Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide. In this study, we aimed to explore the potential biomarkers and key regulatory pathways related to HCC using integrated bioinformatic analysis and validation. The microarray data of GSE12717 and GSE54238 were downloaded from the Gene Expression Omnibus database. A competing endogenous RNA (ceRNA) network was constructed based on potential long-noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA interactions. A total of 191 mRNAs, 8 miRNAs, and 5 lncRNAs were selected to construct the ceRNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to predict their biological functions. The PI3K-Akt signaling pathway was significantly enriched. Kaplan-Meier survival analysis based on the Gene Expression Profiling Interactive Analysis (GEPIA) database was conducted for the weighted mRNAs and lncRNAs. The results showed that SRC, GMPS, CDK2, FEN1, EZH2, ZWINT, MTHFD1L, GINS2, and MAPKAPK5-AS1 were significantly upregulated in tumor tissues. The relative expression levels of these genes were significantly upregulated in HCC patients based on the StarBase database. For further validation, the expression levels of these genes were detected by real-time quantitative reverse transcription-polymerase chain reaction in 20 HCC tumor tissues and paired paracancerous tissues. Receiver operating characteristic analysis revealed that CDK2, MTHFD1L, SRC, ZWINT, and MAPKAPK5-AS1 had significant diagnostic value in HCC, but further studies are needed to explore their mechanisms in HCC.
Keywords: bioinformatic analysis; hepatocellular carcinoma; network; noncoding RNA; survival analysis.