ABSTRACT Introduction: Oral cancer imposes substantial global health challenges, with emerging evidence linking microbial dysbiosis to disease development. This narrative review examines whether modulating oral bacterial communities represents a viable prevention strategy. Methods: We conducted a narrative synthesis of peer-reviewed literature (2020–2025) using PubMed, Scopus, and Web of Science. Search terms included “oral microbiome,” “oral cancer,” “oral squamous cell carcinoma,” “Fusobacterium nucleatum,” “Porphyromonas gingivalis,” “probiotics,” and “dysbiosis.” We prioritized systematic reviews, meta-analyses, randomized controlled trials (RCTs), and mechanistic studies examining bacterial signatures, carcinogenic pathways, and microbiome-targeted interventions. Results: We identified 36 relevant studies, including 8 meta-analyses, 15 systematic reviews, 7 RCTs, and 6 mechanistic investigations. Meta-analyses consistently demonstrate enrichment of Fusobacterium nucleatum (standardized mean difference 0.65, 95% confidence interval CI 0.43–0.87), Porphyromonas gingivalis (hazard ratio 1.74, 95% CI 1.15–2.62), and Prevotella species in oral squamous cell carcinoma (OSCC) tissues. Periodontitis represents an independent risk factor with pooled odds ratios (OR) of 3.17 (95% CI 1.78–5.64) and 3.32 (95% CI 1.84–5.99). Mediterranean dietary patterns show the strongest intervention evidence with 60%–80% risk reduction (OR 0.20–0.565). Probiotics effectively prevent oral mucositis in cancer therapy (risk reduction 35%, risk ratio 0.65, 95% CI 0.53–0.81). Salivary microbiome profiling demonstrates diagnostic potential for OSCC detection. Discussion: Compelling associations exist between oral dysbiosis and cancer development, though definitive proof of causation remains incomplete. The primary limitation involves the absence of randomized trials using cancer incidence as endpoints. Current evidence supports periodontal disease management and dietary counseling, while probiotic cancer prevention requires rigorous clinical validation before implementation.
Ahmed Abdulaziz Almohammadi (Thu,) studied this question.