Abstract

Abstract Introduction: With an overall five-year survival rate of only 46%, ovarian cancer is the most lethal gynecologic malignancy. Treatment includes surgical cytoreduction (debulking) followed by chemotherapy with platinum and taxane agents, and prognosis generally depends upon clinical characteristics, such as stage of disease at diagnosis, success of surgical debulking, and histologic subtype. However, even among women with comparable clinical characteristics, there can be variation in survival. Part of this variability may be due to inherited genetic variation in genes related to the absorption, distribution, metabolism, and excretion (ADME) of pharmacologic agents commonly used to treat ovarian cancer. Approach: To test the hypothesis that pharmacogenetic variants influence ovarian cancer prognosis, we assembled a clinical cohort of confirmed epithelial ovarian cancer cases from electronic medical records (EMR) at the Vanderbilt University Medical Center (VUMC) with banked DNA samples available. Clinical characteristics were abstracted from EMR using natural language processing (NLP)-assisted EMR review and a REDCap data collection instrument. Genotyping was conducted on the Sequenom iPLEX ADME PGx panel at the Vanderbilt Technologies for Advanced Genomics (VANTAGE) core facility. Associations with overall survival were evaluated using multivariable proportional hazards regression. Results: We identified a total of 391 epithelial ovarian cancer cases with banked DNA from VUMC EHR. Clinical characteristic abstracted by NLP followed expected distributions; the majority of cases were Caucasian (87%), with serous histology (63%), late-stage (62%), high-grade (60%) disease. Most common treatments included surgical cytoreduction (93%) and chemotherapy with a platinum (83%) and/or taxane agent (82%) agent. DNA was successfully pulled, plated, and genotyped for 327 cases (81.3%) for 73 common ADME variants in 30 genes. To prevent population stratification, genetic analyses were restricted to 287 Caucasians, where five nominally significant overall survival associations were identified: ABCB1 rs1045642, ABCC2 rs2273697, CYP2A6 rs1801272, CYP2E1 rs2070673, and SLCO2B1 rs2306168. Additional analyses, including for gene and drug scores, are currently under way. Conclusions: Individual variation in ADME genes may contribute to variation in ovarian cancer survival. Future steps include testing associations for replication, and evaluation of response to treatment. In addition, this research demonstrates that EMR-based study populations, in concert with linked biorepositories, can facilitate research on ovarian cancer. Citation Format: Ayush Giri, Rebecca T. Levinson, Spencer Keene, Gwendolyn Holman, Stacy D. Smith, Leshaun Clayton, Whitney Lovett, Samantha P. Stansel, Malcolm-Robert Bringhurst Snyder, Jason T. Fromal, Gabriella D. Cozzi, Dineo Khabele, Alicia Beeghly-Fadiel. Preliminary results from the Pharmacogenetics Ovarian Cancer Knowledge to Individualize Treatment (POCKIT) study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4229.

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