000294791 001__ 294791 000294791 005__ 20241204090648.0 000294791 0247_ $$2doi$$a10.1016/j.xgen.2024.100511 000294791 037__ $$aDKFZ-2024-02503 000294791 082__ $$a610 000294791 1001_ $$aWoodcock, Dan J.$$b0 000294791 245__ $$aGenomic evolution shapes prostate cancer disease type 000294791 260__ $$aAmsterdam$$bElsevier$$c2024 000294791 3367_ $$2DRIVER$$aarticle 000294791 3367_ $$2DataCite$$aOutput Types/Journal article 000294791 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1733299276_24286 000294791 3367_ $$2BibTeX$$aARTICLE 000294791 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000294791 3367_ $$00$$2EndNote$$aJournal Article 000294791 520__ $$aThe 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.Keywords: AR binding; cancer evolution; evotype model; evotypes; ordering; prostate cancer. 000294791 536__ $$0G:(DE-HGF)POF4-312$$a312 - Funktionelle und strukturelle Genomforschung (POF4-312)$$cPOF4-312$$fPOF IV$$x0 000294791 588__ $$aDataset connected to CrossRef, Journals: inrepo02.dkfz.de 000294791 7001_ $$aSahli, Atef$$b1 000294791 7001_ $$aTeslo, Ruxandra$$b2 000294791 7001_ $$aBhandari, Vinayak$$b3 000294791 7001_ $$aGruber, Andreas J.$$b4 000294791 7001_ $$aZiubroniewicz, Aleksandra$$b5 000294791 7001_ $$aGundem, Gunes$$b6 000294791 7001_ $$aXu, Yaobo$$b7 000294791 7001_ $$aButler, Adam$$b8 000294791 7001_ $$aAnokian, Ezequiel$$b9 000294791 7001_ $$aPope, Bernard J.$$b10 000294791 7001_ $$aJung, Chol-Hee$$b11 000294791 7001_ $$aTarabichi, Maxime$$b12 000294791 7001_ $$0P:(DE-He78)40af5fd3ec583f9dc5da1c7c7e00524f$$aDentro, Stefan$$b13$$udkfz 000294791 7001_ $$aFarmery, J. Henry R.$$b14 000294791 7001_ $$aVan Loo, Peter$$b15 000294791 7001_ $$aWarren, Anne Y.$$b16 000294791 7001_ $$aGnanapragasam, Vincent$$b17 000294791 7001_ $$aHamdy, Freddie C.$$b18 000294791 7001_ $$aBova, G. Steven$$b19 000294791 7001_ $$aFoster, Christopher S.$$b20 000294791 7001_ $$aNeal, David E.$$b21 000294791 7001_ $$aLu, Yong-Jie$$b22 000294791 7001_ $$aKote-Jarai, Zsofia$$b23 000294791 7001_ $$aFraser, Michael$$b24 000294791 7001_ $$aBristow, Robert G.$$b25 000294791 7001_ $$aBoutros, Paul C.$$b26 000294791 7001_ $$aCostello, Anthony J.$$b27 000294791 7001_ $$aCorcoran, Niall M.$$b28 000294791 7001_ $$aHovens, Christopher M.$$b29 000294791 7001_ $$aMassie, Charlie E.$$b30 000294791 7001_ $$aLynch, Andy G.$$b31 000294791 7001_ $$aBrewer, Daniel S.$$b32 000294791 7001_ $$aEeles, Rosalind A.$$b33 000294791 7001_ $$aCooper, Colin S.$$b34 000294791 7001_ $$aWedge, David C.$$b35 000294791 773__ $$0PERI:(DE-600)3110160-4$$a10.1016/j.xgen.2024.100511$$gVol. 4, no. 3, p. 100511 -$$n3$$p100511 -$$tCell genomics$$v4$$x2666-979X$$y2024 000294791 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)40af5fd3ec583f9dc5da1c7c7e00524f$$aDeutsches Krebsforschungszentrum$$b13$$kDKFZ 000294791 9131_ $$0G:(DE-HGF)POF4-312$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vFunktionelle und strukturelle Genomforschung$$x0 000294791 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-08-29 000294791 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-08-29 000294791 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2023-08-29 000294791 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2023-05-09T12:14:04Z 000294791 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2023-05-09T12:14:04Z 000294791 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Double anonymous peer review$$d2023-05-09T12:14:04Z 000294791 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2023-08-29 000294791 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2023-08-29 000294791 9201_ $$0I:(DE-He78)B450-20160331$$kB450$$lKünstl. Intelligenz in der Onkologie$$x0 000294791 980__ $$ajournal 000294791 980__ $$aUSER 000294791 980__ $$aVDBRELEVANT 000294791 980__ $$aI:(DE-He78)B450-20160331