Yonsei University team develops model to detect cancer using only oral bacteria

A research team at Yonsei University has developed a novel model capable of distinguishing between stomach and colorectal cancer using only bacteria found in the mouth. The study, led by Professor Kim Ji-hyun of the Department of Systems Biology, identified a new clue within oral microbes that can differentiate between healthy individuals and cancer patients.

The researchers developed a "oral-fecal (MF) microbial transfer index" by measuring the distribution of microbes from the oral cavity to the gastrointestinal tract. They found that this index effectively differentiates between colorectal and stomach cancer. This non-invasive diagnostic strategy, based on microbial communities (microbiome), offers a promising approach to cancer detection.

Stomach and colorectal cancers are leading causes of cancer incidence and mortality, making early detection crucial. The incidence of these cancers is increasing among younger populations, with "young colorectal cancer" rates being particularly high among OECD countries. Adults swallow about a liter of saliva daily, introducing approximately one trillion oral microbes into their digestive system. While the digestive tract typically prevents oral microbes from surviving, the researchers focused on the possibility that this barrier weakens in individuals with various diseases.

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The fact that we can identify cancer-related signals simply by rinsing the mouth has significant implications for lowering the barrier to cancer screening.

The study revealed that the microbial transfer index was higher in patients with stomach and colorectal cancer. The distribution of transferred microbes in the oral cavity and gut also correlated with lifestyle factors and health indicators such as exercise habits, blood cholesterol levels, white blood cell counts, and thyroid function. This suggests that the influx of oral microbes into the gut is linked not only to cancer but also to overall health status.

Different microbial transfer patterns were observed depending on the type and stage of cancer, with some patterns appearing even in the early stages. This indicates that these patterns reflect the cancer's characteristics and progression, holding potential as early diagnostic markers. The research team constructed a classification model using the random forest technique to distinguish between healthy individuals and those with stomach or colorectal cancer based on transferred microbial information. Notably, the model could detect cancer-related signals using only oral samples, which are easier to collect and less invasive than stool samples, potentially simplifying cancer screening.

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This study is significant because it develops a quantitative index to measure the phenomenon of oral microbes being found in the gut on an individual basis and connects it to a model for distinguishing stomach and colorectal cancer, thereby presenting the clinical applicability of oral-gut microbial transfer for the first time.