Finding the Statistical Rules of Blood Regeneration
On September 26 , as part of the Fields Centre for
Mathematical Medicine Seminar Series , Professor Sidhartha Goyal from the University of Toronto presented a phenomenological model of blood regeneration to explain how 100 billion new blood cells are made every day from a much smaller pool of blood stem cells .
Using data from a primate experiment that tracked the offspring of blood stem cell clones over time , Goyal studied the clone size distribution , or how much each initial stem cell contributes to the final blood pool . Two interesting results emerged : first , the distribution was very broad , with some clones contributing as much as 10 % of the blood and others contributing very little ; second , the size distribution remained constant even as the various clones ebbed and surged in numbers .
“ The stability is in this distribution rather than the individual actors ,” says Goyal .
To explain results such as these , the idea of cellular heterogeneity has taken centre stage in blood research – is there some fundamental cell-level difference that determines which clone will overtake the others ?
Using a simple , three-compartment model of stem cells , progenitor cells , and somatic cells , Goyal found that , in fact , the same broad distributions can be reproduced without any differences in the starting population of blood stem cells . That is , the results obtained in the primate experiment could be explained purely by chance .
“ This model allowed us to generate a new hypothesis , which right now is completely counterintuitive to anybody who thinks about these things . That is the real reason to do math models in my mind ."
“ The truth is probably somewhere in the middle ,” he explains , with some clone success due to cell-specific differences and some due to chance ."
But if chance is a major driver as Goyal ’ s results suggest , then the model makes some interesting predictions that could have profound implications in the treatment of blood diseases like leukemia . Currently leukemia is treated with chemotherapy and bone marrow transplant in order to rid the body of the defective blood stem cell pool and replace it with a healthy one . But if the presence of a large number of cancerous blood cells is not due to their superiority over other normal cells , but simply because of statistical probability , then perhaps the defective cells can be replaced in a different way .
Goyal reasons that if the clone size distribution could be reset and allowed to broaden again , the results may be different , with the cancerous clone now contributing very little to the blood pool . This could be done , Goyal suggests , by adding growth factors , increasing the differentiation and proliferation rate of all clones and transiently evening the playing field .
“ This model allowed us to generate a new hypothesis , which right now is completely counterintuitive to anybody who thinks about these things . That is the real reason to do math models in my mind – that ’ s the real contribution .”
Goyal is now looking for collaborators to test these predictions either in vitro or in animal models . The results could change the way we think about treating blood cancers . �
— Malgosia Ip
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