Evidence map›Paper›PMID 31350582›Full record

ArticleJournal of mathematical biology2019

A structured population model of clonal selection in acute leukemias with multiple maturation stages.

Tommaso Lorenzi, Anna Marciniak-Czochra, Thomas Stiehl

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Article in Journal of mathematical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Tommaso LorenziSchool of Mathematics and Statistics, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9SS, UK.
Anna Marciniak-CzochraInstitute of Applied Mathematics, BIOQUANT and IWR, Heidelberg University, Im Neuenheimer Feld 205, 69120, Heidelberg, Germany. Anna.Marciniak@iwr.uni-heidelberg.de.ORCID 0000-0002-5831-6505
Thomas StiehlInstitute of Applied Mathematics, Heidelberg University, Im Neuenheimer Feld 205, 69120, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent progress in genetic techniques has shed light on the complex co-evolution of malignant cell clones in leukemias. However, several aspects of clonal selection still remain unclear. In this paper, we present a multi-compartmental continuously structured population model of selection dynamics in acute leukemias, which consists of a system of coupled integro-differential equations. Our model can be analysed in a more efficient way than classical models formulated in terms of ordinary differential equations. Exploiting the analytical tractability of this model, we investigate how clonal selection is shaped by the self-renewal fraction and the proliferation rate of leukemic cells at different maturation stages. We integrate analytical results with numerical solutions of a calibrated version of the model based on real patient data. In summary, our mathematical results formalise the biological notion that clonal selection is driven by the self-renewal fraction of leukemic stem cells and the clones that possess the highest value of this parameter are ultimately selected. Moreover, we demonstrate that the self-renewal fraction and the proliferation rate of non-stem cells do not have a substantial impact on clonal selection. Taken together, our results indicate that interclonal variability in the self-renewal fraction of leukemic stem cells provides the necessary substrate for clonal selection to act upon.

Indexed as

Clonal EvolutionModels, BiologicalAcute DiseaseCell DifferentiationCell ProliferationCell Self RenewalClone CellsComputer SimulationHumansLeukemiaMathematical ConceptsNeoplastic Stem CellsAcute leukemiaAsymptotic analysisClonal selectionContinuously structured population modelsIntegro-differential equations

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.