Identification of anoikis-related subtypes in hepatocellular carcinoma and construction of prognostic model: Construction of prognostic model

This study aimed to investigate the distinct subtypes of anoikis in hepatocellular carcinoma (HCC) and their underlying molecular mechanisms, and to construct a prognostic risk model. The gene expression profiles of HCC were downloaded from the cancer genome atlas and gene expression omnibus database, while anoikis-related genes were obtained from the GeneCards database. Unsupervised clustering algorithms were applied based on the expression of differentially expressed anoikis genes to identify related subtypes. Survival curves were used to analyze the differences in survival between subtypes, and the enrichment pathways and immune microenvironment differences were explored. Limma analysis, Cox proportional hazards regression analysis, and Least absolute shrinkage and selection operator regression algorithms were utilized to identify genes affecting the prognosis of subtypes and to construct a prognostic model, while also classifying high and low-risk groups for immune correlation analysis. The study identified 2 subtypes, C1 and C2, which showed significant differences in survival probability, enriched pathways, and immune microenvironment. SFN, BUB1, BSG, and HMOX1 were identified as prognostic genes, and a prognostic model was successfully constructed. There were significant differences in prognosis, expression of prognostic genes, and immune microenvironment between the high-risk and low-risk groups. The identification of different subtypes of anoikis in HCC and the construction of a prognostic model provide new insights and directions for the treatment and prognosis research of HCC.