Abstract
The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.
Original language | English |
---|---|
Article number | 100511 |
Journal | Cell Genomics |
Volume | 4 |
Issue number | 3 |
Early online date | 29 Feb 2024 |
DOIs | |
Publication status | Published - 13 Mar 2024 |
Keywords
- AR binding
- cancer evolution
- evotype model
- evotypes
- ordering
- prostate cancer
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Genomic evolution shapes prostate cancer disease type. / Woodcock, Dan J.; Sahli, Atef; Teslo, Ruxandra et al.
In: Cell Genomics, Vol. 4, No. 3, 100511, 13.03.2024.Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Genomic evolution shapes prostate cancer disease type
AU - Woodcock, Dan J.
AU - Sahli, Atef
AU - Teslo, Ruxandra
AU - Bhandari, Vinayak
AU - Gruber, Andreas J.
AU - Ziubroniewicz, Aleksandra
AU - Gundem, Gunes
AU - Xu, Yaobo
AU - Butler, Adam
AU - Anokian, Ezequiel
AU - Pope, Bernard J.
AU - Jung, Chol-Hee
AU - Tarabichi, Maxime
AU - Dentro, Stefan C.
AU - Farmery, J. Henry R.
AU - Van Loo, Peter
AU - Warren, Anne Y.
AU - Gnanapragasam, Vincent
AU - Hamdy, Freddie C.
AU - Bova, G. Steven
AU - Foster, Christopher S.
AU - Neal, David E.
AU - Lu, Yong-Jie
AU - Kote-Jarai, Zsofia
AU - Fraser, Michael
AU - Bristow, Robert G.
AU - Boutros, Paul C.
AU - Costello, Anthony J.
AU - Corcoran, Niall M.
AU - Hovens, Christopher M.
AU - Massie, Charlie E.
AU - Lynch, Andy G.
AU - Brewer, Daniel S.
AU - Eeles, Rosalind A.
AU - Cooper, Colin S.
AU - Wedge, David C.
N1 - Funding Information: The authors acknowledge support from Cancer Research UK C5047/A29626, C5047/A22530, C309/A11566, C368/A6743, A368/A7990, and C14303/A17197; the Dallaglio Foundation; Prostate Cancer UK; and Prostate Cancer Research. We also acknowledge NIHR support to The Biomedical Research Centre at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust; Cancer Research UK funding to The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust CRUK Centre; and the National Cancer Research Institute (National Institute of Health Research [NIHR] Collaborative Study: “Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT)”) (grant G0500966/75466 ). We thank the National Institute for Health Research; Hutchison Whampoa Limited; University of Cambridge; the Human Research Tissue Bank (Addenbrooke’s Hospital), which is supported by the NIHR Cambridge Biomedical Research Centre; and The Core Facilities at the Cancer Research UK Cambridge Institute. The Cambridge Human Research Tissue Bank and A.Y.W. are supported by the NIHR Cambridge Biomedical Research Centre. C.E.M. was supported by a CRUK Major Centre Award through the CRUK Cambridge Centre Early Detection Programme and Urological Malignancies Programme. A.J.G. was funded by an SNF postdoctoral mobility fellowship (P2BSP3_178591). J.H.R.F. was supported by a Cancer Research UK Programme Grant to Simon Tavaré (C14303/A17197), as, partially, was A.G.L. A.G.L. acknowledges the support of the University of St Andrews. A.G.L. and J.H.R.F. also acknowledge the support of the Cambridge Cancer Research Fund. This work was supported by The Francis Crick Institute , which receives its core funding from Cancer Research UK (CC2008), the UK Medical Research Council (CC2008), and the Wellcome Trust (CC2008) (M.T. and P.V.L.). M.T. was a postdoctoral fellow supported by the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie grant agreement no. 747852-SIOMICS ). P.V.L. is a CPRIT Scholar in Cancer Research, acknowledges CPRIT grant support ( RR210006 ), and was a Winton Group Leader in recognition of the Winton Charitable Foundation’s support toward the establishment of The Francis Crick Institute . G.S.B. was supported by the Academy of Finland , the Cancer Society of Finland , and the Sigrid Jusélius Foundation . The Melbourne Prostate Cancer Research Group was supported by NHMRC project grants 1024081 (N.M.C. and C.M.H.) and 1047581 (C.M.H. and N.M.C.), as well as a federal grant from the Australian Department of Health and Aging to the Epworth Cancer Centre, Epworth Hospital (A.J.C., N.M.C., and C.M.H.). B.J.P. was supported by a Victorian Health and Medical Research Fellowship. The Canadian Prostate Cancer Genome Network was supported by Prostate Cancer Canada with funds from Movember and by the Ontario Institute for Cancer Research. P.C.B. was supported by the NIH / NCI under award number P30CA016042. V.B. was funded by a fellowship from the Canadian Institutes for Health Research and was supported by a Michael Smith Foreign Study Supplement from the Canadian Institutes for Health Research. We also acknowledge support from the Bob Champion Cancer Research Trust , the Masonic Charitable Foundation, the King Family, and the Stephen Hargrave Foundation. Computation used the Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Centre for Human Genetics and the Big Data Institute supported by Health Data Research UK and the NIHR Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. Rights retention statement: For the purpose of open access, the authors have applied a CC BY public copyright license to any author-accepted manuscript version arising from this submission.
PY - 2024/3/13
Y1 - 2024/3/13
N2 - The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.
AB - The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.
KW - AR binding
KW - cancer evolution
KW - evotype model
KW - evotypes
KW - ordering
KW - prostate cancer
UR - http://www.scopus.com/inward/record.url?scp=85186331848&partnerID=8YFLogxK
U2 - 10.1016/j.xgen.2024.100511
DO - 10.1016/j.xgen.2024.100511
M3 - Article
VL - 4
JO - Cell Genomics
JF - Cell Genomics
SN - 2666-979X
IS - 3
M1 - 100511
ER -