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

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous breast cancer subtype with few effective targeted therapies and frequent resistance to chemotherapy. 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. Collectively, we establish a transcriptional and chromatin-informed framework to capture TNBC regulatory state and expand TF-guided precision medicine to this breast cancer subtype.