Premium
Integration of ERG gene mapping and gene‐expression profiling identifies distinct categories of human prostate cancer
Author(s) -
Jhavar Sameer,
Brewer Daniel,
Edwards Sandra,
KoteJarai Zsofia,
Attard Gerhardt,
Clark Jeremy,
Flohr Penny,
Christmas Timothy,
Thompson Alan,
Parker Matthew,
Shepherd Christopher,
Stenman UlfHakan,
Marchbank Tania,
Playford Raymond J.,
Woodhouse Christopher,
Ogden Christopher,
Fisher Cyril,
Kovacs Gyula,
Corbishley Cathy,
Jameson Charles,
Norman Andy,
DeBono Johann,
Bjartell Anders,
Eeles Rosalind,
Cooper Colin S.
Publication year - 2009
Publication title -
bju international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.773
H-Index - 148
eISSN - 1464-410X
pISSN - 1464-4096
DOI - 10.1111/j.1464-410x.2008.08200.x
Subject(s) - erg , prostate cancer , biology , prostate , gene expression profiling , gene , gene expression , computational biology , cancer research , cancer , microarray , genetics , neuroscience , retina
OBJECTIVE To integrate the mapping of ERG alterations with the collection of expression microarray (EMA) data, as previous EMA analyses have failed to consider the genetic heterogeneity and complex patterns of ERG alteration frequently found in cancerous prostates. MATERIALS AND METHODS We determined genome‐wide expression levels with GeneChip Human Exon 1.0 ST arrays (Affymetrix, Santa Clara, CA, USA) using RNA prepared from 35 specimens of prostate cancer from 28 prostates. RESULTS The expression profiles showed clustering, in unsupervised hierarchical analyses, into two distinct prostate cancer categories, with one group strongly associated with indicators of poor clinical outcome. The two categories are not tightly linked to ERG status. By analysis of the data we identified a subgroup of cancers lacking ERG rearrangements that showed an outlier pattern of SPINK1 mRNA expression. There was a major distinction between ERG rearranged and non‐rearranged cancers that involves the levels of expression of genes linked to exposure to β‐oestradiol, and to retinoic acid. CONCLUSIONS Expression profiling of prostate cancer samples containing single patterns of ERG alterations can provide novel insights into the mechanism of prostate cancer development, and support the view that factors other than ERG status are the major determinants of poor clinical outcome.