<p>Bioinformatics analysis of molecular genetic targets and key pathways for hepatocellular carcinoma</p>

Abstract

Background Hepatocellular carcinoma (HCC) is the second leading cause of death among cancers worldwide. In this study, we aimed to identify the molecular target genes and detect the key mechanisms of HCC. Three gene expression profiles (GSE84006, GSE14323, GSE14811) and two miRNA expression profiles (GSE40744, GSE36915) were analyzed to determine the molecular target genes, microRNAs (miRNAs) and the potential molecular mechanisms in HCC. Methods All profiles were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs) was analyzed by the GEO2R method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment analysis performed database for Integrated Discovery, Visualization and Annotation. The miRNA-gene network and protein–protein interaction (PPI) network were correlated by the Cytoscape software. The key target genes were identified by the CytoHubba plugin, Molecular Complex Detection (MCODE) plugin and miRNA-gene network. The identified hub genes were testified for survival curve using the Kaplan–Meier plotter database. Results Expression profiles had 592 overlapped DEGs. The majority of the DEGs were enriched in membrane-bounded organelles and intracellular membrane-bounded organelles. These DEGs were significantly enriched in metabolic, protein processing in the endoplasmic reticulum and thyroid cancer pathways. PPI network analysis showed these genes were mostly involved in the pathogenic Escherichia coli infection and the regulation of actin cytoskeleton pathways. Combining these results, we identified 10 key genes involving in the progression of HCC. Finally, PLK1 , PRCC , PRPF4 and PSMA7 exhibited higher expression levels in HCC patients with poor prognosis than those for lower expression via Kaplan–Meier plotter database. Conclusion PLK1 , PRCC , PRPF4 and PSMA7 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, protein processing in the endoplasmic reticulum and the thyroid cancer pathway may play vital roles in the progression of HCC.

Construction of a potential microRNA, transcription factor and mRNA regulatory network in hepatocellular carcinoma

“…For example, miR-424 can bind CDK1 and reduce translation, activate the Hippo pathway and extracellular signaling-mediated kinase pathway, and inhibit the proliferation of breast cancer cells (41). Xie et al (41) and Tu et al (12). identified potentially valuable miRNAs using different datasets.…”

Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma

“…In addition, there are studies reporting splicing signatures associated with the prognosis of esophageal cancer ( Lin et al., 2018 ; Mao et al., 2019 ). Through the splicing mechanism, PRPF4, SRSF1, and HNRNPM regulate the cell proliferation, migration, and invasion in different cancers, including lung cancer ( Choi, 2012 ; Chang and Lin, 2019 ), breast cancer ( Anczuków et al., 2015 ; Sun et al., 2017 ; Park et al., 2019 ), cutaneous squamous cell carcinoma ( Zhang et al., 2018 ), hepatocellular carcinoma ( Tu et al., 2019 ), esophagus dysplasia ( Varghese et al., 2015 ; Fitzgerald et al., 2018 ), gastric cancer ( Wu et al., 2019 ), cervical cancer ( Dong et al., 2019 ), and Ewing's sarcoma ( Passacantilli et al., 2017 ).…”

N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

“…U1snRNP is reported to suppress the migration and invasion of multiple types of tumor cells [ 36 ]. Additionally, genes of the snRNP polypeptide family also exert an important role in the tumorigenesis and prognosis of cancers [ 37 , 38 ]. For example, the high expression of snRNP polypeptide G, which is another indispensable component in the formation of snRNPs, is positively associated with the occurrence, progression and severity of breast, lung, and colon cancers [ 39 – 41 ].…”