Dataset Information

Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

ABSTRACT:

Background

It has been proposed that hepatitis delta virus (HDV) induces hepatic carcinogenesis by distinct molecular events compared with hepatocellular carcinoma (HCC) that is commonly induced by other hepatitis viruses. This study aimed to explore the underlying mechanism by identifying the key genes for HDV-HCC using bioinformatics analysis.

Methods

The GSE107170 dataset was downloaded and the differentially expressed genes (DEGs) were obtained by the online tool GEO2R. Gene otology (GO) functional analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R packages. The protein-protein interaction (PPI) network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Hub genes were selected by Cytoscape software according to degree algorithm. The hub genes were further validated in terms of expression and survival analysis based on public databases.

Results

A total of 93 commonly upregulated genes and 36 commonly downregulated genes were found. The top 5 upregulated hub genes were TFRC, ACTR2, ARPC1A, ARPC3, and ARPC2. The top 5 downregulated hub genes were CTNNB1, CCND1, CDKN1B, CDK4, and CDKN1A. In the validation analysis, the expressions of ARPC1A, ARPC3, and CDK4 were promoted in general liver cancer samples. Higher expressions of ARPC2 and CDK4 and lower expressions of CDKN1A, CCND1, and CDKN1B were associated with worse prognosis in general HCC patients.

Conclusion

The present study identifies a series of key genes that may be involved in the carcinogenesis of HDV-HCC and used as prognostic factors.

SUBMITTER: Zhang C

PROVIDER: S-EPMC8975377 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

Zhang Cheng C Wu Shan S Yang Xiao-Dong XD Xu Hui H Ma Tai T Zhu Qi-Xing QX

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology 20210201 2

<h4>Background</h4>It has been proposed that hepatitis delta virus (HDV) induces hepatic carcinogenesis by distinct molecular events compared with hepatocellular carcinoma (HCC) that is commonly induced by other hepatitis viruses. This study aimed to explore the underlying mechanism by identifying the key genes for HDV-HCC using bioinformatics analysis.<h4>Methods</h4>The GSE107170 dataset was downloaded and the differentially expressed genes (DEGs) were obtained by the online tool GEO2R. Gene o ...[more]

PMID: 33960941

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Project description:Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Project description:BackgroundThe majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.MethodsGSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.ResultsBy GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.ConclusionsFive abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

Dataset Information

Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

Background

Methods

Results

Conclusion

Publications

Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

Similar Datasets

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