Decoding the gene expression program evolved in odontogenic keratocyst by the combination of deep transcriptomics analyses and computational biology tools

Background Transcriptomics analysis of odontogenic keratocysts (OKCs) has been described in 3 microarray-based studies utilizing fresh-frozen or formalin-fixed paraffin-embedded samples. To date, RNA-sequencing (RNA-seq) technology has been applied only for the transcriptomics analysis of OKC-derived fibroblasts. Objective RNA-seq analysis of the entire OKC tissue will enable the identification of the gene expression profile that accompanies OKC development. Methods Total RNA was extracted from formalin-fixed paraffin-embedded samples of 3 OKCs and 3 dental follicles of third molars. RNA library preparation and 150-bp paired-end sequencing were implemented using an Illumina Hiseq4000 Sequencer followed by application of advanced computational biology tools; for example, edgeR software package and Galaxy platform. Results RNA-sequencing resulted in ∼15 to 40 million paired-end reads per sample. A total of 1335 differentially expressed genes (DEGs) between OKCs and dental follicles (fold change ≥2) were captured. Gene ontology classification analysis identified markers of epidermal cell development and differentiation (e.g., DSP, TFAP2A, FOXM1) among the top upregulated DEGs, markers of extracellular matrix organization and nervous system regulation (e.g., ADAMTS14, COL3A1, NAV3), among the top downregulated DEGs, and various transcription factors in both categories exemplified by the upregulation of the epidermal master regulator TP63 in OKCs. Conclusions This is the first RNA-seq-based study of the entire OKC. The preliminarily results show significant upregulation of genes commuting to epidermis development/differentiation, a finding consistent with OKC histopathologic phenotype. The identification of novel DEGs is critical to access unknown elements of the molecular mechanism underlying OKC pathogenesis and biologic behavior, with potential for future therapeutic applications.