Computers in Biology and MedicineEvolutionary BiologyPeer-reviewed journal article
Stochastic modelling of prostate progenitor architecture
Abstract
Prostate cancer is a significant global health concern. Experimental and clinical research have contributed to the improvement of treatment outcomes dramatically in the past decade. However, much of the structure of the prostate and its constituent cell types remains unclear: observations of phenotypic switching between basal and luminal cells, as well as intermediate cell types between them, make classifying the components of the prostate an ongoing challenge. Importantly, a tumours cell type of origin seems to play a role in the aggressiveness and genetic heterogeneity of the cancer. To understand how different structures between cell types impact the emergence and treatment of prostate cancer, we model the emergence of a tumour by a fit mutant arising amongst healthy cells via a compartmental modelling approach. We label cells in different compartments based on their phenotype and allow for phenotypic switching between them. We measure the time until and probability of invasion and extinction of this mutant in healthy prostates through individual-based simulations. We find that less-tight population size regulation of the luminal compartment allows for the explosive population growth associated with cancer. Tumours arising in the basal compartment require more time to spread but are more strongly embedded within the prostate, explaining the longer latency and higher aggressiveness and persistence associated with these tumours. Interestingly, the inclusion of a hybrid compartment does not qualitatively change the observations, raising questions as to what mechanistic role intermediate phenotypes play in prostate cancer emergence, if any. Our model contributes to dissecting the relationship between prostate structure and outcomes for cancers arising therein.
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