Abstract
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.
Highlights
As the fifth most common cancer, Head and Neck Squamous Cell Carcinoma (HNSCC) is responsible for 600,000 new cases and over 300,000 deaths per year worldwide [1, 2]
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
Candidate genes with differential expression in HNSCC detected by outlier statistics In order to identify relevant gene candidates in HNSCC, we used gene expression array data from a discovery cohort of 44 HNSCC primary tumors and 25 non-cancer normal tissue samples described in our previous publications (Supplementary Table 1 and [21,22,23])
Summary
As the fifth most common cancer, Head and Neck Squamous Cell Carcinoma (HNSCC) is responsible for 600,000 new cases and over 300,000 deaths per year worldwide [1, 2]. Development of low toxicity targeted therapeutics and biomarkers for early detection could improve survival rate and quality of life for HNSCC patients. The process of single-gene investigation is time and labor intensive, while high-throughput profiling enables more rapid discovery of targetable disease-specific modifications. Recent high throughput profiling of HNSCC identified number of targetable disease-specific modifications, such as genetic mutations and differentially expressed genes in HNSCC primary tissues or cell lines compared to normal samples [8,9,10,11,12,13,14,15,16]. Integration of high throughput data from expression and methylation platforms may enhance accurate discovery of cancerdriving genes so they can be used as disease biomarkers or therapy targets [19]
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