Exploration of the relationship between apoptosis related characteristic genes and the prognosis of HCC.

The acquisition of resistance to anoikis is a critical driver of metastasis in various tumor types. However, the combined role of anoikis apoptosis in the progression and prognosis of hepatocellular carcinoma (HCC) remains largely unexplored. This study integrates known anoikis genes with single-cell datasets to identify differentially expressed Anoikis (DE-Anoikis) through unsupervised clustering, enabling the classification of samples from The Cancer Genome Atlas (TCGA). A prognostic risk model was constructed using univariate Cox proportional hazards regression and validated with external datasets from the International Cancer Genome Consortium (ICGC) and the Gene Expression Omnibus (GEO). The results revealed significant prognostic differences among DE-Anoikis-based HCC molecular subtypes, with functional enrichment analyses highlighting metabolic reprogramming differences. Furthermore, the anoikis-related prognostic model demonstrated robust predictive accuracy across multiple validation datasets. Two potential therapeutic drugs exhibited sensitivity in low-risk patients, offering novel insights into HCC treatment. Overall, this study identifies a unique subgroup of apoptosis-associated HCC and a prognostic model, providing further biological insights into the molecular mechanisms and therapeutic strategies for HCC.