Metagenomic characterization of oral microbiome signatures to predict upper gastrointestinal and pancreaticobiliary cancers: a case–control study - Sujin Oh; Jaihwan Kim; Cheol Min Shin; Hyo-Jung Lee; Hye Seung Lee; Kyoung Un Park (Journal of Translational Medicine)
Abstract Background This study investigated the oral microbiome signatures associated with upper gastrointestinal (GI) and pancreaticobiliary cancers. Methods Saliva samples from cancer patients and age- and sex-matched healthy controls were analyzed using 16S rRNA-targeted sequencing, followed by comprehensive bioinformatics analysis. Results Significant dissimilarities in microbial composition were observed between cancer patients and controls across esophageal cancer (EC), gastric cancer (GC), biliary tract cancer (BC), and pancreatic cancer (PC) groups (R2 = 0.067, = 0.075, = 0.068, and = 0.044; p = 0.001, = 0.001, = 0.002, and = 0.004, respectively). Additionally, the oral microbiome composition significantly differed by the four cancer sites (p = 0.001 for EC vs. GC, EC vs. BC, EC vs. PC, GC vs. BC, and GC vs. PC; p = 0.013 for BC vs. PC). We built oral metagenomic classifiers to predict cancer and selected specific microbial taxa with diagnostic properties. For EC, the classifier differentiated cancer patients and controls with good accuracy (area under the curve [AUC] = 0.791) and included three genera: Akkermansia, Escherichia-Shigella, and Subdoligranulum. For GC, the classifier exhibited high discriminative power (AUC = 0.961); it included five genera (Escherichia-Shigella, Gemella, Holdemanella, Actinomyces, and Stomatobaculum) and three species (Eubacterium sp. oral clone EI074, Ruminococcus sp. Marseille-P328, and Leptotrichia wadei F0279). However, microbial taxa with diagnostic features for BC and PC were not identified. Conclusions These findings suggested that the oral microbiome composition may serve as an indicator of tumorigenesis in upper GI and pancreaticobiliary cancers. The development of oral metagenomic classifiers for EC and GC demonstrates the potential value of microbial biomarkers in cancer screening.