A calibrated agent-based computer model of stochastic cell dynamics in normal human colon crypts useful for in silico experiments

Abstract

BackgroundNormal colon crypts consist of stem cells, proliferating cells, and differentiated cells. Abnormal rates of proliferation and differentiation can initiate colon cancer. We have measured the variation in the number of each of these cell types in multiple crypts in normal human biopsy specimens. This has provided the opportunity to produce a calibrated computational model that simulates cell dynamics in normal human crypts, and by changing model parameter values, to simulate the initiation and treatment of colon cancer.ResultsAn agent-based model of stochastic cell dynamics in human colon crypts was developed in the multi-platform open-source application NetLogo. It was assumed that each cell’s probability of proliferation and probability of death is determined by its position in two gradients along the crypt axis, a divide gradient and in a die gradient. A cell’s type is not intrinsic, but rather is determined by its position in the divide gradient. Cell types are dynamic, plastic, and inter-convertible. Parameter values were determined for the shape of each of the gradients, and for a cell’s response to the gradients. This was done by parameter sweeps that indicated the values that reproduced the measured number and variation of each cell type, and produced quasi-stationary stochastic dynamics. The behavior of the model was verified by its ability to reproduce the experimentally observed monocolonal conversion by neutral drift, the formation of adenomas resulting from mutations either at the top or bottom of the crypt, and by the robust ability of crypts to recover from perturbation by cytotoxic agents. One use of the virtual crypt model was demonstrated by evaluating different cancer chemotherapy and radiation scheduling protocols.ConclusionsA virtual crypt has been developed that simulates the quasi-stationary stochastic cell dynamics of normal human colon crypts. It is unique in that it has been calibrated with measurements of human biopsy specimens, and it can simulate the variation of cell types in addition to the average number of each cell type. The utility of the model was demonstrated with in silico experiments that evaluated cancer therapy protocols. The model is available for others to conduct additional experiments.

Determining the control networks regulating stem cell lineages in colonic crypts

“…Bravo and Axelrod (2013) performed detailed measurements of the number of each of the three cell types (SCs, TACs, DCs) in 49 colon crypts in human biopsy specimens. In this paper we will examine each of the 32 possible networks (including the 20 networks explicitly presented in Komarova (2013) plus 12 additional ones) to determine whether it can produce the correct measured means and variances of cell population numbers.…”

YY1 is indispensable for Lgr5 + intestinal stem cell renewal

“…Mouse models of human colorectal cancer show that intestinal stem cells can function as cells of origin for cancer (11,12). There is a clear imperative to understand the regulatory mechanisms governing intestinal stem cell function.…”

Optimizing nanomedicine pharmacokinetics using physiologically based pharmacokinetics modelling

“…These phenomena can be influenced by several factors, defining complex interplay which can be successfully represented through mathematics. Pharmacodynamic models have been published for several different disease areas and their relative therapies, such as cancer (Bravo and Axelrod, 2013), malaria (Patel et al, 2013), diabetes (Wilkins et al, 2013) and human immunodeficiency virus (Jacqmin et al, 2008;Duwal et al, 2012). Drug resistance and response to anticancer therapy have been simulated using a semi-mechanistic pharmacodynamic model for the delivery of anticancer agents to hepatocellular carcinoma using nanoparticles (Pascal et al, 2013).…”