A generalized Luria–Delbrück model
Abstract
We develop extensions of the Luria-Delbrück model that explicitly consider non-exponential growth of normal cells and a birth-death process with mean exponential or Gompertz growth of mutants. Death of mutant cells can be important in clones arising during cancer progression. The use of a birth-death process for growth of mutant cells, as opposed to a pure birth process as in previous work on the Luria-Delbrück model, leads to a large increase in the extra Poisson variation in the size of the mutant cell populations, which needs to be addressed in statistical analyses. We also discuss connections with previous work on carcinogenesis models.
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Under the assumptions considered above, bacterial growth in the presence of a sub-inhibitory concentration of an antibiotic has, apart from increasing the number of cell divisions, the additional effect of decreasing the net growth rate of the non-mutant cells, leading to ρ* > 1 and thus further inflating mutant counts.
“Under the assumptions considered above, bacterial growth in the presence of a sub-inhibitory concentration of an antibiotic has, apart from increasing the number of cell divisions, the additional effect of decreasing the net growth rate of the non-mutant cells, leading to ρ * > 1 and thus further inflating mutant counts.”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [44]
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Sarkar, S., Ma, W. T., & Sandri, G. V. H. (1992) · Genetica · doi:10.1007/bf00120324 · Cited by 181 · see citing works
Analysis of the Luria–Delbrück distribution using discrete convolution powers
Ma, W. T., Sandri, G. V., & Sarkar, S. (1992) · Journal of Applied Probability · doi:10.1017/s0021900200043023 · Cited by 121 · see citing works
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The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers
Diaz Jr, L. A., Williams, R. T., Wu, J., Kinde, I., Hecht, J. R., Berlin, J., Allen, B., Bozic, I., Reiter, J. G., Nowak, M. A., et al. (2012) · Nature · doi:10.1038/nature11219 · Cited by 1,713 · see citing works
flan: an R package for inference on mutation models.
Mazoyer, A., Drouilhet, R., Despréaux, S., & Ycart, B. (2017) · The R Journal · doi:10.32614/rj-2017-029 · Cited by 33 · see citing works
Łazowski, K. (2023) · Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis · doi:10.1016/j.mrfmmm.2023.111816 · Cited by 10 · see citing works
- Authors
- Dewanji, A., Luebeck, E. G., & Moolgavkar, S. H.
- Affiliations
- Indian Statistical Institute (IN)
- Fred Hutch Cancer Center (US)
- Corresponding author
- Moolgavkar, S.H.
- Venue
- Mathematical Biosciences
- Publisher
- Elsevier BV
- Published
- 2005-10
- Volume
- 197
- Issue
- 2
- Pages
- 140-152
- ISSN
- 0025-5564 (ISSN-L)
- OpenAlex
- W1966001093
- Cited by
- 64
- References
- 3
- Citations by year
- 2025: 5 · 2024: 1 · 2023: 5 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 2 · 2016: 4 · 2015: 4 · 2014: 6 · 2013: 5 · 2012: 6
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Mathematical Biosciences (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA047658)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Keywords
- tumor progression, birth-death processes, Gompertz growth, carcinogenesis models, clonal evolution
- MeSH terms
- Models, Biological, Mutation, Stochastic Processes, Cell Growth Processes
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