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Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer

Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic...

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Autores principales: Sang, Qingqing, Dai, Wentao, Yu, Junxian, Chen, Yunqin, Fan, Zhiyuan, Liu, Jixiang, Li, Fangyuan, Li, Jianfang, Wu, Xiongyan, Hou, Junyi, Yu, Beiqin, Feng, Haoran, Zhu, Zheng-Gang, Su, Liping, Li, Yuan-Yuan, Liu, Bingya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9411533/
https://www.ncbi.nlm.nih.gov/pubmed/36032070
http://dx.doi.org/10.3389/fimmu.2022.983632
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author Sang, Qingqing
Dai, Wentao
Yu, Junxian
Chen, Yunqin
Fan, Zhiyuan
Liu, Jixiang
Li, Fangyuan
Li, Jianfang
Wu, Xiongyan
Hou, Junyi
Yu, Beiqin
Feng, Haoran
Zhu, Zheng-Gang
Su, Liping
Li, Yuan-Yuan
Liu, Bingya
author_facet Sang, Qingqing
Dai, Wentao
Yu, Junxian
Chen, Yunqin
Fan, Zhiyuan
Liu, Jixiang
Li, Fangyuan
Li, Jianfang
Wu, Xiongyan
Hou, Junyi
Yu, Beiqin
Feng, Haoran
Zhu, Zheng-Gang
Su, Liping
Li, Yuan-Yuan
Liu, Bingya
author_sort Sang, Qingqing
collection PubMed
description Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments.
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spelling pubmed-94115332022-08-27 Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer Sang, Qingqing Dai, Wentao Yu, Junxian Chen, Yunqin Fan, Zhiyuan Liu, Jixiang Li, Fangyuan Li, Jianfang Wu, Xiongyan Hou, Junyi Yu, Beiqin Feng, Haoran Zhu, Zheng-Gang Su, Liping Li, Yuan-Yuan Liu, Bingya Front Immunol Immunology Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments. Frontiers Media S.A. 2022-08-12 /pmc/articles/PMC9411533/ /pubmed/36032070 http://dx.doi.org/10.3389/fimmu.2022.983632 Text en Copyright © 2022 Sang, Dai, Yu, Chen, Fan, Liu, Li, Li, Wu, Hou, Yu, Feng, Zhu, Su, Li and Liu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Sang, Qingqing
Dai, Wentao
Yu, Junxian
Chen, Yunqin
Fan, Zhiyuan
Liu, Jixiang
Li, Fangyuan
Li, Jianfang
Wu, Xiongyan
Hou, Junyi
Yu, Beiqin
Feng, Haoran
Zhu, Zheng-Gang
Su, Liping
Li, Yuan-Yuan
Liu, Bingya
Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title_full Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title_fullStr Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title_full_unstemmed Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title_short Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
title_sort identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9411533/
https://www.ncbi.nlm.nih.gov/pubmed/36032070
http://dx.doi.org/10.3389/fimmu.2022.983632
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