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Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study
Author(s) -
Helen RossAdams,
Alastair Lamb,
Mark Dunning,
Silvia Halim,
Johan Lindberg,
Charles Massie,
Lars Egevad,
Robert B. Russell,
Antonio RamosMontoya,
Sarah L. Vowler,
Nitin Sharma,
Jonathan Kay,
Hayley C. Whitaker,
J Clark,
Rachel Hurst,
Vincent J. Gnanapragasam,
Nimish Shah,
Anne Y. Warren,
Christopher S. Cooper,
Andy G. Lynch,
Rory Stark,
Ian G. Mills,
Henrik Grönberg,
David E. Neal
Publication year - 2015
Publication title -
ebiomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.596
H-Index - 63
ISSN - 2352-3964
DOI - 10.1016/j.ebiom.2015.07.017
Subject(s) - risk stratification , prostate cancer , transcriptome , computational biology , oncology , cohort , medicine , stratification (seeds) , bioinformatics , biology , cancer , genetics , gene , gene expression , seed dormancy , germination , botany , dormancy
Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

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