Literature DB >> 25974336

Quantitative impact of immunomodulation versus oncolysis with cytokine-expressing virus therapeutics.

Peter S Kim1, Joseph J Crivelli, Il-Kyu Choi, Chae-Ok Yun, Joanna R Wares.   

Abstract

The past century's description of oncolytic virotherapy as a cancer treatment involving specially-engineered viruses that exploit immune deficiencies to selectively lyse cancer cells is no longer adequate. Some of the most promising therapeutic candidates are now being engineered to produce immunostimulatory factors, such as cytokines and co-stimulatory molecules, which, in addition to viral oncolysis, initiate a cytotoxic immune attack against the tumor. This study addresses the combined effects of viral oncolysis and T-cell-mediated oncolysis. We employ a mathematical model of virotherapy that induces release of cytokine IL-12 and co-stimulatory molecule 4-1BB ligand. We found that the model closely matches previously published data, and while viral oncolysis is fundamental in reducing tumor burden, increased stimulation of cytotoxic T cells leads to a short-term reduction in tumor size, but a faster relapse. In addition, we found that combinations of specialist viruses that express either IL-12 or 4-1BBL might initially act more potently against tumors than a generalist virus that simultaneously expresses both, but the advantage is likely not large enough to replace treatment using the generalist virus. Finally, according to our model and its current assumptions, virotherapy appears to be optimizable through targeted design and treatment combinations to substantially improve therapeutic outcomes.

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Year:  2015        PMID: 25974336     DOI: 10.3934/mbe.2015.12.841

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  9 in total

1.  Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.

Authors:  Syndi Barish; Michael F Ochs; Eduardo D Sontag; Jana L Gevertz
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2.  From Fitting the Average to Fitting the Individual: A Cautionary Tale for Mathematical Modelers.

Authors:  Michael C Luo; Elpiniki Nikolopoulou; Jana L Gevertz
Journal:  Front Oncol       Date:  2022-04-28       Impact factor: 5.738

Review 3.  Computational modeling approaches to the dynamics of oncolytic viruses.

Authors:  Dominik Wodarz
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2016-03-22

4.  Oncolytic virus efficiency inhibited growth of tumour cells with multiple drug resistant phenotype in vivo and in vitro.

Authors:  Elena P Goncharova; Julia S Ruzhenkova; Ivan S Petrov; Sergey N Shchelkunov; Marina A Zenkova
Journal:  J Transl Med       Date:  2016-08-18       Impact factor: 5.531

5.  Oncolytic potency and reduced virus tumor-specificity in oncolytic virotherapy. A mathematical modelling approach.

Authors:  Khaphetsi Joseph Mahasa; Amina Eladdadi; Lisette de Pillis; Rachid Ouifki
Journal:  PLoS One       Date:  2017-09-21       Impact factor: 3.240

6.  Developing a Minimally Structured Mathematical Model of Cancer Treatment with Oncolytic Viruses and Dendritic Cell Injections.

Authors:  Jana L Gevertz; Joanna R Wares
Journal:  Comput Math Methods Med       Date:  2018-10-30       Impact factor: 2.238

7.  An in silico exploration of combining Interleukin-12 with Oxaliplatin to treat liver-metastatic colorectal cancer.

Authors:  Qing Wang; Zhijun Wang; Yan Wu; David J Klinke
Journal:  BMC Cancer       Date:  2020-01-08       Impact factor: 4.430

8.  Investigating Macrophages Plasticity Following Tumour-Immune Interactions During Oncolytic Therapies.

Authors:  R Eftimie; G Eftimie
Journal:  Acta Biotheor       Date:  2019-08-13       Impact factor: 1.774

9.  Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo.

Authors:  Sarah Inglesfield; Aleksandra Jasiulewicz; Matthew Hopwood; James Tyrrell; George Youlden; Maria Mazon-Moya; Owain R Millington; Serge Mostowy; Sara Jabbari; Kerstin Voelz
Journal:  MBio       Date:  2018-03-27       Impact factor: 7.867

  9 in total

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