Integrative analysis of KEAP1/NFE2L2 alterations across 3600+ tumors reveals an NRF2 expression signature as a prognostic biomarker in cancer.

Non-small cell lung cancer (NSCLC) remains a formidable global health challenge, with heterogeneous molecular characteristics influencing prognosis and treatment response. We present a novel computational framework named ASTUTE (Association of SomaTic mUtaTions to gene Expression profiles), designed to perform genotype-phenotype mapping through the integration of genomic and transcriptomic data. Through the systematic analysis of over 3600 samples from diverse NSCLC datasets and multiple cancer types, we uncovered intricate associations between KEAP1/NFE2L2 mutations and the NRF2 pathway activation. Our study identified novel NRF2-related functionalities associated with specific genetic alterations and revealed a KEAP1/NFE2L2 expression signature predictive of prognosis across different cancer types. These findings enhance our understanding of cancer pathogenesis and drug resistance mechanisms mediated by NRF2 activation, paving the way for tailored therapeutic interventions and the development of prognostic biomarkers. Our approach exemplifies the power of integrating genomic and transcriptomic data to elucidate cancer mechanisms, thereby advancing the field of precision oncology.