OP058: Development of an algorithm for oral squamous cell carcinoma risk assessment using micro-RNA markers

Abstract

Purpose The aim was to develop an algorithm for assessment of oral squamous cell carcinoma (OSCC) risk using microRNA (miR) abundance data. Material and methods Quantitative reverse transcription PCR (qRT–PCR) was conducted on RNA isolated from 20 each of formalin fixed and paraffin embedded (FFPE) biopsy samples that were histologically assessed as OSCC or histologically normal epithelium (HNE), as well as additonal oral tissue samples. A panel of 11 miR considered as potential biomarkers of OSCC were assessed with obtained Cq values normalized and statistically analyzed using qBase PLUS (Biogazelle) software. Results Seven miR showed statistically significant abundance differences between the 20 OSCC and 20 HNE. We then developed an algorithm for assessment of OSCC-risk (the “miR-OSCC-risk”) that gave sensitivity and specificity calculations for the HNE and OSCC samples tested. The algorithm output indicated high (flagged as red), indeterminate (amber) or low (green) risk, that showed a sensitivity of 87.5%; specificity of 92.3%; positive predictive value of 93.3%; negative predictive value of 85.7%; and an accuracy of 89.6%. The abundances of the panel miR and the predictive accuracy of the algorithm was tested further using other oral lesion samples. Oral mucosal lichen planus, mild dysplastic lesions and cytological scrapings of normal epithelia were in the majority of instances determined to be of low risk by the algorithm whereas the severely dysplastic lesions were in the majority determined to be of high risk and warranting further clinical and histological investigation. Conclusions The developed miR-OSCC-risk algorithm can be used with qRT-PCR miRNA abundance data to provide an indication of OSCC risk that has potentially significant clinical utility. The diagnostic procedure developed here could be of benefit in the assessment of oral lesions of unknown pathology by the targeting of lesions requiring biopsy.