Meta-analysis reveals Helicobacter pylori mutual exclusivity and reproducible gastric microbiome alterations during gastric carcinoma progression

ABSTRACT

Accumulating evidence shows that the gastric bacterial community may contribute to the development of gastric cancer (GC). However, the reported alterations of gastric microbiota were not always consistent among the literature. To assess reproducible signals in gastric microbiota during the progression of GC across studies, we performed a meta-analysis of nine publicly available 16S datasets with standard tools of the state-of-the-art. Despite study-specific batch effect, significant changes in the composition of the gastric microbiome were found during the progression of gastric carcinogenesis, especially when the Helicobacter pylori (HP) reads were removed from analyses to mitigate its compositional effect as they accounted for extremely large proportions of sequencing depths in many gastric samples. Differential microbes, including Fusobacterium, Leptotrichia, and several lactic acid bacteria such as Bifidobacterium, Lactobacillus, and Streptococcus anginosus, which were frequently and significantly enriched in GC patients compared with gastritis across studies, had good discriminatory capacity to distinguish GC samples from gastritis. Oral microbes were significantly enriched in GC compared to precancerous stages. Intriguingly, we observed mutual exclusivity of different HP species across studies. In addition, the comparison between gastric fluid and mucosal microbiome suggested their convergent dysbiosis during gastric disease progression. Taken together, our systematic analysis identified novel and consistent microbial patterns in gastric carcinogenesis.

KEYWORDS:

• Meta-analysis
• gastric cancer
• gastric microbiome
• Helicobacter pylori
• oral microbes
• compositional effect

Author contributors

ZZ Xu: designed and supervised the study, interpreted the results and revised the manuscript. Y Li and Y Hu: collected data, performed bioinformatics analyses, interpreted the results, and wrote the manuscript. X Zhan: interpreted the results and revised the manuscript. Y Song, M Xu, S Wang and X Huang: assisted data collection and bioinformatics analyses.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data and code availability

Raw 16s rRNA sequencing data are available from the NCBI Sequence Read Archive (see Table 1 for the identifiers of included datasets). Codes have been uploaded to https://github.com/daydayup-ly/GC-meta-analysis for reproducibility.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2023.2197835.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China (grant no. 31970088) and the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (grant no. 2020YFA0509600).