<p>Hepatocellular carcinoma (HCC) is a prevalent and deadly malignancy, with a significant global impact. In this study, the role of circadian rhythm genes in HCC prognosis was investigated. Publicly available gene expression datasets from TCGA and GEO were analyzed to identify differentially expressed circadian genes. Weighted gene co-expression network analysis (WGCNA) was performed to construct circadian gene modules, which were then correlated with clinical traits. Unsupervised clustering identified two distinct HCC subtypes based on circadian gene expression profiles, with significant differences in overall survival. Functional enrichment analysis revealed that these subtypes are associated with distinct metabolic and immune-related pathways. A prognostic model was constructed using LASSO regression, incorporating key circadian genes that stratified patients into high- and low-risk groups. The model was validated in independent cohorts and demonstrated robust predictive power. Additionally, a nomogram integrating circadian gene expression with clinical factors was developed to enhance individualized prognostic predictions. Further validation of key genes, particularly GPT (glutamate pyruvate transaminase), highlighted its potential as a tumor suppressor and therapeutic target within HCC. Experimental validation using qRT-PCR and IHC confirmed elevated expression levels of GHR, IGFBP3, and GPT in tumor tissues, underscoring their clinical relevance and prognostic value. These findings underscore the importance of circadian rhythm disruptions in HCC progression and suggest potential therapeutic targets for improving patient outcomes.</p>