Rxivist logo

Copy number motifs expose genome instability type and predict driver events and disease outcome in breast cancer

By Arne V. Pladsen, Gro Nilsen, Oscar M Rueda, Miriam Ragle Aure, Ørnulf Borgan, Knut Liestøl, Valeria Vitelli, Arnoldo Frigessi, Anita Langerød, OSBREAC, Anthony Mathelier, Olav Engebråten, David C Wedge, Peter Van Loo, Carlos Caldas, Anne-Lise Børresen-Dale, Hege G. Russnes, Ole Christian Lingjærde

Posted 14 Sep 2019
bioRxiv DOI: 10.1101/769356

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.

Download data

  • Downloaded 387 times
  • Download rankings, all-time:
    • Site-wide: 68,785
    • In bioinformatics: 6,617
  • Year to date:
    • Site-wide: 125,676
  • Since beginning of last month:
    • Site-wide: 122,382

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)