Cargando…

Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes

BACKGROUND: Integrin β (ITGB) superfamily plays an essential role in the intercellular connection and signal transmission. It was exhibited that overexpressing of ITGB family members promotes the malignant progression of lung adenocarcinoma (LUAD), but the relationship between ITGB superfamily and t...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yuanlin, Fu, Linhai, Wang, Bin, Li, Zhupeng, Wei, Desheng, Wang, Haiyong, Zhang, Chu, Ma, Zhifeng, Zhu, Ting, Yu, Guangmao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169214/
https://www.ncbi.nlm.nih.gov/pubmed/35403268
http://dx.doi.org/10.1002/jcla.24419
_version_ 1784721161056157696
author Wu, Yuanlin
Fu, Linhai
Wang, Bin
Li, Zhupeng
Wei, Desheng
Wang, Haiyong
Zhang, Chu
Ma, Zhifeng
Zhu, Ting
Yu, Guangmao
author_facet Wu, Yuanlin
Fu, Linhai
Wang, Bin
Li, Zhupeng
Wei, Desheng
Wang, Haiyong
Zhang, Chu
Ma, Zhifeng
Zhu, Ting
Yu, Guangmao
author_sort Wu, Yuanlin
collection PubMed
description BACKGROUND: Integrin β (ITGB) superfamily plays an essential role in the intercellular connection and signal transmission. It was exhibited that overexpressing of ITGB family members promotes the malignant progression of lung adenocarcinoma (LUAD), but the relationship between ITGB superfamily and the LUAD prognosis remains unclear. METHODS: In this study, the samples were assigned to different subgroups utilizing non‐negative matrix factorization clustering according to the expression of ITGB family members in LUAD. Kaplan–Meier (K‐M) survival analysis revealed the significant differences in the prognosis between different ITGB subgroups. Subsequently, we screened differentially expressed genes among different subgroups and conducted univariate Cox analysis, random forest feature selection, and multivariate Cox analysis. 9‐feature genes (FAM83A, AKAP12, PKP2, CYP17A1, GJB3, TMPRSS11F, KRT81, MARCH4, and STC1) in the ITGB superfamily were selected to establish a prognostic assessment model for LAUD. RESULTS: In accordance with the median risk score, LUAD samples were divided into high‐ and low‐risk groups. The receiver operating characteristic (ROC) curve of LUAD patients’ survival was predicted via K‐M survival curve and principal component analysis dimensionality reduction. This model was found to have a favorable performance in LUAD prognostic assessment. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes between groups and Gene Set Enrichment Analysis (GSEA) of intergroup samples confirmed that the high‐ and low‐risk groups had evident differences mainly in the function of extracellular matrix (ECM) interaction. Risk score and univariate and multivariate Cox regression analyses of clinical factors showed that the prognostic model could be applied as an independent prognostic factor for LUAD. Then, we draw the nomogram of 1‐, 3‐, and 5‐year survival of LUAD patients predicted with the risk score and clinical factors. Calibration curve and clinical decision curve proved the favorable predictive ability of nomogram. CONCLUSION: We constructed a LUAD prognostic risk model based on the ITGB superfamily, which can provide guidance for clinicians on their prognostic judgment.
format Online
Article
Text
id pubmed-9169214
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-91692142022-06-07 Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes Wu, Yuanlin Fu, Linhai Wang, Bin Li, Zhupeng Wei, Desheng Wang, Haiyong Zhang, Chu Ma, Zhifeng Zhu, Ting Yu, Guangmao J Clin Lab Anal Research Articles BACKGROUND: Integrin β (ITGB) superfamily plays an essential role in the intercellular connection and signal transmission. It was exhibited that overexpressing of ITGB family members promotes the malignant progression of lung adenocarcinoma (LUAD), but the relationship between ITGB superfamily and the LUAD prognosis remains unclear. METHODS: In this study, the samples were assigned to different subgroups utilizing non‐negative matrix factorization clustering according to the expression of ITGB family members in LUAD. Kaplan–Meier (K‐M) survival analysis revealed the significant differences in the prognosis between different ITGB subgroups. Subsequently, we screened differentially expressed genes among different subgroups and conducted univariate Cox analysis, random forest feature selection, and multivariate Cox analysis. 9‐feature genes (FAM83A, AKAP12, PKP2, CYP17A1, GJB3, TMPRSS11F, KRT81, MARCH4, and STC1) in the ITGB superfamily were selected to establish a prognostic assessment model for LAUD. RESULTS: In accordance with the median risk score, LUAD samples were divided into high‐ and low‐risk groups. The receiver operating characteristic (ROC) curve of LUAD patients’ survival was predicted via K‐M survival curve and principal component analysis dimensionality reduction. This model was found to have a favorable performance in LUAD prognostic assessment. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes between groups and Gene Set Enrichment Analysis (GSEA) of intergroup samples confirmed that the high‐ and low‐risk groups had evident differences mainly in the function of extracellular matrix (ECM) interaction. Risk score and univariate and multivariate Cox regression analyses of clinical factors showed that the prognostic model could be applied as an independent prognostic factor for LUAD. Then, we draw the nomogram of 1‐, 3‐, and 5‐year survival of LUAD patients predicted with the risk score and clinical factors. Calibration curve and clinical decision curve proved the favorable predictive ability of nomogram. CONCLUSION: We constructed a LUAD prognostic risk model based on the ITGB superfamily, which can provide guidance for clinicians on their prognostic judgment. John Wiley and Sons Inc. 2022-04-11 /pmc/articles/PMC9169214/ /pubmed/35403268 http://dx.doi.org/10.1002/jcla.24419 Text en © 2022 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Wu, Yuanlin
Fu, Linhai
Wang, Bin
Li, Zhupeng
Wei, Desheng
Wang, Haiyong
Zhang, Chu
Ma, Zhifeng
Zhu, Ting
Yu, Guangmao
Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title_full Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title_fullStr Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title_full_unstemmed Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title_short Construction of a prognostic risk assessment model for lung adenocarcinoma based on Integrin β family‐related genes
title_sort construction of a prognostic risk assessment model for lung adenocarcinoma based on integrin β family‐related genes
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169214/
https://www.ncbi.nlm.nih.gov/pubmed/35403268
http://dx.doi.org/10.1002/jcla.24419
work_keys_str_mv AT wuyuanlin constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT fulinhai constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT wangbin constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT lizhupeng constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT weidesheng constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT wanghaiyong constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT zhangchu constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT mazhifeng constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT zhuting constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes
AT yuguangmao constructionofaprognosticriskassessmentmodelforlungadenocarcinomabasedonintegrinbfamilyrelatedgenes