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Metabolism-associated molecular classification of gastric adenocarcinoma.


ABSTRACT: 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.

SUBMITTER: Ye Y 

PROVIDER: S-EPMC9709214 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Metabolism-associated molecular classification of gastric adenocarcinoma.

Ye Yuqing Y   Yang Wenyun W   Ruan Xinjia X   Xu Li L   Cheng Wenxuan W   Zhao Mengmeng M   Wang Xin X   Chen Xinyi X   Cai Daren D   Li Guanjie G   Wang Yuhang Y   Yan Fangrong F   Lu Xiaofan X   Jiang Liyun L  

Frontiers in oncology 20221116


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-associate  ...[more]

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