학술논문
Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories.
Document Type
article
Author
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
Source
Cancer cell. 34(6)
Subject
Language
Abstract
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.