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Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories.
- Gerhauser, Clarissa;
- Favero, Francesco;
- Risch, Thomas;
- Simon, Ronald;
- Feuerbach, Lars;
- Assenov, Yassen;
- Heckmann, Doreen;
- Sidiropoulos, Nikos;
- Waszak, Sebastian M;
- Hübschmann, Daniel;
- Urbanucci, Alfonso;
- Girma, Etsehiwot G;
- Kuryshev, Vladimir;
- Klimczak, Leszek J;
- Saini, Natalie;
- Stütz, Adrian M;
- Weichenhan, Dieter;
- Böttcher, Lisa-Marie;
- Toth, Reka;
- Hendriksen, Josephine D;
- Koop, Christina;
- Lutsik, Pavlo;
- Matzk, Sören;
- Warnatz, Hans-Jörg;
- Amstislavskiy, Vyacheslav;
- Feuerstein, Clarissa;
- Raeder, Benjamin;
- Bogatyrova, Olga;
- Schmitz, Eva-Maria;
- Hube-Magg, Claudia;
- Kluth, Martina;
- Huland, Hartwig;
- Graefen, Markus;
- Lawerenz, Chris;
- Henry, Gervaise H;
- Yamaguchi, Takafumi N;
- Malewska, Alicia;
- Meiners, Jan;
- Schilling, Daniela;
- Reisinger, Eva;
- Eils, Roland;
- Schlesner, Matthias;
- Strand, Douglas W;
- Bristow, Robert G;
- Boutros, Paul C;
- von Kalle, Christof;
- Gordenin, Dmitry;
- Sültmann, Holger;
- Brors, Benedikt;
- Sauter, Guido;
- Plass, Christoph;
- Yaspo, Marie-Laure;
- Korbel, Jan O;
- Schlomm, Thorsten;
- Weischenfeldt, Joachim
- et al.
Published Web Location
https://doi.org/10.1016/j.ccell.2018.10.016Abstract
Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ≤55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.
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