SR2-5: The DNA Copy Number Landscapes and Genomic Architecture; Relevance for Progression and Outcome.
Authors: A-L Børresen-Dale
Journal: Cancer Research (2011)

Abstract Patterns of genomic aberrations have been defined that underlie specific expression subgroups of breast cancer (BC) that may infer paths of tumor progression and shed light on mechanisms involved. Classifications built on levels of genomic distortion have been shown to have prognostic value. We recently developed two platform-independent algorithms to explore genomic architectural distortion using aCGH data to measure whole-arm gains and losses [whole arm aberration index (WAAI)] and complex rearrangements [complex arm aberration index (CAAI)]. By applying CAAI and WAAI to data from 595 BC patients, we were able to separate the cases into eight subgroups with different distributions of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the luminal-related groups, whereas the complexity identified by CAAI had an overall independent prognostic power. The results emphasized the relation among structural genomic alterations, molecular subtype, and clinical behavior and showed that objective score of genomic complexity (CAAI) is an independent prognostic marker. The CAAI algorithm calculates complexity scores per chromosome arm and is based on relatively large genomic stretches, in megabase order of magnitude. We have further developed this method to calculate probe-focused complexity scores per sample, a continuous complexity index (CCI), that increases the resolution significantly by calculating complexity scores for every genomic locus. CCI was calculated based on data derived from aCGH analyses of a set of 394 invasive ductal BCs. This approach enabled us to identify novel regions frequently subjected to high levels distortion and furthermore, to pinpoint regions with increased complexity which was associated with more aggressive disease. A total of 25 recurrent regions with high level complexity were identified. Regional complexities on chromosome arms 8p, 11q and 17q were each associated with clinical parameters associated with aggressive disease. Complexity patterns were different between tumors of different gene expression subtypes. Multivariate Cox analysis revealed that regional complexity on 17q21.32-q21.33 was significantly associated with shorter survival, independent of established clinical variables. The new algorithm developed represents a novel tool that can be utilized to identify smaller genomic regions of importance as well the genes therein that could be further explored. References Bergamaschi A. et al. Genes Chromosomes. Cancer 45, 1033–1040 (2006). Hicks J. et al. Genome Res. 16(12):1465–79, (2006) Kristensen VN and Vaske C et al. (2011) PNAS, spec BC issue (in press) Russnes HG and Vollan HK et al. (2010) Sci. Transl. Med. 2, 38ra47 Stephens P et al. (2009) Nature. 462, 1005–1010 Aaroe J and Myhre S et al. under review Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr SR2-5.