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Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis
Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and reve...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689388/ https://www.ncbi.nlm.nih.gov/pubmed/31410310 http://dx.doi.org/10.7717/peerj.7436 |
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author | Liu, Ze-Kun Zhang, Ren-Yu Yong, Yu-Le Zhang, Zhi-Yun Li, Can Chen, Zhi-Nan Bian, Huijie |
author_facet | Liu, Ze-Kun Zhang, Ren-Yu Yong, Yu-Le Zhang, Zhi-Yun Li, Can Chen, Zhi-Nan Bian, Huijie |
author_sort | Liu, Ze-Kun |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and revealed potential molecular mechanisms. Here, we reported the gene expression profile GSE121248 findings from 70 HCC and 37 adjacent normal tissues, all of which had chronic hepatitis B virus (HBV) infection, we were seeking to identify the dysregulated pathways, crucial genes and therapeutic targets implicated in HBV-associated HCC. We found 164 differentially expressed genes (DEGs) (92 downregulated genes and 72 upregulated genes). Gene ontology (GO) analysis of DEGs revealed significant functional enrichment of mitotic nuclear division, cell division, and the epoxygenase P450 pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were mainly enriched in metabolism, cell cycle regulation and the p53 signaling pathway. The Mcode plugin was calculated to construct a module complex of DEGs, and the module was mainly enriched in cell cycle checkpoints, RHO GTPase effectors and cytochrome P450. Considering a weak contribution of each gene, gene set enrichment analysis (GSEA) was performed, revealing results consistent with those described above. Six crucial proteins were selected based on the degree of centrality, including NDC80, ESR1, ZWINT, NCAPG, ENO3 and CENPF. Real-time quantitative PCR analysis validated the six crucial genes had the same expression trend as predicted. Furthermore, the methylation data of The Cancer Genome Atlas (TCGA) with HCC showed that mRNA expression of crucial genes was negatively correlated with methylation levels of their promoter region. The overall survival reflected that high expression of NDC80, CENPF, ZWINT, and NCAPG significantly predicted poor prognosis, whereas ESR1 high expression exhibited a favorable prognosis. The identification of the crucial genes and pathways would contribute to the development of novel molecular targets and biomarker-driven treatments for HCC. |
format | Online Article Text |
id | pubmed-6689388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-66893882019-08-13 Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis Liu, Ze-Kun Zhang, Ren-Yu Yong, Yu-Le Zhang, Zhi-Yun Li, Can Chen, Zhi-Nan Bian, Huijie PeerJ Bioinformatics Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant cancers with no effective targets and treatments. However, the molecular pathogenesis of HCC remains largely uncertain. The aims of our study were to find crucial genes involved in HCC through multidimensional methods and revealed potential molecular mechanisms. Here, we reported the gene expression profile GSE121248 findings from 70 HCC and 37 adjacent normal tissues, all of which had chronic hepatitis B virus (HBV) infection, we were seeking to identify the dysregulated pathways, crucial genes and therapeutic targets implicated in HBV-associated HCC. We found 164 differentially expressed genes (DEGs) (92 downregulated genes and 72 upregulated genes). Gene ontology (GO) analysis of DEGs revealed significant functional enrichment of mitotic nuclear division, cell division, and the epoxygenase P450 pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the DEGs were mainly enriched in metabolism, cell cycle regulation and the p53 signaling pathway. The Mcode plugin was calculated to construct a module complex of DEGs, and the module was mainly enriched in cell cycle checkpoints, RHO GTPase effectors and cytochrome P450. Considering a weak contribution of each gene, gene set enrichment analysis (GSEA) was performed, revealing results consistent with those described above. Six crucial proteins were selected based on the degree of centrality, including NDC80, ESR1, ZWINT, NCAPG, ENO3 and CENPF. Real-time quantitative PCR analysis validated the six crucial genes had the same expression trend as predicted. Furthermore, the methylation data of The Cancer Genome Atlas (TCGA) with HCC showed that mRNA expression of crucial genes was negatively correlated with methylation levels of their promoter region. The overall survival reflected that high expression of NDC80, CENPF, ZWINT, and NCAPG significantly predicted poor prognosis, whereas ESR1 high expression exhibited a favorable prognosis. The identification of the crucial genes and pathways would contribute to the development of novel molecular targets and biomarker-driven treatments for HCC. PeerJ Inc. 2019-08-08 /pmc/articles/PMC6689388/ /pubmed/31410310 http://dx.doi.org/10.7717/peerj.7436 Text en ©2019 Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Liu, Ze-Kun Zhang, Ren-Yu Yong, Yu-Le Zhang, Zhi-Yun Li, Can Chen, Zhi-Nan Bian, Huijie Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title | Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title_full | Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title_fullStr | Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title_full_unstemmed | Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title_short | Identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
title_sort | identification of crucial genes based on expression profiles of hepatocellular carcinomas by bioinformatics analysis |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6689388/ https://www.ncbi.nlm.nih.gov/pubmed/31410310 http://dx.doi.org/10.7717/peerj.7436 |
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