2023 BMC oral health

Salivary level of microRNA-146a and microRNA-155 biomarkers in patients with oral lichen planus versus oral squamous cell carcinoma.

, , , , , , , ,

BMC oral health Vol. 23 (1) : 433 • Jun 2023

BACKGROUND: Oral lichen planus (OLP) is a chronic inflammatory disease of the oral mucosa, which has potential for malignant transformation. MicroRNAs play an important role in immunopathogenesis of OLP, and may be used for prediction of its malignant transformation. This study aimed to assess the salivary level of microRNA-146a and microRNA-155 biomarkers in patients with OLP and oral squamous cell carcinoma (OSCC). METHODS: In this case-control study, unstimulated saliva samples were collected from 60 patients, including 15 patients with dysplastic OLP, 15 OLP patients without dysplasia, 15 patients with OSCC, and 15 healthy controls according to the Navazesh technique. After RNA extraction, the expression of microRNA-146a and microRNA-155 was quantified by real-time quantitative polymerase chain reaction (RT-qPCR). The data were analyzed by the Kruskal-Wallis and Dunn-Bonferroni tests. RESULTS: The difference in expression of microRNA-146a and microRNA-155 among the four groups was significant (P < 0.05). Pairwise comparisons of the groups showed significantly higher expression of microRNA-146a in OLP (P = 0.004) and dysplastic OLP (P = 0.046) patients compared with the control group. Up-regulation of this biomarker in OSCC patients was not significant compared with the control group (P = 0.076). Up-regulation of micro-RNA-155 was only significant in OLP group, compared with the control group (P = 0.009). No other significant differences were found (P > 0.05). CONCLUSION: Considering the altered expression of MicroRNA-146a and microRNA-155 in dysplastic OLP and OSCC, their altered expression may serve as an alarming sign of malignancy. However, further investigations are still required.

No clinical trial protocols linked to this paper

Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.
PICO Elements

No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.

Paper Details
MeSH Terms
Associated Data

No associated datasets or code repositories found for this paper.

Related Papers

Related paper suggestions will be available in future updates.