Literature DB >> 21363914

Mathematical modeling predicts synergistic antitumor effects of combining a macrophage-based, hypoxia-targeted gene therapy with chemotherapy.

Markus R Owen1, I Johanna Stamper, Munitta Muthana, Giles W Richardson, Jon Dobson, Claire E Lewis, Helen M Byrne.   

Abstract

Tumor hypoxia is associated with low rates of cell proliferation and poor drug delivery, limiting the efficacy of many conventional therapies such as chemotherapy. Because many macrophages accumulate in hypoxic regions of tumors, one way to target tumor cells in these regions could be to use genetically engineered macrophages that express therapeutic genes when exposed to hypoxia. Systemic delivery of such therapeutic macrophages may also be enhanced by preloading them with nanomagnets and applying a magnetic field to the tumor site. Here, we use a new mathematical model to compare the effects of conventional cyclophosphamide therapy with those induced when macrophages are used to deliver hypoxia-inducible cytochrome P450 to locally activate cyclophosphamide. Our mathematical model describes the spatiotemporal dynamics of vascular tumor growth and treats cells as distinct entities. Model simulations predict that combining conventional and macrophage-based therapies would be synergistic, producing greater antitumor effects than the additive effects of each form of therapy. We find that timing is crucial in this combined approach with efficacy being greatest when the macrophage-based, hypoxia-targeted therapy is administered shortly before or concurrently with chemotherapy. Last, we show that therapy with genetically engineered macrophages is markedly enhanced by using the magnetic approach described above, and that this enhancement depends mainly on the strength of the applied field, rather than its direction. This insight may be important in the treatment of nonsuperficial tumors, where generating a specific orientation of a magnetic field may prove difficult. In conclusion, we demonstrate that mathematical modeling can be used to design and maximize the efficacy of combined therapeutic approaches in cancer. ©2011 AACR.

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Year:  2011        PMID: 21363914      PMCID: PMC3527892          DOI: 10.1158/0008-5472.CAN-10-2834

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  35 in total

1.  Vessel maturation effects on tumour growth: validation of a computer model in implanted human ovarian carcinoma spheroids.

Authors:  L Arakelyan; Y Merbl; Z Agur
Journal:  Eur J Cancer       Date:  2005-01       Impact factor: 9.162

Review 2.  Hypoxia in cancer: significance and impact on clinical outcome.

Authors:  Peter Vaupel; Arnulf Mayer
Journal:  Cancer Metastasis Rev       Date:  2007-06       Impact factor: 9.264

Review 3.  Hypoxia regulates macrophage functions in inflammation.

Authors:  Craig Murdoch; Munitta Muthana; Claire E Lewis
Journal:  J Immunol       Date:  2005-11-15       Impact factor: 5.422

4.  Structural adaptation of microvascular networks: functional roles of adaptive responses.

Authors:  A R Pries; B Reglin; T W Secomb
Journal:  Am J Physiol Heart Circ Physiol       Date:  2001-09       Impact factor: 4.733

5.  Nonlinear modelling of cancer: bridging the gap between cells and tumours.

Authors:  J S Lowengrub; H B Frieboes; F Jin; Y-L Chuang; X Li; P Macklin; S M Wise; V Cristini
Journal:  Nonlinearity       Date:  2010

6.  A cellular automaton model for tumour growth in inhomogeneous environment.

Authors:  T Alarcón; H M Byrne; P K Maini
Journal:  J Theor Biol       Date:  2003-11-21       Impact factor: 2.691

7.  Effects of hypoxia and limited diffusion in tumor cell microenvironment on bystander effect of P450 prodrug therapy.

Authors:  M Günther; D J Waxman; E Wagner; M Ogris
Journal:  Cancer Gene Ther       Date:  2006-03-17       Impact factor: 5.987

Review 8.  Tumor-associated macrophages: effectors of angiogenesis and tumor progression.

Authors:  Seth B Coffelt; Russell Hughes; Claire E Lewis
Journal:  Biochim Biophys Acta       Date:  2009-03-06

9.  Tumor regression by combined immunotherapy and hyperthermia using magnetic nanoparticles in an experimental subcutaneous murine melanoma.

Authors:  Akira Ito; Kouji Tanaka; Kazuyoshi Kondo; Masashige Shinkai; Hiroyuki Honda; Kazuhiko Matsumoto; Toshiaki Saida; Takeshi Kobayashi
Journal:  Cancer Sci       Date:  2003-03       Impact factor: 6.716

10.  Macrophage-based anti-cancer therapy: modelling different modes of tumour targeting.

Authors:  Steven D Webb; Markus R Owen; Helen M Byrne; Craig Murdoch; Claire E Lewis
Journal:  Bull Math Biol       Date:  2007-03-01       Impact factor: 1.758

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  30 in total

Review 1.  Mathematical modeling of tumor-immune cell interactions.

Authors:  Grace E Mahlbacher; Kara C Reihmer; Hermann B Frieboes
Journal:  J Theor Biol       Date:  2019-03-02       Impact factor: 2.691

Review 2.  Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues.

Authors:  Aleksandra Karolak; Dmitry A Markov; Lisa J McCawley; Katarzyna A Rejniak
Journal:  J R Soc Interface       Date:  2018-01       Impact factor: 4.118

3.  Mathematical analysis of a model for the growth of the bovine corpus luteum.

Authors:  Sotiris A Prokopiou; Helen M Byrne; Mike R Jeffrey; Robert S Robinson; George E Mann; Markus R Owen
Journal:  J Math Biol       Date:  2013-12-13       Impact factor: 2.259

4.  Modeling of tumor response to macrophage and T lymphocyte interactions in the liver metastatic microenvironment.

Authors:  Louis T Curtis; Susanne Sebens; Hermann B Frieboes
Journal:  Cancer Immunol Immunother       Date:  2020-11-12       Impact factor: 6.968

5.  On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

Authors:  Grazziela P Figueredo; Tanvi V Joshi; James M Osborne; Helen M Byrne; Markus R Owen
Journal:  Interface Focus       Date:  2013-04-06       Impact factor: 3.906

6.  A bioimage informatics based reconstruction of breast tumor microvasculature with computational blood flow predictions.

Authors:  Spyros K Stamatelos; Eugene Kim; Arvind P Pathak; Aleksander S Popel
Journal:  Microvasc Res       Date:  2013-12-14       Impact factor: 3.514

Review 7.  Mathematical models of tumor cell proliferation: A review of the literature.

Authors:  Angela M Jarrett; Ernesto A B F Lima; David A Hormuth; Matthew T McKenna; Xinzeng Feng; David A Ekrut; Anna Claudia M Resende; Amy Brock; Thomas E Yankeelov
Journal:  Expert Rev Anticancer Ther       Date:  2018-10-22       Impact factor: 4.512

8.  Enhanced performance of macrophage-encapsulated nanoparticle albumin-bound-paclitaxel in hypo-perfused cancer lesions.

Authors:  Fransisca Leonard; Louis T Curtis; Pooja Yesantharao; Tomonori Tanei; Jenolyn F Alexander; Min Wu; John Lowengrub; Xuewu Liu; Mauro Ferrari; Kenji Yokoi; Hermann B Frieboes; Biana Godin
Journal:  Nanoscale       Date:  2016-01-28       Impact factor: 7.790

9.  Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results.

Authors:  Angela M Jarrett; David A Hormuth; Stephanie L Barnes; Xinzeng Feng; Wei Huang; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2018-05-17       Impact factor: 3.609

10.  Modeling triple-negative breast cancer heterogeneity: Effects of stromal macrophages, fibroblasts and tumor vasculature.

Authors:  Kerri-Ann Norton; Kideok Jin; Aleksander S Popel
Journal:  J Theor Biol       Date:  2018-05-08       Impact factor: 2.691

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