Dataset Information

Cappuccio2007 - Tumor-immune system interactions and determination of the optimal therapeutic protocol in immunotherapy

ABSTRACT: This ordinary differential equation model is the Panetta-Kirschner model of tumor-immune interactions is described in the publication: Cappuccio A, Castiglione F, Piccoli B." Determination of the optimal therapeutic protocols in cancer immunotherapy." Math Biosci. 2007 Sep;209(1):1-13. doi: 10.1016/j.mbs.2007.02.009. Comment: The model represented in Equations 1-3 is the Panetta-Kirschner model and was used to reproduce Fig. 1. N.B.: Labelling of Fig. 1 graphs in manuscript mismatches with simulation results - CTL and tumor cell plots swapped. Abstract: Cancer immunotherapy aims at eliciting an immune system response against the tumor. However, it is often characterized by toxic side-effects. Limiting the tumor growth and, concurrently, avoiding the toxicity of a drug, is the problem of protocol design. We formulate this question as an optimization problem and derive an algorithm for its solution. Unlike the standard optimal control approach, the algorithm simulates impulse-like drug administrations. It relies on an exact computation of the gradient of the cost function with respect to any protocol by means of the variational equations, that can be solved in parallel with the system. In comparison with previous versions of this method [F. Castiglione, B. Piccoli, Optimal control in a model of dendritic cell transfection cancer immunotherapy, Bull. Math. Biol. 68 (2006) 255-274; B. Piccoli, F. Castiglione, Optimal vaccine scheduling in cancer immunotherapy, Physica A. 370 (2) (2007) 672-680], we optimize both the timing and the dosage of each administration and introduce a penalty term to avoid clustering of subsequent injections, a requirement consistent with the clinical practice. In addition, we implement the optimization scheme to simulate the case of multi-therapies. The procedure works for any ODE system describing the pharmacokinetics and pharmacodynamics of an arbitrary number of therapeutic agents. In this work, it was tested for a well known model of the tumor-immune system interaction [D. Kirschner, J.C. Panetta, Modeling immunotherapy of tumor-immune interaction, J. Math. Biol. 37 (1998) 235-252]. Exploring three immunotherapeutic scenarios (CTL therapy, IL-2 therapy and combined therapy), we display the stability and efficacy of the optimization method, obtaining protocols that are successful compromises between various clinical requirements.

SUBMITTER: Emilia Chen

PROVIDER: BIOMD0000001036 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000001036?filename=Cappuccio2007%20-%20Fig1.sedml	Other
	BIOMD0000001036?filename=Cappuccio2007-biopax2.owl	Owl
	BIOMD0000001036?filename=Cappuccio2007-biopax3.owl	Owl
	BIOMD0000001036?filename=Cappuccio2007-matlab.m	Other
	BIOMD0000001036?filename=Cappuccio2007-octave.m	Other

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Publications

Determination of the optimal therapeutic protocols in cancer immunotherapy.

Cappuccio Antonio A Castiglione Filippo F Piccoli Benedetto B

Mathematical biosciences 20070306 1

Cancer immunotherapy aims at eliciting an immune system response against the tumor. However, it is often characterized by toxic side-effects. Limiting the tumor growth and, concurrently, avoiding the toxicity of a drug, is the problem of protocol design. We formulate this question as an optimization problem and derive an algorithm for its solution. Unlike the standard optimal control approach, the algorithm simulates impulse-like drug administrations. It relies on an exact computation of the gra ...[more]

PMID: 17416392

Publication: 1/2

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Project description:This a model from the article: Modeling immunotherapy of the tumor-immune interaction. Kirschner D, Panetta JC. J Math Biol 1998 Sep;37(3):235-52 9785481 , Abstract: A number of lines of evidence suggest that immunotherapy with the cytokine interleukin-2 (IL-2) may boost the immune system to fight tumors. CD4+ T cells, the cells that orchestrate the immune response, use these cytokines as signaling mechanisms for immune-response stimulation as well as lymphocyte stimulation, growth, and differentiation. Because tumor cells begin as 'self', the immune system may not respond in an effective way to eradicate them. Adoptive cellular immunotherapy can potentially restore or enhance these effects. We illustrate through mathematical modeling the dynamics between tumor cells, immune-effector cells, and IL-2. These efforts are able to explain both short tumor oscillations in tumor sizes as well as long-term tumor relapse. We then explore the effects of adoptive cellular immunotherapy on the model and describe under what circumstances the tumor can be eliminated. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Kirschner D, Panetta JC. (1998) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.