Comprehensive analysis of GSEC/miR-101-3p/SNX16/PAPOLG axis in hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies. A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during HCC process. The present study aimed to identify a regulatory axis of the ceRNA network associated with the development of HCC. The roles of SNX16 and PAPOLG in HCC were comprehensively analyzed using bioinformatics tools. Subsequently, the “mRNA-miRNA-lncRNA” model was then used to predict the upstream miRNAs and lncRNAs of SNX16 and PAPOLG using the miRNet database, and the miRNAs with low expression and good prognosis in HCC and the lncRNAs with high expression and poor prognosis in HCC were screened by differential expression and survival analysis. Finally, the risk-prognosis models of ceRNA network axes were constructed by univariate and multifactorial Cox proportional risk analysis, and the immune correlations of ceRNA network axes were analyzed using the TIMER and GEPIA database. In this study, the relevant ceRNA network axis GSEC/miR-101-3p/SNX16/PAPOLG with HCC prognosis was constructed, in which GSEC, SNX16, and PAPOLG were highly expressed in HCC with poor prognosis, while miR-101-3p was lowly expressed in HCC with good prognosis. The risk-prognosis model predicted AUC of 0.691, 0.623, and 0.626 for patient survival at 1, 3, and 5 years, respectively. Immuno-infiltration analysis suggested that the GSEC/miR-101-3p/SNX16/PAPOLG axis might affect macrophage polarization. The GSEC/miR-101-3p/SNX16/PAPOLG axis of the ceRNA network axis might be an important factor associated with HCC prognosis and immune infiltration.