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

## TL;DR

This study combines gene, genomic, and protein data to identify key transcription factors involved in lung cancer and their impact on patient survival.

## Contribution

A novel data integration approach to infer transcription factor activity in lung adenocarcinoma using multi-omics data.

## Key findings

- 34 transcription factors showed perturbed activity in lung cancer samples based on target gene expression.
- Phosphorylation events were linked to modulation of transcription factor activity.
- ERG was identified as a key regulator in lung adenocarcinoma with strong survival correlation.

## Abstract

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.