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Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

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Risch,  Thomas
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Warnatz,  Hans-Jörg
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Amstislavskiy,  Vyacheslav
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Yaspo,  Marie-Laure
Gene Regulation and Systems Biology of Cancer (Marie-Laure Yaspo), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Gerhauser.pdf
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Citation

Gerhauser, C., Favero, F., Risch, T., Simon, R., Feuerbach, L., Assenov, Y., et al. (2018). Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories. Cancer Cell, 34(6), 996-1011. doi:10.1016/j.ccell.2018.10.016.


Cite as: http://hdl.handle.net/21.11116/0000-0002-E51A-F
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.