Abstract A06: Integration of synthetic lethality and genomic data to identify significant molecular vulnerabilities in ovarian cancer
Authors: Sethi Geetika , Pathak Harsh , Zhang Hong , Zhou Yan , Einarson Margaret B. , Vathipadiekal Vinod , Gunewardena Sumedha , Birrer Michael J. , Godwin Andrew K. 
Published: August 2014

Abstract
Background: Epithelial ovarian cancer (EOC) is the second leading cause of death from a gynecologic malignancy in the U.S. The overall survival rate has not changed over the last 30 years thereby necessitating new therapeutic approaches. Targeted therapeutics that have come to the forefront of exploration such as anti-VEGF and anti-EGFR, have resulted in only marginal improvements in overall survival. We have used a functional genomics approach followed by analyzing TCGA (The Cancer Genome Atlas) ovarian dataset to help identify significant potential molecular targets that represent key points of therapeutic intervention.
Methods: We employed an unbiased high-throughput lethality screen using a 24,088 siRNA library targeting 6,022 “druggable” genes and tested for effects on growth and/or survival of A1847 EOC cells. Candidate hits from the primary screen were rescreened in a secondary screen across six additional EOC cell lines (OVCAR5, SKOV3, A2780, C30, CP70 and UPN275), and three non-tumorigenic, immortalized human ovarian surface epithelial (HOSE) cell lines (HIO-80, HIO-117, HIO-120). We further validated and eliminated the leading hits which may be due to potential off-target effects by rescreening individual siRNAs from the initial siRNAs pools and by performing quantitative RT-PCR and western blotting. Mechanistic exploration with each of the lead candidates was performed in A2780 cells using Guava cell cycle and Nexin assays. Clinical datasets for lead candidate genes were obtained from https://tcga-data.nci.nih.gov/tcga/ (n=494) and analyzed for gene expression, DNA methylation, copy number variation (CNV) and survival (Kaplan-Meier analysis).
Results: Building on the concept of “oncogenic addiction” we performed a primary lethality screen using A1847 cells and identified 300 genes that were considered essential for tumor cell growth and/or survival. These hits were defined as a gene that reduced cell viability by &gt;15% with a false discovery rate of ≤5%. In the secondary screen, each of the ten cell lines exhibited a unique number of hits ranging from 27-94% of the total siRNAs screened. Fifty-three gene candidates were found to exhibit effects in all seven tumorigenic cell lines. Extensive validation of these hits refined the list to four top priority candidates (HSPA5, NDC80, NUF2 and PTN) that reduced the viability of all the EOC cell lines with minimal effects on the non-tumorigenic HOSE lines. In A2780 cells, HSPA5, NDC80, NUF2 and PTN siRNA treatment led to an average 2.5-fold (n=3, p&lt;0.05) increase in apoptotic cells as compared to control siRNA. Analysis of TCGA ovarian dataset showed NDC80, NUF2 and PTN to be over-expressed (&gt;1.5-fold increase compared with normal tissues) in 99.8%, 99.8% and 40% of patients, respectively. CNV analysis for these three genes showed that the samples with copy number gain exhibited an average 1.6-fold increase (p-value &lt;0.0001, &lt;0.0001 and &lt;0.05 for NDC80, NUF2 and PTN, respectively) in gene expression as compared to samples with no copy number gain. HSPA5 was not found to be significantly over-expressed in ovarian tumors as evaluated by TCGA. DNA methylation analysis showed promoter regions of NDC80, NUF2 and PTN to be hypomethylated (beta values &lt;0.25) in 94% of the tumor samples. KM-survival analysis showed that higher expression of NUF2 mRNA was related to poor prognosis in ovarian cancer patients.
Conclusion: Our functional studies integrated with genomics data provide an important, unbiased avenue towards addressing an urgent and unmet clinical need for identification of prospective therapeutic targets for drug discovery and treatment of ovarian cancer.
Citation Format: Geetika Sethi, Harsh Pathak, Hong Zhang, Yan Zhou, Margaret B. Einarson, Vinod Vathipadiekal, Sumedha Gunewardena, Michael J. Birrer, Andrew K. Godwin. Integration of synthetic lethality and genomic data to identify significant molecular vulnerabilities in ovarian cancer. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr A06.