Machine learning models diagnose oral squamous cell carcinoma based on cross-cohort oral microbial signatures.

ABSTRACT:

Introduction

The saliva microbiome of oral squamous cell carcinoma (OSCC) patients has been gradually unveiled, but there is a lack of cross-cohort studies, and there is no non-invasive diagnostic model across cohorts for OSCC.

Methods

This study aimed to investigate the differences in saliva microbial composition between OSCC patients and healthy individuals using cross-cohort saliva microbiome data, comprising 354 healthy individuals and 311 OSCC patients (total n=665).

Results

We found significant differences in saliva microbial composition between OSCC patients and healthy people. Seven microorganisms were significantly reduced and seven were significantly increased in OSCC patients, serving as potential biomarkers. Machine learning models, including Random

SUBMITTER: Wang M 

PROVIDER: S-EPMC12815763 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature