Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease

Hui Yu,1 Weikang Guo,2 Yunduo Liu,2 Yaoxian Wang2 1Cardiopulmonary Function Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Republic of China; 2Gynecological Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Re...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yu H, Guo W, Liu Y, Wang Y
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2021
Materias:	copd gene signatures immune infiltration transcriptional regulation Diseases of the respiratory system RC705-779
Acceso en línea:	https://doaj.org/article/31e93c05a38d45e3a4241ca829cebbec
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:31e93c05a38d45e3a4241ca829cebbec
record_format	dspace
spelling	oai:doaj.org-article:31e93c05a38d45e3a4241ca829cebbec2021-11-07T18:42:56ZImmune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease1178-2005https://doaj.org/article/31e93c05a38d45e3a4241ca829cebbec2021-11-01T00:00:00Zhttps://www.dovepress.com/immune-characteristics-analysis-and-transcriptional-regulation-predict-peer-reviewed-fulltext-article-COPDhttps://doaj.org/toc/1178-2005Hui Yu,1 Weikang Guo,2 Yunduo Liu,2 Yaoxian Wang2 1Cardiopulmonary Function Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Republic of China; 2Gynecological Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Republic of ChinaCorrespondence: Yaoxian WangGynecological Department, Harbin Medical University Cancer Hospital, No. 150 Haping Road, Nangang District, Harbin, Heilongjiang, 150081, People’s Republic of ChinaTel +86-0451-86298578Email wyxxs012@126.comPurpose: The variation in inflammation in chronic obstructive pulmonary disease (COPD) between individuals is genetically determined. This study aimed to identify gene signatures of COPD through bioinformatics analysis based on multiple gene sets and explore their immune characteristics and transcriptional regulation mechanisms.Methods: Data from four microarrays were downloaded from the Gene Expression Omnibus database to screen differentially expressed genes (DEGs) between COPD patients and controls. Weighted gene co-expression network analysis was applied to identify trait-related modules and then select key module-related DEGs. The optimized gene set of signatures was obtained using the least absolute shrinkage and selection operator (LASSO) regression analysis. The CIBERSORT algorithm and Pearson correlation test were used to analyze the relationship between gene signatures and immune cells. Finally, public databases were used to predict the transcription factors (TFs) and upstream miRNAs.Results: A total of 127 DEGs in COPD were identified from the combined dataset. By considering the intersection of DEGs and genes in two trait-related modules, 83 key module-related DEGs were identified, which were mainly enriched in interleukin-related pathways. Seven-gene signatures, including MTHFD2, KANK3, GFPT2, PHLDA1, HS3ST2, FGG, and RPS4Y1, were further selected using the LASSO algorithm. These gene signatures showed the predictive potential for COPD risks and were significantly correlated with 18 types of immune cells. Finally, nine miRNAs and three TFs were predicted to target MTHFD2, GFPT2, PHLDA1, and FGG.Conclusion: We proposed the seven-gene-signature to predict COPD risk and explored its potential immune characteristics and regulatory mechanisms.Keywords: COPD, gene signatures, immune infiltration, transcriptional regulationYu HGuo WLiu YWang YDove Medical Pressarticlecopdgene signaturesimmune infiltrationtranscriptional regulationDiseases of the respiratory systemRC705-779ENInternational Journal of COPD, Vol Volume 16, Pp 3027-3039 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	copd gene signatures immune infiltration transcriptional regulation Diseases of the respiratory system RC705-779
spellingShingle	copd gene signatures immune infiltration transcriptional regulation Diseases of the respiratory system RC705-779 Yu H Guo W Liu Y Wang Y Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
description	Hui Yu,1 Weikang Guo,2 Yunduo Liu,2 Yaoxian Wang2 1Cardiopulmonary Function Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Republic of China; 2Gynecological Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, 150081, People’s Republic of ChinaCorrespondence: Yaoxian WangGynecological Department, Harbin Medical University Cancer Hospital, No. 150 Haping Road, Nangang District, Harbin, Heilongjiang, 150081, People’s Republic of ChinaTel +86-0451-86298578Email wyxxs012@126.comPurpose: The variation in inflammation in chronic obstructive pulmonary disease (COPD) between individuals is genetically determined. This study aimed to identify gene signatures of COPD through bioinformatics analysis based on multiple gene sets and explore their immune characteristics and transcriptional regulation mechanisms.Methods: Data from four microarrays were downloaded from the Gene Expression Omnibus database to screen differentially expressed genes (DEGs) between COPD patients and controls. Weighted gene co-expression network analysis was applied to identify trait-related modules and then select key module-related DEGs. The optimized gene set of signatures was obtained using the least absolute shrinkage and selection operator (LASSO) regression analysis. The CIBERSORT algorithm and Pearson correlation test were used to analyze the relationship between gene signatures and immune cells. Finally, public databases were used to predict the transcription factors (TFs) and upstream miRNAs.Results: A total of 127 DEGs in COPD were identified from the combined dataset. By considering the intersection of DEGs and genes in two trait-related modules, 83 key module-related DEGs were identified, which were mainly enriched in interleukin-related pathways. Seven-gene signatures, including MTHFD2, KANK3, GFPT2, PHLDA1, HS3ST2, FGG, and RPS4Y1, were further selected using the LASSO algorithm. These gene signatures showed the predictive potential for COPD risks and were significantly correlated with 18 types of immune cells. Finally, nine miRNAs and three TFs were predicted to target MTHFD2, GFPT2, PHLDA1, and FGG.Conclusion: We proposed the seven-gene-signature to predict COPD risk and explored its potential immune characteristics and regulatory mechanisms.Keywords: COPD, gene signatures, immune infiltration, transcriptional regulation
format	article
author	Yu H Guo W Liu Y Wang Y
author_facet	Yu H Guo W Liu Y Wang Y
author_sort	Yu H
title	Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
title_short	Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
title_full	Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
title_fullStr	Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
title_full_unstemmed	Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease
title_sort	immune characteristics analysis and transcriptional regulation prediction based on gene signatures of chronic obstructive pulmonary disease
publisher	Dove Medical Press
publishDate	2021
url	https://doaj.org/article/31e93c05a38d45e3a4241ca829cebbec
work_keys_str_mv	AT yuh immunecharacteristicsanalysisandtranscriptionalregulationpredictionbasedongenesignaturesofchronicobstructivepulmonarydisease AT guow immunecharacteristicsanalysisandtranscriptionalregulationpredictionbasedongenesignaturesofchronicobstructivepulmonarydisease AT liuy immunecharacteristicsanalysisandtranscriptionalregulationpredictionbasedongenesignaturesofchronicobstructivepulmonarydisease AT wangy immunecharacteristicsanalysisandtranscriptionalregulationpredictionbasedongenesignaturesofchronicobstructivepulmonarydisease
_version_	1718443270085804032

Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease

Ejemplares similares