Modeling protective anti-tumor immunity via preventative cancer vaccines using a hybrid agent-based and delay differential equation approach

PLoS Comput Biol. 2012;8(10):e1002742. doi: 10.1371/journal.pcbi.1002742. Epub 2012 Oct 25.

Abstract

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Antigens, Neoplasm / immunology
  • Cancer Vaccines / immunology*
  • Computational Biology / methods
  • Humans
  • Lymph Nodes / immunology
  • Models, Immunological*
  • Neoplasms / immunology*
  • Neoplasms / prevention & control*
  • T-Lymphocytes, Cytotoxic / immunology

Substances

  • Antigens, Neoplasm
  • Cancer Vaccines

Grants and funding

Peter Kim was supported in part by the School of Mathematics and Statistics, University of Sydney, Australia (http://www.maths.usyd.edu.au/) and by the Australian Research Council Discovery Early Career Research Award DE120101113 (http://www.arc.gov.au/ncgp/decra.htm). Peter Lee was supported in part by the City of Hope and Beckman Research Institute (http://www.cityofhope.org/research/beckman-research-institute/Pages/default.aspx) and by the Department of Defense Era of Hope Scholar Award for breast cancer research BC051650 (http://www.grants.gov/search/search.do?mode=VIEW&oppId=88415). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.