Metabolites associated with microbes regulate human immunity, inhibit bacterial colonization, and promote pathogenicity. Integrating microbe and metabolome research in GC provides a direction for understanding the microbe-associated pathophysiological process of metabolic changes and disease occurrence. The present study included 30 GC patients with 30 cancerous tissues and paired non-cancerous tissues (NCs) as controls. LC-MS/MS metabolomics and 16S rRNA sequencing were performed to obtain the metabolic and microbial characteristics. Integrated analysis of the microbes and metabolomes was conducted to explore the coexistence relationship between the microbial and metabolic characteristics of GC and to identify microbial-related metabolite diagnostic markers. The metabolic analysis showed that the overall metabolite distribution differed between the GC tissues and the NC tissues: 25 metabolites were enriched in the NC tissues and 42 metabolites were enriched in the GC tissues. The α and β microbial diversities were higher in the GC tissues than in the NC tissues, with 11 differential phyla and 52 differential genera. In the correlation and coexistence integrated analysis, 66 differential metabolites were correlated and coexisted, with specific differential microbes. The microbes in the GC tissue likely regulated eight metabolic pathways. In the efficacy evaluation of the microbial-related differential metabolites in the diagnosis of GC, 12 differential metabolites (area under the curve [AUC] >0.9) exerted relatively high diagnostic efficiency, and the combined diagnostic efficacy of 5 to 6 microbial-related differential metabolites was higher than the diagnostic efficacy of a single feature. Therefore, microbial diversity and metabolite distribution differed between the GC tissues and the NC tissues. Microbial-related metabolites may be involved in eight major metabolism-based biological processes in GC and represent potential diagnostic markers.
与微生物相关的代谢物能够调节人体免疫、抑制细菌定植并促进致病性。在胃癌研究中整合微生物组与代谢组学，为理解代谢变化与疾病发生的微生物相关病理生理过程提供了方向。本研究纳入30例胃癌患者，采集30份癌组织及配对的癌旁正常组织作为对照。通过LC-MS/MS代谢组学和16S rRNA测序技术获取代谢与微生物特征。对微生物组与代谢组进行整合分析，探究胃癌微生物特征与代谢特征的共存关系，并筛选微生物相关代谢物诊断标志物。代谢分析显示，癌组织与正常组织的整体代谢物分布存在差异：正常组织富集25种代谢物，癌组织富集42种代谢物。癌组织的α和β微生物多样性均高于正常组织，共鉴定出11个差异菌门和52个差异菌属。在相关性及共存性整合分析中，66种差异代谢物与特定差异微生物存在相关性及共存关系。癌组织中的微生物可能调控八条代谢通路。在微生物相关差异代谢物对胃癌诊断效能的评估中，12种差异代谢物（曲线下面积[AUC]＞0.9）表现出较高的诊断效能，且5-6种微生物相关差异代谢物的联合诊断效能优于单一特征。因此，胃癌组织与正常组织在微生物多样性及代谢物分布上均存在差异。微生物相关代谢物可能参与胃癌中八条基于代谢的核心生物学过程，并具有成为潜在诊断标志物的价值。
肿瘤(癌症)患者之家