Copy number motifs expose genome instability type and predict driver events and disease outcome in breast cancer
Arne V. Pladsen,
Oscar M Rueda,
Miriam Ragle Aure,
David C. Wedge,
Peter Van Loo,
Hege G. Russnes,
Ole Christian Lingjærde
Posted 14 Sep 2019
bioRxiv DOI: 10.1101/769356
Posted 14 Sep 2019
Tumor evolution is dependent on and constrained by the genotypes emerging from genome instability. We hypothesized that non-site-specific copy number motifs would correlate with underlying replication defects and also with tumor and patient fate. Six feature detectors were defined to characterize and score the local spatial behaviour of a copy number profile. By accumulating scores across genomic regions, a low-dimensional representation of the tumor genome was obtained. The proposed Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to 2384 breast tumors from three breast cancer cohorts, revealing distinct copy number motifs in established molecular subtypes. A prognostic index combining the features predicted breast cancer specific survival better than both the genomic instability index (GII) and all commonly used clinical stratifications. CARMA offers effective comparison of tumor subgroups and extracts biologically and clinically relevant features from allele-specific copy number profiles.
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