[GNB2L1 gene expression and clinical value in hepatocellular carcinoma based on bioinformatics]

Objective: To analyze guanine nucleotide-binding protein subunit beta-2-like 1 (GNB2L1) expression based on bioinformatics, so as to evaluate its role and its relationship with survival rate during the occurrence and development of hepatocellular carcinoma. Methods: GEPIA, UALCAN and HPA databases were used to analyze the expression level of GNB2L1 and its relationship with HCC survival rate. Mutations in the GNB2L1 gene and their impact on survival were analyzed using the cBioPortal database. LinkedOmics database was used to analyze GNB2L1-related genes in HCC. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed simultaneously. STEING database was used to construct the GNB2L1 protein interaction network. TIMER database was used to analyze the relationship between GNB2L1 gene expression and immune infiltration in hepatocellular carcinoma. Differential expression of GNB2L1 in plasma platelets of HCC patients and healthy controls was analyzed using mRNA-based sequencing technology. Data between groups were compared using an independent-samples t-test. Results: GNB2L1 expression level was significantly increased in HCC tissues (P<0.05), and its expression was significantly correlated with body weight, classification and stage (P<0.05). The overall survival rate was higher in GNB2L1 low expression group (P<0.001). GNB2L1 and its related genes were related to biological process regulation, metabolic process, protein binding, oxidative phosphorylation, JAK-STAT signaling pathway, Ras signaling pathway and so on. GNB2L1 had interaction with RPS12, RPS11 and RPL19, and participated in multiple biological processes such as liver regeneration and positive regulation of endogenous apoptotic signaling pathway. GNB2L1 expression was significantly positively correlated with the infiltration degree of various immune cells in HCC (P<0.05). Cox regression analysis showed that GNB2L1 was an independent risk factor for lower survival rate in patients with HCC [Hazard ratio (95% confidence interval)=1.456 (1.034~2.051), P=0.031]. GNB2L1expression levels were significantly higher in platelets of HCC patients than that of healthy controls (10.40±1.36 vs. 9.58±0.51, t=2.194, P=0.037). Conclusion: GNB2L1 has high expression and close relationship to survival rate in HCC. Therefore, GNB2L1 may be a potential biomarker of HCC.