Identifying the Drivers and Targeting Chemo Resistance in Ovarian Cancer

Ovarian cancer is the most lethal gynecological malignancy. Although majority of the cancer cases are initially sensitive to platinum-based chemotherapy, most patients eventually develop recurrence and succumb to chemoresistant disease. Our lack of understanding of the key drivers that lead to the resistant state poses a critical roadblock that impedes therapeutic progress in the field. The long-term goal of our research is to understand the chromatin and transcriptional regulatory networks that allow cells to adapt to new environmental or developmental cues. The overall objective of this study, which is the next step toward attainment of our long-term goal, is to identify the major regulatory networks that allow ovarian cancer cells to survive chemotherapy. This knowledge will identify improved and effective therapeutics options. To achieve this, we started with epigenome mapping and transcriptome analysis of an in vitro system in which we employed chemonaïve, chemoresistant, and resensitized isogenic cells. Integrative analysis of expression profiles (RNA-Seq) and epigenomic features of promoter and enhancer elements (H3K27ac ChIP-Seq), identified large number of typical enhancers and a subset of “super enhancers” that are specifically activated in resistant cells. Notably, pharmacological disruption of super enhancers by a small molecule epigenetic inhibitor confers cisplatin sensitivity to previously resistant cells in vitro and inhibits in vivo tumor growth in a xenograft model of resistant cells. Super enhancers tend to regulate the expression of master regulators of a given cellular state (1, 2). Among the top target genes of the resistant specific super enhancers (RSSE) were multiple transcription factors, whose depletion with CRISPR mediated knock significantly sensitized the resistant cells to chemotherapy. These preliminary data led to the central hypothesis that aberrant transcriptional program in chemoresistant cells is driven by a set of genes who