In a Molecular Systems Biology paper released this week, our team at the University of Toronto revealed a new mathematical model that links functional cellular assays to specific model outputs, defines cell-level kinetic parameters such as cell cycle rates and self-renewal probabilities as functions of culture variables, and simulates feedback regulation using cell–cell interaction networks. In lay terms, we created a model that can explain communication between cells, specifically cells that control the growth of blood cells.
The goal of our study was to understand what regulated human blood stem cell growth outside of the body. Blood stem cell transplantation is used to treat and cure genetic blood diseases, such as anemia, and blood cancers, like leukemia and lymphoma. Usually, the more blood stem cells you have to transplant, the better the outcome. But while there is great demand, there is not a large supply, primarily because it is so hard to grow blood stem cells in vitro. Scientists have been working for years to expand these cells, but nobody has yet been able to find a robust and reliable method.
In the human body, cells talk to each other using secreted factors. Sometimes they send messages that encourage cell growth and sometimes they send messages that disrupt cell growth. Our model provides a formal framework to try to understand the codes that cells use in this communication system. We tested our model predictions by culturing umbilical cord blood stem cells and measured the effects of specific manipulations on blood stem and progenitors cell output. We found that we could influence communication between cells, disrupting cellular cross-talk that hindered growth and encouraging cross-talk that stimulated growth. Our model is a useful tool to simulate blood culture outputs and to test, in silico (in computer simulations), new ideas about how to improve blood stem cell growth. We’ve applied this model to cell cultures in various configurations, and also expanded it to provide insight how blood stem cells may be regulated in humans under normal and abnormal conditions, such as in patients with leukemia
Using our model, we can use a computer to predict conditions for enhanced blood stem cell growth outside of the body. This should contribute towards efforts to generate a greater supply of blood stem cells for transplantation, which would greatly impact the hundreds of thousands of people suffering from blood diseases and cancers around the world.
— Peter Zandstra and Daniel Kirouac, University of Toronto
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