Abstract LB-405: High density SNP array copy number analysis of esophageal adenocarcinoma: Associations with clinical outcomes

Abstract

Abstract Introduction: Identification of common genomic changes in tumors has revealed many genes involved in carcinogenesis and has led to prognostic tests and/or therapeutic intervention strategies. While there is considerable overlap of genomic changes and genes identified in different tumors, there are also many tumor-specific differences. Esophageal cancer is the sixth leading cause of cancer death worldwide with two distinct histologies: Squamous cell carcinoma and esophageal adenocarcinoma (EAC). The incidence of EAC is increasing dramatically and EAC is now the most common esophageal malignancy in the United States. While several studies have explored genome wide DNA copy number changes in EAC, most are low resolution and include few tumors. Consequently these studies lack the ability to precisely define specific genes involved in regions of gain and loss, cannot identify infrequent events, and have little power to make associations with clinical endpoints such as survival and metastasis. Materials and Methods: We analyzed genomic DNA from 114 independent EAC samples using Affymetrix SNP 6.0 arrays. Normal samples from the same population were used as the reference. Analysis was performed with Nexus 5.0 Copy Number software using the SNPRank segmentation algorithm. Frequent genomic changes were identified and associations with patient survival, stage and metastasis were explored. Results: In addition to previously reported changes in EAC, we identified several events (Table 1) targeting genes known to be involved in cancer but not previously reported in EAC. We also identified many new genomic changes in EAC. Furthermore, the high resolution and large size of our dataset greatly refined the minimal regions involved and allowed us to identify specific regions that are correlated with patient survival. Conclusion: High resolution DNA copy number analysis of a large EAC cohort has identified many novel regions of frequent copy number change and has allowed refinement of previously reported regions. In addition, some regions have been found to correlate with patient survival.Table 1:Frequencies of genomic aberrations in EAC Previously reportedaberrationsChromosomeGene(s)TypeFrequency 3FHITLoss54% 7CDK6Gain22% 8GATA4Gain19% MYCGain34% 9CDKN2A/pl6Loss35% 11CCND1Gain16% 16WWOXLoss31% 17ERBB2Gain17% 18GATA6Gain28% 19DCCLoss23%New aberrations1PRUNEGain12% 3ROBOl/DUTTl Loss9.5% PIK3CAGain9% 4RegionLoss14% containing FAT1 and CDKN2AIP 6VEGFAGain23% 6MYBGain5% 7SMURF1High19% level gain EGFRGain18% METGain5% PARK2Loss5% 8RegionGain10% containing ANK1 and MYST3 9PTPRDLoss23% RegionGain12% containing TLN1 and CREB3 10VCLGain9.5% RegionHigh8% containinglevel gain FGFR2 and NSME4A 11OPCMLLoss8% 12KRASHigh28% level gain 13RegionGain15% containing ELFI RegionGain13% containing STARDL3 and KL 17RegionGain15% containing KRT genes RegionGain15% containing GAST, EIF1, and HAP1 18CDH2Loss15% APCDD1Gain13% 19CCNE1Gain10% Cluster ofGain8% ZNF genes 20RegionGain33% containing ZNF217and SUMOIPI Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-405.