The relative timing of mutations in a breast cancer genome

Newman, Scott, Howarth, Karen D., Greenman, Christopher, Bignell, Graham R., Tavaré, Simon and Edwards, Paul A. W. (2013) The relative timing of mutations in a breast cancer genome. PLoS One, 8 (6). ISSN 1932-6203

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Abstract

Many tumors have highly rearranged genomes, but a major unknown is the relative importance and timing of genome rearrangements compared to sequence-level mutation. Chromosome instability might arise early, be a late event contributing little to cancer development, or happen as a single catastrophic event. Another unknown is which of the point mutations and rearrangements are selected. To address these questions we show, using the breast cancer cell line HCC1187 as a model, that we can reconstruct the likely history of a breast cancer genome. We assembled probably the most complete map to date of a cancer genome, by combining molecular cytogenetic analysis with sequence data. In particular, we assigned most sequence-level mutations to individual chromosomes by sequencing of flow sorted chromosomes. The parent of origin of each chromosome was assigned from SNP arrays. We were then able to classify most of the mutations as earlier or later according to whether they occurred before or after a landmark event in the evolution of the genome, endoreduplication (duplication of its entire genome). Genome rearrangements and sequence-level mutations were fairly evenly divided earlier and later, suggesting that genetic instability was relatively constant throughout the life of this tumor, and chromosome instability was not a late event. Mutations that caused chromosome instability would be in the earlier set. Strikingly, the great majority of inactivating mutations and in-frame gene fusions happened earlier. The non-random timing of some of the mutations may be evidence that they were selected.

Item Type:	Article
Additional Information:	© 2013 Newman et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords:	sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:	Faculty of Science > School of Computing Sciences Faculty of Science > School of Natural Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology
Depositing User:	Pure Connector
Date Deposited:	09 Jun 2014 20:34
Last Modified:	19 Apr 2023 00:08
URI:	https://ueaeprints.uea.ac.uk/id/eprint/48558
DOI:	10.1371/journal.pone.0064991

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