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Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma

Purpose: Stomach adenocarcinoma (STAD) is one of the most common malignant tumors, and its occurrence and prognosis are closely related to inflammation. The aim of the present study was to identify gene signatures and construct an immune-related gene (IRG) prognostic model in STAD using bioinformati...

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Autores principales: Wu, Ming, Xia, Yu, Wang, Yadong, Fan, Fei, Li, Xian, Song, Jukun, Ding, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593539/
https://www.ncbi.nlm.nih.gov/pubmed/33112406
http://dx.doi.org/10.1042/BSR20201012
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author Wu, Ming
Xia, Yu
Wang, Yadong
Fan, Fei
Li, Xian
Song, Jukun
Ding, Jie
author_facet Wu, Ming
Xia, Yu
Wang, Yadong
Fan, Fei
Li, Xian
Song, Jukun
Ding, Jie
author_sort Wu, Ming
collection PubMed
description Purpose: Stomach adenocarcinoma (STAD) is one of the most common malignant tumors, and its occurrence and prognosis are closely related to inflammation. The aim of the present study was to identify gene signatures and construct an immune-related gene (IRG) prognostic model in STAD using bioinformatics analysis. Methods: RNA sequencing data from healthy samples and samples with STAD, IRGs, and transcription factors were analyzed. The hub IRGs were identified using univariate and multivariate Cox regression analyses. Using the hub IRGs, we constructed an IRG prognostic model. The relationships between IRG prognostic models and clinical data were tested. Results: A total of 289 differentially expressed IRGs and 20 prognostic IRGs were screened with a threshold of P<0.05. Through multivariate stepwise Cox regression analysis, we developed a prognostic model based on seven IRGs. The prognostic model was validated using a GEO dataset (GSE 84437). The IRGs were significantly correlated with the clinical outcomes (age, histological grade, N, and M stage) of STAD patients. The infiltration abundances of dendritic cells and macrophages were higher in the high-risk group than in the low-risk group. Conclusions: Our results provide novel insights into the pathogenesis of STAD. An IRG prognostic model based on seven IRGs exhibited the predictive value, and have potential application value in clinical decision-making and individualized treatment.
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spelling pubmed-75935392020-11-02 Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma Wu, Ming Xia, Yu Wang, Yadong Fan, Fei Li, Xian Song, Jukun Ding, Jie Biosci Rep Bioinformatics Purpose: Stomach adenocarcinoma (STAD) is one of the most common malignant tumors, and its occurrence and prognosis are closely related to inflammation. The aim of the present study was to identify gene signatures and construct an immune-related gene (IRG) prognostic model in STAD using bioinformatics analysis. Methods: RNA sequencing data from healthy samples and samples with STAD, IRGs, and transcription factors were analyzed. The hub IRGs were identified using univariate and multivariate Cox regression analyses. Using the hub IRGs, we constructed an IRG prognostic model. The relationships between IRG prognostic models and clinical data were tested. Results: A total of 289 differentially expressed IRGs and 20 prognostic IRGs were screened with a threshold of P<0.05. Through multivariate stepwise Cox regression analysis, we developed a prognostic model based on seven IRGs. The prognostic model was validated using a GEO dataset (GSE 84437). The IRGs were significantly correlated with the clinical outcomes (age, histological grade, N, and M stage) of STAD patients. The infiltration abundances of dendritic cells and macrophages were higher in the high-risk group than in the low-risk group. Conclusions: Our results provide novel insights into the pathogenesis of STAD. An IRG prognostic model based on seven IRGs exhibited the predictive value, and have potential application value in clinical decision-making and individualized treatment. Portland Press Ltd. 2020-10-28 /pmc/articles/PMC7593539/ /pubmed/33112406 http://dx.doi.org/10.1042/BSR20201012 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Bioinformatics
Wu, Ming
Xia, Yu
Wang, Yadong
Fan, Fei
Li, Xian
Song, Jukun
Ding, Jie
Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title_full Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title_fullStr Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title_full_unstemmed Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title_short Development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
title_sort development and validation of an immune-related gene prognostic model for stomach adenocarcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593539/
https://www.ncbi.nlm.nih.gov/pubmed/33112406
http://dx.doi.org/10.1042/BSR20201012
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