Machine learning-driven multi-omics integration uncovers a senescence associated molecular axis in HCC
Talaiti Tuergan·Tuerganaili Aji·Yierfan Yilihaer·Yingmei Shao·Tiemin Jiang·Bingwei Liu·Aimitaji Abulaiti
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,