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


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Authors

Pereira, Bernard 
Chin, Suet-Feung 
Rueda, Oscar M 
Vollan, Hans-Kristian Moen 
Provenzano, Elena 

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.

Description

Keywords

Adult, Aged, Breast Neoplasms, Class I Phosphatidylinositol 3-Kinases, DNA Copy Number Variations, Female, Genes, Tumor Suppressor, Genetic Association Studies, Humans, Kaplan-Meier Estimate, Middle Aged, Mutation, Prognosis, Proportional Hazards Models, Transcriptome

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

7

Publisher

Springer Science and Business Media LLC
Sponsorship
Cancer Research Uk (None)
Cancer Research UK (CB4140)
Cancer Research UK (unknown)
Cancer Research UK (C507/A16278)
Cancer Research UK (unknown)
Cancer Research UK (60098573)
Cancer Research UK (unknown)
Department of Health (via National Institute for Health Research (NIHR)) (unknown)
Cambridge University Hospitals NHS Foundation Trust (CUH) (unknown)
Cancer Research Uk (None)
Cambridge University Hospitals NHS Foundation Trust (CUH) (RG51913)
Wellcome Trust (106566/Z/14/Z)
Cancer Research UK (C14303/A17197)
The METABRIC project was funded by Cancer Research UK, the British Columbia Cancer Foundation and Canadian Breast Cancer Foundation BC/Yukon. This sequencing project was funded by CRUK grant C507/A16278 and Illumina UK performed all the sequencing. The authors also acknowledge the support of the University of Cambridge, Hutchinson Whampoa, the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre, the Centre for Translational Genomics (CTAG) Vancouver and the BCCA Breast Cancer Outcomes Unit. We thank the Genomics, Histopathology, and Biorepository Core Facilities at the Cancer Research UK Cambridge Institute, and the Addenbrooke’s Human Research Tissue Bank (supported by the National Institute for Health Research Cambridge Biomedical Research Centre).