Researchers have discovered early signals from the body that indicate oral cavity cancer, allowing for earlier detection of the disease.

Researchers have long suggested that changes in the oral microbiome—a collection of bacteria in the mouth—may play a role in the development of squamous cell carcinoma of the oral cavity (SCCOC). However, previous studies have yielded conflicting results regarding the bacterial profiles in individuals with this disease. A new study aimed to clarify these discrepancies by analyzing data from 11 prior studies, ultimately providing more clarity to this theory, as reported.

Squamous cell carcinoma of the oral cavity is a life-threatening disease that arises in the cells lining the oral cavity and is often diagnosed at advanced stages, complicating treatment. According to the International Agency for Research on Cancer, approximately 450,000 people die from SCCOC each year.

A research team led by Dr. Zhencang Jie Xu from Southern Medical University in Shenzhen, China, identified consistent bacterial patterns in the saliva of individuals with SCCOC. The findings, published in the journal mSystems, confirmed that certain bacteria, including Streptococcus, Lactobacillus, and Prevotella, were more prevalent among patients with SCCOC.

Furthermore, the study revealed that the disease disrupts the normal structure of the microbiome, which is related to age and gender, making bacterial changes less predictable. Previous studies comparing saliva samples from healthy individuals and SCCOC patients produced ambiguous results—some indicated an increase in microbial diversity, while others reported a decrease.

Xu's team resolved this inconsistency by aggregating data, demonstrating that SCCOC changes not only the levels of individual bacteria but also how these microbes interact with the human body. The research indicated that these disruptions may play a role in disease progression, providing scientists with insights into potential early signs of the disease.

The researchers took another step toward combating the disease by training a machine learning model to identify microbial patterns associated with SCCOC. When tested, the model accurately identified individuals with SCCOC, with its accuracy increasing as more data were included. This suggests that a saliva-based screening tool for early detection of SCCOC may be developed in the future.

However, Xu cautions that further research is needed to confirm the findings in larger and more diverse populations before such a test can be utilized in clinical practice. Xu's team plans to continue studying bacterial patterns in different populations and to monitor high-risk individuals over time.

The scientists aim to understand why some individuals are more susceptible to SCCOC and whether specific bacterial changes can serve as early indicators of the disease. If these patterns are validated in larger studies, saliva analysis could become a straightforward, non-invasive method for early cancer detection, potentially improving survival rates.

As researchers uncover more connections between the microbiota and our overall health, the analysis of microorganisms may become a crucial component of future medical diagnostics for serious diseases at early stages.

Important! This article is based on the latest scientific and medical research and does not contradict them. The text is for informational purposes only and does not contain medical advice. For diagnosis, please consult a physician.