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2017 ; 9
(9
): ä Nephropedia Template TP
gab.com Text
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English Wikipedia
Fighting Cancer with Mathematics and Viruses
#MMPMID28832539
Santiago DN
; Heidbuechel JPW
; Kandell WM
; Walker R
; Djeu J
; Engeland CE
; Abate-Daga D
; Enderling H
Viruses
2017[Aug]; 9
(9
): ä PMID28832539
show ga
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.
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