Abstract

Abstract There is an urgent need to develop better understanding of the drug responsivenes in ovarian cancer (OC), particularly in the clear cell and mucinous subtypes, which tend to be resistant to the commonly used platinum-based regimens. This would help to improve survival and facilitate precision medicine approaches to therapy. In order to discover previously unsuspected anti-cancer effects with approved and emerging drugs, we applied Drug Sensitivity and Resistance Testing (DSRT) technology (Pemovska et al., Cancer Discovery, 2013) to determine detailed dose-response effects of 300 drugs in 25 established OC cell lines (10 serous, 10 clear cell and 5 mucinous ovarian cancer cell lines). The panel covered 160 approved drugs as well as 162 emerging, investigational and pre-clinical oncology compounds such as kinase and non-kinase inhibitors. All drugs were tested in 5 different concentrations covering a 10,000-fold concentration range using Labcyte nano-dispensing technology, in order to generate detailed dose-response curves for each drug in each cell line. The area under the curve was estimated from the dose-response curve to obtain the drug sensitivity score. Bioinformatic processing of the drug response data from OC cell lines resulted in several key observations. First, the DSRT data made it possible to classify OC cell lines into four functional taxonomic subtypes based on comprehensive drug responses. Interestingly, these clusters did not depend on the histological origin of the OC cell lines. Second, the 322 drugs were clustered into functional subsets based on the response data across the 25 OC cell lines. Most of this clustering followed the expected chemical similarity and target space of the drugs, such as topoisomerase II inhibitors, MEK inhibitors, mTOR inhibitors and Taxanes each clustering in their own subgroups. Third, we found that many emerging, currently not-yet-approved drugs were active in subgroups of OC cell lines, including both kinase as well as non-kinase drugs, such as HDAC inhibitors Entinostat and Belinostat. DSRT technology provides a powerful strategy for assessing drug response in OC cell models, and it could also help to asses drug responses in patient-derived ex vivo model systems of OC. Analysis of correlations of DSRT data with genomic data of the cell lines is underway and will yield new translational and pharmacogenomic opportunities for OC. Citation Format: Akira Hirasawa, Astrid Murumägi, Mariliina Arjama, Bhagwan Yadav, John Patrick Mpindi, Krister Wennerberg, Tero Aittokallio, Daisuke Aoki, Olli Kallioniemi. Systematic high-throughput drug sensitivity and resistance testing (DSRT) of ovarian cancer cell lines indicates novel therapeutic possibilities with existing and emerging drugs. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5384. doi:10.1158/1538-7445.AM2014-5384

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