Núcleo de Pesquisas em Oncologia, Universidade Federal do Pará, Belém, Brazil.
Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém, Brazil.
Pathobiology. 2021;88(2):156-169. doi: 10.1159/000512833. Epub 2021 Feb 15.
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.
由于研究人群、临床情况和宏基因组方法的多样性导致的变化,鉴定胃癌(GC)中的微生物组模式存在很大争议。幽门螺杆菌仍然是影响胃癌发生的主要微生物,似乎是该过程初始步骤所必需的。然而,也描述了另一种非幽门螺杆菌微生物组模式,主要在癌变的最后步骤。不幸的是,提出的大多数结果不可重复,并且没有共识的候选者来分享幽门螺杆菌的主角地位。达成一致解释宏基因组数据的限制包括在整个过程的每一步都存在污染,这可能导致相关的误解。此外,还可以解决微生物组改变的功能后果。为了最大限度地减少由于样本量小和生物信息学评估和解释缺乏标准化而导致的方法偏差和限制,我们对与胃癌发生相关的各种条件的公开可用宏基因组数据进行了全面分析。主要是,我们没有仅仅分析每个现有出版物的结果,而是提出了一种新方法,允许对总样本量进行全面分析,旨在通过使用来自不同来源的大量样本,在标准方案中产生可靠的解释,从而减少由于样本数量少和缺乏生物信息学评估和解释的标准化而导致的方法偏差和限制。主要结果中,弯曲菌属和普雷沃菌属在每个组的“前 6 位”属中。弯曲菌属是慢性胃炎(CG)、胃癌(GC)和相邻(ADJ)组中的第一个,而普雷沃菌属是健康对照组(HC)样本中的主要细菌。在每种临床情况下,细菌群的丰度不同,细菌代谢途径也沿着癌变级联过程发生分歧。这些信息可能支持未来的微生物组干预,以应对癌变过程和/或降低 GC 风险。