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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 |
Sumario: | 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. |
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