Abstract 38: Copy number aberration detected in head and neck carcinomas using OncoSNP and influence on gene expression

Abstract

Abstract Introduction: It is important to understand the molecular mechanisms acting in potentially malignant epithelial lesions of the oral mucosa and determine whether the disorder will remain stable, regress or progress to squamous cell carcinoma (OSCC). Some may transform to invasive OSCC independent of developing dysplasia as an intermediate step. Understanding the mechanisms and identifying predictive biomarkers is critical for treatment decisions. Accurate DNA copy number alterations (CNAs) and loss of heterozygosity (LOH) estimates in cancer cells are now detectable using single nucleotide polymorphism (SNP) genotyping microarrays and can be combined with gene expression data. Discovering genomic structural aberrations and their relationship to the expression levels of the genes therein can provide a basis for a deeper understanding of the molecular mechanisms leading to dysplasia and cancer. The main goal of this work is to explore the influence of structural mutations on gene expression in cancer. To do so we are using a dataset of 32 head and neck samples. Immortal carcinoma and dysplasia information were obtained from cell lines, while the mortal carcinoma and dysplasia information were obtained from primary cultures. Methods: The genotypic data were obtained from Illumina 550K Bead arrays and the gene expressions from Affymetrix HGU-133A microarrays. The CNAs and LOHs were determined using a newly developed statistical framework, OncoSNP, which can process complex data derived from heterogeneous samples. The software uses both the log R ratio and the B allele frequency in a Bayesian framework to estimate the genomic aberrations. Results: Firstly the genomic pattern of CNA and LOH were studied, displaying strong structure and identifying a subgroup of immortal samples with high level of amplification across all chromosomes. Secondly the matching gene expressions were analyzed. Finally both genomic and gene expression datasets were combined and genes of high/low gene expression response to underlying copy number changes were searched for. As a result we produced 3 classes of genes that show different behaviour in their expression levels as a response to copy number changes. The 1st group is formed by those genes whose gene expression correlates significantly to the underlying CN changes, we use a Spearman correlation. The 2nd and 3rd gene lists were chosen such that they do not correlate to CN but whose gene expression show high/low coefficient of variation respectively. We then went on to perform pathway analysis to show that these gene sets belong to distinct pathways related to cancer. The non responding group is enriched for genes related to metabolism, while the responding group is enriched for genes belonging to cell signalling pathways. These findings will help to understand how relatively large and variable genomic changes through LOH and CNA can lead to similar disease phenotypes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 38. doi:10.1158/1538-7445.AM2011-38