Cell-intrinsic platinum response and associated genetic and gene expression signatures in ovarian cancer

Abstract Ovarian cancers are still largely treated with platinum-based chemotherapy as the standard of care, yet few biomarkers of clinical response have had an impact on clinical decision making. Previous work has relied on poor models of the most common subtypes of epithelial ovarian cancers and necessitates a careful examination of the most suitable in vitro models. We performed extensive drug dose response assays and gene expression profiling on 36 ovarian cancer cell lines across over seven subtypes. This is the largest quantitative database of quantitative cisplatin and carboplatin response in ovarian cancer cell lines. Our results demonstrate that cell lines largely fall either well above or below the clinical maximally achievable dose (C max ) of each compound. We performed differential expression analysis for high-grade serous ovarian carcinoma cell lines. Further, we generated two platinum-resistant derivatives each for OVCAR3 and OVCAR4. Combined with clinically resistant PEO1/PEO4/PEO6 and PEA1/PEA2 isogenic models, we performed differential expression analysis for seven platinum-resistant isogenic pairs. Common themes in differential expression were innate immunity/STAT activation, epithelial-to-mesenchymal transition (EMT) and stemness, and platinum influx/efflux regulators. We also performed copy number signature analysis and orthogonal measures of homologous recombination deficiency (HRD) scar scores and copy number burden, which is the first report to our knowledge applying field-standard copy number signatures to ovarian cancer cell lines. We also examined markers and functional readouts of stemness that revealed that cell lines are poor models for examination of stemness contributions to platinum resistance, suggesting that this is a transient state. Overall, this study serves as a resource to determine the best cell lines to utilize for ovarian cancer research on certain subtypes and platinum response studies, as well as sparks new hypotheses for future study in ovarian cancer.