Multi-omics integrated analysis identifies key biomarkers for hepatocellular carcinoma

Due to the high malignancy of hepatocellular carcinoma and the fact that <20% of patients can be diagnosed in the early stages, the postoperative recurrence rate for advanced or metastatic liver cancer patients can reach up to 70%, with a 5-year survival rate of <10%. We attempt to explore new and effective biomarkers for hepatocellular carcinoma and analyze them in conjunction with multiple omics approaches. Therefore, in order to explore the key etiological factors of hepatocellular carcinoma and new treatment methods, we utilized various approaches, including transcriptome-wide association studies, summary data-based Mendelian randomization analysis, weighted correlation network analysis, machine learning, spatial transcriptomics, molecular docking, virtual screening, and phenome-wide association studies. We confirmed the heterogeneity of Cornichon Family Member 4 (CNIH4) in hepatocellular carcinoma and its relevance to the immune microenvironment, cancer-immunity cycle, and intratumoral infections. Additionally, we explored small-molecule compounds that can interact with CNIH4 and analyzed their potential side effects. We obtained the key biomarker of hepatocellular carcinoma-CNIH4 by combining conventional transcriptome analysis results with spatial transcriptome, intratumoral infection data, and immune microenvironment analysis. Although our results reveal novel insights into hepatocellular carcinoma pathogenesis, further validation with clinical samples is needed to strengthen the conclusions. We believe that CNIH4 may serve as a potential therapeutic target for hepatocellular carcinoma in the future.