NYMC Faculty Publications

The Salivary Metatranscriptome as an Accurate Diagnostic Indicator of Oral Cancer

Author Type(s)

Faculty

DOI

10.1038/s41525-021-00257-x

Journal Title

NPJ Genomic Medicine

First Page

105

Last Page

105

Document Type

Article

Publication Date

12-8-2021

Department

Pharmacology

Second Department

Pathology, Microbiology and Immunology

Abstract

Despite advances in cancer treatment, the 5-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n = 433) collected from oral premalignant disorders (OPMD), OC patients (n = 71) and normal controls (n = 171). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to 83% (92.3% for stage 1 cancer) and specificity up to 97.9%. Our metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of taxa and functional pathways associated with OC. We demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.

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