Literature DB >> 19825370

Mathematical modeling as a tool for planning anticancer therapy.

Andrzej Swierniak1, Marek Kimmel, Jaroslaw Smieja.   

Abstract

We review a large volume of literature concerning mathematical models of cancer therapy, oriented towards optimization of treatment protocols. The review, although partly idiosyncratic, covers such major areas of therapy optimization as phase-specific chemotherapy, antiangiogenic therapy and therapy under drug resistance. We start from early cell cycle progression models, very simple but admitting explicit mathematical solutions, based on methods of control theory. We continue with more complex models involving evolution of drug resistance and pharmacokinetic and pharmacodynamic effects. Then, we consider two more recent areas: angiogenesis of tumors and molecular signaling within and among cells. We discuss biological background and mathematical techniques of this field, which has a large although only partly realized potential for contributing to cancer treatment.

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Year:  2009        PMID: 19825370      PMCID: PMC2813310          DOI: 10.1016/j.ejphar.2009.08.041

Source DB:  PubMed          Journal:  Eur J Pharmacol        ISSN: 0014-2999            Impact factor:   4.432


  117 in total

1.  Evolution of resistance during clonal expansion.

Authors:  Yoh Iwasa; Martin A Nowak; Franziska Michor
Journal:  Genetics       Date:  2006-04       Impact factor: 4.562

2.  The dynamics of gene amplification described as a multitype compartmental model and as a branching process.

Authors:  L E Harnevo; Z Agur
Journal:  Math Biosci       Date:  1991-02       Impact factor: 2.144

Review 3.  The angiopoietins: Yin and Yang in angiogenesis.

Authors:  S Davis; G D Yancopoulos
Journal:  Curr Top Microbiol Immunol       Date:  1999       Impact factor: 4.291

4.  Theoretical basis for cell cycle analysis: II. Further studies on labelled mitosis wave method.

Authors:  M Takahashi
Journal:  J Theor Biol       Date:  1968-02       Impact factor: 2.691

5.  Optimal control analysis in the chemotherapy of IgG multiple myeloma.

Authors:  G W Swan; T L Vincent
Journal:  Bull Math Biol       Date:  1977       Impact factor: 1.758

6.  Optimization of interleukin-21 immunotherapeutic strategies.

Authors:  Antonio Cappuccio; Moran Elishmereni; Zvia Agur
Journal:  J Theor Biol       Date:  2007-05-18       Impact factor: 2.691

7.  Mutations in the gene for the granulocyte colony-stimulating-factor receptor in patients with acute myeloid leukemia preceded by severe congenital neutropenia.

Authors:  F Dong; R K Brynes; N Tidow; K Welte; B Löwenberg; I P Touw
Journal:  N Engl J Med       Date:  1995-08-24       Impact factor: 91.245

Review 8.  Mechanisms and strategies to overcome multiple drug resistance in cancer.

Authors:  Tomris Ozben
Journal:  FEBS Lett       Date:  2006-02-17       Impact factor: 4.124

9.  Integrating cell-cycle progression, drug penetration and energy metabolism to identify improved cancer therapeutic strategies.

Authors:  Raja Venkatasubramanian; Michael A Henson; Neil S Forbes
Journal:  J Theor Biol       Date:  2008-02-21       Impact factor: 2.691

Review 10.  Targeting multidrug resistance in cancer.

Authors:  Gergely Szakács; Jill K Paterson; Joseph A Ludwig; Catherine Booth-Genthe; Michael M Gottesman
Journal:  Nat Rev Drug Discov       Date:  2006-03       Impact factor: 84.694

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  21 in total

Review 1.  The dynamics of drug resistance: a mathematical perspective.

Authors:  Orit Lavi; Michael M Gottesman; Doron Levy
Journal:  Drug Resist Updat       Date:  2012-03-03       Impact factor: 18.500

2.  Formalizing an integrative, multidisciplinary cancer therapy discovery workflow.

Authors:  Mary F McGuire; Heiko Enderling; Dorothy I Wallace; Jaspreet Batra; Marie Jordan; Sushil Kumar; John C Panetta; Eddy Pasquier
Journal:  Cancer Res       Date:  2013-08-16       Impact factor: 12.701

Review 3.  Array of translational systems pharmacodynamic models of anti-cancer drugs.

Authors:  Sihem Ait-Oudhia; Donald E Mager
Journal:  J Pharmacokinet Pharmacodyn       Date:  2016-10-22       Impact factor: 2.745

4.  Mathematical model of heterogeneous cancer growth with an autocrine signalling pathway.

Authors:  G-M Hu; C-Y Lee; Y-Y Chen; N-N Pang; W J Tzeng
Journal:  Cell Prolif       Date:  2012-07-11       Impact factor: 6.831

Review 5.  Limiting tumor seeding as a therapeutic approach for metastatic disease.

Authors:  Asurayya Worrede; Olimpia Meucci; Alessandro Fatatis
Journal:  Pharmacol Ther       Date:  2019-03-12       Impact factor: 12.310

6.  Predicting Time to Relapse in Acute Myeloid Leukemia through Stochastic Modeling of Minimal Residual Disease Based on Clonality Data.

Authors:  Khanh N Dinh; Roman Jaksik; Seth J Corey; Marek Kimmel
Journal:  Comput Syst Oncol       Date:  2021-09-14

7.  Modeling iontophoretic drug delivery in a microfluidic device.

Authors:  Maryam Moarefian; Rafael V Davalos; Danesh K Tafti; Luke E Achenie; Caroline N Jones
Journal:  Lab Chip       Date:  2020-09-01       Impact factor: 6.799

8.  Comparison of three a-priori models in the prediction of serum lithium concentration.

Authors:  Rajiv Radhakrishnan; Milanduth Kanigere; Jayakumar Menon; Sam Calvin; Krishnamachari Srinivasan
Journal:  Indian J Pharmacol       Date:  2012-03       Impact factor: 1.200

9.  Mathematical optimization of the combination of radiation and differentiation therapies for cancer.

Authors:  Jeff W N Bachman; Thomas Hillen
Journal:  Front Oncol       Date:  2013-03-18       Impact factor: 6.244

10.  Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance.

Authors:  Daniel Nichol; Peter Jeavons; Alexander G Fletcher; Robert A Bonomo; Philip K Maini; Jerome L Paul; Robert A Gatenby; Alexander R A Anderson; Jacob G Scott
Journal:  PLoS Comput Biol       Date:  2015-09-11       Impact factor: 4.475

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