Abstract 3171: Analysis of copy number and LOH in germline samples from different tumor types in The Cancer Genome Atlas (TCGA) project.
Authors: Shams Soheil , Keshavan Raja , Schiffman Joshua D. 
Published: August 2014

Using data from The Cancer Genome Atlas (TCGA) project and HapMap consortium, we examined the hypothesis that existing copy number polymorphisms might predispose individuals to cancer and if different common CNVs bias toward different cancer types. This analysis was performed using a subset of the TCGA data, obtained from blood derived “normal” samples of cancer patients. All the data was generated using Affymetrix SNP 6.0 arrays (Affymetrix, Inc.) and processed using Nexus Copy Number ver. 6.1 (BioDiscovery, Inc.). The project contained 451 Glioblastoma (GBM), 353 Colon cancer, and 245 Skin cancer samples in addition to 211 HapMap samples which we used as reference since these individuals were supposed to be healthy. Using Fisher's Exact test, we compared each different cancer types to the HapMap samples to identify regions of copy number change with FDR corrected p-value of less than 0.05 and difference in frequency between each population of at least 10%. Many of the regions found in this process encompass regions identified as common CNV polymorphisms as reported in the Database of Genomic Variance (DGV). For example, a polymorphic region on 8p23.1 containing a number of genes from the Beta defensin family involved in defense response to bacterium were seen significantly gained in germline samples obtained from cancer patients as compared to the HapMap samples (11% in HapMap, 42% in Colon Cancer, 28% in GBM, and 32% in Skin cancer). Additionally, some interesting regions were identified that were not seen as polymorphic in the general population, did not show up in the HapMap samples or reported in DGV, but had high prevalence in the blood derived normal samples from cancer patients. Using gene enrichment analysis on genes discovered in these regions we identified a number of known cancer specific pathways that were highly enriched (e.g. KEGG Glioma and Melanoma pathways being statistically significantly enriched). Looking at the effected genes in these pathways we identified small focal and recurrent events that often only spanned a small portion of a gene covering a few exons. This included genes such as PIK3CA where a focal gain covering exons 10-14 were observed in none of the HapMap samples but in 21% of the germline of patients with Colon cancer, 9% of GBM and 14% of Skin cancer patients. A similar focal and recurrent gain was observed in KIT covering exons 2-7 with no gains in the HapMap samples and 55% in Colon, 15% in GBM, and 50% in Skin cancer patients. Similar observations were also made for other well-known cancer genes such as RAF1 and EGFR but to a lesser extent. We are in a process of comparing matched tumor/normal cases to further investigate possible evolution of these changes from the germline to the surrounding tissue (also available from the TCGA database) to the primary tumor samples.

Citation Format: Soheil Shams, Raja Keshavan, Joshua D. Schiffman. Analysis of copy number and LOH in germline samples from different tumor types in The Cancer Genome Atlas (TCGA) project. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3171. doi:10.1158/1538-7445.AM2013-3171