Oral bacteriome and its association with cancer-specific mortality

Objectives: Cancer is the leading cause of death in the United States, with more than 600,000 deaths annually. Emerging evidence suggests that alterations in the oral microbiota, one of the body's most diverse microbial communities, may influence cancer outcomes. However, associations between microbial diversity and composition with cancer mortality remain poorly understood. We aimed to identify associations between oral microbiome diversity and bacterial abundance with cancer-specific mortality. Methods: We analyzed 441 participants from the 2009-2012 National Health and Nutrition Examination Study (NHANES) linked to National Death Index (NDI). Oral rinse samples were 16S rRNA V4 amplicon-sequenced and resolved to the genus level using SILVA v123. Alpha diversity was calculated after rarefaction to 2,000 reads. Cancer deaths were defined using ICD-10 malignant neoplasm codes. As an exploratory analysis, supervised random forest models (1,000 trees; 100 random seeds; “randomForest” R package) were applied to centered log-ratio (CLR) transformed abundance values to identify genera associated with cancer-mortality, with importance measured by Mean Decrease Accuracy. Survey-weighted multivariable Cox proportional models estimated adjusted hazard ratios for cancer-specific mortality by alpha diversity and genus abundance, adjusting for age, sex, race/ethnicity, poverty income ratio, lifetime smoking history, and self-rated oral health. Bonferroni correction accounted for multiple hypothesis testing. Results: Higher alpha diversity was associated with lower cancer-specific mortality, with significant inverse associations for Shannon (aHR 0.72, 95% CI 0.53-0.98) and Inverse Simpson's Index (aHR 0.13, 95% CI 0.02-0.73), while Faith's Phylogenetic Diversity and observed ASV richness were not significant. In the exploratory random analysis using random forest, Prevotella_7, Gemella, Bergeyella, Fusobacterium, Ruminococcaceae_UCG-014, Alloprevotella, and Oribacterium emerged as potential discriminatory genera for cancer deaths versus non-cancer deaths (MDA > 5.75). In adjusted Cox models, participants with Bergeyella abundance above the median (aHR 0.59; 95% CI 0.35-0.99) and participants with Oribacterium (aHR 0.52; 95% CI 0.32-0.81) had lower cancer-specific mortality. After adjustment, the other genera identified in the exploratory analysis were not significant for cancer-mortality. Conclusion: The oral microbiome harbors bacteria that may be potentially predictive of cancer-specific mortality. Although prior literature provides limited support for Bergeyella's and Oribacterium's roles in cancer mortality, our results underscore the need for further studies to validate our results and for examining biomarkers and targets for microbiome-informed prevention strategies.