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Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis
The antiviral treatment efficacy varies among chronic hepatitis B (CHB) patients and the underlying mechanism is unclear. An integrated bioinformatics analysis was performed to investigate the host factors that affect the therapeutic responsiveness in CHB patients. Four GEO data sets (GSE54747, GSE2...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278120/ https://www.ncbi.nlm.nih.gov/pubmed/34041839 http://dx.doi.org/10.1111/jcmm.16655 |
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author | He, Yi Zhou, Yingzhi Wang, Huimin Yin, Jingyang Chang, Yunan Hu, Peng Ren, Hong Xu, Hongmei |
author_facet | He, Yi Zhou, Yingzhi Wang, Huimin Yin, Jingyang Chang, Yunan Hu, Peng Ren, Hong Xu, Hongmei |
author_sort | He, Yi |
collection | PubMed |
description | The antiviral treatment efficacy varies among chronic hepatitis B (CHB) patients and the underlying mechanism is unclear. An integrated bioinformatics analysis was performed to investigate the host factors that affect the therapeutic responsiveness in CHB patients. Four GEO data sets (GSE54747, GSE27555, GSE66698 and GSE66699) were downloaded from the Gene Expression Omnibus (GEO) database and analysed to identify differentially expressed genes(DEGs). Enrichment analyses of the DEGs were conducted using the DAVID database. Immune cell infiltration characteristics were analysed by CIBERSORT. Upstream miRNAs and lncRNAs of hub DEGs were identified by miRWalk 3.0 and miRNet in combination with the MNDR platform. As a result, seventy‐seven overlapping DEGs and 15 hub genes were identified including CCL5, CXCL9, MYH2, CXCR4, CD74, CCL4, HLA‐DRB1, ACTA1, CD69, CXCL10, HLA‐DRB5, HLA‐DQB1, CXCL13, STAT1 and CKM. The enrichment analyses revealed that the DEGs were mainly enriched in immune response and chemokine signalling pathways. Investigation of immune cell infiltration in liver samples suggested significantly different infiltration between responders and non‐responders, mainly characterized by higher proportions of CD8+ T cells and activated NK cells in non‐responders. The prediction of upstream miRNAs and lncRNAs led to the identification of a potential mRNA‐miRNA‐lncRNA regulatory network composed of 2 lncRNAs (H19 and GAS5) and 5 miRNAs (hsa‐mir‐106b‐5p, hsa‐mir‐17‐5p, hsa‐mir‐20a‐5p, hsa‐mir‐6720‐5p and hsa‐mir‐93‐5p) targeting CCL5 mRNA. In conclusion, our study suggested that host genetic factors could affect therapeutic responsiveness in CHB patients. The antiviral process might be associated with the chemokine‐mediated immune response and immune cell infiltration in the liver microenvironment. |
format | Online Article Text |
id | pubmed-8278120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82781202021-07-15 Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis He, Yi Zhou, Yingzhi Wang, Huimin Yin, Jingyang Chang, Yunan Hu, Peng Ren, Hong Xu, Hongmei J Cell Mol Med Original Articles The antiviral treatment efficacy varies among chronic hepatitis B (CHB) patients and the underlying mechanism is unclear. An integrated bioinformatics analysis was performed to investigate the host factors that affect the therapeutic responsiveness in CHB patients. Four GEO data sets (GSE54747, GSE27555, GSE66698 and GSE66699) were downloaded from the Gene Expression Omnibus (GEO) database and analysed to identify differentially expressed genes(DEGs). Enrichment analyses of the DEGs were conducted using the DAVID database. Immune cell infiltration characteristics were analysed by CIBERSORT. Upstream miRNAs and lncRNAs of hub DEGs were identified by miRWalk 3.0 and miRNet in combination with the MNDR platform. As a result, seventy‐seven overlapping DEGs and 15 hub genes were identified including CCL5, CXCL9, MYH2, CXCR4, CD74, CCL4, HLA‐DRB1, ACTA1, CD69, CXCL10, HLA‐DRB5, HLA‐DQB1, CXCL13, STAT1 and CKM. The enrichment analyses revealed that the DEGs were mainly enriched in immune response and chemokine signalling pathways. Investigation of immune cell infiltration in liver samples suggested significantly different infiltration between responders and non‐responders, mainly characterized by higher proportions of CD8+ T cells and activated NK cells in non‐responders. The prediction of upstream miRNAs and lncRNAs led to the identification of a potential mRNA‐miRNA‐lncRNA regulatory network composed of 2 lncRNAs (H19 and GAS5) and 5 miRNAs (hsa‐mir‐106b‐5p, hsa‐mir‐17‐5p, hsa‐mir‐20a‐5p, hsa‐mir‐6720‐5p and hsa‐mir‐93‐5p) targeting CCL5 mRNA. In conclusion, our study suggested that host genetic factors could affect therapeutic responsiveness in CHB patients. The antiviral process might be associated with the chemokine‐mediated immune response and immune cell infiltration in the liver microenvironment. John Wiley and Sons Inc. 2021-05-26 2021-07 /pmc/articles/PMC8278120/ /pubmed/34041839 http://dx.doi.org/10.1111/jcmm.16655 Text en © 2021 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles He, Yi Zhou, Yingzhi Wang, Huimin Yin, Jingyang Chang, Yunan Hu, Peng Ren, Hong Xu, Hongmei Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title | Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title_full | Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title_fullStr | Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title_full_unstemmed | Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title_short | Identifying potential biomarkers in hepatitis B virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
title_sort | identifying potential biomarkers in hepatitis b virus infection and its response to the antiviral therapy by integrated bioinformatic analysis |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278120/ https://www.ncbi.nlm.nih.gov/pubmed/34041839 http://dx.doi.org/10.1111/jcmm.16655 |
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