Supplementary Material for: Gastric Cancer Microbiome
datasetposted on 15.02.2021, 08:36 by Barra W.F., Sarquis D.P., Khayat A.S., Khayat B.C.M., Demachki S., Anaissi A.K.M., Ishak G., Santos N.P.C., dosSantos S.E.B., Burbano R.R., Moreira F.C., deAssumpção P.P.
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.