Integrating transcription factor networks with chromatin accessibility as markers of survival outcome and drug response in triple-negative breast cancer

Here, we integrated transcriptional regulatory network inference with chromatin accessibility across a large-scale multi-system collection of primary tumors, patient-derived xenografts (PDXs) and model cell lines to quantify Transcription Factor (TF) activity and identified regulators that underpin TNBC identity.

This approach prioritized 94 high-confidence TNBC TFs whose activity scores capture inter-tumor heterogeneity and independently stratify patient outcome across clinical endpoints. Linking TF activity to pharmacogenomics drug sensitivity profiles identifies reproducible drug-TF associations across independent datasets, including NFE2L3 and CBFB activity as predictors of sensitivity to mTOR inhibition, which we validated in everolimus-treated TNBC PDX models.