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Modeling cell proliferation in human acute myeloid leukemia xenografts.


ABSTRACT:

Motivation

Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often complex to achieve. To overcome these limitations, model-driven approaches can be exploited to investigate different aspects of cell population dynamics.

Results

In this work, we present ProCell, a novel modeling and simulation framework to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events. We apply ProCell to compare different models of cell proliferation in AML, notably leveraging experimental data derived from human xenografts in mice. ProCell is coupled with Fuzzy Self-Tuning Particle Swarm Optimization, a swarm-intelligence settings-free algorithm used to automatically infer the models parameterizations. Our results provide new insights on the intricate organization of AML cells with highly heterogeneous proliferative potential, highlighting the important role played by quiescent cells and proliferating cells characterized by different rates of division in the progression and evolution of the disease, thus hinting at the necessity to further characterize tumor cell subpopulations.

Availability and implementation

The source code of ProCell and the experimental data used in this work are available under the GPL 2.0 license on GITHUB at the following URL: https://github.com/aresio/ProCell.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Nobile MS 

PROVIDER: S-EPMC6748761 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

Modeling cell proliferation in human acute myeloid leukemia xenografts.

Nobile Marco S MS   Vlachou Thalia T   Spolaor Simone S   Bossi Daniela D   Cazzaniga Paolo P   Lanfrancone Luisa L   Mauri Giancarlo G   Pelicci Pier Giuseppe PG   Besozzi Daniela D  

Bioinformatics (Oxford, England) 20190901 18


<h4>Motivation</h4>Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often comp  ...[more]

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