AI-based Platform for Ovarian Cancer Biomarker Discovery and Refinement

Ovarian cancer ranks fifth in cancer deaths among women. The revolution in our understanding of genetic and molecular drivers of other cancers has resulted in major improvements in how such cancers are routinely managed. However, standard clinical management of ovarian cancer have not seen any improvements. Significant clinical implications have been achieved by the classification of ovarian cancer based on genetic markers. Pathologists achieve a cornerstone in cancer diagnosis and prognostication by studying the visual microscopic study of diseased tissue (histology). Histology reveals wealth visual information of disease biology about the aggregation effect of genetic alterations on cancer cells. In this project, we plan to produce automated AI-based differential diagnostic tool for major ovarian cancer subtypes, and moreover, investigate the relationship between genetic markers, histology and disease outcome. We then combine these kinds of data for a comprehensive profile of each tumor. New knowledge generated from this project will shed light on the link between histology and genetic markers and identify potential biomarkers that can be rapidly and accurately tested to stratify ovarian cancer for accurate treatment selection.