Hypoxia- and Anoikis-Related lncRNA Signature Defines Molecular Subtypes and Predicts Prognosis and Immunotherapy Response in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is characterized by high incidence and mortality rates, with hypoxia and anoikis resistance playing crucial roles in its progression and metastasis. While long non-coding RNA (lncRNA) significantly influence tumor biology, their roles in hypoxia-anoikis-resistant HCC remain unclear. Methods: This study utilized RNA-seq data and clinical information from the TCGA and GEO databases to analyze 154 hypoxia- and anoikis-related lncRNAs and identify differentially expressed candidates. Cluster analysis with Consensus Cluster Plus revealed links to clinical outcomes and genomic features. Tumor immune microenvironment and pathway enrichment were assessed using CIBERSORT and ssGSEA. A nine-gene risk model was developed via LASSO Cox regression and internally validated. Preliminary experimental assays suggested that the identified lncRNAs may influence apoptosis under hypoxia and anoikis conditions. Results: HCC patients were classified into two molecular subtypes, C1 and C2, with distinct prognostic outcomes and clinical features. These subtypes showed distinct immune infiltration characteristics and differential immunotherapy response scores. A nine-lncRNA prognostic model effectively predicted overall survival (OS), with the high-risk group showing increased immunosuppressive elements, such as Tregs and inactivated M0 macrophages, suggesting limited immunotherapy efficacy. Chemotherapy sensitivity analysis revealed varying drug responses between risk groups, while hypoxia- and anoikis-related lncRNAs, including LINC01554, FIRRE, LINC01139, LINC01134 and NBAT1 were downregulated in this model. Conclusion: Research has demonstrated that hypoxia- and anoikis-related lncRNAs serve as reliable biomarkers for predicting liver cancer prognosis and immunotherapy response, offering potential for developing novel therapeutic targets and strategies to enhance treatment outcomes and patient prognosis.