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Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. Many studies suggest that autophagy may be related to disease progression and prognosis in IPF. However, the mechanisms involved have not been fully elucidated. METHODS: We incorporated 232 autophagy-...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791216/ https://www.ncbi.nlm.nih.gov/pubmed/36578501 http://dx.doi.org/10.3389/fimmu.2022.1049361 |
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author | Fan, Guoqing Liu, Jingjing Wu, Zhen Li, Caiyu Zhang, Ying |
author_facet | Fan, Guoqing Liu, Jingjing Wu, Zhen Li, Caiyu Zhang, Ying |
author_sort | Fan, Guoqing |
collection | PubMed |
description | BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. Many studies suggest that autophagy may be related to disease progression and prognosis in IPF. However, the mechanisms involved have not been fully elucidated. METHODS: We incorporated 232 autophagy-associated genes (AAGs) and two datasets, GSE28042 and GSE27957, from the GEO database. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression were used to construct the autophagy-associated prognostic model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the functions of these autophagy-associated genes. CIBERSORT algorithm was used to calculate the immune cell infiltration between patients in the high-risk score and low-risk score groups. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was performed to explore the mRNA expression of five genes in the autophagy-associated risk model. RESULTS: We constructed a 5-autophagy-associated genes signature based on Univariate Cox analysis and LASSO regression. In our autophagy-associated risk model, IPF patients in the high-risk group demonstrated a poor overall survival rate compared to patients in the low-risk group. For 1-, 2-, and 3-year survival rates, the AUC predictive value of the AAG signature was 0.670, 0.787, and 0.864, respectively. These results were validated in the GSE27957 cohort, confirming the good prognostic effect of our model. GO and KEGG pathway analyses enriched immune-related pathways between the high-risk and low-risk groups. And there was also a significant difference in immune cell infiltration between two groups. And the results of qRT-PCR showed that the expression levels of FOXO1, IRGM, MYC, and PRKCQ were significantly decreased in the Peripheral Blood Mononuclear Cell (PBMC) of IPF patient samples. CONCLUSION: Our study constructed and validated an autophagy-associated risk model based on MYC, MAPK1, IRGM, PRKCQ, and FOXO1. And those five genes may influence the progression of IPF by regulating immune responses and immune cells. |
format | Online Article Text |
id | pubmed-9791216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97912162022-12-27 Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis Fan, Guoqing Liu, Jingjing Wu, Zhen Li, Caiyu Zhang, Ying Front Immunol Immunology BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease. Many studies suggest that autophagy may be related to disease progression and prognosis in IPF. However, the mechanisms involved have not been fully elucidated. METHODS: We incorporated 232 autophagy-associated genes (AAGs) and two datasets, GSE28042 and GSE27957, from the GEO database. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression were used to construct the autophagy-associated prognostic model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the functions of these autophagy-associated genes. CIBERSORT algorithm was used to calculate the immune cell infiltration between patients in the high-risk score and low-risk score groups. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was performed to explore the mRNA expression of five genes in the autophagy-associated risk model. RESULTS: We constructed a 5-autophagy-associated genes signature based on Univariate Cox analysis and LASSO regression. In our autophagy-associated risk model, IPF patients in the high-risk group demonstrated a poor overall survival rate compared to patients in the low-risk group. For 1-, 2-, and 3-year survival rates, the AUC predictive value of the AAG signature was 0.670, 0.787, and 0.864, respectively. These results were validated in the GSE27957 cohort, confirming the good prognostic effect of our model. GO and KEGG pathway analyses enriched immune-related pathways between the high-risk and low-risk groups. And there was also a significant difference in immune cell infiltration between two groups. And the results of qRT-PCR showed that the expression levels of FOXO1, IRGM, MYC, and PRKCQ were significantly decreased in the Peripheral Blood Mononuclear Cell (PBMC) of IPF patient samples. CONCLUSION: Our study constructed and validated an autophagy-associated risk model based on MYC, MAPK1, IRGM, PRKCQ, and FOXO1. And those five genes may influence the progression of IPF by regulating immune responses and immune cells. Frontiers Media S.A. 2022-12-12 /pmc/articles/PMC9791216/ /pubmed/36578501 http://dx.doi.org/10.3389/fimmu.2022.1049361 Text en Copyright © 2022 Fan, Liu, Wu, Li 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 | Immunology Fan, Guoqing Liu, Jingjing Wu, Zhen Li, Caiyu Zhang, Ying Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title | Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title_full | Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title_fullStr | Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title_full_unstemmed | Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title_short | Development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
title_sort | development and validation of the prognostic model based on autophagy-associated genes in idiopathic pulmonary fibrosis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791216/ https://www.ncbi.nlm.nih.gov/pubmed/36578501 http://dx.doi.org/10.3389/fimmu.2022.1049361 |
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