A generalizable cross-continent prediction of esophageal squamous cell carcinoma using the oral microbiome
Esophageal squamous cell carcinoma (ESCC) is a disease with limited tools for early screening and a poor prognosis. Symptoms typically appear late, and early cancer is hard to detect without endoscopic screening, which is inaccessible in most high-risk areas. Saliva is easily accessible, and its microbiome composition can serve as a marker for upper gastrointestinal tract disease. We studied the potential utility of an oral microbiome signature for ESCC in South Africa, a region with a high incidence of the disease. In a cohort of 48 ESCC patients and 110 controls, we found marked alterations in the oral microbiome in patients with ESCC, including significantly reduced alpha diversity and increased Fusobacterium nucleatum. We devised machine learning models that classify ESCC using microbiome data, finding good performance on held-out samples (area under receiver operating characteristic curve of 0.96), and demonstrated generalization to data across independent studies conducted in different geographic regions (0.64-0.81). Overall, our results demonstrate the potential of the oral microbiome to serve as a non-invasive screening tool for ESCC.