The diagnostic potential of salivary microRNA for early detection of oral squamous cell carcinoma in healthy vs. affected patients: A systematic review.

Abstract

Introduction: Oral squamous cell carcinoma (OSCC) is the most common oral malignancy, comprising over 90% of oral cancers. Despite advances in treatment, its late diagnosis and high recurrence contribute to poor prognosis. Conventional diagnostic methods often overlook early-stage disease. Salivary microRNAs (miRNAs), which are stable, non-coding RNAs involved in gene regulation, have emerged as promising non- invasive biomarkers for early OSCC detection. Objectives: This systematic review identifies salivary miRNAs with diagnostic value in OSCC and compares their expression in affected patients versus healthy controls. It also explores intermediate phenotypes such as oral potentially malignant disorders (OPMD), oral lichen planus (OLP), and OSCC in remission (OSCC-R) to understand miRNA changes across the disease spectrum. Materials and Methods: A systematic literature search of PubMed, Scopus, and Web of Science was conducted in line with PRISMA-P guidelines. Eligible studies included adult patients with OSCC, OPMD, OLP, or OSCC-R, and compared salivary miRNA expression with healthy individuals. Results: Fourteen studies comprising 914 participants met inclusion criteria. Thirty-seven differentially expressed salivary miRNAs were identified. miR-21, miR-31, and miR-423- 5p were consistently upregulated in OSCC, while miR-138, miR-424, and miR-30c-5p were downregulated. Several studies also examined OPMD, OLP, and OSCC-R, revealing intermediate expression patterns indicative of disease progression. Conclusion: Salivary miRNAs exhibit distinct expression profiles between OSCC and healthy controls, underscoring their diagnostic potential. miR-21 and miR-31 show strong biomarker capabilities, while tumor-suppressive miRNAs like miR-138 and miR-145 further support risk stratification. Including intermediate phenotypes provides additional insights into early detection and monitoring. Standardized methodologies and large-scale validation are needed for clinical implementation.