Subclonal diversification of primary breast cancer revealed by multiregion sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-07

AUTHORS

Lucy R Yates, Moritz Gerstung, Stian Knappskog, Christine Desmedt, Gunes Gundem, Peter Van Loo, Turid Aas, Ludmil B Alexandrov, Denis Larsimont, Helen Davies, Yilong Li, Young Seok Ju, Manasa Ramakrishna, Hans Kristian Haugland, Peer Kaare Lilleng, Serena Nik-Zainal, Stuart McLaren, Adam Butler, Sancha Martin, Dominic Glodzik, Andrew Menzies, Keiran Raine, Jonathan Hinton, David Jones, Laura J Mudie, Bing Jiang, Delphine Vincent, April Greene-Colozzi, Pierre-Yves Adnet, Aquila Fatima, Marion Maetens, Michail Ignatiadis, Michael R Stratton, Christos Sotiriou, Andrea L Richardson, Per Eystein Lønning, David C Wedge, Peter J Campbell

ABSTRACT

The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer. More... »

PAGES

751-759

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nm.3886

    DOI

    http://dx.doi.org/10.1038/nm.3886

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1046110380

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26099045


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