Integrated Multi-Omics Analysis Reveals Synergistic Mechanisms of Chromosomal Instability and Immunosuppressive Microenvironment in Hepatocellular Carcinoma: A Prognostic Model and Therapeutic Implications Targeting RNF2

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors. However, current treatment regimens remain inadequate, and further investigation into its molecular mechanisms and therapeutic targets is warranted. In this study, we employed an integrated multi-omics analysis strategy to compare gene expression profiles between tumor tissues and adjacent non-tumor tissues from HCC patients using data from the GEO database, aiming to identify differentially expressed genes (DEGs). Functional enrichment analysis indicated that up-regulated genes were significantly enriched in mitotic processes, particularly chromosome separation, while down-regulated genes were associated with immune response dysregulation. A three-gene prognostic model (RKMYT1/RNF2/HIST1HAJ), constructed using LASSO-Cox regression, demonstrated significant predictive efficacy in a cohort of 52 HCC patients. Additionally, external validation confirmed the robustness and rationality of this prognostic model. According to ssGSEA and ESTIMATE algorithms, the HCC microenvironment exhibited reduced infiltration of dendritic cells and other immune cells, along with aberrant neutrophil polarization. This study elucidates the synergistic mechanism underlying chromosomal dynamic abnormalities and an immunosuppressive microenvironment, proposing RNF2-mediated genomic instability as a potential therapeutic vulnerability, thereby providing novel biomarkers and potential combined therapeutic targets for precision therapy in HCC.