Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target

Abstract : Outcome predictors based on gene signatures have been successfully applied in breast cancer but similar predictors have not been developed for ovarian cancer. We identified a tumor microenvironment-based gene signature that correlates with poor survival in ovarian cancer patients. We are refining this gene signature to develop biomarkers for the identification of patients with adverse outcomes on standard treatment. In the first part of this project, we have analyzed a gene signature for the identification of patients who are unlikely to benefit from standard surgery and/or chemotherapy and should be considered for clinical trials targeting specific pathways in the tumor microenvironment. Specifically, we found that suboptimal surgical outcome is associated with a molecularly aggressive subtype of ovarian cancer characterized by the presence of reactive tumor stroma, which likely contributes to chemotherapy resistance. In the second part of the project, we will validate the gene signature in patient samples and develop a preliminary quantitative assay for use in the clinical setting. A validated gene signature to identify patients with adverse outcomes has the potential to reduce both the human and financial costs of ineffective therapies and associated toxicities. This will facilitate more individualized treatment decisions and improve the quality of care for patients with ovarian cancer.