Association of Microbiome with Oral Squamous Cell Carcinoma: A Systematic Review of the Metagenomic Studies

• Main Authors: Lee Su Mun, See Wye Lum, Genevieve Kong Yuiin Sze, Cheong Hock Yoong, Kwek Ching Yung, Liong Kah Lok, Divya Gopinath
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: oral cancer; microbiome; bacteriome; oral microbiota; metagenomics; microbiota
• Online Access: https://www.mdpi.com/1660-4601/18/14/7224
• ISSN: 1661-7827; 1660-4601

The past decade has witnessed a surge in epidemiological studies that have explored the relationship between the oral microbiome and oral cancer. Owing to the diversity of the published data, a comprehensive systematic overview of the currently available evidence is critical. This review summarises the current evidence on the metagenomic studies on the oral microbiome in oral cancer. A systematic search was conducted in Medline and Embase databases to identify original studies examining the differences in the oral microbiome of oral cancer cases and controls. A total of twenty-six studies were identified that reported differences in microbial abundance between oral squamous cell carcinoma (OSCC) and controls. Although almost all the studies identified microbial dysbiosis to be associated with oral cancer, the detailed qualitative analysis did not reveal the presence/abundance of any individual bacteria or a consortium to be consistently enriched in OSCC samples across the studies. Interestingly, few studies reported a surge of periodontopathogenic taxa, especially <i>Fusobacteria</i>, whereas others demonstrated a depletion of commensal taxa <i>Streptococci</i>. Considerable heterogeneity could be identified in the parameters used for designing the studies as well as reporting the microbial data. If microbiome data needs to be translated in the future, to complement the clinical parameters for diagnosis and prognosis of oral cancer, further studies with the integration of clinical variables, adequate statistical power, reproducible methods, and models are required.