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Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer
BACKGROUND: Microsatellite instability‐high (MSI‐H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI‐H status have a good response to immune checkpoint blockade management...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883573/ https://www.ncbi.nlm.nih.gov/pubmed/35789544 http://dx.doi.org/10.1002/cam4.4975 |
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author | Zhang, Mili Cao, Can Li, Xu Gu, Qisheng Xu, Yixin Zhu, Ziyan Xu, Duogang Wei, Shanshan Chen, Haonan Yang, Yuqin Gao, Hugh Yu, Liang Li, Jikun |
author_facet | Zhang, Mili Cao, Can Li, Xu Gu, Qisheng Xu, Yixin Zhu, Ziyan Xu, Duogang Wei, Shanshan Chen, Haonan Yang, Yuqin Gao, Hugh Yu, Liang Li, Jikun |
author_sort | Zhang, Mili |
collection | PubMed |
description | BACKGROUND: Microsatellite instability‐high (MSI‐H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI‐H status have a good response to immune checkpoint blockade management. However, heterogeneity within the subtype and the underlying mechanisms of shaping tumor microenvironments remain poorly understood. METHODS: RNA expression levels and clinical parameters of GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The data were analyzed using single‐sample Gene Set Enrichment Analysis (ssGSEA), univariate Cox regression, multivariate Cox regression, and Least Absolute Shrinkage Selection Operator (LASSO) regression. In addition, multiplex immunohistochemistry (mIHC) was used in our clinical cohort for the tumor microenvironment study. RESULTS: By ssGSEA and survival analysis, the EMT signaling pathway was identified as a representative pathway, which can stratify the patients with MSI‐H GC with significant survival predictive power. Then, a novel representative EMT‐related five‐gene signature (namely CALU, PCOLCE2, PLOD2, SGCD, and THBS2) was established from EMT signaling gene set, which sensitivity and specificity were further validated in the independent GEO database (GSE62254) cohort for disease outcome prediction. Based on public single‐cell data and in situ immunohistochemistry, we found that most of these five genes were abundantly expressed in cancer‐associated fibroblasts. Furthermore, patients with high or low risk divided by this five‐gene signature exhibited a strong correlation of the distinct patterns of tumor immune microenvironment. By mIHC staining of sections from 30 patients with MSI‐H status, we showed that the patients with better prognoses had the increased infiltration of CD8(+) cells in the primary tumoral tissue. CONCLUSION: Our study developed a simple five‐gene signature for stratifying MSI‐H GC patients with survival predictive power. |
format | Online Article Text |
id | pubmed-9883573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98835732023-01-31 Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer Zhang, Mili Cao, Can Li, Xu Gu, Qisheng Xu, Yixin Zhu, Ziyan Xu, Duogang Wei, Shanshan Chen, Haonan Yang, Yuqin Gao, Hugh Yu, Liang Li, Jikun Cancer Med Research Articles BACKGROUND: Microsatellite instability‐high (MSI‐H) subgroup of gastric cancer (GC) is characterized by a high tumor mutational burden, increased lymphocytic infiltration, and enhanced inflammatory cytokines. GC patients with MSI‐H status have a good response to immune checkpoint blockade management. However, heterogeneity within the subtype and the underlying mechanisms of shaping tumor microenvironments remain poorly understood. METHODS: RNA expression levels and clinical parameters of GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The data were analyzed using single‐sample Gene Set Enrichment Analysis (ssGSEA), univariate Cox regression, multivariate Cox regression, and Least Absolute Shrinkage Selection Operator (LASSO) regression. In addition, multiplex immunohistochemistry (mIHC) was used in our clinical cohort for the tumor microenvironment study. RESULTS: By ssGSEA and survival analysis, the EMT signaling pathway was identified as a representative pathway, which can stratify the patients with MSI‐H GC with significant survival predictive power. Then, a novel representative EMT‐related five‐gene signature (namely CALU, PCOLCE2, PLOD2, SGCD, and THBS2) was established from EMT signaling gene set, which sensitivity and specificity were further validated in the independent GEO database (GSE62254) cohort for disease outcome prediction. Based on public single‐cell data and in situ immunohistochemistry, we found that most of these five genes were abundantly expressed in cancer‐associated fibroblasts. Furthermore, patients with high or low risk divided by this five‐gene signature exhibited a strong correlation of the distinct patterns of tumor immune microenvironment. By mIHC staining of sections from 30 patients with MSI‐H status, we showed that the patients with better prognoses had the increased infiltration of CD8(+) cells in the primary tumoral tissue. CONCLUSION: Our study developed a simple five‐gene signature for stratifying MSI‐H GC patients with survival predictive power. John Wiley and Sons Inc. 2022-07-04 /pmc/articles/PMC9883573/ /pubmed/35789544 http://dx.doi.org/10.1002/cam4.4975 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. 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 Zhang, Mili Cao, Can Li, Xu Gu, Qisheng Xu, Yixin Zhu, Ziyan Xu, Duogang Wei, Shanshan Chen, Haonan Yang, Yuqin Gao, Hugh Yu, Liang Li, Jikun Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title | Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title_full | Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title_fullStr | Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title_full_unstemmed | Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title_short | Five EMT‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
title_sort | five emt‐related genes signature predicts overall survival and immune environment in microsatellite instability‐high gastric cancer |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883573/ https://www.ncbi.nlm.nih.gov/pubmed/35789544 http://dx.doi.org/10.1002/cam4.4975 |
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