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Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis

The molecular mechanisms underlying hepatocellular carcinoma (HCC) progression remain largely undefined. Here, we identified 176 commonly upregulated genes in HCC tissues based on three Gene Expression Omnibus datasets and The Cancer Genome Atlas (TCGA) cohort. We integrated survival and methylation...

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Autores principales: Hua, Shengni, Ji, Zhonghua, Quan, Yingyao, Zhan, Meixiao, Wang, Hao, Li, Wei, Li, Yong, He, Xu, Lu, Ligong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138582/
https://www.ncbi.nlm.nih.gov/pubmed/32213663
http://dx.doi.org/10.18632/aging.102969
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author Hua, Shengni
Ji, Zhonghua
Quan, Yingyao
Zhan, Meixiao
Wang, Hao
Li, Wei
Li, Yong
He, Xu
Lu, Ligong
author_facet Hua, Shengni
Ji, Zhonghua
Quan, Yingyao
Zhan, Meixiao
Wang, Hao
Li, Wei
Li, Yong
He, Xu
Lu, Ligong
author_sort Hua, Shengni
collection PubMed
description The molecular mechanisms underlying hepatocellular carcinoma (HCC) progression remain largely undefined. Here, we identified 176 commonly upregulated genes in HCC tissues based on three Gene Expression Omnibus datasets and The Cancer Genome Atlas (TCGA) cohort. We integrated survival and methylation analyses to further obtain 12 upregulated genes for validation. These genes were overexpressed in HCC tissues at the transcription and protein levels, and increased mRNA levels were related to higher tumor grades and cancer stages. The expression of all markers was negatively associated with overall and disease-free survival in HCC patients. Most of these hub genes can promote HCC proliferation and/or metastasis. These 12 hub genes were also overexpressed and had strong prognostic value in many other cancer types. Methylation and gene copy number analyses indicated that the upregulation of these hub genes was probably due to hypomethylation or increased gene copy numbers. Further, the methylation levels of three genes, KPNA2, MCM3, and LRRC1, were associated with HCC clinical features. Moreover, the levels of most hub genes were related to immune cell infiltration in HCC microenvironments. Finally, we identified three upregulated genes (KPNA2, TARBP1, and RNASEH2A) that could comprehensively and accurately provide diagnostic and prognostic value for HCC patients.
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spelling pubmed-71385822020-04-13 Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis Hua, Shengni Ji, Zhonghua Quan, Yingyao Zhan, Meixiao Wang, Hao Li, Wei Li, Yong He, Xu Lu, Ligong Aging (Albany NY) Research Paper The molecular mechanisms underlying hepatocellular carcinoma (HCC) progression remain largely undefined. Here, we identified 176 commonly upregulated genes in HCC tissues based on three Gene Expression Omnibus datasets and The Cancer Genome Atlas (TCGA) cohort. We integrated survival and methylation analyses to further obtain 12 upregulated genes for validation. These genes were overexpressed in HCC tissues at the transcription and protein levels, and increased mRNA levels were related to higher tumor grades and cancer stages. The expression of all markers was negatively associated with overall and disease-free survival in HCC patients. Most of these hub genes can promote HCC proliferation and/or metastasis. These 12 hub genes were also overexpressed and had strong prognostic value in many other cancer types. Methylation and gene copy number analyses indicated that the upregulation of these hub genes was probably due to hypomethylation or increased gene copy numbers. Further, the methylation levels of three genes, KPNA2, MCM3, and LRRC1, were associated with HCC clinical features. Moreover, the levels of most hub genes were related to immune cell infiltration in HCC microenvironments. Finally, we identified three upregulated genes (KPNA2, TARBP1, and RNASEH2A) that could comprehensively and accurately provide diagnostic and prognostic value for HCC patients. Impact Journals 2020-03-26 /pmc/articles/PMC7138582/ /pubmed/32213663 http://dx.doi.org/10.18632/aging.102969 Text en Copyright © 2020 Hua et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Hua, Shengni
Ji, Zhonghua
Quan, Yingyao
Zhan, Meixiao
Wang, Hao
Li, Wei
Li, Yong
He, Xu
Lu, Ligong
Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title_full Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title_fullStr Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title_full_unstemmed Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title_short Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
title_sort identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138582/
https://www.ncbi.nlm.nih.gov/pubmed/32213663
http://dx.doi.org/10.18632/aging.102969
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