Cancer spatial evolution in a changing microenvironment

Molecular and Population Genetics Laboratory, Oxford Centre for Cancer Gene Research, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
DOI
10.7287/peerj.preprints.3052v1
Subject Areas
Computational Biology, Ecology, Evolutionary Studies, Genetics, Oncology
Keywords
Cancer Evolution, Ecology and Evolution, Changing Microenvironment, Adaptive Evolution
Copyright
© 2017 Jiang et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Jiang X, Tomlinson IP. 2017. Cancer spatial evolution in a changing microenvironment. PeerJ Preprints 5:e3052v1

Abstract

Cancer development as an ecological and evolutionary process is poorly understood, which includes early cancer evolution, malignancy and metastasis. It was hypothesised that the tumour microenvironment (TME) plays a critical role in this process. Unfortunately, in most cancer modelling studies the TME is ignored or considered static and different cancers are often studied in isolation. There is a lack of a general theory of cancer adaptive evolution (CAE). Here I establish a genetic and phenotypic model of cancer three-dimensional (3D) spatial evolution in a changing TME. With 3D individual-based simulations I show how cancer cells adapt to diverse changing TME conditions and selection intensities. I am able to capture key histological characteristics of various cancer forms including complex dynamics of spatial-temporal heterogeneity of subclonal fitness and subclonal mixing, ball-like and non-ball-like subclonal structures. Moreover, I identify key evolutionary and phylogenetic patterns of CAE under various combinations of phenotypic, genetic, population genetic and changing TME conditions. I show classical drivers, mini drivers, Darwinian and neutral/nearly neutral evolution and cost of complexity. I demonstrate the importance of ecology in CAE. I show that there are fundamental differences in the mode of CAE when the TME is changing, which is the limiting factor of CAE. Finally, I discuss important implications for cancer evolution theories and cancer personalised medicine.

Author Comment

Poster presentation for the Evolutionary systems biology of cells symposium of SMBE 2017.