Abstract 5371: Drug repositioning with a bioinformatics platform that integrates the TCGA, cMap and CCLE

Abstract

Abstract Cancer In silico Drug Discovery Tools (CIDD) is a drug discovery platform that enables researchers to generate hypotheses for the following three general problems: 1) to determine if clinical phenotypes or gene mutations for a cancer are functional, inducing unique gene expression alterations, 2) to find candidate drugs to treat, or repress, these expression changes, and 3) to identify cell lines that resemble the tumors being studied for subsequent in vitro experimentation. CIDD integrates clinical and experimental data from The Cancer Genome Atlas (TCGA), the Connectivity Map (cMap) and the Cancer Cell Line Encyclopedia (CCLE) to perform in silico drug discovery experiments. CIDD generates gene expression signatures representative of the phenotypes or mutations being studied, characterizes the signatures using MSigDB, identifies candidate drugs to repress these signatures using data from the cMap, and finds optimal cell lines for in vitro drug testing using experimental data from the CCLE. The primary results of a CIDD execution are a biologically interpretable candidate drug list and a list of cell lines for subsequent drug experimentation. We applied CIDD for the identification of candidate drugs to treat BRAF V600E colorectal cancer (CRC). CIDD identified EGFR and proteasome inhibitors as candidate drugs, while proposing 7 large intestine cell lines from the CCLE for potential in vitro testing. CIDD is a command-line based tool written in Python and depends on R. We have developed a companion Python-based data management utility, tcga_util, which provides automated downloading and querying of TCGA data from the command-line, which we feel will be of substantial and independent interest to researchers wishing to use data from the TCGA. CIDD and tcga_util are available for download at http://scheet.org/software. Citation Format: Francis A. San Lucas, Jerry Fowler, Scott Kopetz, Eduardo Vilar, Paul Scheet. Drug repositioning with a bioinformatics platform that integrates the TCGA, cMap and CCLE. [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 5371. doi:10.1158/1538-7445.AM2014-5371