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    The role of spatial variations of abiotic factors in mediating intratumour phenotypic heterogeneity

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    Type
    Article
    Authors
    Lorenzi, Tommaso
    Venkataraman, Chandrasekhar cc
    Lorz, Alexander
    Chaplain, Mark A.J. cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    KAUST Grant Number
    BAS/1/1648-01-01
    BAS/1/1648-01-02
    Date
    2018-05-08
    Online Publication Date
    2018-05-08
    Print Publication Date
    2018-08
    Permanent link to this record
    http://hdl.handle.net/10754/627825
    
    Metadata
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    Abstract
    We present here a space- and phenotype-structured model of selection dynamics between cancer cells within a solid tumour. In the framework of this model, we combine formal analyses with numerical simulations to investigate in silico the role played by the spatial distribution of abiotic components of the tumour microenvironment in mediating phenotypic selection of cancer cells. Numerical simulations are performed both on the 3D geometry of an in silico multicellular tumour spheroid and on the 3D geometry of an in vivo human hepatic tumour, which was imaged using computerised tomography. The results obtained show that inhomogeneities in the spatial distribution of oxygen, currently observed in solid tumours, can promote the creation of distinct local niches and lead to the selection of different phenotypic variants within the same tumour. This process fosters the emergence of stable phenotypic heterogeneity and supports the presence of hypoxic cells resistant to cytotoxic therapy prior to treatment. Our theoretical results demonstrate the importance of integrating spatial data with ecological principles when evaluating the therapeutic response of solid tumours to cytotoxic therapy.
    Citation
    Lorenzi T, Venkataraman C, Lorz A, Chaplain MAJ (2018) The role of spatial variations of abiotic factors in mediating intratumour phenotypic heterogeneity. Journal of Theoretical Biology. Available: http://dx.doi.org/10.1016/j.jtbi.2018.05.002.
    Sponsors
    The authors would like to thank Dana-Adriana Botesteanu for her helpful feedback and insightful comments and suggestions. CV wishes to acknowledge partial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642866. AL was supported by King Abdullah University of Science and Technology (KAUST) baseline and start-up funds (BAS/1/1648-01-01 and BAS/1/1648-01-02). MAJC gratefully acknowledge support of EPSRC grant no. EP/N014642/1.
    Publisher
    Elsevier BV
    Journal
    Journal of Theoretical Biology
    DOI
    10.1016/j.jtbi.2018.05.002
    PubMed ID
    29750997
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0022519318302273
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.jtbi.2018.05.002
    Scopus Count
    Collections
    Articles; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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