmkeinl apdsssvvvs 
               
               
                   
                 glmvatkyev svyalkdtlt 
               
               
                   
               
               
                 1801 
                 srpaqgvvtt lenvspprra rvtdatetti tiswrtktet 
               
               
                   
                 itgfqvdavp angqtpiqrt 
               
               
                   
               
               
                 1861 
                 ikpdvrsyti tglqpgtdyk iylytlndna rsspvvidas 
               
               
                   
                 taidapsnlr flattpnsll 
               
               
                   
               
               
                 1921 
                 vswqpprari tgyiikyekp gspprevvpr prpgvteati 
               
               
                   
                 tglepgteyt iyvialknnq 
               
               
                   
               
               
                 1981 
                 ksepligrkk tdelpqlvtl phpnlhgpei ldvpstvqkt 
               
               
                   
                 pfvthpgydt gngiqlpgts 
               
               
                   
               
               
                 2041 
                 gqqpsvgqqm ifeehgfrrt tppttatpir hrprpyppnv 
               
               
                   
                 geeiqighip redvdyhlyp 
               
               
                   
               
               
                 2101 
                 hgpglnpnas tgqealsqtt iswapfqdts eyiischpvg 
               
               
                   
                 tdeeplqfrv pgtstsatlt 
               
               
                   
               
               
                 2161 
                 gltrgatynv ivealkdqqr hkvreevvtv gnsvneglnq 
               
               
                   
                 ptddscfdpy tvshyavgde 
               
               
                   
               
               
                 2221 
                 wermsesgfk llcqclgfgs ghfrcdssrw chdngvnyki 
               
               
                   
                 gekwdrqgen gqmmsctclg 
               
               
                   
               
               
                 2281 
                 ngkgefkcdp heatcyddgk tyhvgeqwqk eylgaicsct 
               
               
                   
                 cfggqrgwrc dncrrpggep 
               
               
                   
               
               
                 2341 
                 spegttgqsy nqysqryhqr tntnvncpie cfmpldvqad 
               
               
                   
                 redsre 
               
             
          
         
       
     
         [0098]    By “Cancer Antigen 72-4 (CA-72-4)” also referred to as “TAG-72” is meant a glycoprotein biomarker which is recognized by monoclonal antibody B72.3. 
         [0099]    By “prostasin” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAB19071 or AAC41759 or a fragment thereof. An exemplary sequence of prostasin is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 maqkgvlgpg qlgavailly lgllrsgtga egaeapcgva 
               
               
                   
                 pqaritggss avagqwpwqv 
               
               
                   
               
               
                 61 
                 sityegvhvc ggslvseqwv lsaahcfpse hhkeayevkl 
               
               
                   
                 gahqldsyse dakvstlkdi 
               
               
                   
               
               
                 121 
                 iphpsylqeg sqgdiallql srpitfsryi rpiclpaana 
               
               
                   
                 sfpnglhctv tgwghvapsv 
               
               
                   
               
               
                 181 
                 slltpkplqq levplisret cnclynidak peephfvqed 
               
               
                   
                 mvcagyvegg kdacqgdsgg 
               
               
                   
               
               
                 241 
                 plscpveglw yltgivswgd acgarnrpgv ytlassyasw 
               
               
                   
                 iqskvtelqp rvvpqtqesq 
               
               
                   
               
               
                 301 
                 pdsnlcgshl afssapaqgl lrpilflplg lalgllspwl 
               
               
                   
                 seh 
               
             
          
         
       
     
         [0100]    By “Tissue Inhibitor of Metalloproteinases 1 (TIMP-1)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers NP — 003245 or P01033 or a fragment thereof. An exemplary sequence of TIMP-1 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mapfeplasg illllwliap sractcvpph pqtafcnsdl 
               
               
                   
                 virakfvgtp evnqttlyqr 
               
               
                   
               
               
                 61 
                 yeikmtkmyk gfqalgdaad irfvytpame svcgyfhrsh 
               
               
                   
                 nrseefliag klqdgllhit 
               
               
                   
               
               
                 121 
                 tcsfvapwns lslaqrrgft ktytvgceec tvfpclsipc 
               
               
                   
                 klqsgthclw tdqllqgsek 
               
               
                   
               
               
                 181 
                 gfqsrhlacl prepglctwq slrsqia 
               
             
          
         
       
     
         [0101]    By “Interleukin 8 (IL-8)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P10145 or AAH13615 or a fragment thereof. An exemplary sequence of IL-8 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mtsklavall aaflisaalc egavlprsak elrcqcikty 
               
               
                   
                 skpfhpkfik elrviesgph 
               
               
                   
               
               
                 61 
                 canteiivkl sdgrelcldp kenwvqrvve kflkraens 
               
             
          
         
       
     
         [0102]    By “Matrix Metalloproteinase-7 (MMP-7)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P09237 or NP — 002414 or a fragment thereof. An exemplary sequence of MMP-7 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mrltvlcavc llpgslalpl pqeaggmsel qweqaqdylk 
               
               
                   
                 rfylydsetk nansleaklk 
               
               
                   
               
               
                 61 
                 emqkffglpi tgmlnsrvie imqkprcgvp dvaeyslfpn 
               
               
                   
                 spkwtskvvt yrivsytrdl 
               
               
                   
               
               
                 121 
                 phitvdrlvs kalnmwgkei plhfrkvvwg tadimigfar 
               
               
                   
                 gahgdsypfd gpgntlahaf 
               
               
                   
               
               
                 181 
                 apgtglggda hfdederwtd gsslginfly aathelghsl 
               
               
                   
                 gmghssdpna vmyptygngd 
               
               
                   
               
               
                 241 
                 pqnfklsqdd ikgiqklygk rsnsrkk 
               
             
          
         
       
     
         [0103]    By “Interleukin 6 (IL-6)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P05231, NP — 000591, or AAH15511 or a fragment thereof. An exemplary sequence of IL-6 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mnsfstsafg pvafslglll vlpaafpapv ppgedskdva 
               
               
                   
                 aphrqpltss eridkqiryi 
               
               
                   
               
               
                 61 
                 ldgisalrke tcnksnmces skealaennl nlpkmaekdg 
               
               
                   
                 cfqsgfneet clvkiitgll 
               
               
                   
               
               
                 121 
                 efevyleylq nrfesseeqa ravqmstkvl iqflqkkakn 
               
               
                   
                 ldaittpdpt tnaslltklq 
               
               
                   
               
               
                 181 
                 aqnqwlqdmt thlilrsfke flqsslralr qm 
               
             
          
         
       
     
         [0104]    By “Vascular Endothelial Growth Factor B (VEGF-B)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P49765, AAC50721, or AAB06274 or a fragment thereof. An exemplary sequence of VEGF-B is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mspllrrlll aallqlapaq apvsqpdapg hqrkvvswid 
               
               
                   
                 vytratcqpr evvvpltvel 
               
               
                   
               
               
                 61 
                 mgtvakqlvp scvtvqrcgg ccpddglecv ptgqhqvrmq 
               
               
                   
                 ilmirypssq lgemsleehs 
               
               
                   
               
               
                 121 
                 qcecrpkkkd savkpdraat phhrpqprsv pgwdsapgap 
               
               
                   
                 spadithptp apgpsahaap 
               
               
                   
               
               
                 181 
                 sttsaltpgp aaaaadaaas svakgga 
               
             
          
         
       
     
         [0105]    By “calprotectin” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAB33355, AAB25118, or P06702 or a fragment thereof. An exemplary sequence of calprotectin is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mtckmsqler nietiintfh qysvklghpd tlnqgefkel 
               
               
                   
                 vrkdlqnflk kenknekvie 
               
               
                   
               
               
                 61 
                 himedldtna dkqlsfeefi mlmarltwas hekmhegdeg 
               
               
                   
                 pghhhkpglg egtp 
               
             
          
         
       
     
         [0106]    By “Insulin-like Growth Factor-Binding Protein 2 (IGFBP-2)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAA03246 or AAA36048 or a fragment thereof. An exemplary sequence of IGFBP-2 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mlprvgcpal plppppllpl lpllllllga sgggggarae 
               
               
                   
                 vlfrcppctp erlaacgppp 
               
               
                   
               
               
                 61 
                 vappaavaav aggarmpcae lvrepgcgcc svcarlegea 
               
               
                   
                 cgvytprcgq glrcyphpgs 
               
               
                   
               
               
                 121 
                 elplqalvmg egtcekrrda eygaspeqva dngddhsegg 
               
               
                   
                 lvenhvdstm nmlggggsag 
               
               
                   
               
               
                 181 
                 rkplksgmke lavfrekvte qhrqmgkggk hhlgleepkk 
               
               
                   
                 lrpppartpc qqeldqvler 
               
               
                   
               
               
                 241 
                 istmrlpder gplehlyslh ipncdkhgly nlkqckmsln 
               
               
                   
                 gqrgecwcvn pntgkliqga 
               
               
                   
               
               
                 301 
                 ptirgdpech lfyneqqear gvhtqrmq 
               
             
          
         
       
     
         [0107]    By “Lectin-Like Oxidized LDL Receptor 1 (LOX-1)” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P78380 or NP — 002534 or a fragment thereof. An exemplary sequence of LOX-1 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mtfddlkiqt vkdqpdeksn gkkakglqfl yspwwclaaa 
               
               
                   
                 tlgvlclglv vtimvlgmql 
               
               
                   
               
               
                 61 
                 sqvsdlltqe qanlthqkkk legqisarqq aeeasqesen 
               
               
                   
                 elkemietla rklnekskeq 
               
               
                   
               
               
                 121 
                 melhhqnlnl qetlkrvanc sapcpqdwiw hgencylfss 
               
               
                   
                 gsfnweksqe kclsldakll 
               
               
                   
               
               
                 181 
                 kinstadldf iqqaisyssf pfwmglsrrn psypwlwedg 
               
               
                   
                 splmphlfrv rgavsqtyps 
               
               
                   
               
               
                 241 
                 gtcayiqrga vyaencilaa fsicqkkanl raq 
               
             
          
         
       
     
         [0108]    By “neuropilin-1” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAP80144, AAP78927, AAG41895, or ABY87548 or a fragment thereof. An exemplary sequence of neuropilin-1 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 merglpllca vlalvlapag afrndkcgdt ikiespgylt 
               
               
                   
                 spgyphsyhp sekcewliqa 
               
               
                   
               
               
                 61 
                 pdpyqrimin fnphfdledr dckydyvevf dgenenghfr 
               
               
                   
                 gkfcgkiapp pvvssgpflf 
               
               
                   
               
               
                 121 
                 ikfvsdyeth gagfsiryei fkrgpecsqn yttpsgviks 
               
               
                   
                 pgfpekypns lectyivfap 
               
               
                   
               
               
                 181 
                 kmseiilefe sfdlepdsnp pggmfcrydr leiwdgfpdv 
               
               
                   
                 gphigrycgq ktpgrirsss 
               
               
                   
               
               
                 241 
                 gilsmvfytd saiakegfsa nysvlqssvs edfkcmealg 
               
               
                   
                 mesgeihsdq itassqystn 
               
               
                   
               
               
                 301 
                 wsaersrlny pengwtpged syrewiqvdl gllrfvtavg 
               
               
                   
                 tqgaisketk kkyyvktyki 
               
               
                   
               
               
                 361 
                 dvssngedwi tikegnkpvl fqgntnptdv vvavfpkpli 
               
               
                   
                 trfvrikpat wetgismrfe 
               
               
                   
               
               
                 421 
                 vygckitdyp csgmlgmvsg lisdsqitss nqgdrnwmpe 
               
               
                   
                 nirlvtsrsg walppaphsy 
               
               
                   
               
               
                 481 
                 inewlqidlg eekivrgiii qggkhrenkv fmrkfkigys 
               
               
                   
                 nngsdwkmim ddskrkaksf 
               
               
                   
               
               
                 541 
                 egnnnydtpe lrtfpalstr firiyperat hgglglrmel 
               
               
                   
                 lgceveapta gpttpngnlv 
               
               
                   
               
               
                 601 
                 decdddqanc hsgtgddfql tggttvlate kptvidstiq 
               
               
                   
                 sefptygfnc efgwgshktf 
               
               
                   
               
               
                 661 
                 chwehdnhvq lkwsvltskt gpiqdhtgdg nfiysqaden 
               
               
                   
                 qkgkvarlvs pvvysqnsah 
               
               
                   
               
               
                 721 
                 cmtfwyhmsg shvgtlrvkl ryqkpeeydq lvwmaighqg 
               
               
                   
                 dhwkegrvll hkslklyqvi 
               
               
                   
               
               
                 781 
                 fegeigkgnl ggiavddisi nnhisqedca kpadldkknp 
               
               
                   
                 eikidetgst pgyegegegd 
               
               
                   
               
               
                 841 
                 knisrkpgnv lktldpilit iiamsalgvl lgavcgvvly 
               
               
                   
                 cacwhngmse rnlsalenyn 
               
               
                   
               
               
                 901 
                 felvdgvklk kdklntqsty sea 
               
             
          
         
       
     
         [0109]    By “TNFR2” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers P20333 or NP — 001057 or a fragment thereof. An exemplary sequence of TNFR2 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mapvavwaal avglelwaaa halpaqvaft pyapepgstc 
               
               
                   
                 rlreyydqta qmccskcspg 
               
               
                   
               
               
                 61 
                 qhakvfctkt sdtvcdsced stytqlwnwv peclscgsrc 
               
               
                   
                 ssdqvetqac treqnrictc 
               
               
                   
               
               
                 121 
                 rpgwycalsk qegcrlcapl rkcrpgfgva rpgtetsdvv 
               
               
                   
                 ckpcapgtfs nttsstdicr 
               
               
                   
               
               
                 181 
                 phqicnvvai pgnasmdavc tstsptrsma pgavhlpqpv 
               
               
                   
                 strsqhtqpt pepstapsts 
               
               
                   
               
               
                 241 
                 fllpmgpspp aegstgdfal pvglivgvta lglliigvvn 
               
               
                   
                 cvimtqvkkk plclqreakv 
               
               
                   
               
               
                 301 
                 phlpadkarg tqgpeqqhll itapssssss lessasaldr 
               
               
                   
                 raptrnqpqa pgveasgage 
               
               
                   
               
               
                 361 
                 arastgssds spgghgtqvn vtcivnvcss sdhssqcssq 
               
               
                   
                 asstmgdtds spsespkdeq 
               
               
                   
               
               
                 421 
                 vpfskeecaf rsqletpetl lgsteekplp lgvpdagmkp s 
               
             
          
         
       
     
         [0110]    By “MPIF-1” is meant a polypeptide biomarker having at least 85% sequence identity to NCBI accession numbers AAB51134 or P55773 or a fragment thereof. An exemplary sequence of MPIF-1 is: 
         [0000]    
       
         
               
               
             
           
               
                 1 
                 mkvsvaalsc lmlvtalgsq arvtkdaete fmmsklplen 
               
               
                   
                 pvlldrfhat sadccisytp 
               
               
                   
               
               
                 61 
                 rsipcslles yfetnsecsk pgvifltkkg rrfcanpsdk 
               
               
                   
                 qvqvcmrmlk ldtriktrkn 
               
             
          
         
       
     
       DETAILED DESCRIPTION 
       [0111]    The biomarker panels and associated methods and products were identified through the analysis of analyte levels of various molecular species in human blood serum drawn from subjects having ovarian cancer of various stages and subtypes, subjects having non-cancer gynecological disorders and normal subjects. The immunoassays described below were courteously performed by our colleagues at Rules-Based Medicine of Austin, Tex. using their Multi-Analyte Profile (MAP) Luminex® platform. 
         [0112]    While a preferred sample is blood serum, it is contemplated that an appropriate sample can be derived from any biological source or sample, such as tissues, extracts, cell cultures, including cells (for example, tumor cells), cell lysates, and physiological fluids, such as, for example, whole blood, plasma, serum, saliva, ductal lavage, ocular lens fluid, cerebral spinal fluid, sweat, urine, milk, ascites fluid, synovial fluid, peritoneal fluid and the like. The sample can be obtained from animals, preferably mammals, more preferably primates, and most preferably humans using species specific binding agents that are equivalent to those discussed below in the context of human sample analysis. It is further contemplated that these techniques and marker panels may be used to evaluate drug therapy in rodents and other animals, including transgenic animals, relevant to the development of human and veterinary therapeutics. 
         [0113]    The sample can be treated prior to use by conventional techniques, such as preparing plasma from blood, diluting viscous fluids, and the like. Methods of sample treatment can involve filtration, distillation, extraction, concentration, inactivation of interfering components, addition of chaotropes, the addition of reagents, and the like. Nucleic acids (including silencer, regulatory and interfering RNA) may be isolated and their levels of expression for the analytes described below also used in the methods of the invention. 
       Samples and Analytical Platform. 
       [0114]    The set of blood serum samples that was analyzed to generate most of the data discussed below contained 150 ovarian cancer samples and 150 non-ovarian cancer samples. The ovarian cancer sample samples further comprised the following epithelial ovarian cancer subtypes: serous (64), clear cell (22), endometrioid (35), mucinous (15), mixed, that is, consisting of more than one subtype (14). The stage distribution of the ovarian cancer samples was: Stage I (41), Stage II (23), Stage III (68), Stage IV (12) and unknown stage (6). 
         [0115]    The non-ovarian cancer sample set includes the following ovarian conditions: benign (104), normal ovary (29) and “low malignant potential/borderline (3). The sample set also includes serum from patients with other cancers: cervical cancer (7), endometrial cancer (6) and uterine cancer (1). 
         [0116]    Antibodies that are specific for a biomarker antigen polypeptide of the invention are readily generated as monoclonal antibodies or as polyclonal antisera, or may be produced as genetically engineered immunoglobulins (Ig) that are designed to have desirable properties using methods well known in the art. For example, by way of illustration and not limitation, antibodies may include recombinant IgGs, chimeric fusion proteins having immunoglobulin derived sequences or “humanized” antibodies (see, e.g., U.S. Pat. Nos. 5,693,762; 5,585,089; 4,816,567; 5,225,539; 5,530,101; and references cited therein) that may all be used for detection of a human biomarker polypeptide according to the methods described herein. Such antibodies may be prepared as provided herein, including by immunization with biomarker polypeptides as described below. For example, as provided herein, nucleic acid sequences encoding biomarker polypeptides are disclosed, such that those skilled in the art may routinely prepare these polypeptides for use as immunogens. 
         [0117]    The term “antibodies” includes polyclonal antibodies, monoclonal antibodies, fragments thereof such as F(ab′).sub.2, and Fab fragments, as well as any naturally occurring or recombinantly produced binding partners, which are molecules that specifically bind a biomarker polypeptide. Antibodies are defined to be “immunospecific” or specifically binding if they bind HE4a polypeptide with a K.sub.a of greater than or equal to about 10 −4  M, preferably of greater than or equal to about 10 −5 M, more preferably of greater than or equal to about 10 and still more preferably of greater than or equal to about 10.sup . . . sup.7 M.sup.-1. Affinities of binding partners  −6  M or antibodies can be readily determined using conventional techniques, for example those described by Scatchard et al., Ann. N.Y. Acad. Sci. 51:660 (1949). Determination of other proteins as binding partners of a biomarker polypeptide can be performed using any of a number of known methods for identifying and obtaining proteins that specifically interact with other proteins or polypeptides, for example, a yeast two-hybrid screening system such as that described in U.S. Pat. No. 5,283,173 and U.S. Pat. No. 5,468,614, or the equivalent. The methods described herein also includes the use of a biomarker polypeptide, and peptides based on the amino acid sequence of a biomarker polypeptide, to prepare binding partners and antibodies that specifically bind to a biomarker polypeptide. 
         [0118]    Antibodies may generally be prepared by any of a variety of techniques known to those of ordinary skill in the art (see, e.g., Harlow and Lane, Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory, 1988). In one such technique, an immunogen comprising a biomarker polypeptide, for example a cell having a biomarker polypeptide on its surface or an isolated biomarker polypeptide is initially injected into a suitable animal (e.g., mice, rats, rabbits, sheep and goats), preferably according to a predetermined schedule incorporating one or more booster immunizations, and the animals are bled periodically. Polyclonal antibodies specific for the biomarker polypeptide may then be purified from such antisera by, for example, affinity chromatography using the polypeptide coupled to a suitable solid support. 
         [0119]    Monoclonal antibodies specific for biomarker polypeptides or variants thereof may be prepared, for example, using the technique of Kohler and Milstein (1976 Eur. J. Immunol 6.511-519), and improvements thereto. Briefly, these methods involve the preparation of immortal cell lines capable of producing antibodies having the desired specificity (i.e., reactivity with the mesothelin polypeptide of interest). Such cell lines may be produced, for example, from spleen cells obtained from an animal immunized as described above. The spleen cells are then immortalized by, for example, fusion with a myeloma cell fusion partner, preferably one that is syngeneic with the immunized animal. For example, the spleen cells and myeloma cells may be combined with a membrane fusion promoting agent such as polyethylene glycol or a nonionic detergent for a few minutes, and then plated at low density on a selective medium that supports the growth of hybrid cells, but not myeloma cells. A preferred selection technique uses HAT (hypoxanthine, aminopterin, thymidine) selection. After a sufficient time, usually about 1 to 2 weeks, colonies of hybrids are observed. Single colonies are selected and tested for binding activity against the polypeptide. Hybridomas having high reactivity and specificity are preferred. Hybridomas that generate monoclonal antibodies that specifically bind to biomarker polypeptides are contemplated by the methods described herein. 
         [0120]    Monoclonal antibodies may be isolated from the supernatants of growing hybridoma colonies. In addition, various techniques may be employed to enhance the yield, such as injection of the hybridoma cell line into the peritoneal cavity of a suitable vertebrate host, such as a mouse or other suitable host. Monoclonal antibodies may then be harvested from the ascites fluid or the blood. Contaminants may be removed from the antibodies by conventional techniques, such as chromatography, gel filtration, precipitation, and extraction. For example, antibodies may be purified by chromatography on immobilized Protein G or Protein A using standard techniques. 
         [0121]    Within certain embodiments, the use of antigen-binding fragments of antibodies may be preferred. Such fragments include Fab fragments, which may be prepared using standard techniques (e.g., by digestion with papain to yield Fab and Fc fragments). The Fab and Fc fragments may be separated by affinity chromatography (e.g., on immobilized protein A columns), using standard techniques. Such techniques are well known in the art, see, e.g., Weir, D. M., Handbook of Experimental Immunology, 1986, Blackwell Scientific, Boston. 
         [0122]    Multifunctional fusion proteins having specific binding affinities for pre-selected antigens by virtue of immunoglobulin V-region domains encoded by DNA sequences linked in-frame to sequences encoding various effector proteins are known in the art, for example, as disclosed in EP-B1-0318554, U.S. Pat. No. 5,132,405, U.S. Pat. No. 5,091,513 and U.S. Pat. No. 5,476,786. Such effector proteins include polypeptide domains that may be used to detect binding of the fusion protein by any of a variety of techniques with which those skilled in the art will be familiar, including but not limited to a biotin mimetic sequence (see, e.g., Luo et al., 1998 J. Biotechnol. 65:225 and references cited therein), direct covalent modification with a detectable labeling moiety, non-covalent binding to a specific labeled reporter molecule, enzymatic modification of a detectable substrate or immobilization (covalent or non-covalent) on a solid-phase support. 
         [0123]    Single chain antibodies for use in the methods described herein may also be generated and selected by a method such as phage display (see, e.g., U.S. Pat. No. 5,223,409; Schlebusch et al., 1997 Hybridoma 16:47; and references cited therein). Briefly, in this method, DNA sequences are inserted into the gene III or gene VIII gene of a filamentous phage, such as M13. Several vectors with multicloning sites have been developed for insertion (McLafferty et al., Gene 128:29-36, 1993; Scott and Smith, Science 249:386-390, 1990; Smith and Scott, Methods Enzymol. 217:228-257, 1993). The inserted DNA sequences may be randomly generated or may be variants of a known binding domain for binding to a biomarker polypeptide. Single chain antibodies may readily be generated using this method. Generally, the inserts encode from 6 to 20 amino acids. The peptide encoded by the inserted sequence is displayed on the surface of the bacteriophage. Bacteriophage expressing a binding domain for a biomarker polypeptide are selected by binding to an immobilized biomarker polypeptide, for example a recombinant polypeptide prepared using methods well known in the art and nucleic acid coding sequences as disclosed herein. Unbound phage are removed by a wash, typically containing 10 mM Tris, 1 mM EDTA, and without salt or with a low salt concentration. Bound phage are eluted with a salt containing buffer, for example. The NaCl concentration is increased in a step-wise fashion until all the phage are eluted. Typically, phage binding with higher affinity will be released by higher salt concentrations. Eluted phage are propagated in the bacteria host. Further rounds of selection may be performed to select for a few phage binding with high affinity. The DNA sequence of the insert in the binding phage is then determined. Once the predicted amino acid sequence of the binding peptide is known, sufficient peptide for use herein as an antibody specific for a biomarker polypeptide may be made either by recombinant means or synthetically. Recombinant means are used when the antibody is produced as a fusion protein. The peptide may also be generated as a tandem array of two or more similar or dissimilar peptides, in order to maximize affinity or binding. 
         [0124]    To detect an antigenic determinant reactive with an antibody specific for a biomarker polypeptide, the detection reagent is typically an antibody, which may be prepared as described herein. There are a variety of assay formats known to those of ordinary skill in the art for using an antibody to detect a polypeptide in a sample, including but not limited to enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunofluorimetry, immunoprecipitation, equilibrium dialysis, immunodiffusion and other techniques. See, e.g., Harlow and Lane, Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory, 1988; Weir, D. M., Handbook of Experimental Immunology, 1986, Blackwell Scientific, Boston. For example, the assay may be performed in a Western blot format, wherein a protein preparation from the biological sample is submitted to gel electrophoresis, transferred to a suitable membrane and allowed to react with the antibody. The presence of the antibody on the membrane may then be detected using a suitable detection reagent, as is well known in the art and described below. 
         [0125]    In another embodiment, the assay involves the use of an antibody immobilized on a solid support to bind to the target biomarker polypeptide and remove it from the remainder of the sample. The bound biomarker polypeptide may then be detected using a second antibody reactive with a distinct biomarker polypeptide antigenic determinant, for example, a reagent that contains a detectable reporter moiety. Alternatively, a competitive assay may be utilized, in which a biomarker polypeptide is labeled with a detectable reporter moiety and allowed to bind to the immobilized biomarker polypeptide specific antibody after incubation of the immobilized antibody with the sample. The extent to which components of the sample inhibit the binding of the labeled polypeptide to the antibody is indicative of the reactivity of the sample with the immobilized antibody, and as a result, indicative of the level of biomarker polypeptides in the sample. 
         [0126]    The solid support may be any material known to those of ordinary skill in the art to which the antibody may be attached, such as a test well in a microtiter plate, a nitrocellulose filter or another suitable membrane. Alternatively, the support may be a bead or disc, such as glass, fiberglass, latex or a plastic such as polystyrene or polyvinylchloride. The antibody may be immobilized on the solid support using a variety of techniques known to those in the art, which are amply described in the patent and scientific literature. 
         [0127]    In certain preferred embodiments, the assay for detection of biomarker antigen polypeptide in a sample is a two-antibody sandwich assay. This assay may be performed by first contacting a biomarker polypeptide-specific antibody that has been immobilized on a solid support, commonly the well of a microtiter plate, with the biological sample, such that a soluble molecule naturally occurring in the sample and having an antigenic determinant that is reactive with the antibody is allowed to bind to the immobilized antibody (e.g., a 30 minute incubation time at room temperature is generally sufficient) to form an antigen-antibody complex or an immune complex. Unbound constituents of the sample are then removed from the immobilized immune complexes. Next, a second antibody specific for a biomarker antigen polypeptide is added, wherein the antigen combining site of the second antibody does not competitively inhibit binding of the antigen combining site of the immobilized first antibody to a biomarker polypeptide. The second antibody may be detectably labeled as provided herein, such that it may be directly detected. Alternatively, the second antibody may be indirectly detected through the use of a detectably labeled secondary (or “second stage”) anti-antibody, or by using a specific detection reagent as provided herein. The methods described herein are not limited to any particular detection procedure, as those having familiarity with immunoassays will appreciate that there are numerous reagents and configurations for immunologically detecting a particular antigen (e.g., a mesothelin polypeptide) in a two-antibody sandwich immunoassay. 
         [0128]    In certain preferred embodiments of the methods described herein using the two-antibody sandwich assay described above, the first, immobilized antibody specific for a bioma antigen polypeptide is a polyclonal antibody and the second antibody specific for a biomarker antigen polypeptide is a polyclonal antibody. Any combination of non-competitive biomarker antibodies could be used with the methods described herein. Including monoclonal antibodies, polyclonal antibodies and combinations thereof. In certain other embodiments of the methods described herein the first, immobilized antibody specific for a biomarker antigen polypeptide is a monoclonal antibody and the second antibody specific for a biomarker antigen polypeptide is a polyclonal antibody. In certain other embodiments of the methods described herein the first, immobilized antibody specific for a biomarker antigen polypeptide is a polyclonal antibody and the second antibody specific for a biomarker antigen polypeptide is a monoclonal antibody. In certain other highly preferred embodiments of the methods described herein the first, immobilized antibody specific for a biomarker antigen polypeptide is a monoclonal antibody and the second antibody specific for a biomarker antigen polypeptide is a monoclonal antibody. In other preferred embodiments of the methods described herein the first, immobilized antibody specific for a biomarker antigen polypeptide and/or the second antibody specific for a biomarker antigen polypeptide may be any of the kinds of antibodies known in the art and referred to herein, for example by way of illustration and not limitation, Fab fragments, F(ab′).sub.2 fragments, immunoglobulin V-region fusion proteins or single chain antibodies. Those familiar with the art will appreciate that the methods described herein encompass the use of other antibody forms, fragments, derivatives and the like in the methods disclosed and claimed herein. 
         [0129]    In certain particularly preferred embodiments, the second antibody may contain a detectable reporter moiety or label such as an enzyme, dye, radionuclide, luminescent group, fluorescent group or biotin, or the like. Any reporter moiety or label could be used with the methods described herein, so long as the signal of such is directly related or proportional to the quantity of antibody remaining on the support after wash. The amount of the second antibody that remains bound to the solid support is then determined using a method appropriate for the specific detectable reporter moiety or label. For radioactive groups, scintillation counting or autoradiographic methods are generally appropriate. Antibody-enzyme conjugates may be prepared using a variety of coupling techniques (for review see, e.g., Scouten, W. H., Methods in Enzymology 135:30-65, 1987). Spectroscopic methods may be used to detect dyes (including, for example, colorimetric products of enzyme reactions), luminescent groups and fluorescent groups. Biotin may be detected using avidin or streptavidin, coupled to a different reporter group (commonly a radioactive or fluorescent group or an enzyme). Enzyme reporter groups may generally be detected by the addition of substrate (generally for a specific period of time), followed by spectroscopic, spectrophotometric or other analysis of the reaction products. Standards and standard additions may be used to determine the level of antigen in a sample, using well known techniques. 
         [0130]    In another embodiment, the methods described herein involve use of a biomarker antigen polypeptide as provided herein to screen for the presence of a malignant condition by detection of immunospecifically reactive antibodies in a biological sample from a biological source or subject. According to this embodiment, a biomarker antigen polypeptide (or a fragment or variant thereof including a truncated biomarker antigen polypeptide as provided herein) is detectably labeled and contacted with a biological sample to detect binding to the biomarker antigen polypeptide of an antibody naturally occurring in soluble form in the sample. For example, the biomarker antigen polypeptide may be labeled biosynthetically by using the sequences disclosed herein in concert with well known methods such as incorporation during in vitro translation of a readily detectable (e.g. radioactively labeled) amino acid, or by using other detectable reporter moieties such as those described above. Without wishing to be bound by theory, this embodiment of the methods described herein contemplates that certain biomarker polypeptides such as the biomarker fusion polypeptides disclosed herein, may provide peptides that are particularly immunogenic and so give rise to specific and detectable antibodies. For example, according to this theory certain biomarker fusion polypeptides may represent “non-self” antigens that provoke an avid immune response, while biomarker polypeptides that lack fusion domains may be viewed by the immune system as more resembling “self” antigens that do not readily elicit humoral or cell-mediated immunity. 
         [0131]    Analyte levels in the samples discussed in this specification were measured using a high-throughput, multi-analyte immunoassay platform. A preferred platform is the Luminex® MAP system as developed by Rules-Based Medicine, Inc. in Austin, Tex. It is described on the company&#39;s website and also, for example, in publications such as Chandler et al., “Methods and kits for the diagnosis of acute coronary syndrome, U.S. Patent Application 2007/0003981, published Jan. 4, 2007, and a related application of Spain et al., “Universal Shotgun Assay,” U.S. Patent Application 2005/0221363, published Oct. 6, 2005. This platform has previously been described in Lokshin (2007) and generated data used in other analyses of ovarian cancer biomarkers. However, any immunoassay platform or system may be used. 
         [0132]    In brief, to describe a preferred analyte measurement system, the MAP platform incorporates polystyrene microspheres that are dyed internally with two spectrally distinct fluorochromes. By using accurate ratios of the fluorochromes, an array is created consisting of 100 different microsphere sets with specific spectral addresses. Each microsphere set can display a different surface reactant. Because microsphere sets can be distinguished by their spectral addresses, they can be combined, allowing up to 100 different analytes to be measured simultaneously in a single reaction vessel. A third fluorochrome coupled to a reporter molecule quantifies the biomolecular interaction that has occurred at the microsphere surface. Microspheres are interrogated individually in a rapidly flowing fluid stream as they pass by two separate lasers in the Luminex® analyzer. High-speed digital signal processing classifies the microsphere based on its spectral address and quantifies the reaction on the surface in a few seconds per sample. 
         [0133]    In another embodiment, an immunoassay can be used to detect and analyze markers in a sample. This method comprises: (a) providing an antibody that specifically binds to a marker; (b) contacting a sample with the antibody; and (c) detecting the presence of a complex of the antibody bound to the marker in the sample. 
         [0134]    An immunoassay is an assay that uses an antibody to specifically bind an antigen (e.g., a marker). The immunoassay is characterized by the use of specific binding properties of a particular antibody to isolate, target, and/or quantify the antigen. The phrase “specifically (or selectively) binds” to an antibody or “specifically (or selectively) immunoreactive with,” when referring to a protein or peptide, refers to a binding reaction that is determinative of the presence of the protein in a heterogeneous population of proteins and other biologics. Thus, under designated immunoassay conditions, the specified antibodies bind to a particular protein at least two times the background and do not substantially bind in a significant amount to other proteins present in the sample. Specific binding to an antibody under such conditions may require an antibody that is selected for its specificity for a particular protein. For example, polyclonal antibodies raised to a marker from specific species such as rat, mouse, or human can be selected to obtain only those polyclonal antibodies that are specifically immunoreactive with that marker and not with other proteins, except for polymorphic variants and alleles of the marker. This selection may be achieved by subtracting out antibodies that cross-react with the marker molecules from other species. 
         [0135]    Using the purified markers or their nucleic acid sequences, antibodies that specifically bind to a marker can be prepared using any suitable methods known in the art. See, e.g., Coligan,  Current Protocols in Immunology  (1991); Harlow &amp; Lane,  Antibodies: A Laboratory Manual  (1988); Goding,  Monoclonal Antibodies: Principles and Practice  (2d ed. 1986); and Kohler &amp; Milstein,  Nature  256:495-497 (1975). Such techniques include, but are not limited to, antibody preparation by selection of antibodies from libraries of recombinant antibodies in phage or similar vectors, as well as preparation of polyclonal and monoclonal antibodies by immunizing rabbits or mice (see, e.g., Huse et al.,  Science  246:1275-1281 (1989); Ward et al.,  Nature  341:544-546 (1989)). Typically a specific or selective reaction will be at least twice background signal or noise and more typically more than 10 to 100 times background. 
         [0136]    Generally, a sample obtained from a subject can be contacted with the antibody that specifically binds the marker. Optionally, the antibody can be fixed to a solid support to facilitate washing and subsequent isolation of the complex, prior to contacting the antibody with a sample. Examples of solid supports include glass or plastic in the form of, e.g., a microtiter plate, a stick, a bead, or a microbead. Antibodies can also be attached to a probe substrate or ProteinChip® array described above. The sample is preferably a biological fluid sample taken from a subject. Examples of biological fluid samples include blood, serum, plasma, nipple aspirate, urine, tears, saliva etc. In a preferred embodiment, the biological fluid comprises blood serum. The sample can be diluted with a suitable eluant before contacting the sample to the antibody. 
         [0137]    After incubating the sample with antibodies, the mixture is washed and the antibody-marker complex formed can be detected. This can be accomplished by incubating the washed mixture with a detection reagent. This detection reagent may be, e.g., a second antibody which is labeled with a detectable label. Exemplary detectable labels include magnetic beads (e.g., DYNABEADS™), fluorescent dyes, radiolabels, enzymes (e.g., horse radish peroxide, alkaline phosphatase and others commonly used in an ELISA), and colorimetric labels such as colloidal gold or colored glass or plastic beads. Alternatively, the marker in the sample can be detected using an indirect assay, wherein, for example, a second, labeled antibody is used to detect bound marker-specific antibody, and/or in a competition or inhibition assay wherein, for example, a monoclonal antibody which binds to a distinct epitope of the marker is incubated simultaneously with the mixture. 
         [0138]    Methods for measuring the amount of, or presence of, antibody-marker complex include, for example, detection of fluorescence, luminescence, chemiluminescence, absorbance, reflectance, transmittance, birefringence or refractive index (e.g., surface plasmon resonance, ellipsometry, a resonant mirror method, a grating coupler waveguide method or interferometry). Optical methods include microscopy (both confocal and non-confocal), imaging methods and non-imaging methods. Electrochemical methods include voltametry and amperometry methods. Radio frequency methods include multipolar resonance spectroscopy. Methods for performing these assays are readily known in the art. Useful assays include, for example, an enzyme immune assay (EIA) such as enzyme-linked immunosorbent assay (ELISA), a radioimmune assay (RIA), a Western blot assay, or a slot blot assay. These methods are also described in, e.g.,  Methods in Cell Biology: Antibodies in Cell Biology , volume 37 (Asci, ed. 1993);  Basic and Clinical Immunology  (Stites &amp; Terr, eds., 7th ed. 1991); and Harlow &amp; Lane, supra. 
         [0139]    Throughout the assays, incubation and/or washing steps may be required after each combination of reagents. Incubation steps can vary from about 5 seconds to several hours, preferably from about 5 minutes to about 24 hours. However, the incubation time will depend upon the assay format, marker, volume of solution, concentrations and the like. Usually the assays will be carried out at ambient temperature, although they can be conducted over a range of temperatures, such as 10° C. to 40° C. 
         [0140]    Immunoassays can be used to determine presence or absence of a marker in a sample as well as the quantity of a marker in a sample. The amount of an antibody-marker complex can be determined by comparing to a standard. A standard can be, e.g., a known compound or another protein known to be present in a sample. As noted above, the test amount of marker need not be measured in absolute units, as long as the unit of measurement can be compared to a control. 
         [0141]    The methods for detecting these markers in a sample have many applications. For example, one or more markers can be measured to aid human cancer diagnosis or prognosis. In another example, the methods for detection of the markers can be used to monitor responses in a subject to cancer treatment. In another example, the methods for detecting markers can be used to assay for and to identify compounds that modulate expression of these markers in vivo or in vitro. In a preferred example, the biomarkers are used to differentiate between the different stages of tumor progression, thus aiding in determining appropriate treatment and extent of metastasis of the tumor. 
         [0142]    Another method of measuring the biomarkers includes the use of a combinatorial ligand library synthesized on beads as described in Ser. No. 11/495,842, filed Jul. 28, 2006 and entitled “Methods for Reducing the range in Concentrations of Analyte Species in a Sample”; hereby incorporated by reference in its 
         [0143]    Skilled artisans will recognize that a wide variety of analytical techniques may be used to determine the levels of biomarkers in a sample as is described and claimed in this specification. Other types of binding reagents available to persons skilled in the art may be utilized to measure the levels of the indicated analytes in a sample. For example, a variety of binding agents or binding reagents appropriate to evaluate the levels of a given analyte may readily be identified in the scientific literature. Generally, an appropriate binding agent will bind specifically to an analyte, in other words, it reacts at a detectable level with the analyte but does not react detectably (or reacts with limited cross-reactivity) with other or unrelated analytes. It is contemplated that appropriate binding agents include polyclonal and monoclonal antibodies, aptamers, RNA molecules and the like. Spectrometric methods also may be used to measure the levels of analytes, including immunofluorescence, mass spectrometry, nuclear magnetic resonance and optical spectrometric methods. Depending on the binding agent to be utilized, the samples may be processed, for example, by dilution, purification, denaturation, digestion, fragmentation and the like before analysis as would be known to persons skilled in the art. Also, gene expression, for example, in a tumor cell or lymphocyte also may be determined. 
         [0144]    It is also contemplated that the identified biomarkers may have multiple epitopes for immunassays and/or binding sites for other types of binding agents. Thus, it is contemplated that peptide fragments or other epitopes of the identified biomarkers, isoforms of specific proteins and even compounds upstream or downstream in a biological pathway or that have been post-translationally modified may be substituted for the identified analytes or biomarkers so long as the relevant and relative stoichiometries are taken into account appropriately. Skilled artisans will recognize that alternative antibodies and binding agents can be used to determine the levels of any particular analyte, so long as their various specificities and binding affinities are factored into the analysis. 
         [0145]    A variety of algorithms may be used to measure or determine the levels of expression of the analytes or biomarkers used in the methods and test kits of the present invention. It is generally contemplated that such algorithms will be capable of measuring analyte levels beyond the measurement of simple cut-off values. Thus, it is contemplated that the results of such algorithms will generically be classified as multivariate index analyses by the U.S. Food and Drug Administration. Specific types of algorithms include: knowledge discovery engine (KDE™), regression analysis, discriminant analysis, classification tree analysis, random forests, ProteomeQuest®, support vector machine, One R, kNN and heuristic naive Bayes analysis, neural nets and variants thereof. 
         [0146]    While there are many very sophisticated algorithms that calculate the probability of an unknown sample being a cancer, a simple logistic regression model typically works quite well for building a diagnostic model based on the measurement of a few markers (preferably less than about five). The theory behind that is well known to persons skilled in the art. There are also many options regarding which software can be use—both commercial and free (and open source) packages. 
         [0147]    The training of a logistic model consists of separating the samples into cases and controls and then use the software chosen to optimize the regression coefficients, one for each marker, plus one bias parameter, so as to maximize the likelihood of the logistic model applied to the training data. 
         [0148]    Once trained, the set of regression coefficients defines the logistic model. A person skilled in the art can easily use this type of diagnostic model to predict the probability of any new samples being identified as a case or control, by plugging the levels of the biomarkers into the logistic equation. Furthermore, an ROC can also be constructed by computing the sensitivities and specificities as the cutoff value of the computed probability varies from 0 to 1. The use of Logistic Regression to calculate a probability comprises the following steps: 1) Measure the levels of the biomarkers: 
         [0149]    For each biomarker, its level is measured and recorded. As guidance to practitioners, the following discussion assumes the use of N biomarkers, and their designated measured levels are x 1 , x 2 , . . . x n — 
         [0150]    2) Compute the ‘z’ value: 
         [0151]    A central quantity to compute in a logistic regression model is the ‘z’ parameter. It is defined as follows, 
         [0000]        z=β   0 +β 1   x   1 +β 2   x   2 + . . . +β n   x   n   eq (1)
 
         [0152]    The parameter β0 is called the bias or intercept, while β 1 , β 2 , . . . β n  are called weights. Specifying the βs would define a logistic regression model. Typically, a training process determines the βs where samples with a known state of either “disease” or “benign” are used to optimize a likelihood function by varying the βs. Once the training process is completed, the values of the βs will be chosen to yield the optimal likelihood of a correct determination. 
         [0153]    For an unknown sample with measured biomarker levels: x 1 , x 2 , . . . x n  and a predetermined set of βs, a person skilled in the art can compute the value of z according eq (1). 
         [0154]    3) Compute the value of the Logistic Function: 
         [0155]    The Logistic Function, f(z), is defined as 
         [0000]        f ( z )= e   z /( e   z +1)  eq (2)
 
         [0156]    Given the value of z computed in 2), one can evaluate f(z) according to eq (2). In some applications, the natural logarithm of z is used instead of just z in eq (2). 
         [0157]    4) Make A Diagnostic Call: 
         [0158]    The Logistic Function yields a value between (0.0 and 1.0), for any value of z. In a typical application, a cutoff of 0.5 is used to differentiate between the controls and the cases. Thus a sample with a score that is &gt;0.5 would be called a case, while a sample with a score that is &lt;=0.5 would be called a control. In some applications of the diagnostic process, other cutoff values (for example, 0.65) are used. 
       EXAMPLES 
     Example 1 
       [0159]    The following discussion and examples are provided to describe and illustrate the present invention. As such, they should not be construed to limit the scope of the invention. Those skilled in the art will well appreciate that many other embodiments also fall within the scope of the invention, as it is described in this specification and the claims. 
       Analysis of Data Using the Knowledge Discovery Engine. 
       [0160]    Correlogic has described the use of evolutionary and pattern recognition algorithms in evaluating complex data sets, including the Knowledge Discovery Engine (KDE™) and ProteomeQuest®. See, for example, Hitt et al., U.S. Pat. No. 6,925,389, “Process for Discriminating Between Biological States Based on Hidden Patterns From Biological Data” (issued Aug. 2, 2005); Hitt, U.S. Pat. No. 7,096,206, “Heuristic Method of Classification,” (issued Aug. 22, 2006) and Hitt, U.S. Pat. No. 7,240,038, “Heuristic Method of Classification,” (to be issued Jul. 3, 2007). The use of this technology to evaluate mass spectral data derived from ovarian cancer samples is further elucidated in Hitt et al., “Multiple high-resolution serum proteomic features for ovarian cancer detection,” U.S. Published Patent Application 2006/0064253, published Mar. 23, 2006. 
         [0161]    When analyzing the data set by Correlogic&#39;s Knowledge Discovery Engine, the following five-biomarker panels were found to provide sensitivities and specificities for various stages of ovarian cancer as set forth in Table I. Specifically, KDE Model 1 [2 — 0008 — 20] returned a relatively high accuracy for Stage I ovarian cancer and included these markers: Cancer Antigen 19-9 (CA19-9, Swiss-Prot Accession Number: Q9BXJ9), C Reactive Protein (CRP, Swiss-Prot Accession Number: P02741), Fibroblast Growth Factor-basic Protein (FGF-basic, Swiss-Prot Accession Number: P09038) and Myoglobin (Swiss-Prot Accession Number: P02144). KDE Model 2 [4 — 0002-10] returned a relatively high accuracy for Stage III, IV and “advanced” ovarian cancer and included these markers: Hepatitis C NS4 Antibody (Hep C NS4 Ab), Ribosomal P Antibody and CRP. KDE Model 3 [4 — 0009 — 140] returned a relatively high accuracy for Stage I and included these markers: CA 19-9, TGF alpha, EN-RAGE (Swiss-Prot Accession Number: P80511), Epidermal Growth Factor (EGF, Swiss-Prot Accession Number: P01133) and HSP 90 alpha antibody. KDE Model 4 [4 — 0026 — 100] returned a relatively high accuracy for Stage II and Stages III, W and “advanced” ovarian cancers and included these markers: EN-RAGE, EGF, Cancer Antigen 125 (CA125, Swiss-Prot Accession Number: Q14596), Fibrinogen (Swiss-Prot Accession Number: Alpha chain P02671; Beta chain P02675; Gamma chain P02679), Apolipoprotein CHI (ApoCIII, Swiss-Prot Accession Number: P02656), Cholera Toxin and CA 19-9. KDE Model 5 [4 — 0027 — 20] also returned a relatively high accuracy for Stage II and Stages III, IV and “advanced” ovarian cancers and included these markers: Proteinase 3 (cANCA) antibody, Fibrinogen, CA 125, EGF, CD40 (Swiss-Prot Accession Number: Q6P2H9), Thyroid Stimulating Hormone (TSH, Swiss-Prot Accession Number: Alpha P01215; Beta P01222 P02679, Leptin (Swiss-Prot Accession Number: P41159), CA 19-9 and Lymphotactin (Swiss-Prot Accession Number: P47992). It is contemplated that skilled artisans could use the KDE analytical tools to identify other, potentially useful sets of biomarkers for predictive or diagnostic value based on the levels of selected analytes. Note that the KDE algorithm may select and utilize various markers based on their relative abundances; and that a given marker, for example the level of cholera toxin in Model W may be zero but is relevant in combination with the other markers selected in a particular grouping. 
         [0162]    Skilled artisans will recognize that a limited size data set as was used in this specification may lead to different results, for example, different panels of markers and varying accuracies when comparing the relative performance of KDE with other analytical techniques. These particular KDE models were built on a relatively small data set using 40 stage I ovarian cancers and 40 normal/benigns and were tested blindly on the balance of the stage II, III/IV described above. Thus, the specificity is of the stage I samples reflects sample set size and potential overfitting. The drop in specificity for the balance of the non-ovarian cancer samples also is expected given the relatively larger size of the testing set relative to the training set. Overall, the biomarker panel developed for the stage I samples also provides potentially useful predictive and diagnostic assays for later stages of ovarian cancer given the high sensitivity values. 
         [0163]    However, these examples of biomarker panels illustrate that there are a number of parameters that can be adjusted to impact model performance. For instance in these cases a variety of different numbers of features are combined together, a variety of match values are used, a variety of different lengths of evolution of the genetic algorithm are used and models differing in the number of nodes are generated. By routine experimentation apparent to one skilled in the art, combinations of these parameters can be used to generate other models of clinically relevant performance. 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE I 
               
             
             
               
                   
               
               
                 Results of Analysis Using Knowledge Discovery Engine to develop a stage I specific classification model. 
               
             
          
           
               
                   
                   
                   
                   
                   
                 Sensitivity 
                 Specificity 
                 Accuracy 
                 Sensitivity 
                 Sensitivity 
                   
               
               
                 Model Name 
                 Feature 
                 Match 
                 Generation 
                 Node 
                 Stage I 
                 Stage I 
                 Stage I 
                 Stage II 
                 Stage III-IV 
                 Specificity 
               
               
                   
               
             
          
           
               
                 2_0008_20 
                 4 
                 0.9 
                 20 
                 12 
                 75 
                 100 
                 87.5 
                 60.9 
                 46.5 
                 82.6 
               
               
                 4_0002_10 
                 3 
                 0.7 
                 10 
                 4 
                 75 
                 100 
                 87.5 
                 69.6 
                 82.6 
                 56 
               
               
                 4_0009_140 
                 5 
                 0.6 
                 140 
                 5 
                 75 
                 100 
                 87.5 
                 43.5 
                 39.5 
                 71.6 
               
               
                 4_0026_100 
                 9 
                 0.7 
                 100 
                 5 
                 87.5 
                 100 
                 93.8 
                 78.3 
                 84.9 
                 67 
               
               
                 4_0027_20 
                 9 
                 0.8 
                 20 
                 5 
                 87.5 
                 100 
                 93.8 
                 78.3 
                 84.9 
                 60.6 
               
               
                   
               
             
          
         
       
     
         [0164]    Methods and Analysis Using Random Forests. 
         [0165]    A preferred analytical technique, known to skilled artisans, is that of Breiman, Random Forests. Machine Learning, 2001. 45:5-32; as further described by Segel, Machine Learning Benchmarks and Random Forest Regression, 2004; and Robnik-Sikonja, Improving Random Forests, in Machine Learning, ECML, 2004 Proceedings, J. F. B. e. al., Editor, 2004, Springer: Berlin. Other variants of Random Forests are also useful and contemplated for the methods of the present invention, for example, Regression Forests, Survival Forests, and weighted population Random Forests. 
         [0166]    Since each of the analyte assays is an independent measurement of a variable, under some circumstances, known to those skilled in the art, it is appropriate to scale the data to adjust for the differing variances of each assay. In such cases, biweight, MAD or equivalent scaling would be appropriate, although in some cases, scaling would not be expected to have a significant impact. A bootstrap layer on top of the Random Forests was used in obtaining the results discussed below. 
         [0167]    In preferred embodiments of the present invention, contemplated panels of biomarkers are: 
         [0168]    a. Cancer Antigen 125 (CA125, Swiss-Prot Accession Number: Q14596) and Epidermal Growth Factor Receptor (EGF-R, Swiss-Prot Accession Number: P00533). 
         [0169]    b. CA125 and C Reactive Protein (CRP, Swiss-Prot Accession Number: P02741). 
         [0170]    c. CA125, CRP and EGF-R. 
         [0171]    d. Any one or more of CA125, CRP and EGF-R, plus any one or more of Ferritin (Swiss-Prot Accession Number: Heavy chain P02794; Light chain P02792), Interleukin-8 (IL-8, Swiss-Prot Accession Number: P10145), and Tissue Inhibitor of Metalloproteinases 1 (TIMP-1, Swiss-Prot Accession Number: P01033), 
         [0172]    e. Any one of the biomarker panels presented in Table H and Table III. 
         [0173]    f. Any of the foregoing panels of biomarkers (a e) plus any one or more of the other biomarkers in the following list if not previously included in the foregoing panels (a-e): Alpha-2 Macroglobulin (A2M, Swiss-Prot Accession Number: P01023), Apolipoprotein A1-1 (ApoA1, Swiss-Prot Accession Number: P02647), Apolipoprotein C-III (ApoCIII, Swiss-Prot Accession Number: P02656), Apolipoprotein H (ApoH, Swiss-Prot Accession Number: P02749), Beta-2 Microglobulin (B2M, Swiss-Prot Accession Number: P23560), Betacellulin (Swiss-Prot Accession Number: P35070), C Reactive Protein (CRP, Swiss-Prot Accession Number: P02741). Cancer Antigen 19-9 (CA19-9, Swiss-Prot Accession Number: Q9BXJ9), Cancer Antigen 125 (CA125, Swiss-Prot Accession Number: Q14596), Collagen Type 2 Antibody, Creatine Kinase-MB (CK-MB, Swiss-Prot Accession Number: Brain P12277; Muscle P06732), C Reactive Protein (CRP, Swiss-Prot Accession Number: P02741), Connective Tissue Growth Factor (CTGF, Swiss-Prot Accession Number: P29279), Double Stranded DNA Antibody (dsDNA Ab), EN-RAGE (Swiss-Prot Accession Number: P80511), Eotaxin (C-C motif chemokine 11, small-inducible cytokine A11 and Eosinophil chemotactic protein, Swiss-Prot Accession Number: P51671), Epidermal Growth Factor Receptor (EGF-R, Swiss-Prot Accession Number: P00533), Ferritin (Swiss-Prot Accession Number: Heavy chain P02794; Light chain P02792), Follicle-stimulating hormone (MI, Follicle-stimulating hormone beta subunit, FSH-beta, FSH-B, Follitropin beta chain, Follitropin subunit beta, Swiss-Prot Accession Number: P01225), Haptoglobin (Swiss-Prot Accession Number: P00738), flE4 (Major epididymis-specific protein E4, Epididymal secretory protein E4, Putative protease inhibitor WAP5 and WAP four-disulfide core domain protein 2, Swiss-Prot Accession Number: Q14508), Insulin (Swiss-Prot Accession Number: P01308), Insulin-like Growth Factor 1 (IGF-1, Swiss-Prot Accession Number: P01343), Insulin like growth factor II (IGF-II, Somatomedin-A, Swiss-Prot Accession Number: P01344), Insulin Factor VII (Swiss-Prot Accession Number: P08709), Interleukin-6 (IL-6, Swiss-Prot Accession Number: P05231), Interleukin-8 (IL-8, Swiss-Prot Accession Number: P10145), Interleukin-10 (IL-10, Swiss-Prot Accession Number: P22301), Interleukin-18 (IL-18, Swiss-Prot Accession Number: Q14116), Leptin (Swiss-Prot Accession Number: P41159), Lymphotactin (Swiss-Prot Accession Number: P47992), Macrophage-derived Chemokine (MDC, Swiss-Prot Accession Number: 000626), Macrophage Inhibotory Factor (SWISS PROT), Macrophage Inflammatory Protein 1 alpha (MIP-lalpha, Swiss-Prot Accession Number: P10147), Macrophage migration inhibitory factor (MIF, Phenylpyruvate tautomerase, Glycosylation-inhibiting factor, GIF, Swiss-Prot Accession Number: P14174), Myoglobin (Swiss-Prot Accession Number: P02144), Ostopontin (Bone sialoprotein 1, Secreted phosphoprotein 1, SPP-1, Urinary stone protein, Nephropontin, Uropontin, Swiss-Prot Accession Number: P10451), Pancreatic Islet Cells (GAD) Antibody, Prolactin (Swiss-Prot Accession Number: P01236), Stem Cell Factor (SCF, Swiss-Prot Accession Number: P21583), Tenascin C (Swiss-Prot Accession Number: P24821), Tissue Inhibitor of Metalloproteinases 1 (TIMP-1, Swiss-Prot Accession Number: P01033), Tumor Necrosis Factor-alpha (TNF-alpha, Swiss-Prot Accession Number: P01375), Tumor Necrosis Factor RII (TNF-RII, Swiss-Prot Accession Number: Q92956), von Willebrand Factor (vWF, Swiss-Prot Accession Number: PO4275) and the other biomarkers identified as being informative for cancer in the references cited in this specification. 
         [0174]    Using the Random Forests analytical approach, a preferred seven biomarker panel was identified that has a high predictive value for Stage I ovarian cancer. It includes: ApoA1, ApoCIII, CA125, CRP, EGF-R, IL-18 and Tenascin. In the course of building and selecting the relatively more accurate models for Stage I cancers generated by Random Forests using these biomarkers, the sensitivity for Stage I ovarian cancers ranged from about 80% to about 85%. Sensitivity was also about 95 for Stage II and about 94% sensitive for Stage III/IV. The overall specificity was about 70%. 
         [0175]    Similarly, a preferred seven biomarker panel was identified that has a high predictive value for Stage H. It includes: B2M, CA125, CK-MB, CRP, Ferritin, IL-8 and TIMP1. A preferred model for Stage H had a sensitivity of about 82% and a specificity of about 88%. 
         [0176]    For Stage III, Stage IV and Advanced ovarian cancer, the following 19 biomarker panel was identified: A2M, CA125, CRP, CTGF, EGF-R, EN-RAGE, Ferritin, Haptoglobin, IGF-1, IL-8, IL-10, Insulin, Leptin, Lymphotactin, MDC, TIMP-1, TNF-alpha, TNF-RII, vWF. A preferred model for Stage III/IV had a sensitivity of about 86% and a specificity of about 89%. 
         [0177]    Other preferred biomarker or analyte panels for detecting, diagnosing and monitoring ovarian cancer are shown in Table H and in Table TIT. These panels include CA-125, CRP and EGF-R and, in most cases, CA19-9. In Table II, 20 such panels of seven analytes each selected from 20 preferred analytes are displayed in columns numbered 1 through 20. In Table III, another 20 such panels of seven analytes each selected from 23 preferred analytes are displayed in columns numbered 1 through 20. 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE II 
               
             
             
               
                   
               
               
                 Additional Biomarker Panels 
               
             
          
           
               
                   
                 1 
                 2 
                 3 
                 4 
                 5 
                 6 
                 7 
                 8 
                 9 
                 10 
                 11 
                 12 
                 13 
                 14 
                 15 
                 16 
                 17 
                 18 
                 19 
                 20 
               
               
                   
                   
               
             
          
           
               
                 CA125 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 CRP 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 EGF-R 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 CA19-9 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                   
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 Haptoglobin 
               
               
                 Serum Amyloid P 
                   
                   
                 x 
                   
                   
                 x 
                   
                   
                 x 
               
               
                 Apo A1 
                   
                   
                   
                   
                   
                   
                 x 
                   
                 x 
               
               
                 IL-6 
                   
                   
                 x 
                 x 
                   
                   
                   
                 x 
                   
                 x 
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                 x 
               
               
                 Myoglobin 
                   
                   
                   
                   
                 x 
                   
                   
                   
                   
                 x 
                 x 
                 x 
                   
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 MIP-1a 
                 x 
                 x 
                 x 
                 x 
                   
                   
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                   
                   
                 x 
               
               
                 EN-RAGE 
               
               
                 CK-MB 
               
               
                 vWF 
                   
                 x 
                   
                 x 
                   
                   
                 x 
               
               
                 Leptin 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                 x 
               
               
                 Apo CIII 
                   
                   
                   
                   
                 x 
                 x 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
               
               
                 Growth Hormone 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                 x 
                 x 
                 x 
                   
                 x 
                 x 
               
               
                 IL-10 
               
               
                 IL-18 
                 x 
                   
                   
                   
                 x 
                 x 
                   
                 x 
                   
                   
                   
                 x 
                   
                 x 
                   
                   
                   
                   
                 x 
                 x 
               
               
                 Myeloperoxidase 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                   
                 x 
               
               
                 VCAM-1 
                 x 
                 x 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
               
               
                   
               
             
          
         
       
     
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE III 
               
             
             
               
                   
               
               
                 Additional Biomarker Panels 
               
             
          
           
               
                   
                 1 
                 2 
                 3 
                 4 
                 5 
                 6 
                 7 
                 8 
                 9 
                 10 
                 11 
                 12 
                 13 
                 14 
                 15 
                 16 
                 17 
                 18 
                 19 
                 20 
               
               
                   
                   
               
             
          
           
               
                 CA125 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 CRP 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 EGF-R 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 CA19-9 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                   
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 Haptoglobin 
               
               
                 Serum Amyloid P 
                   
                   
                   
                   
                   
                   
                 x 
                   
                   
                   
                   
                 x 
                   
                   
                   
                   
                 x 
               
               
                 Apo A1 
                   
                   
                 x 
                   
                   
                   
                   
                   
                   
                 x 
               
               
                 IL-6 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                 x 
                   
                 x 
                 x 
                   
                   
                 x 
                 x 
               
               
                 Myoglobin 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
               
               
                 MIP-1a 
                 x 
                   
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                 x 
                   
                   
                 x 
                   
                 x 
                 x 
                 x 
                   
                 x 
                   
                 x 
               
               
                 EN-RAGE 
               
               
                 CK-MB 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
               
               
                 vWF 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                 x 
                   
                   
                 x 
                   
                   
                 x 
               
               
                 Leptin 
                 x 
                 x 
                   
                   
                   
                   
                   
                   
                   
                 x 
               
               
                 Apo CIII 
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                   
                 x 
                   
                 x 
                   
                   
                 x 
                 x 
                 x 
               
               
                 Growth Hormone 
               
               
                 IL-10 
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
                   
                   
                   
                   
                 x 
               
               
                 IL-18 
               
               
                 Myeloperoxidase 
                   
                 x 
                   
                   
                   
                 x 
                   
                   
                   
                   
                   
                 x 
               
               
                 VCAM-1 
               
               
                 Insulin 
                   
                   
                   
                 x 
               
               
                 Ferritin 
                   
                   
                   
                   
                 x 
                   
                   
                   
                   
                   
                   
                   
                 x 
                 x 
                   
                   
                 x 
                   
                   
                 x 
               
               
                 Haptoglobin 
                   
                   
                   
                   
                   
                   
                   
                   
                 x 
               
               
                   
               
             
          
         
       
     
         [0178]    Other preferred biomarker panels (or models) for all stages of ovarian cancer include: (a) CA-125, CRP, EGF-R, CA-19-9, Apo-AI, Apo-CIII, IL-6, IL-18, MIP-1a, Tenascin C and Myoglobin; (b) CA125, CRP, CA19-9, EGF-R, Myoglobin, IL-18, Apo CIII; and (c) CA125, CRP, EGF-R, CA19-9, Apo CM, MIP-1a, Myoglobin, IL-18, IL-6, Apo AI, Tenascin C, vWF, Haptoglobin, IL-10. Optionally, any one or more of the following biomarkers may be added to these or to any of the other biomarker panels disclosed above in text or tables (to the extent that any such panels are not already specifically identified therein): vWF, Haptoglobin, IL-10, IGF-I, IGF-II, Prolactin, HE4, ACE, ASP and Resistin. 
         [0179]    It is contemplated by the present inventors that additional, informative sets of analytes (or biomarkers) include any one or more, two or more, three or more and for or more of the analytes presented below in Table IV, as well as any of the biomarker sets in Tables I, II or III combined with any one or more of the analytes in Table IV, and any one or more of the markers in Table IV combined with any of the other biomarker sets discussed in Paragraphs 70-75, above, or identified elsewhere in this specification. Additional set of informative analytes for use in the test kits and methods of the present invention include any one or more of CA-125, CRP, ECG-R and HE-4 together with any one or more of the biomarkers in Table IV. 
         [0180]    Thus, contemplated sets of biomarkers include combinations such as: CA-125, CRP and one or more (or two or more) of the biomarkers in Table IV; CA-125, EGF-R and any one or more (or two or more) of the biomarkers in Table IV; CA-125, HE-4 and any one or more (or two or more) of the biomarkers in Table IV; CRP, EGF-R and any one or more (or two or more) of the biomarkers in Table IV; CRP, HE-4 and any one or more (or two or more) of the biomarkers in Table IV; and EGF-R, HE-4 and any one or more (or two or more) of the biomarkers in Table IV. It is contemplated that markers of informative value in the foregoing biomarker sets according to the present invention include VCAM-1, IL-6R, IL-18R and sortillin. 
         [0181]    Additionally, biomarker panels comprising any one or more (or two or more) of the biomarkers in Table IV together with any two or more, three or more and four or more of these three sets of biomarkers: (a) CA125, Transthyretin, ApoA-I, B2-microglobulin and Transferrin; (b) CA125 and leptin, prolactin, osteopontin, and insulin-like growth factor-II; and (c) OvaPlex: CA125, C-reactive protein, serum amyloid A, IL-6 and IL-8. 
         [0182]    In general, soluble forms of these analytes are contemplated, including protein and peptide fragments and domains that are shed into the circulating blood and lymph streams. These analytes may be detected and analyzed in blood, lymph, serum, urine and other bodily fluids. Also contemplated in the compositions and methods of the present invention are autoantibodies against any of the disclosed biomarkers, as well as nucleotides that encode these biomarkers, and that may be detected and quantified as another indirect way to assess the levels of these markers. Aptamers and other compounds useful for the detection of such molecular species are well known to persons skilled in the art. 
         [0000]    
       
         
               
               
             
               
               
             
           
               
                 TABLE IV 
               
               
                   
               
               
                 Analyte # 
                 Informative Analytes 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 1 
                 CA 15-3 (MUC-1) 
               
               
                 2 
                 Her2/Neu (erbB-2) 
               
               
                 3 
                 Kallikrein-5 
               
               
                 4 
                 Macrophage Inhibitory Factor (MIF) 
               
               
                 5 
                 Osteopontin 
               
               
                 6 
                 TAG-72 
               
               
                 7 
                 Total IGF-II 
               
               
                 8 
                 HE4 
               
               
                 9 
                 Il6-R 
               
               
                 10 
                 Il6-R shedded form of full-length IL6-R 
               
               
                 11 
                 IL18-R 
               
               
                 12 
                 IL-18BP 
               
               
                 13 
                 VCAM-1 
               
               
                 14 
                 IP-10 (interferon-gamma inducible 10 kD protein) 
               
               
                 15 
                 SMRP 
               
               
                 16 
                 TgII (tissue transglutaminase) 
               
               
                 17 
                 Exotaxin-1 
               
               
                 18 
                 Cyfra 21-1(cytokeratin 19 fragment) 
               
               
                 19 
                 IGF2BP3 
               
               
                 20 
                 TIMP-1 
               
               
                 21 
                 Alpha-1 Antitrypsin 
               
               
                 22 
                 MMP7 
               
               
                 23 
                 TAG-72 
               
               
                 24 
                 IL-8 
               
               
                 25 
                 IL-6 
               
               
                 26 
                 Sortillin 
               
               
                 27 
                 CD40 
               
               
                 28 
                 CA 15-3 
               
               
                 29 
                 Alpha 1-Antichymotrypsin 
               
               
                 30 
                 VEGF 
               
               
                 21 
                 TTR (pre-albumin) 
               
               
                 22 
                 Haptoglobin 
               
               
                   
               
             
          
         
       
     
         [0183]    Any two or more of the preferred biomarkers described above will have predictive value, however, adding one or more of the other preferred markers to any of the analytical panels described herein may increase the panel&#39;s predictive value for clinical purposes. For example, adding one or more of the different biomarkers listed above or otherwise identified in the references cited in this specification may also increase the biomarker panel&#39;s predictive value and are therefore expressly contemplated. Skilled artisans can readily assess the utility of such additional biomarkers. It is contemplated that additional biomarker appropriate for addition to the sets (or panels) of biomarkers disclosed or claimed in this specification will not result in a decrease in either sensitivity or specificity without a corresponding increase in either sensitivity or specificity or without a corresponding increase in robustness of the biomarker panel overall. A sensitivity and/or specificity of at least about 80% or higher are preferred, more preferably at least about 85% or higher, and most preferably at least about 90% or 95% or higher. 
         [0184]    The results of the disclosed diagnostic may be output for the benefit of the user or diagnostician, or may otherwise be displayed on a medium such as, but not limited to, a computer screen, a computer readable medium, a piece of paper, or any other visible medium. 
         [0185]    The foregoing embodiments and advantages of this invention are set forth, in part, in the preceding description and examples and, in part, will be apparent to persons skilled in the art from this description and examples and may be further realized from practicing the invention as disclosed herein. For example, the techniques of the present invention are readily applicable to monitoring the progression of ovarian cancer in an individual, by evaluating a specimen or biological sample as described above and then repeating the evaluation at one or more later points in time, such that a difference in the expression or disregulation of the relevant biomarkers over time is indicative of the progression of the ovarian cancer in that individual or the responsiveness to therapy. All references, patents, journal articles, web pages and other documents identified in this patent application are hereby incorporated by reference in their entireties. 
       Example 2 
       [0186]    Sera were from a prospective, collection undertaken specifically to develop and validate the performance of an ovarian cancer test. All samples were collected under a uniform protocol from 11 different sites, which were monitored for adherence. The Western Institutional Review Board (Olympia, Wash.) and the IRBs of the individual sites approved the studies under FDA Investigational Device Exemption (IDE) number G050132. The collection sites (and IRBs) were Cedars-Sinai Medical Center, Los Angeles, Calif. (Cedars-Sinai Institutional Review Board); Florida Gynecologic Oncology, Fort Meyers, FL (Lee Memorial Health System Institutional Review Committee); Florida Hospital Cancer institute, Orlando, Fla. (Florida Hospital Institutional Review Board); The Harry and Jeanette Weinberg Lancer Institute at Franklin Square Hospital, Baltimore, NM (MedStar Research Institute Georgetown Oncology Institutional Review Board); Holy Cross Hospital, Silver Spring, Md. (Holy Cross Institutional Review Board); North Shore—Long Island Jewish Health System, Manhasset, N.Y. (Institutional Review Board North Shore-Long Island Jewish Health System); SUNY at Stony Brook, N.Y., Stony Brook, N.Y. (Committee on Research Involving Human Subjects SUNY Stony Brook); University of Alabama at Birmingham, Birmingham, Ala. (The University of Alabama at Birmingham Institutional Review Board for Human Use); University of Southern California, Norris Cancer Center, Los Angeles, Calif. and Women&#39;s and Children&#39;s Hospital, Los Angeles, Calif. (University of Southern California Health Sciences Campus institutional. Review Board); Wake Forest University Health Sciences, Winston-Salem, N.C. (Institutional Review Board Wake Forest University School of Medicine); and Women and Infants Hospital of Rhode Island, Providence, R.I. (Institutional Review Board Women and Infants&#39; Hospital of Rhode Island). The study inclusion criteria were women, at least 18 years of age, symptomatic of ovarian cancer according to the National Comprehensive Cancer Network (NCCN) Ovarian Cancer Treatment Guidelines for Patients, which includes women with or without a pelvic mass. Participants had to be scheduled for gynecologic surgery based on concern they had ovarian cancer, and post-surgical pathological evaluation of the ovaries and excised tissues was required to establish clinical truth of disease status. Exclusion criteria were women who did not meet the inclusion criteria, could not provide informed consent, were pregnant, or previously treated for ovarian cancer. Written informed consent was obtained for each participant in the study. All data were de-identified and no results were returned to the physicians or patients. 
         [0187]    149 samples were used from the patients with pathology-confirmed ovarian cancer and 350 samples from the patients with pathology-confirmed benign conditions ( FIG. 1 ). The ovarian cancer samples included all stages and common subtypes of the disease. The benign samples included the common types of benign conditions seen in the entire study population. Complete clinicopatbology reports, obtained following surgery, along with the patient age, race, staging, subtype and coded collection site accompanied each sample. 
         [0188]    Prior to any intervention, blood samples (10 ml) were collected into red top glass Vacutainer tubes. The blood was clotted for at least 30 minutes at room temperature, centrifuged at 3,500 g for 10 minutes, and the resulting serum removed into pre-labeled cryotubes, and stored promptly at −80° C. Processing from blood draw to freezing was completed within 2 hours. All samples were shipped on dry ice to a single designated site for storage. To aliquot, all samples were thawed in a water and ice slurry then transferred into sample tubes labeled with coded identifiers that blinded all subsequent experimenters to the sample disease status. 
       Multiplex Immunoassays 
       [0189]    Two hundred and fifty nine serum biomarkers were measured using a set of proprietary multiplexed immunoassays (Human DiscoveryMAP® v1.0 and Human OncologyMAP® v1.0; ( FIG. 2 ). Each assay was calibrated using an 8-point standard curve, performed in duplicate. Median Fluorescence Intensity (MFI) measurements were interpolated into final protein concentrations using curve-fitting software. Assay performance was verified using quality control (QC) samples at low, medium and high levels for each analyte in duplicate. All standard and QC samples were in a complex serum-based matrix to match the sample background matrix. Since sera were analyzed at a previously optimized dilution, any reading above the maximum concentration of the calibration curve was assigned the concentration of the highest standard, whereas any below the minimum concentration was assigned the value 0. For analysis, the sample run order was randomized to avoid any sequential bias due to presence or absence of disease, subtype or stage of disease, patient age, or age of serum sample. 
       Data Analysis 
       [0190]    Descriptive statistics, Receiver Operating Characteristic (ROC) curves and graphical displays (dot plots) for serum analyte concentrations were performed using commercially available software packages. Statistical differences were determined using the nonparametric Kruskal-Wallis test (ANOVA) followed by Dunn&#39;s multiple comparison post-test. For all statistical comparisons a P-value&lt;0.05 was interpreted as statistically significant. A Pearson correlation matrix was created using a multi-spectral analysis application. 
         [0191]    Using multiplexed immunoassays, the levels of 259 molecules were simultaneously measured in sera from 149 patients with pathology-confirmed epithelial ovarian cancer and 350 individuals with benign ovarian conditions ( FIG. 1 ). To facilitate the determination of the ability of biomarkers to differentiate between symptomatically similar cancer and benign gynecological conditions, all samples were obtained from the same clinical population—women presenting for surgery primarily based on the presence of an adnexal mass. All samples were collected before any intervention and before the disease status was known. Disease status was subsequently identified by pathology exams of the excised tissue. Sera were collected using a single sample collection protocol that was monitored for compliance. The study was conducted prospectively at 11 sites that were also monitored for protocol adherence. This assured sample quality and removed the possibility of any collection, processing or biological biases in the sample set, a concern for many other studies. No normal healthy samples were used in this study, as they are typically easier to classify than benign conditions and introduce confounding factors such as lower stress levels compared to patients facing surgery. As expected, the median patient age was higher in individuals with ovarian cancer (61 years) than those with benign conditions (51 years) and increased with the stage of disease present ( FIG. 1 ). The distribution of the ovarian cancer subtypes was similar to the distribution seen for all ovarian cancer cases in the US population as a whole, with a larger proportion of serous carcinoma (55%) than other subtypes ( FIG. 1 ). The benign controls in the study were representative of common benign ovarian conditions including cystadenoma, cystadenofibroma and fibroma. 
         [0192]    To ensure consistency and aid in biomarker comparisons, all 259 markers and 499 samples were measured on a single platform at a single site using a panel of rigorously qualified, high-throughput, multiplexed immunoassays. This survey built on our previous profiling of 104 serum biomarkers. The majority of the additional 155 serum biomarkers in the present study were developed as part of two NCI-funded Small Business Innovative Research (SBIR) awards specifically targeted at markers that had reasonable literature support to suggest a significant role in cancer biomarker. The selected biomarkers covered a broad range of biological functions, primarily implicated in cancer including cancer antigens, hormones, clotting factors, tissue modeling factors, lipoprotein constituents, proteases and protease inhibitors, markers of cardiovascular risk, growth factors, cytokine/chemokines, soluble forms of cell-signaling receptors, and inflammatory and acute phase reactants ( FIG. 2 ). The present study is the broadest and most consistent single study of immunoassay profiling of molecules using fully characterized, quality-controlled samples. 
         [0193]    For each biomarker, an ROC curve was generated and its area under the curve (AUC) value compared to that of an uninformative marker (AUC=0.500). A total of 175 biomarkers were dysregulated (P-values&gt;0.05) in the ovarian cancer samples relative to the benign gynecological conditions. Of these, 136 biomarkers were up-regulated and 39 down-regulated ( FIGS. 3 and 4 ). The biomarkers with the greatest AUC values were predominantly up-regulated in ovarian cancer ( FIGS. 3 ,  4 , and  5 ) with values ranging from 0.599 to 0.933. The most up-regulated markers were HE4 and CA-125 with AUC values of 0.933 and 0.907, respectively, followed by interleukin-2 receptor α (IL-2 receptor α), α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, cancer antigen 72-4 (CA-72-4) and prostasin, with AUC values between 0.829 and 0.800 ( FIG. 3 ). The remaining 127 up-regulated biomarkers had a continuum of AUC values from 0.797 to 0.556 ( FIG. 4 ). Thirty-four of the remaining 127 markers had AUC values above 0.700. For down-regulated biomarkers, the AUC values ranged from 0.556 to 0.745 ( FIG. 4 ). The two most informative of these stood out as transthyretin (0.745) and apolipoprotein A-IV (0.713), while the remaining biomarkers had AUC values below 0.700. 
         [0194]    This is the first time that thirteen of the twenty biomarkers with the highest AUC values, namely HE4, IL-2 receptor α, YKL-40, cellular fibronectin, CA 72-4, prostasin, MMP-7, VEGF-B, Calprotectin, IGFBP-2, LOX-1, neuropilin-1 and MPIF-1 have been accurately quantified together, on a coherent set of samples, under uniformly controlled analytical conditions, to determine their discriminative power for ovarian cancer. This approach improves biomarker comparisons and should aid in the selection of biomarkers in the development of multi-biomarker panels. 
         [0195]    As a comparison between the two most informative biomarkers in this study, the sensitivity for HE4 and CA-125 was determined over a range of specificity values. In addition, the optimal cut-off value, defined as that yielding the greatest sum of specificity and sensitivity was calculated for each biomarker. The sensitivity for HE4 alone decreased from 89.0% to 57.1% as specificity increased from 80% to 99.6%, while for CA-125 alone the sensitivity decreased from 85.2% to 30.2%. The optimal cut-off for HFA and CA-125 was 54.8 pM and 52.5 U/mL, respectively giving sensitivity values of 86.6% and 74.5%, respectively, and specificity values of 89.4% and 93.7%, respectively. As expected from ROC curves, there are trade-offs when no individual biomarker shows high specificity at a predetermined high sensitivity value. For example, at 100% sensitivity, both HE4 and CA-125 were 0% specific. At 98% sensitivity, HE4 had 30.6% specificity and CA-125 had 35.4% specificity. However, to see relatively good specificity values, the sensitivities had to be lowered to approximately 95%. At 95% sensitivity, HFA had 50.9% specificity and CA-125 had 45.4% specificity. These values, along with the AUC values, indicated that on this population, HE4 performed slightly better than CA-125. In addition, these results show that none of the biomarkers in this study are sufficiently informative as standalone ovarian cancer biomarkers for broad applications and that biomarker panels are needed to improve performance to clinically acceptable levels. 
         [0196]    To determine if some biomarkers might have greater discrimination for different stages of cancer, especially early stage, the nine biomarkers with AUC values above 0.800 on FIGO stage I and II samples were compared where there is the greatest need for marker-based detection ( FIG. 6 ). For FIGO stage I samples, both HE4 and CA-125 were highly discriminative (P-values&lt;0.001), followed in descending order by C-reactive protein and CA 72-4 (P-values 0.001-0.01) then α1-antitrypsin, YKL-40 and prostasin (P-values 0.01-0.05). For IL2-receptor α and cellular fibronectin, there were no statistical differences between stage I cancer and benign conditions (P-values&gt;0.05). For FIGO stage II samples, both HE4 and CA-125 were again highly discriminative (P-values&lt;0.001), followed by for IL2-receptor α, α1-antitrypsin, YKL-40 and CA 72-4 (P-values 0.001-0.01) and then C-reactive protein and cellular fibronectin (P-values 0.01-0.05). For prostasin, there was no statistical difference (P-value&gt;0.05). 
         [0197]    The same nine biomarkers were evaluated to determine if there were statistically significant differences between samples from women with benign conditions and women with each individual subtype of ovarian cancer ( FIG. 7 ). For clear cell carcinomas, α1-antitrypsin and C-reactive protein were highly discriminatory (P-values&lt;0.001), followed in descending order by HE4, CA-125 and IL2-receptor α (P-values 0.01-0.05). For YKL-40, cellular fibronectin, CA 72-4 and prostasin there were no statistical differences (P-value&gt;0.05). For endometrioid carcinomas, there were highly significant differences for HE4 and CA-125 (P-values&lt;0.001) and significant differences for C-reactive protein, cellular fibronectin, CA 72-4 (P-values 0.01-0.05). For α1-antitrypsin, IL2-receptor α, YKL-40 and prostasin there were no statistical differences (P-values&gt;0.05). For mucinous carcinomas, only CA 72-4 had a significant difference (P-value 0.01-0.05). For serous and mixed carcinomas, all nine biomarkers had highly significant differences (P-value&lt;0.001). Therefore, with the exception of mucinous carcinomas, the nine biomarkers are informative for all common ovarian cancer subtypes, however, their different discriminative powers suggests that different combinations of markers may be useful for different subtypes. While it would have been preferential to find more informative biomarkers for the mucinous subtype, it is relatively rare. Indeed, only 6.0% of the cancers in the study were of mucinous subtype ( FIG. 1 ). 
         [0198]    For simplicity and cost effectiveness, the use of a single biomarker is preferred over multiple biomarkers. However, it is clear that single biomarkers may not be able to capture the inherent diversity of complexes diseases such as ovarian cancer. An informative test seeks to combine multiple biomarkers in a way that each marker adds a different type of discrimination either to the entire patient population or the population subdivisions made by the other markers. Simply put, markers with poor correlation with one another have a greater chance of individually contributing to a panel than markers with strong correlation with one another. Therefore, correlation analysis was performed on the strongest ovarian cancer markers—the 124 biomarkers with AUC values greater than 0.600. The co-varying molecules were sorted agglomeratively with hierarchical clustering using Pearson correlation coefficients as the distance measure. The pair-wise results were assembled into a 124×124 matrix (numbered 0-123) and displayed using a heat map where an intense red color signifies strong positive correlation and blue signifies a negative correlation ( FIG. 8 ). There were four major clusters (Clusters A through D;  FIGS. 8-13 ), each cluster representing markers strongly correlating with each other. Each of these clusters contained markers that are strong ovarian cancer markers. Cluster A (markers 1-10) contained two strong ovarian cancer markers, CA 72-4 and MPIF-1 ( FIGS. 9 and 10 ). TNFR2 was found in Cluster B (markers 58-67; Figures XXX (Tables S3 and S5). Cluster C (markers 79-87) contained the two strongest ovarian cancer markers (HFA, CA-125) as well as prostasin and VEGF-B ( FIGS. 9 and 12 ). The strongest correlations with CA-125 were mesothelin (Pearson correlation coefficient=0.600), maspin (0.599), VEGF-D (0.568), prostasin (0.551), kallikrein-7 (0.507) and VEGF-B (0.505). Maspin (0.517) correlated with HE4 the strongest, followed by TIMP-1 (0.470), prostasin (0.463), IL-2 receptor α (0.424), VEGF-B (0.413) and VEGF-D (0.409). Finally, the largest cluster (Cluster D; biomarkers 32-55), was composed of loosely correlated markers that contained several good ovarian cancer markers including calprotectin, LOX-1, IL-6, YKL-40, cellular fibronectin, neuropilin-1, α1-antitrypsin, TIMP-1, C-reactive protein and IL-2 receptor α ( FIGS. 9 and 13 ). These correlation data can help drive the development of biomarkers panels and may give insights into pathways that are disrupted in ovarian cancer. 
         [0199]    The combined performance of the nine markers with AUC values greater than 0.800 were evaluated to determine the predictive value of a simple multi-marker scenario. The nine markers were combined using logistic regression which yielded an AUC of 0.950 (Standard error: 0.01213; 95% CI: 0.926-0.974; P-value: &lt;0.0001). Next this performance was compared against the five markers in the FDA-cleared OVA1 test. The samples in this study were collected by gynecologic oncologists. A similar study population was reported in the OVA1 510(k) summary with 100% sensitivity (invasive ovarian cancer only) and 32.9% specificity. The five markers combined and a logistic regression model was built. Consistent with the OVA1 510(k) summary, with this sample set, at 32.9% specificity, OVA1 biomarkers gave a sensitivity of 98.0%. Interestingly, with these samples, at a specificity of 32.9%, CA-125 alone had a sensitivity of 98.0%. This indicated that the additional OVA markers contributed little, if any, to the overall classification. Indeed, the AUC value for the five OVA1 biomarkers was 0.912 (Standard error 0.0157; 95% CI: 0.881-0.943; P-value: &lt;0.0001), barely higher than CA-125 alone which had an AUC of 0.907 (Standard error 0.01571; 95% CI: 0.877-0.938; P-value: &lt;0.0001). The two models were further compared by determining the sensitivity of models at fixed specificity values and the specificity of models at fixed sensitivity values ( FIGS. 14 and 15 ). In general, the logistic regression model built on the top 9 markers outperformed the model built on OVA1 markers at all points of the ROC curve. At fixed specificity values between 80 and 95%, the top 9 model was 8 to 10% more sensitive that the model built on the OVA1 markers. At higher specificity (99%), the top 9 model was approximately 19% more sensitive. At fixed sensitivity between 80 and 99%, the top 9 model was between 8 and 25% more specific than the model built on the OVA1 markers. 
         [0200]    As both the top nine and OVA1 panels contained markers that may perform differently for pre- and post-menopausal women, the performance of the two panels were compared by menopausal status. For the top nine panel, the AUC value for pre-menopausal women was lower (0.937) than for post-menopausal women (0.953). This is consistent with the individual marker analysis that demonstrated that the top three individual markers (HE4, CA-125 and IL2-Rα) all performed better for the post-menopausal women (0.927, 0.927 and 0.824, respectively; ( FIG. 16 ) than for the pre-menopausal women (0.912, 0.907 and 0.812, respectively). For the OVA1 panel, the AUC value for pre-menopausal women was slightly lower (0.920) than for post-menopausal women (0.924). Again, this is consistent with the individual marker analysis that demonstrated that CA-125, the marker that appears to drive the performance of the OVA 1 panel, performed worse for the group of pre-menopausal women (0.907) than for post-menopausal women (0.927). 
         [0201]    New biomarkers have been identified that are capable of discriminating between samples drawn from women with benign ovarian conditions and those from women with ovarian cancer. Preliminary multivariate analysis, using a logistic regression model on the nine most informative biomarkers appeared to have significantly improved performance over the OVA1 biomarkers. This analysis indicates that our data have the potential to improve on OVA1 and other tests.