Mucin-microbiome signatures shape the tumor microenvironment in gastric cancer

Abstract

Background and aims We aimed to identify mucin-microbiome signatures shaping the tumor microenvironment in gastric adenocarcinomas and clinical outcomes. Methods We performed high-throughput profiling of the mucin phenotypes present in 108 gastric adenocarcinomas and 20 functional dyspepsia cases using validated mucin-based RT-qPCRs with subsequent immunohistochemistry validation and correlated the data with clinical outcome parameters. The gastric microbiota was assessed by 16S rRNA gene sequencing, taxonomy, and community composition determined, microbial networks analyzed, and the metagenome inferred in association with mucin phenotypes and expression. Results Gastric adenocarcinomas with an intestinal mucin environment or high-level MUC13 expression are associated with poor survival. On the contrary, gastric MUC5AC or MUC6 abundance was associated with a more favorable outcome. The oral taxa Neisseria, Prevotella, and Veillonella had centralities in tumors with intestinal and mixed phenotypes and were associated with MUC13 overexpression, highlighting their role as potential drivers in MUC13 signaling in GC. Furthermore, dense bacterial networks were observed in intestinal and mixed mucin phenotype tumors whereas the lowest community complexity was shown in null mucin phenotype tumors due to higher Helicobacter abundance resulting in a more decreased diversity. Enrichment of oral or intestinal microbes was mucin phenotype dependent. More specifically, intestinal mucin phenotype tumors favored the establishment of pro-inflammatory oral taxa forming strong co-occurrence networks. Conclusions Our results emphasize key roles for mucins in gastric cancer prognosis and shaping microbial networks in the tumor microenvironment. Specifically, the enriched oral taxa associated with aberrant MUC13 expression can be potential biomarkers in predicting disease outcomes.

Intratumor bacteria is associated with prognosis in clear-cell renal cell carcinoma

“…Recent debate over the landmark cancer microbiome study by Poore et al 1 has drawn much attention in the oncobiome community. In their recent report 25 , Salzberg’s team reasoned two major points that Poore’s data should be interpreted with caution, including contamination of human reads into microbial signaling and overinflation of microbial reads by machine learning.…”

“…Intratumor microorganisms, especially intratumor bacteria (ITB) signature has shown prognostic effect in a variety of cancer types including gastric cancer 1 , colorectal cancer 2 , hepatocellular cancer 3 , etc., establishing microbiome as a novel omics or “second genome” of cancer 4 . However, ITB may vary to vast extents that renders intratumor microbe findings in some cases, hardly reproducible 5 .…”