Preprint Review Version 1 NOT YET PEER-REVIEWED

Fighting Cancer with Mathematics and Viruses

Version 1 : Received: 15 July 2017 / Approved: 17 July 2017 / Online: 17 July 2017 (13:01:09 CEST)

A peer-reviewed article of this Preprint also exists.

Santiago, D.N.; Heidbuechel, J.P.W.; Kandell, W.M.; Walker, R.; Djeu, J.; Engeland, C.E.; Abate-Daga, D.; Enderling, H. Fighting Cancer with Mathematics and Viruses. Viruses 2017, 9, 239. Santiago, D.N.; Heidbuechel, J.P.W.; Kandell, W.M.; Walker, R.; Djeu, J.; Engeland, C.E.; Abate-Daga, D.; Enderling, H. Fighting Cancer with Mathematics and Viruses. Viruses 2017, 9, 239.

Journal reference: Viruses 2017, 9, 239
DOI: 10.3390/v9090239

Abstract

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 anti-tumor 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 fields of research for more efficient development and effective treatments.

Subject Areas

oncolytic virotherapy; combination therapy; mathematical model; immune system; cancer; immunotherapy

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