Reliable biomarkers to identify women with early-stage ovarian cancer (OVCa) are currently lacking. So are the predictive markers associated with the development of resistance to anticancer compounds such as cisplatin during chemotherapy. A high-throughput whole genome yeast genetic screen was used to identify genes which are important in sensitivity to anticancer drugs, including cisplatin, doxorubicin, and velcade. For each of these drug screens, several genes/pathways, which, when deleted in yeast confer resistance to the drugs were found.
The human orthologues of the identified genes were evaluated for their roles in cisplatin and doxorubicin treatment in ovarian cancers, leukemia, and breast cancer. shRNA technology was used to knock down some of the identified genes to validate whether these genes contributed to drug resistance as well as cancer susceptibility in human. The top pathways identified are genes involved in nucleotide metabolism, mRNA catabolism, and sumoylation. The goal of this project is to identify the association of the genes in these pathways with sensitivity to treatment and survival in ovarian cancer patients and the mechanisms by which they contribute to resistance in chemotherapies.
Our current research focus is to develop combinatorial blockade strategies to overcome suppressive tumor microenvironment and to enhance T cell’s anti-tumor ability in ovarian cancer. Specifically, we are testing the efficacy of blockade of multiple immune inhibitor receptors, such as PD-1 (program cell death 1), LAG-3 (lymphocyte activation gene 1) and CTLA-4 (cytotoxic T lymphocyte antigen 4) on tumor infiltrating T cells using an orthotopic murine ovarian cancer model. The long term goal is to identify molecular mechanisms by which immune inhibitory receptors collaborate in regulating T cell signaling and function and to utilize these findings in designing better strategies for the treatment of ovarian cancer.