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Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment

The survival rate of stomach adenocarcinoma patients with immune and stromal scores and different clinicopathological features obtained from the TCGA datasets was systematically compared. A list of genes that are correlated with stomach adenocarcinoma microenvironment were extracted using the TCGA d...

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Autores principales: Yao, Kunhou, Wei, Lunshou, Zhang, Junjie, Wang, Chenyu, Wang, Chaoyang, Qin, Changjiang, Li, Song
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485698/
https://www.ncbi.nlm.nih.gov/pubmed/32833670
http://dx.doi.org/10.18632/aging.103646
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author Yao, Kunhou
Wei, Lunshou
Zhang, Junjie
Wang, Chenyu
Wang, Chaoyang
Qin, Changjiang
Li, Song
author_facet Yao, Kunhou
Wei, Lunshou
Zhang, Junjie
Wang, Chenyu
Wang, Chaoyang
Qin, Changjiang
Li, Song
author_sort Yao, Kunhou
collection PubMed
description The survival rate of stomach adenocarcinoma patients with immune and stromal scores and different clinicopathological features obtained from the TCGA datasets was systematically compared. A list of genes that are correlated with stomach adenocarcinoma microenvironment were extracted using the TCGA database to predict the prognosis and survival. In addition, the differentially expressed genes were extracted by comparing the immune and stromal scores of the groups. The protein-protein interaction network, and functional and pathway enrichment analyses of differentially expressed genes were performed. A total of 8 hub genes were selected from the differentially expressed genes to predict the overall survival and disease-free survival rates. GPNMB was selected from the hub genes based on the survival and prognosis analyses. A nomogram was built by including the potential risk factors based on multivariate Cox analysis. Cell function experiments and xenograft tumors were conducted in vivo to further verify the role of GPNMB in tumor progression. The predicted microRNA, miR-30b-3p, might act as upstream negative regulator and binding to 3’ UTR of GPNMB, confirming by fluorescent enzyme reporter gene experiment. In summary, immune-related scores are crucial factors in the malignant progression of stomach adenocarcinoma and GPNMB acts as a potentially useful prognostic factor for stratification and in developing the treatment strategy
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spelling pubmed-74856982020-09-14 Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment Yao, Kunhou Wei, Lunshou Zhang, Junjie Wang, Chenyu Wang, Chaoyang Qin, Changjiang Li, Song Aging (Albany NY) Research Paper The survival rate of stomach adenocarcinoma patients with immune and stromal scores and different clinicopathological features obtained from the TCGA datasets was systematically compared. A list of genes that are correlated with stomach adenocarcinoma microenvironment were extracted using the TCGA database to predict the prognosis and survival. In addition, the differentially expressed genes were extracted by comparing the immune and stromal scores of the groups. The protein-protein interaction network, and functional and pathway enrichment analyses of differentially expressed genes were performed. A total of 8 hub genes were selected from the differentially expressed genes to predict the overall survival and disease-free survival rates. GPNMB was selected from the hub genes based on the survival and prognosis analyses. A nomogram was built by including the potential risk factors based on multivariate Cox analysis. Cell function experiments and xenograft tumors were conducted in vivo to further verify the role of GPNMB in tumor progression. The predicted microRNA, miR-30b-3p, might act as upstream negative regulator and binding to 3’ UTR of GPNMB, confirming by fluorescent enzyme reporter gene experiment. In summary, immune-related scores are crucial factors in the malignant progression of stomach adenocarcinoma and GPNMB acts as a potentially useful prognostic factor for stratification and in developing the treatment strategy Impact Journals 2020-08-21 /pmc/articles/PMC7485698/ /pubmed/32833670 http://dx.doi.org/10.18632/aging.103646 Text en Copyright © 2020 Yao et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Yao, Kunhou
Wei, Lunshou
Zhang, Junjie
Wang, Chenyu
Wang, Chaoyang
Qin, Changjiang
Li, Song
Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title_full Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title_fullStr Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title_full_unstemmed Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title_short Prognostic values of GPNMB identified by mining TCGA database and STAD microenvironment
title_sort prognostic values of gpnmb identified by mining tcga database and stad microenvironment
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485698/
https://www.ncbi.nlm.nih.gov/pubmed/32833670
http://dx.doi.org/10.18632/aging.103646
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