Tumor architecture and emergence of strong genetic alterations are bottlenecks for clonal evolution in primary prostate cancer.

Autor:	Kreten F; Institute for Applied Mathematics, University of Bonn, Bonn 53115, Germany; Institute of Pathology, University Hospital Cologne, Cologne 50937, Germany. Electronic address: florian.kreten@uk-koeln.de., Büttner R; Institute of Pathology, University Hospital Cologne, Cologne 50937, Germany., Peifer M; University of Cologne, Medical Faculty, Cologne 50937, Germany., Harder C; Institute of Pathology, University Hospital Cologne, Cologne 50937, Germany., Hillmer AM; Institute of Pathology, University Hospital Cologne, Cologne 50937, Germany., Abedpour N; University of Cologne, Medical Faculty, Cologne 50937, Germany., Bovier A; Institute for Applied Mathematics, University of Bonn, Bonn 53115, Germany., Tolkach Y; Institute of Pathology, University Hospital Cologne, Cologne 50937, Germany. Electronic address: yuri.tolkach@gmail.com.
Jazyk:	angličtina
Zdroj:	Cell systems [Cell Syst] 2024 Nov 20; Vol. 15 (11), pp. 1061-1074.e7. Date of Electronic Publication: 2024 Nov 13.
DOI:	10.1016/j.cels.2024.10.005
Abstrakt:	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. Competing Interests: Declaration of interests The authors declare no competing interests. (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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