A biased competition theory of cytotoxic T lymphocyte interaction with tumor nodules

PLoS One. 2015 Mar 27;10(3):e0120053. doi: 10.1371/journal.pone.0120053. eCollection 2015.

Abstract

The dynamics of the interaction between Cytotoxic T Lymphocytes (CTL) and tumor cells has been addressed in depth, in particular using numerical simulations. However, stochastic mathematical models that take into account the competitive interaction between CTL and tumors undergoing immunoediting, a process of tumor cell escape from immunesurveillance, are presently missing. Here, we introduce a stochastic dynamical particle interaction model based on experimentally measured parameters that allows to describe CTL function during immunoediting. The model describes the competitive interaction between CTL and melanoma cell nodules and allows temporal and two-dimensional spatial progression. The model is designed to provide probabilistic estimates of tumor eradication through numerical simulations in which tunable parameters influencing CTL efficacy against a tumor nodule undergoing immunoediting are tested. Our model shows that the rate of CTL/tumor nodule productive collisions during the initial time of interaction determines the success of CTL in tumor eradication. It allows efficient cytotoxic function before the tumor cells acquire a substantial resistance to CTL attack, due to mutations stochastically occurring during cell division. Interestingly, a bias in CTL motility inducing a progressive attraction towards a few scout CTL, which have detected the nodule enhances early productive collisions and tumor eradication. Taken together, our results are compatible with a biased competition theory of CTL function in which CTL efficacy against a tumor nodule undergoing immunoediting is strongly dependent on guidance of CTL trajectories by scout siblings. They highlight unprecedented aspects of immune cell behavior that might inspire new CTL-based therapeutic strategies against tumors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Melanoma / immunology*
  • Melanoma / pathology*
  • Models, Biological
  • Models, Immunological*
  • Monitoring, Immunologic
  • Stochastic Processes
  • T-Lymphocytes, Cytotoxic / metabolism*
  • Tumor Cells, Cultured
  • Tumor Escape

Grant support

This work was supported by grants from the Association pour la Recherche sur le Cancer (SL220100601347), from the Institut National du Cancer (n° 2012-054) and from the Agence Nationale de la Recherche (Laboratoire d’Excellence Toulouse Cancer). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.