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

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, ma...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 114; no. 31; pp. E6277 - E6286
Main Authors Barish, Syndi, Ochs, Michael F., Sontag, Eduardo D., Gevertz, Jana L.
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 01.08.2017
SeriesPNAS Plus
Subjects
Biological Sciences
Cancer
Cancer immunotherapy
Dendritic cells
Experimental data
Immunostimulation
Immunotherapy
Mathematical analysis
Mathematical models
Melanoma
Nonparametric statistics
Oncolysis
Optimization
Physical Sciences
PNAS Plus
Population (statistical)
Population studies
Robustness (mathematics)
Scheduling
Statistical analysis
Temporal variations
Therapy
Vaccines
Viruses
mathematical modeling
cancer treatment
robust therapies
virotherapy
immunotherapy
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Summary:Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists.
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Author contributions: E.D.S. and J.L.G. designed research; S.B. and J.L.G. performed research; S.B., M.F.O., E.D.S., and J.L.G. analyzed data; S.B. and J.L.G. wrote the paper; and M.F.O. oversaw statistical analyses.
1Present address: Graduate Program in Biological & Biomedical Sciences, Yale University, New Haven, CT 06520.
Edited by Martin A. Nowak, Harvard University, Cambridge, MA, and accepted by Editorial Board Member Rakesh K. Jain June 15, 2017 (received for review February 27, 2017)
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.1703355114