, , and Reflect the Prognosis of Hepatocellular Carcinoma, as Determined by Weighted Gene Coexpression Network Analysis.

BACKGROUND

Hepatocellular carcinoma (HCC) is characterized by increased mortality and poor prognosis. We aimed to identify potential prognostic markers by weighted gene coexpression network analysis (WGCNA), to assist clinical outcome prediction and improve treatment decisions for HCC patients.

METHODS

Prognosis-related gene modules were first established by WGCNA. Venn diagrams obtained intersection genes of module genes and differentially expressed genes. The Kaplan-Meier overall survival curves and disease-free survival curves of intersection genes were further analyzed on the Gene Expression Profiling Interactive Analysis website. Chi-square tests were performed to explore the associations between prognostic gene expressions and clinicopathological features.

RESULTS

, , and were identified as both prognosis-related genes and differentially expressed genes. (HR: 1.7, = 0.003) and (HR: 1.8, < 0.001) exhibited a significant difference between the high- and low-expression groups in the overall survival analysis, while (HR: 1.4, = 0.052) was not statistically significant. (HR: 1.5, = 0.006), (HR: 1.7, < 0.001), and (HR: 1.6, = 0.003) were all statistically significant in the disease-free survival analysis. All three genes were significantly associated with race and fetoprotein values ( < 0.05). expression was associated with tumor stage ( = 0.01), and expression was associated with new tumor events ( = 0.03).

CONCLUSION

Overexpression of , and are associated with poor prognosis, and these genes could serve as potential prognostic markers and therapeutic targets for HCC.