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[Preprint]. 2025 Mar 17:arXiv:2503.13189v1.

Causes of evolutionary divergence in prostate cancer

Emre Esentürk¹, Atef Sahli², Valeriia Haberland³, Aleksandra Ziuboniewicz⁴, Christopher Wirth², G Steven Bova⁵, Robert G Bristow^{6

7

8}, Mark N Brook⁹, Benedikt Brors^{10

11

12}, Adam Butler¹³, Géraldine Cancel-Tassin^{14

15}, Kevin Cl Cheng^{16

17}, Colin S Cooper³, Niall M Corcoran^{18

19

20}, Olivier Cussenot¹⁴, Ros A Eeles^{9

21}, Francesco Favero^{22

23}, Clarissa Gerhauser²⁴, Abraham Gihawi³, Etsehiwot G Girma^{22

23}, Vincent J Gnanapragasam²⁵, Andreas J Gruber²⁶, Anis Hamid¹⁹, Vanessa M Hayes^{27

28

29}, Housheng Hansen He³⁰, Christopher M Hovens³¹, Eddie Luidy Imada³², G Maria Jakobsdottir^{33

34}, Chol-Hee Jung³⁵, Francesca Khani³², Zsofia Kote-Jarai^{9

21}, Philippe Lamy^{36

37}, Gregory Leeman¹³, Massimo Loda^{32

4}, Pavlo Lutsik^{24

38}, Luigi Marchionni³², Ramyar Molania^{39

40}, Anthony T Papenfuss^{39

40}, Diogo Pellegrina¹⁶, Bernard Pope^{35

41

19}, Lucio R Queiroz³², Tobias Rausch⁴², Jüri Reimand^{16

43

17}, Brian Robinson³², Thorsten Schlomm⁴⁴, Karina D Sørensen^{36

37}, Sebastian Uhrig¹⁰, Joachim Weischenfeldt^{22

23

44}, Yaobo Xu¹³, Takafumi N Yamaguchi⁴⁵, Claudio Zanettini³², Andy G Lynch⁴⁶, David C Wedge², Daniel S Brewer^{47

48}, Dan J Woodcock⁴

Affiliations

¹ Nuffield Department of Medicine, University of Oxford, UK.
² Manchester Cancer Research Centre, The University of Manchester, UK.
³ Norwich Medical School, University of East Anglia, UK.
⁴ Nuffield Department of Surgical Sciences, University of Oxford, UK.
⁵ Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University, Finland.
⁶ Manchester Cancer Research Centre and Cancer Research UK Manchester Institute, The University of Manchester, UK.
⁷ Christie NHS Foundation Trust, UK.
⁸ Div Cancer Sciences, Faculty of Biology, Medicine & Health, University of Manchester, UK.
⁹ The Institute of Cancer Research, UK.
¹⁰ Division Applied Bioinformatics, German Cancer Research Center (DKFZ), Germany.
¹¹ German Cancer Consortium (DKTK), Core Center Heidelberg, and National Center for Tumor Diseases (NCT), Germany.
¹² Medical Faculty Heidelberg and Faculty of Biosciences, Heidelberg University, Germany.
¹³ Wellcome Sanger Institute, UK.
¹⁴ CeRePP (Centre de Recherche sur les Pathologies Prostatiques et Urologiques), France.
¹⁵ Sorbonne Université, GRC n°5 Predictive Onco-Urology, APHP, Tenon Hospital, France.
¹⁶ Computational Biology Program, Ontario Institute for Cancer Research, Canada.
¹⁷ Department of Medical Biophysics, University of Toronto, Canada.
¹⁸ Department of Urology, Royal Melbourne Hospital, Australia.
¹⁹ Department of Surgery, The University of Melbourne, Australia.
²⁰ Department of Urology, Western Health, Australia.
²¹ The Royal Marsden NHS Foundation Trust, London & Sutton.
²² Biotech Research & Innovation Centre (BRIC) - University of Copenhagen, Denmark.
²³ Finsen Laboratory, Copenhagen University Hospital - Rigshospitalet, Denmark.
²⁴ Division Cancer Epigenomics, German Cancer Research Center (DKFZ), Germany.
²⁵ Department of Surgery, Urology, University of Cambridge & Cambridge University Hospitals NHS Trust, Cambridge Urology Translational Research and Clinical Trials (Office), Cambridge Biomedical Campus, Addenbrooke's Hospital Site, S Wards Building, UK.
²⁶ University of Konstanz, Germany.
²⁷ School of Medical Sciences, University of Sydney, Faculty of Medicine & Health, Australia.
²⁸ School of Health Systems & Public Health, University of Pretoria, South Africa.
²⁹ Manchester Cancer Research Centre, University of Manchester, UK.
³⁰ Princess Margaret Cancer Centre, University Health Network; Department of Medical Biophysics, University of Toronto, Canada.
³¹ Department of Surgery, The Collaborative Centre for Genomic Cancer Medicine, The University of Melbourne, Australia.
³² Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, USA.
³³ Division of Cancer Sciences, The University of Manchester, UK.
³⁴ Christie Hospital, The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, UK.
³⁵ Melbourne Bioinformatics, The University of Melbourne, Australia.
³⁶ Department of Molecular Medicine, Aarhus University Hospital, Denmark.
³⁷ Department of Clinical Medicine, Aarhus University, Denmark.
³⁸ Department of Oncology, KU Leuven, Belgium.
³⁹ Walter and Eliza Hall Institute of Medical Research, Australia.
⁴⁰ Department of Medical Biology, The University of Melbourne, Australia.
⁴¹ Australian BioCommons, The University of Melbourne, Australia.
⁴² Genome Biology, European Molecular Biology Laboratory (EMBL), Germany.
⁴³ Department of Molecular Genetics, University of Toronto, Canada.
⁴⁴ Department of Urology, Charité - Universitätsmedizin Berlin, Germany.
⁴⁵ Jonsson Comprehensive Cancer Center, University of California - Los Angeles, USA.
⁴⁶ School of Medicine, School of Mathematics & Statistics, University of St Andrews, UK.
⁴⁷ Metabolic Health research centre, Norwich Medical School, University of East Anglia, UK.
⁴⁸ The Earlham Institute, UK.

PMID: 40166741
PMCID: PMC11957227

Causes of evolutionary divergence in prostate cancer

Emre Esentürk et al. ArXiv. 2025.

[Preprint]. 2025 Mar 17:arXiv:2503.13189v1.

Authors

Affiliations

¹ Nuffield Department of Medicine, University of Oxford, UK.
² Manchester Cancer Research Centre, The University of Manchester, UK.
³ Norwich Medical School, University of East Anglia, UK.
⁴ Nuffield Department of Surgical Sciences, University of Oxford, UK.
⁵ Prostate Cancer Research Center, Faculty of Medicine and Health Technology, Tampere University, Finland.
⁶ Manchester Cancer Research Centre and Cancer Research UK Manchester Institute, The University of Manchester, UK.
⁷ Christie NHS Foundation Trust, UK.
⁸ Div Cancer Sciences, Faculty of Biology, Medicine & Health, University of Manchester, UK.
⁹ The Institute of Cancer Research, UK.
¹⁰ Division Applied Bioinformatics, German Cancer Research Center (DKFZ), Germany.
¹¹ German Cancer Consortium (DKTK), Core Center Heidelberg, and National Center for Tumor Diseases (NCT), Germany.
¹² Medical Faculty Heidelberg and Faculty of Biosciences, Heidelberg University, Germany.
¹³ Wellcome Sanger Institute, UK.
¹⁴ CeRePP (Centre de Recherche sur les Pathologies Prostatiques et Urologiques), France.
¹⁵ Sorbonne Université, GRC n°5 Predictive Onco-Urology, APHP, Tenon Hospital, France.
¹⁶ Computational Biology Program, Ontario Institute for Cancer Research, Canada.
¹⁷ Department of Medical Biophysics, University of Toronto, Canada.
¹⁸ Department of Urology, Royal Melbourne Hospital, Australia.
¹⁹ Department of Surgery, The University of Melbourne, Australia.
²⁰ Department of Urology, Western Health, Australia.
²¹ The Royal Marsden NHS Foundation Trust, London & Sutton.
²² Biotech Research & Innovation Centre (BRIC) - University of Copenhagen, Denmark.
²³ Finsen Laboratory, Copenhagen University Hospital - Rigshospitalet, Denmark.
²⁴ Division Cancer Epigenomics, German Cancer Research Center (DKFZ), Germany.
²⁵ Department of Surgery, Urology, University of Cambridge & Cambridge University Hospitals NHS Trust, Cambridge Urology Translational Research and Clinical Trials (Office), Cambridge Biomedical Campus, Addenbrooke's Hospital Site, S Wards Building, UK.
²⁶ University of Konstanz, Germany.
²⁷ School of Medical Sciences, University of Sydney, Faculty of Medicine & Health, Australia.
²⁸ School of Health Systems & Public Health, University of Pretoria, South Africa.
²⁹ Manchester Cancer Research Centre, University of Manchester, UK.
³⁰ Princess Margaret Cancer Centre, University Health Network; Department of Medical Biophysics, University of Toronto, Canada.
³¹ Department of Surgery, The Collaborative Centre for Genomic Cancer Medicine, The University of Melbourne, Australia.
³² Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, USA.
³³ Division of Cancer Sciences, The University of Manchester, UK.
³⁴ Christie Hospital, The Christie NHS Foundation Trust, Manchester Academic Health Science Centre, UK.
³⁵ Melbourne Bioinformatics, The University of Melbourne, Australia.
³⁶ Department of Molecular Medicine, Aarhus University Hospital, Denmark.
³⁷ Department of Clinical Medicine, Aarhus University, Denmark.
³⁸ Department of Oncology, KU Leuven, Belgium.
³⁹ Walter and Eliza Hall Institute of Medical Research, Australia.
⁴⁰ Department of Medical Biology, The University of Melbourne, Australia.
⁴¹ Australian BioCommons, The University of Melbourne, Australia.
⁴² Genome Biology, European Molecular Biology Laboratory (EMBL), Germany.
⁴³ Department of Molecular Genetics, University of Toronto, Canada.
⁴⁴ Department of Urology, Charité - Universitätsmedizin Berlin, Germany.
⁴⁵ Jonsson Comprehensive Cancer Center, University of California - Los Angeles, USA.
⁴⁶ School of Medicine, School of Mathematics & Statistics, University of St Andrews, UK.
⁴⁷ Metabolic Health research centre, Norwich Medical School, University of East Anglia, UK.
⁴⁸ The Earlham Institute, UK.

PMID: 40166741
PMCID: PMC11957227

Abstract

Cancer progression involves the sequential accumulation of genetic alterations that cumulatively shape the tumour phenotype. In prostate cancer, tumours can follow divergent evolutionary trajectories that lead to distinct subtypes, but the causes of this divergence remain unclear. While causal inference could elucidate the factors involved, conventional methods are unsuitable due to the possibility of unobserved confounders and ambiguity in the direction of causality. Here, we propose a method that circumvents these issues and apply it to genomic data from 829 prostate cancer patients. We identify several genetic alterations that drive divergence as well as others that prevent this transition, locking tumours into one trajectory. Further analysis reveals that these genetic alterations may cause each other, implying a positive-feedback loop that accelerates divergence. Our findings provide insights into how cancer subtypes emerge and offer a foundation for genomic surveillance strategies aimed at monitoring the progression of prostate cancer.

Keywords: cancer evolution; causal inference; causality; evolutionary divergence; prostate cancer.

PubMed Disclaimer

Conflict of interest statement

COMPETING INTERESTS The authors declare no competing interests.

Figures

**Figure 1 |. Causal inference models**
a) The standard instrumental variables/Mendelian Randomisation model that can be used to estimate the causal effect of the exposure on the outcome. b) An invalid instrumental variable model as it has potential confounders that affect the instrument and outcome. c) The proposed causal model that links the cause X and outcome Y, through a mediator M, while incorporating two sets of confounders. d) the effective parametric model after U confounder is subsumed into the network via do-calculus

**Figure 2 |**
(a) A schematic showing how the graph showing the causal chain between CHD1 loss and other genetic alterations is confounded by unknown direction of causality (left); after modifying the inputs with our CCF-based rules we can establish the direction of the causal links between the nodes in this graph (right) (b) heat map of computed $t A C E_{U} (A R, Y)$ (middle row) with upper CI boundary (top row) and lower CI boundary (bottom row)) (c) heat map of computed $t A C E_{U, V} (A R, Y)$ with ned gligible interference of V (middle row); with interference of Vm (top row); with interference of Vs (bottom row) (d) heat map of computed $t A C E_{U} (C H D 1 -, Y)$ (middle row) with upper CI boundary (top row) and lower CI boundary (bottom row (d) heat map of computed $t A C E_{U, V} (C H D 1 -, Y)$ with negligible interference of V (middle row); with interference of Vm (top row); with interference of Vs (bottom row). The events are displayed in the order of their respective associations with the evotypes - Canonical events to the left followed by events with no significant associations to either evotype in the middle and followed by Alternative events to the right.

**Figure 3 |. Heat map of tACEs between pairs of CNAs.**
a) temporal causal effect with confounding through U only, $t A C E_{U} (C N A_{i}, C N A_{j})$ (b) temporal causal effect with confounding through Vs set to provide a lower bound for Alternative events, $t A C E_{U, V s} (C N A_{i}, C N A_{j})$ . (c) temporal causal effect with confounding through Vm set to provide an upper bound for alternative events, $t A C E_{U, V m} (C N A_{i}, C N A_{j})$ . Greyed out associations are not possible (they cannot cause themselves and an LOH always has to precede an HD of the same region).

See this image and copyright information in PMC

References

1. Casas-Selves M. & Degregori J. How cancer shapes evolution, and how evolution shapes cancer. Evolution (N Y) 4, 624–634 (2011). 10.1007/s12052-011-0373-y - DOI - PMC - PubMed
1. Cairns J. Mutation selection and the natural history of cancer. Nature 255, 197–200 (1975). 10.1038/255197a0 - DOI - PubMed
1. Coyne J. A. & Orr H. A. Speciation. (Sinauer Associates, 2004).
1. Gui P. & Bivona T. G. Evolution of metastasis: new tools and insights. Trends Cancer 8, 98–109 (2022). 10.1016/j.trecan.2021.11.002 - DOI - PubMed
1. Beltran H. et al. Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat Med 22, 298–305 (2016). 10.1038/nm.4045 - DOI - PMC - PubMed

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This is a preprint.

Causes of evolutionary divergence in prostate cancer

Affiliations

Causes of evolutionary divergence in prostate cancer

Authors

Affiliations

Abstract

Conflict of interest statement

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