Characteristics of Mechanically Stimulated Genes in Hepatocellular Carcinoma and Their Role as Prognostic Markers

Background: Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor with poor prognosis and high heterogeneity. Mechanical stimuli in the tumor microenvironment (TME) regulate HCC cell biological behavior via mechanosensitive-related genes (MSRGs), but their specific prognostic value and underlying mechanisms remain unclear. Methods: RNA-seq and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) database (accession: TCGA-LIHC, https://portal.gdc.cancer.gov/), and single-cell RNA-seq datasets (accession: GSE149614) were obtained from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). Univariate Cox regression analysis was used to screen MSRGs associated with overall survival (OS). Consensus clustering was performed to identify HCC molecular subtypes based on OS-related MSRGs. LASSO-Cox regression analysis was applied to construct an MSRG-based prognostic risk model, which was validated by Kaplan-Meier survival analysis and time-dependent ROC curves. Functional enrichment analysis, immune microenvironment characterization, genomic variation analysis and drug sensitivity prediction were conducted to explore the biological significance of the risk model. Single-cell RNA-seq analysis was used to map the risk signature to specific cell types, and SHAP analysis combined with in vitro experiments was performed to validate the key driver gene. Results: A total of 39 OS-related MSRGs were identified in HCC, and HCC samples were stratified into two molecular subtypes with distinct prognostic and immune microenvironment characteristics. A six-gene prognostic risk model (HPN, ENDOG, UCN, FYN, ETV1, KCNQ3) was constructed, which exhibited good prognostic discrimination (1-, 3-, 5-year AUC: 0.74, 0.74, 0.73). High-risk patients had shorter OS, a more immunosuppressive TME, and distinct genomic alteration patterns compared with low-risk patients. The two risk groups showed differential sensitivity to clinical targeted drugs (Axitinib, Erlotinib, Sorafenib, Sunitinib). Single-cell analysis revealed cell-type specificity of the risk signature, and KCNQ3 was identified as the key driver gene via SHAP analysis. In vitro experiments confirmed that KCNQ3 Knockdown significantly inhibited the proliferation and clonogenic ability of HCC Huh7 cells. Conclusion: MSRGs are closely associated with the prognosis and immune microenvironment of HCC. The constructed MSRG-based prognostic risk model has reliable predictive value for HCC patient survival, and KCNQ3 may serve as a potential prognostic biomarker and therapeutic target for HCC, providing new insights for personalized treatment of HCC.