A panel of microRNAs can be used to determine oral squamous cell carcinoma

Abstract

Background

Subjective histopathology is currently used to diagnose oral squamous cell carcinoma (OSCC). We tested if abundances of a panel of microRNA could be an objective OSCC indicator.

Method

Literature review enabled identification of 10 microRNAs associated with oral and head and neck malignancies. We extracted RNA from formalin-fixed paraffin embedded biopsies; 20 each with OSCC, dysplasia or histologically normal epithelium (HNE) and 10 with oral lichen planus (OLP). Relative abundances of microRNAs in HNE and OSCC were determined using reverse transcription then real time PCR with global mean normalization. MicroRNAs differentially expressed (test microRNA, T-miR) and non-differentially expressed (normalization microRNA, N-miR) were identified. The raw microRNA Cq data was incorporated in a developed algorithm that output a T-miR expression value (T-miREV) score. Raw Cq data from HNE, OSCC, dysplasia and OLP samples were then used to test the algorithm scoring and OSCC classification.

Results

Four test and normalisation microRNAs were identified. Algorithm output of T-mirEV >1 or <-1 indicated high and low OSCC probability score respectively and gave 88.9% sensitivity, 100% specificity and 93.5% accuracy. Grouping high and intermediate T-mirEV scores (T-miREV ≥-1) resulted in sensitivity of 90%, specificity of 65% and accuracy of 77.5% in OSCC classification. All 20 dysplasias and 8 of 10 OLP had T-miREV ≥-1 indicating intermediate to high probability of malignant changes.

Conclusion

A microRNA panel combined with our algorithm can identify tissue with probable oncogenic changes.

Impact

The developed algorithm serves as a baseline for prospective trials which may result in potential clinical utility.

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