代谢重编程决定了肿瘤分子属性和治疗潜力。然而，胃癌（GC）的综合代谢特征仍不清楚。在此，基于代谢特征的聚类分析确定了具有不同分子和临床特征的三种亚型：MSC1 显示出更好的预后以及三羧酸 (TCA) 循环和脂质代谢的上调，以及频繁的 TP53 和 RHOA 突变； MSC2 预后中等，核苷酸和氨基酸代谢升高，肠道组织学和错配修复缺陷 (dMMR) 丰富； MSC3 预后不良，聚糖和能量代谢增强，伴有弥漫性组织学和频繁的 CDH1 突变。山东省医院 (SDPH) 内部数据集以及匹配的转录组学、代谢组学和空间代谢组学分析也验证了这些发现。此外，我们构建了代谢亚型相关预后基因（MSPG）评分模型来量化单个肿瘤的活性，并发现与铜凋亡信号呈正相关。总之，对代谢物特征的全面识别可以增强对 GC 多样性和异质性的理解。版权所有 © 2024 作者。由爱思唯尔公司出版。保留所有权利。

Metabolic reprogramming dictates tumor molecular attributes and therapeutic potentials. However, the comprehensive metabolic characteristics in gastric cancer (GC) remain obscure. Here, metabolic signature-based clustering analysis identifies three subtypes with distinct molecular and clinical features: MSC1 showed better prognosis and upregulation of the tricarboxylic acid (TCA) cycle and lipid metabolism, combined with frequent TP53 and RHOA mutation; MSC2 had moderate prognosis and elevated nucleotide and amino acid metabolism, enriched by intestinal histology and mismatch repair deficient (dMMR); and MSC3 exhibited poor prognosis and enhanced glycan and energy metabolism, accompanied by diffuse histology and frequent CDH1 mutation. The Shandong Provincial Hospital (SDPH) in-house dataset with matched transcriptomic, metabolomic, and spatial-metabolomic analysis also validated these findings. Further, we constructed the metabolic subtype-related prognosis gene (MSPG) scoring model to quantify the activity of individual tumors and found a positive correlation with cuproptosis signaling. In conclusion, comprehensive recognition of the metabolite signature can enhance the understanding of diversity and heterogeneity in GC.Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.