Predictive markers for ovarian cancer

Inventors

Mansfield, Brian C. • Yip, Ping F. • Amonkar, Suraj • Bertenshaw, Greg P.

Assignees

Aspira Womens Health Inc

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.

Core Innovation

The invention relates to predicting and/or diagnosing ovarian cancer using levels of multiple biomarkers measured in a specimen. The approach relies on multianalyte measurement of biomarker levels and uses panels of biomarkers selected from predefined groups, including measurable fragments thereof. The biomarker panels include myoglobin, CRP, FGF basic protein, CA 19-9, Hepatitis C NS4, Ribosomal P Antibody, TGF alpha, EN-RAGE, EGF, HSP 90 alpha antibody, CA 125, Fibrinogen, Apolipoprotein CIII, Cholera Toxin, Proteinase 3 (cANCA) antibody, CD40, TSH, Leptin, lymphotactin, EGFR, IL-18, Tenascin C, Apolipoprotein A1, Beta-2 Microglobulin, Ferritin, TIMP-1, Creatine Kinase-MB, IL-8, IL-10, Haptoglobin, Insulin, Alpha-2 Macroglobulin, CTGF, TNF-alpha, IGF-1, TNF RII, von Willebrand Factor, MDC, EGF-R, MIP-1, VCAM-1, Serum Amyloid P, ApoA1, and myeloperoxidase.

In the disclosed embodiments, antibody-based reagents measure the biomarker levels, including antibody-containing binding molecules fixed to a microsphere for multiplexed detection. The multianalyte immunoassay context is described as using systems that support measurement of multiple analytes, including preferably Luminex MAP and multiplexed immunoassays using microspheres. The measured biomarker profiles are used as inputs to multivariate/computer models and analysis tools such as Knowledge Discovery Engine (KDE) and Random Forests, including classification tree analysis.

The disclosed diagnostic/predictive framework is associated with epithelial ovarian cancer subtypes and staging (Stage I–IV). The disclosure also describes identifying specific informative biomarker panels derived from KDE and Random Forest, including recurring markers such as CA-125, CRP, and EGF/EGF-R, together with markers including CA19-9, IL-6/IL-8, EN-RAGE, TIMP-1, ferritin, ApoA1/ApoCIII, and vWF. Performance is described in terms of stage-specific sensitivity and specificity, and the disclosure further describes uses in therapy efficacy monitoring and longitudinal assessment of progression by comparing biomarker profiles across subjects over time.

Claims Coverage

The document includes two independent claims. Claim 1 covers a set of reagents to measure biomarker levels in a specimen, while Claim 20 covers antibodies fixed to a microsphere, with both claims defining biomarker selection limited to multiple predefined panels. Across the panels, the inventive coverage is concentrated in the specific multiplex biomarker panels and the binding reagent formats (general reagents versus microsphere-fixed antibodies).

Independent claims cover multiplex biomarker reagent embodiments restricted to one of multiple predefined biomarker panels. One claim broadly recites a reagent set for measuring biomarker levels, while the other specifies antibodies fixed to microspheres, supporting multiplexed biomarker measurement of the same predefined marker panels.

Stated Advantages

Documented Applications