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ABSTRACT: Background
Hepatocellular carcinoma (HCC) remains one of the deadliest malignancies globally, posing substantial health threats and economic burdens. Despite advances in therapeutic modalities-including surgical resection, liver transplantation, and targeted therapies-HCC prognosis remains unsatisfactory. This highlights an urgent need for novel biomarkers to improve prognostic stratification. Senescence-related genes (SRGs) have emerged as promising candidates for HCC prognostic exploration, making their association with clinical outcomes the focus of this study..Methods
Comprehensive machine learning was applied to screen SRGs associated with HCC survival, identifying key prognostic genes. A clinical nomogram based on SRG scores was constructed and validated. NAP1L4 expr
SUBMITTER: Lin J
PROVIDER: S-EPMC12708435 | biostudies-literature | 2025 Nov
REPOSITORIES: biostudies-literature