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Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection

BACKGROUND: The programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) signaling pathway is significantly upregulated in influenza virus infection, which impairs the antiviral response. Blocking this signaling pathway may reduce the damage, lower the virus titer in lung tissue, and alleviate the sympt...

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Autores principales: Ou, Huilin, Chen, Keda, Chen, Linfang, Wu, Hongcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374577/
https://www.ncbi.nlm.nih.gov/pubmed/35962325
http://dx.doi.org/10.1186/s12863-022-01081-7
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author Ou, Huilin
Chen, Keda
Chen, Linfang
Wu, Hongcheng
author_facet Ou, Huilin
Chen, Keda
Chen, Linfang
Wu, Hongcheng
author_sort Ou, Huilin
collection PubMed
description BACKGROUND: The programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) signaling pathway is significantly upregulated in influenza virus infection, which impairs the antiviral response. Blocking this signaling pathway may reduce the damage, lower the virus titer in lung tissue, and alleviate the symptoms of infection to promote recovery. In addition to the enhanced viral immune response, using of immune checkpoint inhibitors in influenza virus infection is controversial, the aim of this study was to identify the key factors and regulatory mechanisms in the PD-1 checkpoint blockade response microenvironment in influenza infection. METHODS: A BALB/c mouse model of influenza A/PR8(H1N1) infection was established then constructed, and whole-transcriptome sequencing including mRNAs, miRNAs (microRNAs), lncRNAs (long noncoding RNAs), and circRNAs (circular RNAs) of mice treated with PD-1 checkpoint blockade by antibody treatment and IgG2a isotype control before infection with A/PR8(H1N1) were performed. Subsequently, the differential expression of transcripts between these two groups was analyzed, followed by functional interaction prediction analysis to investigate gene-regulatory circuits. RESULTS: In total, 84 differentially expressed dif-mRNAs, 36 dif-miRNAs, 90 dif-lncRNAs and 22 dif-circRNAs were found in PD-1 antagonist treated A/PR8(H1N1) influenza-infected lungs compared with the controls (IgG2a isotype control treated before infection). In spleens between the above two groups, 45 dif-mRNAs, 36 dif-miRNAs, 57 dif-lncRNAs, and 24 dif-circRNAs were identified. Direct function enrichment analysis of dif-mRNAs and dif-miRNAs showed that these genes were mainly involved in myocardial damage related to viral infection, mitogen activated protein kinase (MAPK) signaling pathways, RAP1 (Ras-related protein 1) signaling pathway, and Axon guidance. Finally, 595 interaction pairs were obtained for the lungs and 462 interaction pairs for the spleens were obtained in the competing endogenous RNA (ceRNA) complex network, in which the downregulated mmu-miR-7043-3p and Vps39–204 were enriched significantly in PD-1 checkpoint blockade treated A/PR8(H1N1) infection group. CONCLUSIONS: The present study provided a basis for the identification of potential pathways and hub genes that might be involved in the PD-1 checkpoint blockade response microenvironment in influenza infection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-022-01081-7.
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spelling pubmed-93745772022-08-14 Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection Ou, Huilin Chen, Keda Chen, Linfang Wu, Hongcheng BMC Genom Data Research BACKGROUND: The programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) signaling pathway is significantly upregulated in influenza virus infection, which impairs the antiviral response. Blocking this signaling pathway may reduce the damage, lower the virus titer in lung tissue, and alleviate the symptoms of infection to promote recovery. In addition to the enhanced viral immune response, using of immune checkpoint inhibitors in influenza virus infection is controversial, the aim of this study was to identify the key factors and regulatory mechanisms in the PD-1 checkpoint blockade response microenvironment in influenza infection. METHODS: A BALB/c mouse model of influenza A/PR8(H1N1) infection was established then constructed, and whole-transcriptome sequencing including mRNAs, miRNAs (microRNAs), lncRNAs (long noncoding RNAs), and circRNAs (circular RNAs) of mice treated with PD-1 checkpoint blockade by antibody treatment and IgG2a isotype control before infection with A/PR8(H1N1) were performed. Subsequently, the differential expression of transcripts between these two groups was analyzed, followed by functional interaction prediction analysis to investigate gene-regulatory circuits. RESULTS: In total, 84 differentially expressed dif-mRNAs, 36 dif-miRNAs, 90 dif-lncRNAs and 22 dif-circRNAs were found in PD-1 antagonist treated A/PR8(H1N1) influenza-infected lungs compared with the controls (IgG2a isotype control treated before infection). In spleens between the above two groups, 45 dif-mRNAs, 36 dif-miRNAs, 57 dif-lncRNAs, and 24 dif-circRNAs were identified. Direct function enrichment analysis of dif-mRNAs and dif-miRNAs showed that these genes were mainly involved in myocardial damage related to viral infection, mitogen activated protein kinase (MAPK) signaling pathways, RAP1 (Ras-related protein 1) signaling pathway, and Axon guidance. Finally, 595 interaction pairs were obtained for the lungs and 462 interaction pairs for the spleens were obtained in the competing endogenous RNA (ceRNA) complex network, in which the downregulated mmu-miR-7043-3p and Vps39–204 were enriched significantly in PD-1 checkpoint blockade treated A/PR8(H1N1) infection group. CONCLUSIONS: The present study provided a basis for the identification of potential pathways and hub genes that might be involved in the PD-1 checkpoint blockade response microenvironment in influenza infection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-022-01081-7. BioMed Central 2022-08-13 /pmc/articles/PMC9374577/ /pubmed/35962325 http://dx.doi.org/10.1186/s12863-022-01081-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ou, Huilin
Chen, Keda
Chen, Linfang
Wu, Hongcheng
Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title_full Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title_fullStr Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title_full_unstemmed Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title_short Bioinformatic analysis of PD-1 checkpoint blockade response in influenza infection
title_sort bioinformatic analysis of pd-1 checkpoint blockade response in influenza infection
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374577/
https://www.ncbi.nlm.nih.gov/pubmed/35962325
http://dx.doi.org/10.1186/s12863-022-01081-7
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