Abstract
Abstract
Identification of biologically relevant molecular targets responding cooperatively to drug combinations is challenging, yet potentially useful in predicting clinical outcomes. We found that combining sirolimus (rapamycin), an inhibitor of mechanistic target of rapamycin (mTOR), with entinostat (MS-275), a selective class I histone deacytlase (HDAC) inhibitor, was synergistic in controlling 90% of tested cell lines derived from B cell malignancies, including multiple myeloma, mantle cell lymphoma, and murine plasmacytoma, in vitro, and effective in limiting xenograft growth in vivo. To understand the transcriptional underpinnings of the drug synergy, weighted gene co-expression analysis (WGCNA) was adapted to analyze gene expression profile data from cells treated with sirolimus and entinostat individually and in combination. WGCNA delineated the contribution of each inhibitor to the overall gene expression change of the combination by considering not only measures of fold-change and significance testing, but also the degree of gene expression interconnectedness. A co-expression network consisting of five gene modules was defined, where each module represents a unique transcriptional effect of the drug combination. In the next phase of analysis, each gene module was individually tested for functional and clinical enrichment. The module containing genes cooperatively affected by both compounds was highly enriched (p<0.001) for genes involved in cell cycle, immune recognition, and DNA damage/repair, which we have validated. Gene set enrichment analysis of each drug-induced gene expression module demonstrated that genes of all five modules were significantly enriched when healthy donors were compared to MM patients. Finally, interrogation of the cooperative drug signature in patient GEP datasets with survival annotation found it predictive of increased survival (p<0.01), thus linking the drug combination-induced transcriptional changes to predictions for enhanced survival. Thus, systems-level genomic approaches identified markers and a gene signature associated with drug combination activity, disease specificity, and clinical potential.
This proffered talk is also presented as Poster A16.
Citation Format: John Kyle Simmons, Beverly A. Mock, Aleksandra Michalowski, Jyoti Patel, Bih-Rong Wei, R. Mark Simpson, W. Michael Kuehl, Shuling Zhang, Ke Zhang, Ola Landgren. Sorger. A cooperative molecular response to combined mTOR/HDAC inhibition revealed by transcriptional co-expression analysis [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR6.