Modeling cancer’s ecological and evolutionary dynamics

Summary, in English

In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly software tool. By the end of this paper, we hope that readers will be able to construct basic G function models and grasp the usefulness of the framework to understand the games cancer plays in a biologically mechanistic fashion.

• Author: Anuraag Bukkuri; Kenneth J. Pienta; Ian Hockett; Robert H. Austin; Emma U. Hammarlund; Sarah R. Amend; Joel S. Brown
• Department/s: StemTherapy: National Initiative on Stem Cells for Regenerative Therapy; Molecular Evolution; EpiHealth: Epidemiology for Health; LUCC: Lund University Cancer Centre; Lithosphere and Biosphere Science
• Publishing year: 2023-04
• Language: English
• Publication/Series: Medical Oncology
• Volume: 40
• Issue: 4
• Links: http://dx.doi.org/10.1007/s12032-023-01968-0
• Document type: Journal article
• Publisher: Humana Press
• Topic: Bioinformatics and Systems Biology
• Keywords: Cancer evolution; Eco-evolutionary dynamics; Evolutionary game theory; Mathematical modeling; Resistance
• Status: Published
• Research group: Molecular Evolution
• ISBN/ISSN/Other: ISSN: 1357-0560