PT  - JOURNAL ARTICLE
AU  - Dimitrios Voukantsis
AU  - Kenneth Kahn
AU  - Martin Hadley
AU  - Rowan Wilson
AU  - Francesca M. Buffa
TI  - Modelling genotypes in their physical microenvironment to predict single- and multi-cellular behaviour
AID  - 10.1101/360446
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 360446
4099  - http://biorxiv.org/content/early/2018/07/03/360446.1.short
4100  - http://biorxiv.org/content/early/2018/07/03/360446.1.full
AB  - A cell’s phenotype is the set of observable characteristics resulting from the interaction of the genotype with the surrounding environment, determining cell behaviour. Deciphering genotype-phenotype relationships has been crucial to understand normal and disease biology. Analysis of molecular pathways has provided an invaluable tool to such understanding; however, it has typically lacked a component describing the physical context, which is a key determinant of phenotype.In this study, we present a novel modelling framework that enables to study the link between genotype, signalling networks and cell behaviour in a 3D physical environment. To achieve this we bring together Agent Based Modelling, a powerful computational modelling technique, and gene networks. This combination allows biological hypotheses to be tested in a controlled stepwise fashion, and it lends itself naturally to model a heterogeneous population of cells acting and evolving in a dynamic microenvironment, which is needed to predict the evolution of complex multi-cellular dynamics. Importantly, this enables modelling co-occurring intrinsic perturbations, such as mutations, and extrinsic perturbations, such as nutrients availability, and their interactions.Using cancer as a model system, we illustrate the how this framework delivers a unique opportunity to identify determinants of single-cell behaviour, while uncovering emerging properties of multi-cellular growth.Contact Francesca M. Buffa, University of Oxford, francesca.buffa{at}imm.ox.ac.uk