Cargando…
Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies
Background: Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease. Growing evidence indicated that IPAH is a chronic immune disease. This study explored the molecular mechanisms and T cell infiltration of IPAH using integrated bioinformatics methods. Methods: Gene expressio...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811199/ https://www.ncbi.nlm.nih.gov/pubmed/35127829 http://dx.doi.org/10.3389/fmolb.2022.800888 |
_version_ | 1784644380833873920 |
---|---|
author | Yang, Xiaomei Wang, Cheng Lin, Yicheng Zhang, Peng |
author_facet | Yang, Xiaomei Wang, Cheng Lin, Yicheng Zhang, Peng |
author_sort | Yang, Xiaomei |
collection | PubMed |
description | Background: Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease. Growing evidence indicated that IPAH is a chronic immune disease. This study explored the molecular mechanisms and T cell infiltration of IPAH using integrated bioinformatics methods. Methods: Gene expression profiles of dataset GSE113439 were downloaded from the Gene Expression Omnibus and analyzed using R. Protein-protein interaction (PPI) network and gene set enrichment analysis (GSEA) were established by NetworkAnalyst. Gene Ontology enrichment analysis was performed using ClueGO. Transcription factors of differentially expressed genes (DEGs) were estimated using iRegulon. Transcription factors and selected hub genes were verified by real-time polymerase chain reaction (qPCR) in the lung tissues of rats with pulmonary artery hypertension. The least absolute shrinkage and selection operator regression model and the area under the receiver operating characteristic curve (AUC) were applied jointly to identify the crucial hub genes. Moreover, immune infiltration in IPAH was calculated using ImmuCellAI, and the correlation between key hub genes and immune cells was analyzed using R. Results: A total of 512 DEGs were screened, and ten hub genes and three transcription factors were filtered by the DEG PPI network. The DEGs were mainly enriched in mitotic nuclear division, chromosome organization, and nucleocytoplasmic transport. The ten hub genes and three transcription factors were confirmed by qPCR. Moreover, MAPK6 was identified as the most potent biomarker with an AUC of 100%, and ImmuCellAI immune infiltration analysis showed that a higher proportion of CD4-naive T cells and central memory T cells (Tcm) was apparent in the IPAH group, whereas the proportions of cytotoxic T cells (Tc), exhausted T cells (Tex), type 17 T helper cells, effector memory T cells, natural killer T cells (NKT), natural killer cells, gamma-delta T cells, and CD8 T cells were lower. Finally, MAPK6 was positively correlated with Tex and Tcm, and negatively correlated with Tc and NKT. Conclusion: MAPK6 was identified as a crucial hub gene to discriminate IPAH from the normal group. Dysregulated immune reactions were identified in the lung tissue of patients with IPAH. |
format | Online Article Text |
id | pubmed-8811199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88111992022-02-04 Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies Yang, Xiaomei Wang, Cheng Lin, Yicheng Zhang, Peng Front Mol Biosci Molecular Biosciences Background: Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease. Growing evidence indicated that IPAH is a chronic immune disease. This study explored the molecular mechanisms and T cell infiltration of IPAH using integrated bioinformatics methods. Methods: Gene expression profiles of dataset GSE113439 were downloaded from the Gene Expression Omnibus and analyzed using R. Protein-protein interaction (PPI) network and gene set enrichment analysis (GSEA) were established by NetworkAnalyst. Gene Ontology enrichment analysis was performed using ClueGO. Transcription factors of differentially expressed genes (DEGs) were estimated using iRegulon. Transcription factors and selected hub genes were verified by real-time polymerase chain reaction (qPCR) in the lung tissues of rats with pulmonary artery hypertension. The least absolute shrinkage and selection operator regression model and the area under the receiver operating characteristic curve (AUC) were applied jointly to identify the crucial hub genes. Moreover, immune infiltration in IPAH was calculated using ImmuCellAI, and the correlation between key hub genes and immune cells was analyzed using R. Results: A total of 512 DEGs were screened, and ten hub genes and three transcription factors were filtered by the DEG PPI network. The DEGs were mainly enriched in mitotic nuclear division, chromosome organization, and nucleocytoplasmic transport. The ten hub genes and three transcription factors were confirmed by qPCR. Moreover, MAPK6 was identified as the most potent biomarker with an AUC of 100%, and ImmuCellAI immune infiltration analysis showed that a higher proportion of CD4-naive T cells and central memory T cells (Tcm) was apparent in the IPAH group, whereas the proportions of cytotoxic T cells (Tc), exhausted T cells (Tex), type 17 T helper cells, effector memory T cells, natural killer T cells (NKT), natural killer cells, gamma-delta T cells, and CD8 T cells were lower. Finally, MAPK6 was positively correlated with Tex and Tcm, and negatively correlated with Tc and NKT. Conclusion: MAPK6 was identified as a crucial hub gene to discriminate IPAH from the normal group. Dysregulated immune reactions were identified in the lung tissue of patients with IPAH. Frontiers Media S.A. 2022-01-20 /pmc/articles/PMC8811199/ /pubmed/35127829 http://dx.doi.org/10.3389/fmolb.2022.800888 Text en Copyright © 2022 Yang, Wang, Lin and Zhang. 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 | Molecular Biosciences Yang, Xiaomei Wang, Cheng Lin, Yicheng Zhang, Peng Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title | Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title_full | Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title_fullStr | Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title_full_unstemmed | Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title_short | Identification of Crucial Hub Genes and Differential T Cell Infiltration in Idiopathic Pulmonary Arterial Hypertension Using Bioinformatics Strategies |
title_sort | identification of crucial hub genes and differential t cell infiltration in idiopathic pulmonary arterial hypertension using bioinformatics strategies |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811199/ https://www.ncbi.nlm.nih.gov/pubmed/35127829 http://dx.doi.org/10.3389/fmolb.2022.800888 |
work_keys_str_mv | AT yangxiaomei identificationofcrucialhubgenesanddifferentialtcellinfiltrationinidiopathicpulmonaryarterialhypertensionusingbioinformaticsstrategies AT wangcheng identificationofcrucialhubgenesanddifferentialtcellinfiltrationinidiopathicpulmonaryarterialhypertensionusingbioinformaticsstrategies AT linyicheng identificationofcrucialhubgenesanddifferentialtcellinfiltrationinidiopathicpulmonaryarterialhypertensionusingbioinformaticsstrategies AT zhangpeng identificationofcrucialhubgenesanddifferentialtcellinfiltrationinidiopathicpulmonaryarterialhypertensionusingbioinformaticsstrategies |