Integrating gene expression, genomic, and phosphoproteomic data to infer transcription factor activity in lung cancer

Transcription factors (TFs) are key regulators of cellular gene expression programs in health and disease. Here we set out to integrate genomic, transcriptomic, and phosphoproteomic data to characterize TF activity in lung adenocarcinoma patients. Using expression data from patient samples and genomic information on TF binding to super-enhancers, starting from a list of 1667 human TFs we calculated a patient-specific activity score and identified 34 with perturbed activity in the cancer samples, as evidenced by the expression of their direct targets. We then leveraged phosphoproteomic data on the same samples to identify phosphorylation events that modulate TF activity. This novel data integration approach to TF characterization led to the identification of ERG as a key regulator in lung adenocarcinoma whose activity strongly correlates with patient survival.