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Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis

Pulmonary fibrosis (PF) and pulmonary hypertension (PH) have common pathophysiological features, such as the significant remodeling of pulmonary parenchyma and vascular wall. There is no effective specific drug in clinical treatment for these two diseases, resulting in a worse prognosis and higher m...

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Autores principales: Zhao, Hui, Wang, Lan, Yan, Yi, Zhao, Qin-Hua, He, Jing, Jiang, Rong, Luo, Ci-Jun, Qiu, Hong-Ling, Miao, Yu-Qing, Gong, Su-Gang, Yuan, Ping, Wu, Wen-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507338/
https://www.ncbi.nlm.nih.gov/pubmed/37731513
http://dx.doi.org/10.3389/fimmu.2023.1197752
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author Zhao, Hui
Wang, Lan
Yan, Yi
Zhao, Qin-Hua
He, Jing
Jiang, Rong
Luo, Ci-Jun
Qiu, Hong-Ling
Miao, Yu-Qing
Gong, Su-Gang
Yuan, Ping
Wu, Wen-Hui
author_facet Zhao, Hui
Wang, Lan
Yan, Yi
Zhao, Qin-Hua
He, Jing
Jiang, Rong
Luo, Ci-Jun
Qiu, Hong-Ling
Miao, Yu-Qing
Gong, Su-Gang
Yuan, Ping
Wu, Wen-Hui
author_sort Zhao, Hui
collection PubMed
description Pulmonary fibrosis (PF) and pulmonary hypertension (PH) have common pathophysiological features, such as the significant remodeling of pulmonary parenchyma and vascular wall. There is no effective specific drug in clinical treatment for these two diseases, resulting in a worse prognosis and higher mortality. This study aimed to screen the common key genes and immune characteristics of PF and PH by means of bioinformatics to find new common therapeutic targets. Expression profiles are downloaded from the Gene Expression Database. Weighted gene co-expression network analysis is used to identify the co-expression modules related to PF and PH. We used the ClueGO software to enrich and analyze the common genes in PF and PH and obtained the protein–protein interaction (PPI) network. Then, the differential genes were screened out in another cohort of PF and PH, and the shared genes were crossed. Finally, RT-PCR verification and immune infiltration analysis were performed on the intersection genes. In the result, the positive correlation module with the highest correlation between PF and PH was determined, and it was found that lymphocyte activation is a common feature of the pathophysiology of PF and PH. Eight common characteristic genes (ACTR2, COL5A2, COL6A3, CYSLTR1, IGF1, RSPO3, SCARNA17 and SEL1L) were gained. Immune infiltration showed that compared with the control group, resting CD4 memory T cells were upregulated in PF and PH. Combining the results of crossing characteristic genes in ImmPort database and RT-PCR, the important gene IGF1 was obtained. Knocking down IGF1 could significantly reduce the proliferation and apoptosis resistance in pulmonary microvascular endothelial cells, pulmonary smooth muscle cells, and fibroblasts induced by hypoxia, platelet-derived growth factor-BB (PDGF-BB), and transforming growth factor-β1 (TGF-β1), respectively. Our work identified the common biomarkers of PF and PH and provided a new candidate gene for the potential therapeutic targets of PF and PH in the future.
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spelling pubmed-105073382023-09-20 Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis Zhao, Hui Wang, Lan Yan, Yi Zhao, Qin-Hua He, Jing Jiang, Rong Luo, Ci-Jun Qiu, Hong-Ling Miao, Yu-Qing Gong, Su-Gang Yuan, Ping Wu, Wen-Hui Front Immunol Immunology Pulmonary fibrosis (PF) and pulmonary hypertension (PH) have common pathophysiological features, such as the significant remodeling of pulmonary parenchyma and vascular wall. There is no effective specific drug in clinical treatment for these two diseases, resulting in a worse prognosis and higher mortality. This study aimed to screen the common key genes and immune characteristics of PF and PH by means of bioinformatics to find new common therapeutic targets. Expression profiles are downloaded from the Gene Expression Database. Weighted gene co-expression network analysis is used to identify the co-expression modules related to PF and PH. We used the ClueGO software to enrich and analyze the common genes in PF and PH and obtained the protein–protein interaction (PPI) network. Then, the differential genes were screened out in another cohort of PF and PH, and the shared genes were crossed. Finally, RT-PCR verification and immune infiltration analysis were performed on the intersection genes. In the result, the positive correlation module with the highest correlation between PF and PH was determined, and it was found that lymphocyte activation is a common feature of the pathophysiology of PF and PH. Eight common characteristic genes (ACTR2, COL5A2, COL6A3, CYSLTR1, IGF1, RSPO3, SCARNA17 and SEL1L) were gained. Immune infiltration showed that compared with the control group, resting CD4 memory T cells were upregulated in PF and PH. Combining the results of crossing characteristic genes in ImmPort database and RT-PCR, the important gene IGF1 was obtained. Knocking down IGF1 could significantly reduce the proliferation and apoptosis resistance in pulmonary microvascular endothelial cells, pulmonary smooth muscle cells, and fibroblasts induced by hypoxia, platelet-derived growth factor-BB (PDGF-BB), and transforming growth factor-β1 (TGF-β1), respectively. Our work identified the common biomarkers of PF and PH and provided a new candidate gene for the potential therapeutic targets of PF and PH in the future. Frontiers Media S.A. 2023-09-04 /pmc/articles/PMC10507338/ /pubmed/37731513 http://dx.doi.org/10.3389/fimmu.2023.1197752 Text en Copyright © 2023 Zhao, Wang, Yan, Zhao, He, Jiang, Luo, Qiu, Miao, Gong, Yuan and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Zhao, Hui
Wang, Lan
Yan, Yi
Zhao, Qin-Hua
He, Jing
Jiang, Rong
Luo, Ci-Jun
Qiu, Hong-Ling
Miao, Yu-Qing
Gong, Su-Gang
Yuan, Ping
Wu, Wen-Hui
Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title_full Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title_fullStr Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title_full_unstemmed Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title_short Identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
title_sort identification of the shared gene signatures between pulmonary fibrosis and pulmonary hypertension using bioinformatics analysis
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507338/
https://www.ncbi.nlm.nih.gov/pubmed/37731513
http://dx.doi.org/10.3389/fimmu.2023.1197752
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