Copy number analysis identifies novel interactions between genomic loci in ovarian cancer.

Abstract

Ovarian cancer is a heterogeneous disease displaying complex genomic alterations, and consequently, it has been difficult to determine the most relevant copy number alterations with the scale of studies to date. We obtained genome-wide copy number alteration (CNA) data from four different SNP array platforms, with a final data set of 398 ovarian tumours, mostly of the serous histological subtype. Frequent CNA aberrations targeted many thousands of genes. However, high-level amplicons and homozygous deletions enabled filtering of this list to the most relevant. The large data set enabled refinement of minimal regions and identification of rare amplicons such as at 1p34 and 20q11. We performed a novel co-occurrence analysis to assess cooperation and exclusivity of CNAs and analysed their relationship to patient outcome. Positive associations were identified between gains on 19 and 20q, gain of 20q and loss of X, and between several regions of loss, particularly 17q. We found weak correlations of CNA at genomic loci such as 19q12 with clinical outcome. We also assessed genomic instability measures and found a correlation of the number of higher amplitude gains with poorer overall survival. By assembling the largest collection of ovarian copy number data to date, we have been able to identify the most frequent aberrations and their interactions.