Genetic dependencies associated with transcription factor activities in human cancer cell lines

Abstract

Transcription factors (TFs) are key components of the aberrant transcriptional programs in cancer cells. In this study, we used TF activity (TFa), inferred from the downstream regulons as a potential biomarker to identify associated genetic vulnerabilities in cancer cells. Our linear model framework, integrating TFa and genome-wide CRISPR knockout datasets identified 1,770 candidate TFa-target pairs across different cancer types and assessed their survival impact in patient data. As a proof of concept, through inhibitor screens and genetic depletion assays in cell lines, we validated the dependency of cell lines on predicted targets linked to TEAD1, the most prominent TF from our analysis. Overall, these candidate pairs represent an attractive resource for early-stage targets and drug discovery programs in oncology.