A quantitative mouth-to-feces (MF) index measuring oral-to-gut microbial transmission reveals disease-specific signatures that enable accurate, non-invasive diagnosis of gastrointestinal cancers across multiple independent cohorts, with higher sensitivity than the fecal occult blood test.
Key Findings
Methods
A quantitative mouth-to-feces (MF) index was established to measure oral-to-gut microbial transmission using paired oral and fecal microbiome data from 507 participants.
Participants included healthy controls and patients with metabolic disorders or gastrointestinal cancers.
The study analyzed paired oral and fecal microbiome samples simultaneously from the same individuals.
The MF index provides a quantitative measure of ectopic colonization of gut sites by oral bacteria.
The cohort spanned multiple disease categories, enabling comparison across health states.
Results
The MF index revealed elevated mouth-to-gut microbial transmission in gastrointestinal cancer patients.
Cancer patients showed higher MF transmission compared to healthy controls and metabolic disorder patients.
The MF index was strongly associated with host metabolic and inflammatory indicators.
Elevated oral-to-gut transmission appears to be a disease-specific signature distinguishing cancer from other conditions.
The association with inflammatory markers suggests a potential mechanistic link between oral microbial translocation and cancer-related systemic inflammation.
Results
A random forest classifier trained on transmitted microbial taxa accurately distinguished gastric and colorectal cancer from healthy controls.
The classifier was validated across seven independent cohorts.
The model demonstrated accurate classification even when trained solely on oral microbiome data.
Using transmitted taxa (those shared between oral and fecal compartments) as features underpinned the classifier.
Generalizability across seven cohorts suggests the transmission signatures are robust and not cohort-specific.
Results
The MF-based classifier achieved markedly higher sensitivity than the fecal occult blood test (FOBT) for gastrointestinal cancer detection.
The MF-based model was directly benchmarked against the conventional fecal occult blood test (FOBT).
The MF model outperformed FOBT in sensitivity, meaning it detected a greater proportion of true cancer cases.
FOBT is a standard non-invasive screening test, making this comparison clinically relevant.
Higher sensitivity indicates fewer missed cancer diagnoses with the MF-based approach.
Results
Oral microbiome data alone was sufficient to build a classifier capable of diagnosing gastrointestinal cancers.
The random forest model trained solely on oral microbiome data maintained accurate classification of gastric and colorectal cancer.
This finding highlights oral microbiome sampling as a standalone, non-invasive diagnostic modality.
Oral sampling is less burdensome than fecal collection, potentially improving patient compliance in screening programs.
The result suggests oral microbial composition reflects gut disease states through transmission signatures.
Conclusions
MF microbial profiling is proposed as a generalizable, non-invasive framework for gastrointestinal cancer diagnosis and risk stratification.
The framework leverages the spatial compartmentalization of the human microbiome and cross-site transmission patterns.
Validation across seven independent cohorts supports generalizability beyond the discovery cohort of 507 participants.
The approach covers both gastric cancer and colorectal cancer, suggesting broad applicability across gastrointestinal malignancies.
Risk stratification, in addition to diagnosis, is highlighted as a potential application of the MF index.
Background
Oral bacteria can ectopically colonize distal gut sites and this phenomenon is associated with disease states.
The study provides quantitative evidence that oral bacteria travel to and colonize the gut.
This mouth-to-gut transmission is not uniform across health conditions, being elevated in cancer.
The concept of spatially compartmentalized microbiome being disrupted in disease underpins the study's biological framework.
Association with metabolic and inflammatory host indicators suggests transmission is tied to systemic host physiology.
What This Means
This research suggests that bacteria from the mouth can travel to and colonize the gut, and that the extent of this 'mouth-to-gut' transmission is significantly higher in people with gastrointestinal cancers like stomach and colorectal cancer compared to healthy individuals. The researchers studied 507 people by collecting both saliva/oral and stool samples simultaneously, then developed a scoring system called the MF (mouth-to-feces) index to measure how much oral bacteria were showing up in the gut. They found that this score was linked not only to cancer but also to markers of inflammation and metabolic health in the body.
Using the specific bacteria that appeared to have traveled from the mouth to the gut, the researchers built a computer-based diagnostic tool (a random forest classifier) that could tell apart cancer patients from healthy people. Remarkably, this tool worked accurately even when it only used data from oral (mouth) samples, and it held up when tested across seven separate groups of patients from different studies. When compared head-to-head with the standard non-invasive cancer screening test — the fecal occult blood test, which looks for hidden blood in stool — the new MF-based approach detected substantially more cancers.
This research suggests that monitoring which oral bacteria end up in the gut could serve as a new way to screen for stomach and colorectal cancers without invasive procedures. Because collecting a mouth swab or saliva sample is simpler and more comfortable than other tests, this approach could potentially make cancer screening more accessible. The findings open the door to using patterns of microbial movement between body sites as a diagnostic and risk-assessment tool for gastrointestinal disease.