Comprehensive Analysis of Mutation-Based and Expressed Genes-Based Pathways in Head and Neck Squamous Cell Carcinoma

Abstract Background: Over- or under-expression of mRNA results from genetic alterations. Comprehensive pathway analyses based on mRNA expression are as important as single gene level mutations. This study aimed to compare the mutation-and mRNA expression-based signaling pathways in head and neck squamous cell carcinoma (HNSCC), and to match these with potential drug or druggable pathways.Methods: Altogether, 93 recurrent/metastatic HNSCC patients were enrolled. We performed targeted gene sequencing using Agilent 244 customized gene panel for NGS, and nanostring nCounter® for mRNA expression. mRNA expression was classified into over- or under expression groups based on the expression levels that showed 2-fold change in tumor compared with non-tumor tissues. We investigated mutational and nanostring data using the CBSJukebox® system, which is a big-data driven platform to analyze druggable pathways, genes, and protein-protein interaction. Analyses were based on 14 databases related to protein interaction, signaling pathways and drugs such as NCBI, Uniprot, KEGG, Biogrid, DIP, HPRD, and Drugbank. High score interaction genes were mapped to investigate druggable pathways. We calculated Treatment Benefit Prediction Score (TBPS) to identify suitable drugs. Results: By mapping the high score interaction genes to identify druggable pathways, we found that highly related signaling pathways with mutation mapping were Influenza A, pathways in cancer, EBV, HPV, HTLV-1 pathways. Based on mRNA expression and interaction gene scoring model, several pathways were found to be associated with over- and under-expression. Comparison between mutation-based pathway and over-/under-expressed genes-based pathways, we observed that 19.8% of NGS based pathways matched with mRNA over-expressed genes-based pathways, and 43.2% of NGS based pathways consist with mRNA under-expressed genes-based pathways. TBPS found several matching drugs such as immune checkpoint inhibitors, EGFR inhibitors, and FGFR inhibitors.Conclusions: Mutation-based pathway was associated with mRNA under-expressed genes-based pathway. These results suggest that HNSCCs are mainly caused by the loss-of-function mutations. However, big data based platform for druggable pathway can find potential matching drugs.