ArticlePLoS computational biology2016
Quantifying Clonal and Subclonal Passenger Mutations in Cancer Evolution.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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60 citing papers in PubMed, 134 citations in OpenAlex.
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- Neuroblastoma arises in early fetal development and its evolutionary duration predicts outcome.Nature genetics · 2023Article
- Inferring parameters of cancer evolution in chronic lymphocytic leukemia.PLoS computational biology · 2022Article
- Biomarkers of Cancer Stem Cells for Experimental Research and Clinical Application.Journal of personalized medicine · 2022Review
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Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The vast majority of mutations in the exome of cancer cells are passengers, which do not affect the reproductive rate of the cell. Passengers can provide important information about the evolutionary history of an individual cancer, and serve as a molecular clock. Passengers can also become targets for immunotherapy or confer resistance to treatment. We study the stochastic expansion of a population of cancer cells describing the growth of primary tumors or metastatic lesions. We first analyze the process by looking forward in time and calculate the fixation probabilities and frequencies of successive passenger mutations ordered by their time of appearance. We compute the likelihood of specific evolutionary trees, thereby informing the phylogenetic reconstruction of cancer evolution in individual patients. Next, we derive results looking backward in time: for a given subclonal mutation we estimate the number of cancer cells that were present at the time when that mutation arose. We derive exact formulas for the expected numbers of subclonal mutations of any frequency. Fitting this formula to cancer sequencing data leads to an estimate for the ratio of birth and death rates of cancer cells during the early stages of clonal expansion.
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