Innovative Insights into Liver Cancer: Multi-Omics Reveals CriticalSubtypes and Hub Genes

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous malignant tumor characterized by elevated mortality rates and poor diagnostic outcomes. Objective: Accurate identification of cancer subtypes is crucial for guiding personalized treatment and improving patient prognosis. Methods: We present a method for precisely identifying HCC subtypes by integrating multi-omics data. By integrating the GRACES dimensionality reduction and hMKL subtype identification models to analyze 266 HCC patients, we more accurately identified two subtypes significantly associated with overall survival. Results: Our findings indicate that the mortality rates for the high-risk liver cancer subtype and the low-risk liver cancer subtype were 55.9% and 27.9%, respectively, over a three-year period. Pathway activity analysis revealed significant differences in the activity of five pathways between the two subtypes. Additionally, immunocell infiltration analysis demonstrated notable variations in the abundance and status of seven types of immune cells across the subtypes. Further exploration of protein- protein interaction (PPI) networks and centrality indicators led to the identification of 13 upregulated and 14 down-regulated hub genes. Conclusion: There is limited research on ENPP3 (up-regulated) and C3 (down-regulated) in the context of HCC, suggesting their potential as biomarkers. Additionally, low expression levels of PIK3R1, KDR, and CYP3A5, along with high expression levels of EGLN3 and EPO, may indicate a higher risk of liver cancer in patients. Single-gene survival analysis highlighted the significant impact of highly expressed genes on HCC prognosis, with PKM, RRM2, and EPO in the risk score playing crucial roles. conclusion: There is limited research on ENPP3 (up-regulated) and C3 (down-regulated) in the context of HCC, suggesting their potential as biomarkers. Additionally, low expression levels of PIK3R1, KDR, and CYP3A5, along with high expression levels of EGLN3 and EPO, may indicate a higher risk of liver cancer in patients. Single-gene survival analysis highlighted the significant impact of highly expressed genes on HCC prognosis, with PKM, RRM2, and EPO in the risk score playing crucial roles.