Machine learning-driven multi-omics integration uncovers a senescence associated molecular axis in HCC

Background Hepatocellular carcinoma (HCC) exhibits profound molecular heterogeneity and aberrant cellular senescence. This study systematically dissects the senescence-associated molecular landscape to identify key regulators driving HCC progression and immune evasion. Methods Integrating multi-cohort transcriptomic datasets, we developed a robust prognostic signature using 101 machine-learning models, identifying prognostic signature. We employed preliminary proteomic, exploratory metabolomic,