Year: 2017
Type: article
Abstract: MOTIVATION: The traditional view of cancer evolution states that a cancer genome accumulates a sequential ordering of mutations over a long period of time. However, in recent years it has been suggested that a cancer genome may instead undergo a one-time catastrophic event, such as chromothripsis, where a large number of mutations instead occur simultaneously. A number of potential signatures of chromothripsis have been proposed. In this work, we provide a rigorous formulation and analysis of the 'ability to walk the derivative chromosome' signature originally proposed by Korbel and Campbell. In particular, we show that this signature, as originally envisioned, may not always be present in a chromothripsis genome and we provide a precise quantification of under what circumstances it would be present. We also propose a variation on this signature, the H/T alternating fraction, which allows us to overcome some of the limitations of the original signature. RESULTS: We apply our measure to both simulated data and a previously analyzed real cancer dataset and find that the H/T alternating fraction may provide useful signal for distinguishing genomes having acquired mutations simultaneously from those acquired in a sequential fashion. AVAILABILITY AND IMPLEMENTATION: An implementation of the H/T alternating fraction is available at https://bitbucket.org/oesperlab/ht-altfrac. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Source: Bioinformatics
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,989
Funders: National Science Foundation, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, National Institutes of Health, National Human Genome Research Institute, National Cancer Institute
Awards: Pathway and Network Integration of Cancer Genomics and Clinical Data, Computational Characterization of Genetic Heterogeneity, CAREER: Algorithms for Next-Generation Genomics, G6671297155, CRII: III: RUI: Computational Approaches for Inferring the Evolutionary Histories of Cancer Genomes, G77468097
OpenAlex ID: W2952299110