Kato, M., Vasco, D. A., Sugino, R., Narushima, D., Krasnitz, A. (September 2017) Sweepstake evolution revealed by population-genetic analysis of copy-number alterations in single genomes of breast cancer. R Soc Open Sci, 4 (9). p. 171060. ISSN 2054-5703 (Print)2054-5703
Abstract
Single-cell sequencing is a promising technology that can address cancer cell evolution by identifying genetic alterations in individual cells. In a recent study, genome-wide DNA copy numbers of single cells were accurately quantified by single-cell sequencing in breast cancers. Phylogenetic-tree analysis revealed genetically distinct populations, each consisting of homogeneous cells. Bioinformatics methods based on population genetics should be further developed to quantitatively analyse the single-cell sequencing data. We developed a bioinformatics framework that was combined with molecular-evolution theories to analyse copy-number losses. This analysis revealed that most deletions in the breast cancers at the single-cell level were generated by simple stochastic processes. A non-standard type of coalescent theory, the multiple-merger coalescent model, aided by approximate Bayesian computation fit well with the data, allowing us to estimate the population-genetic parameters in addition to false-positive and false-negative rates. The estimated parameters suggest that the cancer cells underwent sweepstake evolution, where only one or very few parental cells produced a descendent cell population. We conclude that breast cancer cells successively substitute in a tumour mass, and the high reproduction of only a portion of cancer cells may confer high adaptability to this cancer.
| Item Type: | Paper |
|---|---|
| Uncontrolled Keywords: | bioinformatics cancer genomics coalescent theory copy-number alteration molecular evolution single-cell sequencing |
| Subjects: | bioinformatics diseases & disorders > cancer > cancer types > breast cancer bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > copy number variants bioinformatics > genomics and proteomics > genetics & nucleic acid processing > population genetics |
| CSHL Authors: | |
| Communities: | CSHL Cancer Center Program > Cancer Genetics CSHL labs > Krasnitz lab CSHL Cancer Center Program > Cancer Genetics and Genomics Program |
| Depositing User: | Matt Covey |
| Date: | September 2017 |
| Date Deposited: | 11 Oct 2017 19:38 |
| Last Modified: | 05 Nov 2020 19:20 |
| PMCID: | PMC5627131 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/35566 |
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