Evolution of a mathematical model of an aggressive-invasive cancer under chemotherapy

In this work, we first propose continuous models of an aggressive-invasive cancer which is characterized by its heterogeneity, by its high proliferation rates and by the potential invasion of cancer cells into surrounding tissue. An acidification environment mechanism is included in the models to analyze the level of invasion. Second, we introduce and analyze their discrete versions obtained by an appropriate discretization. Afterwards a chemotherapy treatment with a gradual effect is added, which includes important aspects as resistance and drug toxicity. Finally we make comparisons among different chemotherapy schemes to identify a suitable combination in order to eradicate or to reduce the growth of the tumor.

[1]  Abdelkader Lakmeche,et al.  Nonlinear mathematical model of pulsed-therapy of heterogeneous tumors , 2001 .

[2]  L. Fan,et al.  Modeling growth of a heterogeneous tumor. , 2003, Journal of theoretical biology.

[3]  R. Mickens Nonstandard Finite Difference Models of Differential Equations , 1993 .

[4]  R. Solé,et al.  Metapopulation dynamics and spatial heterogeneity in cancer , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Carlos Eduardo Pedreira,et al.  Optimal schedule for cancer chemotherapy , 1991, Math. Program..

[6]  D. Cramer,et al.  The role of cervical cytology in the declining morbidity and mortality of cervical cancer , 1974, Cancer.

[7]  D L S McElwain,et al.  A history of the study of solid tumour growth: The contribution of mathematical modelling , 2004, Bulletin of mathematical biology.

[8]  T. Vincent,et al.  An evolutionary model of carcinogenesis. , 2003, Cancer research.

[9]  Ronald E. Mickens,et al.  Advances in the Applications of Nonstandard Finite Difference Schemes , 2005 .

[10]  Silvia Jerez Galiano A nonstandard difference-integral method for the viscous Burgers' equation , 2008, Appl. Math. Comput..

[11]  Ronald E. Mickens,et al.  A positivity‐preserving nonstandard finite difference scheme for the damped wave equation , 2004 .

[12]  R. Gillies,et al.  Why do cancers have high aerobic glycolysis? , 2004, Nature Reviews Cancer.

[13]  Alissa M. Weaver,et al.  Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment , 2006, Cell.

[14]  J. Leith,et al.  Competitive exclusion of clonal subpopulations in heterogeneous tumours after stromal injury. , 1989, British Journal of Cancer.

[15]  J. Panetta,et al.  A mathematical model of drug resistance: heterogeneous tumors. , 1998, Mathematical biosciences.

[16]  E. T. Gawlinski,et al.  A reaction-diffusion model of cancer invasion. , 1996, Cancer research.

[17]  Francisco J. Solis,et al.  Discrete mathematical models of an aggressive heterogeneous tumor growth with chemotherapy treatment , 2009, Math. Comput. Model..

[18]  J. Leith,et al.  Tumor micro-ecology and competitive interactions. , 1987, Journal of theoretical biology.

[19]  Mark A. J. Chaplain,et al.  Mathematical modelling of cancer invasion of tissue: dynamic heterogeneity , 2006, Networks Heterog. Media.

[20]  Ronald E. Mickens,et al.  A new positivity‐preserving nonstandard finite difference scheme for the DWE , 2005 .

[21]  Francisco J. Solis,et al.  Discrete modeling of aggressive tumor growth with gradual effect of chemotherapy , 2013, Math. Comput. Model..

[22]  F. Lang,et al.  Up-regulation of Na(+)-coupled glucose transporter SGLT1 by caveolin-1. , 2013, Biochimica et biophysica acta.

[23]  D. Birnbaum,et al.  Genome-wide search for loss of heterozygosity shows extensive genetic diversity of human breast carcinomas. , 1997, Cancer research.

[24]  Avner Friedman,et al.  A hierarchy of cancer models and their mathematical challenges , 2003 .

[25]  A. Schäffer,et al.  Construction of evolutionary tree models for renal cell carcinoma from comparative genomic hybridization data. , 2000, Cancer research.

[26]  Nicola Bellomo,et al.  On the foundations of cancer modelling: Selected topics, speculations, and perspectives , 2008 .

[27]  Ami Radunskaya,et al.  The dynamics of an optimally controlled tumor model: A case study , 2003 .