Abstract: The present invention provides methods and compositions for detecting early stage ovarian cancer in a patient. Also, methods for evaluating the ovarian cancer state of a patient are described herein. These methods involve the detection, analysis, and classification of biomarkers in biological samples.

Abstract: The present invention provides a protein-based biomarker that is useful in qualifying ovarian cancer status in a patient. In particular, the biomarker of this invention is useful to classify a subject sample as ovarian cancer or non-ovarian cancer. The biomarker can be detected by SELDI mass spectrometry.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status as well as endometrical cancer status in a patient. In particular, it has been found that hepcidin is a biomarker for both ovarian cancer and endometrial cancer and that a panel of biomarkers, including hepcidin, transthyretin and optionally other markers are useful to classify a subject sample as ovarian cancer or non-ovarian cancer. The biomarkers can be detected by SELDI mass spectrometry.

Abstract: The present invention provides methods for assessing an ovarian cancer patient's survival status. Also, methods for evaluating the ovarian cancer state of a patient are described herein. These methods involve the detection, analysis, and classification of biological patterns in biological samples. The biological patterns are obtained using, for example, mass spectrometry systems and other techniques.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status in a patient. In particular, the biomarkers of this invention are useful to classify a subject sample as ovarian cancer, ovarian cancer of low malignant potential, benign ovarian disease or other malignant condition. The biomarkers can be detected by SELDI mass spectrometry, immunoassay, or other means.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status in a patient. In particular, it has been found that the biomarkers set forth in Table 1 are biomarkers for ovarian cancer. The biomarkers can be detected by SELDI mass spectrometry.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status as well as endometrical cancer status in a patient. In particular, it has been found that hepcidin is a biomarker for both ovarian cancer and endometrial cancer and that a panel of biomarkers, including hepcidin, transthyretin and optionally other markers are useful to classify a subject sample as ovarian cancer or non-ovarian cancer. The biomarkers can be detected by SELDI mass spectrometry.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying breast cancer status in a patient. In particular, the biomarkers of this invention are useful to classify a subject sample as breast cancer or non-breast cancer. The biomarkers can be detected by SELDI mass spectrometry.

Abstract: The present invention provides protein-based biomarkers and biomarker combinations that are useful in qualifying ovarian cancer status in a patient. In particular, the biomarkers of this invention are useful to classify a subject sample as ovarian cancer, ovarian cancer of low malignant potential, benign ovarian disease or other malignant condition. The biomarkers can be detected by SELDI mass spectrometry, immunoassay, or other means.

Abstract: The invention provides biomarkers including ?-2-microglobulin, Cystatin C, hsCRP and glucose as well as methods for using the biomarkers for diagnosing and/or assessing the risk of peripheral artery disease in a subject. In some embodiments, the subject being tested may be suffering from or at risk of other circulatory diseases, including coronary artery disease. Hemoglobin A1c or other proxies for measuring glucose levels may be substituted for or measured in addition to glucose in the context of the present invention.

Abstract: This invention provides biomarkers whose concentrations in blood plasma are associated with the presence or absence of PAD in the patient from whom the plasma sample is taken. The invention also provides biomarkers for distinguishing between PAD patients who are long claudicators and PAD patients who are not. In addition, the invention provides methods for identifying additional biomarkers, methods for detecting the biomarkers in patients, and methods for identifying agents, including pharmaceutical agents, which interact with the biomarkers and are useful for preventing or treating PAD in patients.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.

Abstract: A method that analyzes mass spectra using a digital computer is disclosed. The method includes entering into a digital computer a data set obtained from mass spectra from a plurality of samples. Each sample is, or is to be assigned to a class within a class set having two or more classes and each class is characterized by a different biological status. A classification model is then formed. The classification model discriminates between the classes in the class set.