Abstract B1-56: Distinct roles of copy number and loss-of-heterozygosity in predicting prognosis for breast cancer patients
Authors: Ruud GPM van Stiphout, Antoine deWeck, Laura Winchester, Syed A. Haider, Jiannis Ragoussis, Adrian L. Harris, Chris Holmes, Francesca M. Buffa
Journal: Cancer Research (2015)

Abstract Purpose: Novel molecular stratification of the breast cancer population based on genomic aberrations has been recently reported.[1] The main focus has been on deriving prognostic classifiers by integrating gene expression and copy number aberrations (CNAs) data, but the role of other events, such as loss-of-heterozygosity (LOH), has not been extensively characterized in this integrated landscape. Here we consider the respective role of CNAs and LOH in breast cancer, in the context of an integrated genomic analysis, and their impact on clinical outcome. Methods: Currently, retrospective data with gene expression, CNA and LOH were used from 219 patients with early primary breast cancer who were resected in the period 1989-2003.[2] CNA and LOH calls were made using OncoSNP v1.4, a Bayesian model driven genomic analysis tool to call genomic aberrations and characterize LOH status, and statistical analyses were performed in R v3.0.1. The evaluated clinical outcome was distant-recurrence free survival (DRFS). Two gene sets were tested: A) general cancer drivers from the COSMIC cancer gene census and B) all genes across the genome. Significantly amplified (increased DNA copy number with respect to normal tissue), copy neutral (no change in copy number) and deleted cancer drivers were identified by deriving null distributions from permutation analysis. Survival analysis was done using both LogRank and Cox Proportional Hazards methods. The effect of LOH on the gene expression was tested using Mann-Whitney. Benjamini and Hochberg method was used to adjust for multiple testing. Results: A higher than expected LOH occurrence was detected in 168 out of 523 COSMIC defined cancer drivers. Of these, 10 were significantly amplified, 94 were copy neutral and 64 deleted. Within these three copy number groups, patients with LOH vs no LOH were compared for DRFS. LOH was a prognostic event in 14 out of 94 copy neutral group of genes, while 4 and 2 genes were found in the amplified and deleted genes respectively. Furthermore, tumors showing copy neutral LOH events had worse outcome than tumors where these genes are amplified (no LOH) or deleted (LOH). A whole genome analysis showed that a higher global LOH frequency, across the entire genome, is associated with poor prognosis as measured by a decreased DRFS, irrespective of the global level of CNAs in the tumour. Furthermore, 386 of the 5184 genes that showed a higher than expected LOH occurrence, were significantly associated with DRFS with respect to LOH status, and 51 of these were so independently of CNAs and global LOH. Conclusions: LOH in copy neutral patients has an effect on clinical outcome in a subset of cancer drivers and overall genes, irrespective of the global genomic alteration status. This finding supports an approach of measuring and integrating multiple genomic data information, which expectantly improves the accuracy of identifying subgroups of patients, resulting in improved treatment selection. Ongoing work, which will be presented at the meeting, is focused on characterizing these events, and confirming these analyses in the large TCGA dataset[3] with multiple cancer types. References: [1] Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012; 486(7403): 346-52. [2] Buffa FM, Camps C, Winchester L, Snell CE, Gee HE, Sheldon H, et al. microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Cancer Res. 2011; 71(17): 5635-45. [3] Network TCGA. Comprehensive molecular portraits of human breast tumours. Nature. 2012; 490(7418): 61-70. Citation Format: Ruud GPM van Stiphout, Antoine deWeck, Laura Winchester, Syed A. Haider, Jiannis Ragoussis, Adrian L. Harris, Chris Holmes, Francesca M. Buffa. Distinct roles of copy number and loss-of-heterozygosity in predicting prognosis for breast cancer patients. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-56.