Identifying a microbiome pattern in gastric cancer (GC) is hugely debatable due to the variation resulting from the diversity of the studied populations, clinical scenarios, and metagenomic approach. H. pylori remains the main microorganism impacting gastric carcinogenesis and seems necessary for the initial steps of the process. Nevertheless, an additional non-H. pylori microbiome pattern is also described, mainly at the final steps of the carcinogenesis. Unfortunately, most of the presented results are not reproducible, and there are no consensual candidates to share the H. pylori protagonists. Limitations to reach a consistent interpretation of metagenomic data include contamination along every step of the process, which might cause relevant misinterpretations. In addition, the functional consequences of an altered microbiome might be addressed. Aiming to minimize methodological bias and limitations due to small sample size and the lack of standardization of bioinformatics assessment and interpretation, we carried out a comprehensive analysis of the publicly available metagenomic data from various conditions relevant to gastric carcinogenesis. Mainly, instead of just analyzing the results of each available publication, a new approach was launched, allowing the comprehensive analysis of the total sample amount, aiming to produce a reliable interpretation due to using a significant number of samples, from different origins, in a standard protocol. Among the main results, Helicobacter and Prevotella figured in the “top 6” genera of every group. Helicobacter was the first one in chronic gastritis (CG), gastric cancer (GC), and adjacent (ADJ) groups, while Prevotella was the leader among healthy control (HC) samples. Groups of bacteria are differently abundant in each clinical situation, and bacterial metabolic pathways also diverge along the carcinogenesis cascade. This information may support future microbiome interventions aiming to face the carcinogenesis process and/or reduce GC risk.
Pathobiology

中文翻译：

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胃癌微生物组

由于研究人群、临床情况和宏基因组学方法的多样性导致的变异，因此在胃癌 (GC) 中识别微生物组模式存在很大争议。H. pylori仍然是影响胃癌发生的主要微生物，似乎是该过程的初始步骤所必需的。然而，还描述了额外的非幽门螺杆菌微生物组模式，主要是在致癌作用的最后阶段。不幸的是，大多数呈现的结果是不可重复的，并且没有一致的候选人来分享幽门螺杆菌主角。对宏基因组数据进行一致解释的限制包括过程的每个步骤中的污染，这可能会导致相关的误解。此外，可能会解决改变微生物组的功能后果。为了最大程度地减少由于样本量小以及生物信息学评估和解释缺乏标准化而导致的方法学偏差和局限性，我们对来自与胃癌发生相关的各种条件的公开可用的宏基因组数据进行了综合分析。主要是，不是仅仅分析每个可用出版物的结果，而是推出了一种新方法，允许对总样本量进行综合分析，旨在由于使用来自不同来源的大量样本而产生可靠的解释，在标准协议中。在主要结果中，Helicobacter和Prevotella 出现在每个组的“前 6”属中。螺杆菌是慢性胃炎（CG）、胃癌（GC）和相邻（ADJ）组中的第一个，而普氏菌是健康对照（HC）样本中的领先者。在每种临床情况下，细菌群的数量不同，细菌代谢途径也随着致癌作用的级联而不同。这些信息可能支持未来旨在应对致癌过程和/或降低 GC 风险的微生物组干预措施。
病理生物学