Identification of a 9-gene signature related to stemness for prognosis in hepatocellular carcinoma basing on weighted gene coexpression network analysis

Abstract

Background Cancer stem cells (CSCs) are heterogeneous with self-renewal and differentiation ability. The mRNA expression-based stemness index (mRNAsi) described the similarity between tumor cells and CSCs, which is positively associated with the poor prognosis of cancer patients. However, the key prognostic genes related to mRNAsi in hepatocellular carcinoma (HCC) remains unclear. Methods In this study, RNA sequencing (RNA-seq) data of 374 liver HCC (LIHC) and 50 normal liver tissue samples were downloaded from The Cancer Genome Atlas (TCGA) database, with the corresponding clinical phenotypes. Differential expression of genes between tumor and normal tissues were analyzed. Modules correlated to mRNAsi and hub genes were identified using the weighted gene coexpression network analysis (WGCNA) package. Then, the prognostic genes associated with mRNAsi were identified. The expressions of the prognostic genes in HCC tissues were achieved by the human protein atlas (HPA) database. Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the prognostic genes were performed. Finally, the correlations between hub genes and clinical characteristics, immune subtypes, and tumor microenvironment were analyzed. Results A total of 1146 downregulated genes and 5593 upregulated genes were identified in LIHC, compared with normal tissues. A 9-gene signature related to mRNAsi and HCC prognosis including PSMG3, SNRPD1, DTYMK, PIGU, NME1, TXNL4A, IPO4, PES1, and REXO4 was obtained and their expressions were confirmed by the HPA database. High expression of this signature indicates poor prognosis of HCC. Among them, DTYMK and NME1 enriched in pyrimidine metabolism, SNRPD1 and TXNL4A enriched in spliceosome and PIGU enriched in glycosyl phosphatidylinositol (GPI)-anchor biosynthesis pathways. PIGU was an independent prognostic factor of HCC, which was significantly associated with clinical characteristics. High expression of the 9-gene signature was negatively correlated with the stromal cell infiltration, and positively correlated with specific immune subtypes-related to angiogenesis, M1/M2 macrophage polarization, and M2 response. Conclusion A 9-gene signature related to mRNAsi and poor prognosis in HCC were identified, which can be used as biomarkers for the diagnosis of HCC and functional mechanism exploration of CSCs in HCC.