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Nat Commun. 2016 May 10;7:11479. doi: 10.1038/ncomms11479.

The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes.

Author information

1
Cancer Research UK Cambridge Institute, Li Ka Shing Centre, University of Cambridge, Robinson Way, Cambridge CB2 0RE, UK.
2
Department of Oncology, University of Cambridge, Cambridge CB2 2QQ, UK.
3
Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Montebello, Oslo 0310, Norway.
4
The K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo 0318, Norway.
5
Cambridge Breast Unit, Addenbrooke's Hospital, Cambridge University Hospital NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre, Cambridge CB2 2QQ, UK.
6
Cambridge Experimental Cancer Medicine Centre, Cambridge University Hospitals NHS, Hills Road, Cambridge CB2 0QQ, UK.
7
Inivata, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
8
Peter MacCallum Cancer Centre, Melbourne, Victoria 3002, Australia.
9
Illumina, Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK.
10
Division of Cancer and Stem Cells, School of Medicine, University of Nottingham and Nottingham University Hospital NHS Trust, Nottingham NG5 1PB, UK.
11
Department of Pathology and Molecular Medicine, Queen's University/Kingston General Hospital, 76 Stuart Street, Kingston, Ontario, Canada K7L 2V7.
12
Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, British Columbia, Canada V5Z 1L3.
13
Research Institute in Oncology and Hematology, 675 McDermot Avenue, Winnipeg, Mannitoba, Canada R3E 0V9.
14
NIHR Comprehensive Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust and Research Oncology, Cancer Division, King's College London, London SE1 9RT, UK.
15
Strangeways Research Laboratory, University of Cambridge, 2 Worts' Causeway, Cambridge CB1 8RN, UK.

Abstract

The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

PMID:
27161491
PMCID:
PMC4866047
DOI:
10.1038/ncomms11479
[Indexed for MEDLINE]
Free PMC Article

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