Bioinformatics analysis to identify the key genes affecting the progression and prognosis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, which has poor outcome. This study aimed to investigate the key genes implicated in the progression and prognosis of HCC. The RNA-sequencing data of HCC was extracted from The Cancer Genome Atlas database. Using the R package (DESeq), the differentially expressed genes (DEGs) were analyzed. Based on the Cluepedia plug-in in Cytoscape software, enrichment analysis for the protein-coding genes among the DEGs was conducted. Subsequently, protein-protein interaction (PPI) network was built by Cytoscape software. Using survival package, the genes that could distinguish the survival differences of the HCC samples were explored. Moreover, quantitative real-time reverse transcription-PCR (qRT-PCR) experiments were used to detect the expression of key genes. There were 2193 DEGs in HCC samples. For the protein-coding genes among the DEGs, multiple functional terms and pathways were enriched. In the PPI network, cyclin-dependent kinase 1 (CDK1), polo-like kinase 1 (PLK1), Fos proto-oncogene, AP-1 transcription factor subunit (FOS), serum amyloid A1 (SAA1), and lysophosphatidic acid receptor 3 (LPAR3) were hub nodes. CDK1 interacting with PLK1 and FOS, and LPAR3 interacting with FOS and SAA1 were found in the PPI network. Among the 40 network modules, 4 modules were with scores no less than 10. Survival analysis showed that AGR2  and RLN3  could differentiate the high and low risk groups, which were confirmed by qRT-PCR. CDK1 , PLK1 , FOS , SAA1 , and LPAR3  might be key genes affecting the progression of HCC. Besides, AGR2  and RLN3  might be implicated in the prognosis of HCC.