A mathematical model of the metastatic bottleneck predicts patient outcome and response to cancer treatment

PLoS Comput Biol. 2020 Oct 2;16(10):e1008056. doi: 10.1371/journal.pcbi.1008056. eCollection 2020 Oct.

Abstract

Metastases are the main reason for cancer-related deaths. Initiation of metastases, where newly seeded tumor cells expand into colonies, presents a tremendous bottleneck to metastasis formation. Despite its importance, a quantitative description of metastasis initiation and its clinical implications is lacking. Here, we set theoretical grounds for the metastatic bottleneck with a simple stochastic model. The model assumes that the proliferation-to-death rate ratio for the initiating metastatic cells increases when they are surrounded by more of their kind. For a total of 159,191 patients across 13 cancer types, we found that a single cell has an extremely low median probability of successful seeding of the order of 10-8. With increasing colony size, a sharp transition from very unlikely to very likely successful metastasis initiation occurs. The median metastatic bottleneck, defined as the critical colony size that marks this transition, was between 10 and 21 cells. We derived the probability of metastasis occurrence and patient outcome based on primary tumor size at diagnosis and tumor type. The model predicts that the efficacy of patient treatment depends on the primary tumor size but even more so on the severity of the metastatic bottleneck, which is estimated to largely vary between patients. We find that medical interventions aiming at tightening the bottleneck, such as immunotherapy, can be much more efficient than therapies that decrease overall tumor burden, such as chemotherapy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Antineoplastic Agents / therapeutic use
  • Computational Biology
  • Humans
  • Immunotherapy
  • Mice
  • Models, Biological*
  • Neoplasm Metastasis* / pathology
  • Neoplasm Metastasis* / prevention & control
  • Neoplasm Metastasis* / therapy
  • Neoplasms* / mortality
  • Neoplasms* / pathology
  • Neoplasms* / therapy
  • Stochastic Processes
  • Treatment Outcome
  • Tumor Burden

Substances

  • Antineoplastic Agents

Grants and funding

We thank the Center for Interdisciplinary Research (ZiF), Bielefeld University, for partly funding and inspiring this work, via involvement of all authors in the ZiF Cooperation Group ”Multiscale Modeling of Tumor Initiation, Growth and Progression: From Gene Regulation to Evolutionary Dynamics” from September to December, 2016. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 766030 (to E.S. and N.B.; https://ec.europa.eu/programmes/horizon2020/en). T.K. is grateful to his Department of Control Systems and Mechatronics, Faculty of Electronics, Wroclaw University of Technology for funding several visits to Dresden, Warsaw and Basel. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.