Prof. Dr. Anton Bovier
Probability Theory and Stochastic Analysis
bovier@uni-bonn.de View member: Prof. Dr. Anton Bovier
Cell systems
Prostate cancer (PCA) exhibits high levels of intratumoral heterogeneity. In this study, we developed a mathematical model to study the growth and genetic evolution of PCA. We explored the possible evolutionary patterns and demonstrated that tumor architecture represents a major bottleneck for divergent clonal evolution. Early consecutive acquisition of strong genetic alterations serves as a proxy for the formation of aggressive tumors. A limited number of clonal hierarchy patterns were identified. A biopsy study of synthetic tumors shows complex spatial intermixing of clones and delineates the importance of biopsy extent. Deep whole-exome multiregional next-generation DNA sequencing of the primary tumors from five patients was performed to validate the results, supporting our main findings from mathematical modeling. In conclusion, our model provides qualitatively realistic predictions of PCA genomic evolution, closely aligned with the evidence available from patient samples. We share the code of the model for further studies. A record of this paper's transparent peer review process is included in the supplemental information.
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.
PMID: 39541986
Probability Theory and Stochastic Analysis
bovier@uni-bonn.de View member: Prof. Dr. Anton Bovier