Quantification and Analysis of Combination Drug Synergy in High-Throughput Transcriptome Studies

Abstract

We present an integrated experimental and computational approach designed to identify the key cellular components that either contribute to or drive therapeutic synergy of drug combinations with anticancer activity. The approach includes (i) quantification of drug synergy in high throughput transcriptome experiments, (ii) data-driven reverse engineering and forward simulation technology to develop an in silico model predictive of drug synergy, and (iii) utilization of databases of interaction and functional information in hypothesis generation that are validated experimentally in a final step (iv). The goal is to develop an integrated framework that aids in understanding the mechanistic details of drug synergy to design better combination drugs. We illustrate this approach with an application to the analysis of transcriptome changes in cells exposed to the synergistic anticancer drug combination of farnesyl transferase inhibitors (FTIs) combined with taxanes.