Oral Lichen Planus (OLP) is a common chronic inflammatory disease, which involves the mucous membranes of the oral cavity, with an overall age standardized prevalence of 1.27% (0.96% in men and 1.57% in women) as reported in the literature by McCartan and Healy. In our previous work, we exploited a bioinformatics approach, namely the Leader Gene Algorithm (LGA), enabling to underpin the main hub genes (termed as Leader Genes) involved in biological processes. In the case of OLP, we found a complex network made up of 132 genes and, in particular, we found five Leader Genes (namely, JUN, EGFR, FOS, IL2, and ITGB4). Using a subsequent bioinformatics algorithm, we managed to find the 48.39% of the already established OLP-related microRNAs (miRNAs), suggesting that at least half of the OLP-related microRNAome (miRNAome) finely tunes few, highly interconnected hub genes. Now, we would use real clinical samples in order to validate our predicted biomarkers, using molecular biology techniques, mass-spectrometry (MS) and ad hoc in-house developed instruments, such as Nanoconductimetry via Quartz Crystal Microbalance with Dissipation factor monitoring (QCM_D). A unique combination of genomics and proteomics approaches can indeed represent a promising innovation for a personalized treatment of OLP and oral cancer.

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