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Metabolism-associated molecular classification of gastric adenocarcinoma
Most gastric cancers (GC) are adenocarcinomas, whereas GC is a highly heterogeneous disease due to its molecular heterogeneity. However, traditional morphology-based classification systems, including the WHO classification and Lauren’s classification, have limited utility in guiding clinical treatme...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709214/ https://www.ncbi.nlm.nih.gov/pubmed/36465405 http://dx.doi.org/10.3389/fonc.2022.1024985 |
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author | Ye, Yuqing Yang, Wenyun Ruan, Xinjia Xu, Li Cheng, Wenxuan Zhao, Mengmeng Wang, Xin Chen, Xinyi Cai, Daren Li, Guanjie Wang, Yuhang Yan, Fangrong Lu, Xiaofan Jiang, Liyun |
author_facet | Ye, Yuqing Yang, Wenyun Ruan, Xinjia Xu, Li Cheng, Wenxuan Zhao, Mengmeng Wang, Xin Chen, Xinyi Cai, Daren Li, Guanjie Wang, Yuhang Yan, Fangrong Lu, Xiaofan Jiang, Liyun |
author_sort | Ye, Yuqing |
collection | PubMed |
description | Most gastric cancers (GC) are adenocarcinomas, whereas GC is a highly heterogeneous disease due to its molecular heterogeneity. However, traditional morphology-based classification systems, including the WHO classification and Lauren’s classification, have limited utility in guiding clinical treatment. We performed nonnegative matrix factorization (NMF) clustering based on 2752 metabolism-associated genes. We characterized each of the subclasses from multiple angles, including subclass-associated metabolism signatures, immune cell infiltration, clinic10al characteristics, drug sensitivity, and pathway enrichment. As a result, four subtypes were identified: immune suppressed, metabolic, mesenchymal/immune exhausted and hypermutated. The subtypes exhibited significant prognostic differences, which suggests that the metabolism-related classification has clinical significance. Metabolic and hypermutated subtypes have better overall survival, and the hypermutated subtype is likely to be sensitive to anti-PD-1 immunotherapy. In addition, our work showed a strong connection with previously established classifications, especially Lei’s subtype, to which we provided an interpretation based on the immune cell infiltration perspective, deepening the understanding of GC heterogeneity. Finally, a 120-gene classifier was generated to determine the GC classification, and a 10-gene prognostic model was developed for survival time prediction. |
format | Online Article Text |
id | pubmed-9709214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97092142022-12-01 Metabolism-associated molecular classification of gastric adenocarcinoma Ye, Yuqing Yang, Wenyun Ruan, Xinjia Xu, Li Cheng, Wenxuan Zhao, Mengmeng Wang, Xin Chen, Xinyi Cai, Daren Li, Guanjie Wang, Yuhang Yan, Fangrong Lu, Xiaofan Jiang, Liyun Front Oncol Oncology Most gastric cancers (GC) are adenocarcinomas, whereas GC is a highly heterogeneous disease due to its molecular heterogeneity. However, traditional morphology-based classification systems, including the WHO classification and Lauren’s classification, have limited utility in guiding clinical treatment. We performed nonnegative matrix factorization (NMF) clustering based on 2752 metabolism-associated genes. We characterized each of the subclasses from multiple angles, including subclass-associated metabolism signatures, immune cell infiltration, clinic10al characteristics, drug sensitivity, and pathway enrichment. As a result, four subtypes were identified: immune suppressed, metabolic, mesenchymal/immune exhausted and hypermutated. The subtypes exhibited significant prognostic differences, which suggests that the metabolism-related classification has clinical significance. Metabolic and hypermutated subtypes have better overall survival, and the hypermutated subtype is likely to be sensitive to anti-PD-1 immunotherapy. In addition, our work showed a strong connection with previously established classifications, especially Lei’s subtype, to which we provided an interpretation based on the immune cell infiltration perspective, deepening the understanding of GC heterogeneity. Finally, a 120-gene classifier was generated to determine the GC classification, and a 10-gene prognostic model was developed for survival time prediction. Frontiers Media S.A. 2022-11-16 /pmc/articles/PMC9709214/ /pubmed/36465405 http://dx.doi.org/10.3389/fonc.2022.1024985 Text en Copyright © 2022 Ye, Yang, Ruan, Xu, Cheng, Zhao, Wang, Chen, Cai, Li, Wang, Yan, Lu and Jiang 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 | Oncology Ye, Yuqing Yang, Wenyun Ruan, Xinjia Xu, Li Cheng, Wenxuan Zhao, Mengmeng Wang, Xin Chen, Xinyi Cai, Daren Li, Guanjie Wang, Yuhang Yan, Fangrong Lu, Xiaofan Jiang, Liyun Metabolism-associated molecular classification of gastric adenocarcinoma |
title | Metabolism-associated molecular classification of gastric adenocarcinoma |
title_full | Metabolism-associated molecular classification of gastric adenocarcinoma |
title_fullStr | Metabolism-associated molecular classification of gastric adenocarcinoma |
title_full_unstemmed | Metabolism-associated molecular classification of gastric adenocarcinoma |
title_short | Metabolism-associated molecular classification of gastric adenocarcinoma |
title_sort | metabolism-associated molecular classification of gastric adenocarcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709214/ https://www.ncbi.nlm.nih.gov/pubmed/36465405 http://dx.doi.org/10.3389/fonc.2022.1024985 |
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