Background and aims: The incidence of oesophageal adenocarcinoma (OAC) has been increasing rapidly with a dismal survival rate of less than 20%. Understanding the genomic aberrations and biology of this cancer may enhance disease interventions. This study aimed to use genome-wide genomic and expression data to enhance the understanding of OAC pathogenesis and identify groups with differential outcomes.
Methods: Array-comparative genomic hybridisation (aCGH) analysis was carried out on 56 fresh frozen OAC resection samples with long-term clinical follow-up data. Samples with aberrations were further analysed with whole-genome single-nucleotide polymorphism arrays to confirm aCGH findings. Matched gene expression microarray data were used to identify genes with high copy number-expression correlations. Nested-multiplex PCR on DNA from microdissected specimens and fluorescence in situ hybridisation assays were used for target validation. Immunohistochemistry on the same cohort and independent samples (n=371) was used for subsequent validation. Kaplan-Meier survival analyses were performed based on aCGH data after unsupervised K-means clustering (K=5, 50 iterations) and immunohistochemistry data.
Results: aCGH identified 17 common regions (>5% samples) of gains and 11 common regions of losses, including novel regions in OAC (loci 11p13 and 21q21.2). Integration of aCGH data with matched gene expression microarray data highlighted genes with high copy number-expression correlations: two deletions (p16/CDKN2A, MBNL1) and four gains (EGFR, WT1, NEIL2, MTMR9). Immunohistochemistry demonstrated protein over-expression of targets with gains: EGFR (10%), WT1 (20%), NEIL2 (14%) and MTMR9 (25%). These targets individually (p<0.060) and in combination had prognostic significance (p=0.008). On the genomic level, K-means clustering identified a cluster (32% of cohort) with differential log(2) ratios of 16 CGH probes (p<4×10(-7)) and a worse prognosis (median survival=1.37 years; p=0.015).
Conclusions: Integration of aCGH and gene expression data identified copy number aberrations and novel genes with prognostic potential in OAC.