DNA copy number motifs are strong and independent predictors of survival in breast cancer.

Autor: Pladsen AV; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway., Nilsen G; Centre for Bioinformatics, Department of Informatics, University of Oslo, Gaustadalléen 23 B N-0373, Oslo, Norway., Rueda OM; Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK., Aure MR; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway., Borgan Ø; Department of Mathematics, University of Oslo, Moltke Moes vei 35 N-0851, Oslo, Norway., Liestøl K; Centre for Bioinformatics, Department of Informatics, University of Oslo, Gaustadalléen 23 B N-0373, Oslo, Norway., Vitelli V; Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Domus Medica, Sognsvannsveien 9 N-0372, Oslo, Norway., Frigessi A; Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Domus Medica, Sognsvannsveien 9 N-0372, Oslo, Norway., Langerød A; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway., Mathelier A; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway.; Centre for Molecular Medicine Norway, University of Oslo, Forskningsparken, Gaustadalléen 21 N-0349, Oslo, Norway., Engebråten O; Institute for Clinical Medicine, University of Oslo, Kirkeveien 166 N-0450, Oslo, Norway.; Department of Oncology, Oslo University Hospital, POB 4953 Nydalen, N-0424, Oslo, Norway., Kristensen V; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway., Wedge DC; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7FZ, UK.; NIHR Biomedical Research Centre, Warneford Ln, Headington, Oxford, OX3 7JX, UK., Van Loo P; The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK., Caldas C; Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK., Børresen-Dale AL; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway.; Institute for Clinical Medicine, University of Oslo, Kirkeveien 166 N-0450, Oslo, Norway., Russnes HG; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway.; Department of Pathology, Oslo University Hospital, POB 4953 Nydalen N-0424, Oslo, Norway., Lingjærde OC; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Ullernchausseen 70 N-0310, Oslo, Norway. ole@ifi.uio.no.; Centre for Bioinformatics, Department of Informatics, University of Oslo, Gaustadalléen 23 B N-0373, Oslo, Norway. ole@ifi.uio.no.; KG Jebsen Centre for B-cell malignancies, Institute for Clinical Medicine, University of Oslo, Ullernchausseen 70 N-0372, Oslo, Norway. ole@ifi.uio.no.
Jazyk: angličtina
Zdroj: Communications biology [Commun Biol] 2020 Apr 02; Vol. 3 (1), pp. 153. Date of Electronic Publication: 2020 Apr 02.
DOI: 10.1038/s42003-020-0884-6
Abstrakt: Somatic copy number alterations are a frequent sign of genome instability in cancer. A precise characterization of the genome architecture would reveal underlying instability mechanisms and provide an instrument for outcome prediction and treatment guidance. Here we show that the local spatial behavior of copy number profiles conveys important information about this architecture. Six filters were defined to characterize regional traits in copy number profiles, and the resulting Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to tumors in four breast cancer cohorts (n = 2919). The derived motifs represent a layer of information that complements established molecular classifications of breast cancer. A score reflecting presence or absence of motifs provided a highly significant independent prognostic predictor. Results were consistent between cohorts. The nonsite-specific occurrence of the detected patterns suggests that CARMA captures underlying replication and repair defects and could have a future potential in treatment stratification.
Databáze: MEDLINE
Nepřihlášeným uživatelům se plný text nezobrazuje