A novel gene signature based on Like-Smith family members-related genes for predicting the prognosis of hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related deaths globally. The Like-Smith (LSM) family members are involved in RNA metabolism and tumor progression, but their role in HCC remains unclear. This study aims to construct a novel signature based on LSM family members-related genes and explore its clinical value in HCC. Methods: Molecular patterns related to LSM family members were identified through clustering analysis. Differential expression analysis was used to identify genes with potential prognostic significance. Multivariate Cox regression analysis was performed to construct a signature with The Cancer Genome Atlas (TCGA) cohort. The International Cancer Genome Consortium (ICGC) cohort served as external validation. Kaplan-Meier curves and receiver operating characteristic (ROC) curves were used to evaluate the predictive ability. Enrichment analysis, immune infiltration assessment, and single-cell RNA sequencing (scRNA-seq) data analysis were conducted to explore the underlying mechanisms. Results: were highly expressed in hepatocytes. Conclusions: effectively predicts survival outcomes in HCC patients and is closely associated with tumor metabolism and immune regulation. This signature may serve as a valuable tool for prognostic evaluation and guiding personalized treatment strategies for HCC patients.