Human salivary microbiome as a potential non-invasive biomarker for early-onset colorectal cancer screening: a prospective study.

Authors

Junhai Zhen, Mingyue Dong, Yangbo Li, Beibei Cao, Fei Liao, Dandan Lin, Jixiang Zhang, Chuan Liu, Xianwei Zheng, Weiguo Dong

Published in

BMC microbiology. Jul 17, 2026. Epub Jul 17, 2026.

Abstract

The incidence of early-onset colorectal cancer (EOCRC) has been increasing in recent years, the carcinogenesis of which has been linked to oral microbiota alterations. However, it is unknown if the salivary microbiome could help detect EOCRC. Therefore, we aimed to determine whether salivary microbiome profiles can distinguish patients with EOCRC from healthy individuals and to evaluate their diagnostic performance as a non-invasive screening tool.
We collected saliva samples from 65 EOCRC patients and 63 control individuals, the microbiota of which was assessed using high-throughput 16S ribosomal RNA gene V3-V4 region sequencing. We then profiled the saliva microbiota and developed EOCRC screening models using machine learning (ML) algorithms.
The alpha diversity was comparable between salivary microbiomes of the EOCRC patients and control individuals, while the beta diversity exhibited statistical difference between two groups. A differential analysis of the genus-level saliva microbial communities revealed that, in the EOCRC patients, Prevotella, Actinomyces, and Corynebacterium were more abundant, whereas Fusobacterium, Haemophilus, norank_o__Absconditabacteriales_SR1, norank_c__Gracilibacteria, Peptococcus, Eikenella, and Eubacterium_yurii_group were less abundant. Furthermore, in developing the EOCRC screening model based on the salivary microbiome, the neural network model showed the best performance, achieving an AUC of 0.780 and a recall of 0.929, showing potential for distinguishing EOCRC patients from control individuals in this cohort.
This study first highlights the potential dysbiosis of salivary microbiota in EOCRC patients and suggests that salivary microbiome-based biomarkers may serve as potential non-invasive tools for EOCRC screening. Additional research with larger sample sizes would help to further validate these findings.
This study was registered with the Chinese Clinical Trial Registry (registration number: ChiCTR2400087634) on July 31, 2024, retrospectively registered.

PMID:
42469627
Bibliographic data and abstract were imported from PubMed on 18 Jul 2026.

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