Fighting cancer with mathematics and viruses

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex...

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Bibliographic Details
Main Authors: Santiago, Daniel (Author) , Heidbüchel, Johannes P. W. (Author) , Engeland, Christine Elisabeth (Author)
Format: Article (Journal)
Language:English
Published: 23 August 2017
In: Viruses
Year: 2017, Volume: 9, Issue: 9
ISSN:1999-4915
DOI:10.3390/v9090239
Online Access:Verlag, kostenfrei, Volltext: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5618005/
Verlag, kostenfrei, Volltext: http://dx.doi.org/10.3390/v9090239
Verlag, kostenfrei, Volltext: http://www.mdpi.com/1999-4915/9/9/239
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Author Notes:Daniel N. Santiago, Johannes P.W. Heidbuechel, Wendy M. Kandell, Rachel Walker, Julie Djeu, Christine E. Engeland, Daniel Abate-Daga, and Heiko Enderling
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Summary:After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments.
Item Description:Artikel veröffentlicht im "Special issue: Mathematical modeling of virus infections"
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Physical Description:Online Resource
ISSN:1999-4915
DOI:10.3390/v9090239