Over a half million new cases of Head and Neck Squamous Cell Carcinoma (HNSCC) are diagnosed annually worldwide, however, 5 year overall survival is only 50% for HNSCC patients. Recently, high throughput technologies have accelerated the genome-wide characterization of HNSCC. However, comprehensive pipelines with statistical algorithms that account for HNSCC biology and perform independent confirmatory and functional validation of candidates are needed to identify the most biologically relevant genes. We applied outlier statistics to high throughput gene expression data, and identified 76 top-scoring candidates with significant differential expression in tumors compared to normal tissues. We identified 15 epigenetically regulated candidates by focusing on a subset of the genes with a negative correlation between gene expression and promoter methylation. Differential expression and methylation of 3 selected candidates (BANK1, BIN2, and DTX1) were confirmed in an independent HNSCC cohorts from Johns Hopkins and TCGA (The Cancer Genome Atlas). We further performed functional evaluation of NOTCH regulator, DTX1, which was downregulated by promoter hypermethylation in tumors, and demonstrated that decreased expression of DTX1 in HNSCC tumors maybe associated with NOTCH pathway activation and increased migration potential.

Department of Mathematics and Statistics The College of New Jersey Ewing New Jersey USA

Department of Otolaryngology Head and Neck Surgery Johns Hopkins Medical Institutions Baltimore Maryland USA

Department of Otolaryngology Mid Michigan Ear Nose and Throat East Lansing Michigan USA

Department of Pathology Johns Hopkins Medical Institutions Baltimore Maryland USA

Department of Pharmacology UC San Diego Moores Cancer Center La Jolla California USA

Department of Statistics The Chinese University of Hong Kong NT Shatin Hong Kong

Department of Surgery UC San Diego Moores Cancer Center La Jolla California USA

Department of Urology Northwestern University Chicago Illinois USA

Division of Oncology Biostatistics Department of Oncology Johns Hopkins Medical Institutions Baltimore Maryland USA

Institute of Molecular and Translational Medicine Faculty of Medicine and Dentistry Palacky University Olomouc Czech Republic

Laboratory of Systems Biology and Computational Genetics Vavilov Institute of General Genetics Russian Academy of Sciences Moscow Russia

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