Systematic analyses uncover robust salivary microbial signatures and host-microbiome perturbations in oral squamous cell carcinoma.

IF 5 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-01-28 DOI:10.1128/msystems.01247-24
Zewen Han, Yichen Hu, Xin Lin, Hongyu Cheng, Biao Dong, Xuan Liu, Buling Wu, Zhenjiang Zech Xu
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引用次数: 0

Abstract

Oral squamous cell carcinoma (OSCC) is a prevalent malignancy in the oral-maxillofacial region with a poor prognosis. Oral microbiomes play a potential role in the pathogenesis of this disease. However, findings from individual studies have been inconsistent, and a comprehensive understanding of OSCC-associated microbiome dysbiosis remains elusive. Here, we conducted a large-scale meta-analysis by integrating 11 publicly available data sets comprising salivary microbiome profiles of OSCC patients and healthy controls. After correcting for batch effects, we observed significantly elevated alpha diversity and distinct beta-diversity patterns in the OSCC salivary microbiome compared to healthy controls. Leveraging random effects models, we identified robust microbial signatures associated with OSCC across data sets, including enrichment of taxa such as Streptococcus, Lactobacillus, Prevotella, Bulleidia moorei, and Haemophilus in OSCC samples. The machine learning models constructed from these microbial markers accurately predicted OSCC status, highlighting their potential as non-invasive diagnostic biomarkers. Intriguingly, our analyses revealed that the age- and gender-associated signatures in normal saliva microbiome were disrupted in the OSCC, suggesting perturbations in the intricate host-microbe interactions. Collectively, our findings uncovered complex alterations in the oral microbiome in OSCC, providing novel insights into disease etiology and paving the way for microbiome-based diagnostic and therapeutic strategies. Given that the salivary microbiome can reflect the overall health status of the host and that saliva sampling is a safe, non-invasive approach, it may be worthwhile to conduct broader screening of the salivary microbiome in high-risk OSCC populations as implications for early detection.

Importance: The oral cavity hosts a diverse microbial community that plays a crucial role in systemic and oral health. Accumulated research has investigated significant differences in the saliva microbiota associated with oral cancer, suggesting that microbiome dysbiosis may contribute to the pathogenesis of oral squamous cell carcinoma (OSCC). However, the specific microbial alterations linked to OSCC remain controversial. This meta-analysis reveals robust salivary microbiome alterations. Machine learning models using differential operational taxonomic units accurately predicted OSCC status, highlighting the potential of the salivary microbiome as a non-invasive diagnostic biomarker. Interestingly, age- and gender-associated signatures in the normal salivary microbiome were disrupted in OSCC, suggesting perturbations in host-microbe interactions.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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