Predicting master transcription factors from pan-cancer expression data
Critical developmental “master transcription factors” (MTFs) can be subverted during tumorigenesis to control expression of oncogenic transcriptional programs. Current approaches to identify MTFs rely on chromatin immunoprecipitation-sequencing data, which is currently unavailable for many cancer types. We developed the CaCTS (Cancer Core Transcription factor Specificity) algorithm to prioritize candidate MTFs using pan-cancer RNA-sequencing data. CaCTS identified candidate MTFs across 34 tumor types and 140 subtypes, including known MTFs. We also made novel predictions, including for cancer types/subtypes for which MTFs are unknown. This included PAX8, SOX17, and MECOM as candidate MTFs in ovarian cancer (OV). In OV cells, these factors are required for viability, lie proximal to super-enhancers, co-occupy regulatory elements globally and co-bind at critical gene loci encoding OV biomarkers. Identification of tumor MTFs, especially for tumor types with limited understanding of transcriptional drivers, paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers. Overall design: ChIP-Seq of H3K27ac and master transcription factors in ovarian cancer patient samples and cell lines