Cancer Cell
`
`Article
`
`Integrative Genomic Profiling
`of Human Prostate Cancer
`
`Barry S. Taylor,1,8 Nikolaus Schultz,1,8 Haley Hieronymus,2,8 Anuradha Gopalan,3 Yonghong Xiao,3 Brett S. Carver,4
`Vivek K. Arora,2 Poorvi Kaushik,1 Ethan Cerami,1 Boris Reva,1 Yevgeniy Antipin,1 Nicholas Mitsiades,5 Thomas Landers,2
`Igor Dolgalev,2 John E. Major,6 Manda Wilson,6 Nicholas D. Socci,6 Alex E. Lash,6 Adriana Heguy,2 James A. Eastham,4
`Howard I. Scher,5 Victor E. Reuter,3 Peter T. Scardino,4 Chris Sander,1 Charles L. Sawyers,2,7,* and William L. Gerald2,3,9
`1Program in Computational Biology
`2Program in Human Oncology and Pathogenesis (HOPP)
`3Department of Pathology
`4Department of Urology
`5Department of Medicine
`6Bioinformatics Core
`Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
`7Howard Hughes Medical Institute, Chevy Chase, MD 20815-6789, USA
`8These authors contributed equally to this work
`9Deceased
`*Correspondence: sawyersc@mskcc.org
`DOI 10.1016/j.ccr.2010.05.026
`
`SUMMARY
`
`Annotation of prostate cancer genomes provides a foundation for discoveries that can impact disease under-
`standing and treatment. Concordant assessment of DNA copy number, mRNA expression, and focused exon
`resequencing in 218 prostate cancer tumors identified the nuclear receptor coactivator NCOA2 as an onco-
`gene in 11% of tumors. Additionally, the androgen-driven TMPRSS2-ERG fusion was associated with
`a previously unrecognized, prostate-specific deletion at chromosome 3p14 that implicates FOXP1, RYBP,
`and SHQ1 as potential cooperative tumor suppressors. DNA copy-number data from primary tumors
`revealed that copy-number alterations robustly define clusters of low- and high-risk disease beyond that
`achieved by Gleason score. The genomic and clinical outcome data from these patients are now made avail-
`able as a public resource.
`
`INTRODUCTION
`
`Prostate cancer is the most common malignancy in males with
`190,000 new cases diagnosed per year in the United States
`and 27,000 deaths. Prostate tumors show tremendous biolog-
`ical heterogeneity, with some patients dying of metastatic
`disease within 2–3 years of diagnosis whereas others can live
`for 10–20 years with organ-confined disease, likely a reflection
`of underlying genomic diversity. Large-scale cancer genome
`characterization projects studying glioblastoma, lung, colon,
`pancreas, and breast cancers have provided critical new insights
`
`into the molecular classification of cancers and have the poten-
`tial to identify new therapeutic targets (Cancer Genome Atlas
`Research Network, 2008; Ding et al., 2008; Jones et al., 2008;
`Parsons et al., 2008; Sjoblom et al., 2006; Weir et al., 2007;
`Wood et al., 2007). Prostate cancer presents special challenges
`for such large-scale multicenter genomics projects because of
`the relatively small tumor size and admixture with stroma that
`requires careful pathologist-guided dissection.
`A number of groups have reported analyses of transcriptomes
`and copy-number alterations (CNAs)
`in prostate cancer,
`but rarely from the same samples and typically from modest
`
`Significance
`
`Current knowledge of prostate cancer genomes is largely based on small patient cohorts using single modality platforms.
`We present an integrated oncogenomic analysis of 218 primary and metastatic prostate cancers as well as 12 cell lines and
`xenografts. Mutations in known, commonly mutated oncogenes and tumor suppressor genes such as PIK3CA, KRAS,
`BRAF, and TP53 are present but rare. However, integrative analysis of mutations, copy-number alterations, and expression
`changes revealed changes in the PI3K, RAS/RAF, and androgen receptor (AR) pathways in nearly all metastatic samples and
`a high frequency of primary samples. These data clarify the role of several known cancer pathways in prostate cancer, impli-
`cate several new ones, and provide a blueprint for clinical development of pathway inhibitors.
`
`Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc. 11
`
`AVENTIS EXHIBIT 2124
`Mylan v. Aventis, IPR2016-00712
`
`
`

`
`Genomic Characterization of Human Prostate Cancers
`
`Cancer Cell
`
`Table 1. Summary of Clinical Characteristics for the Study
`Cohort
`
`Characteristic
`
`Primary Tumorsa
`
`Metastasesb
`
`Age
`
`Median
`
`Mean
`
`Standard deviation
`
`58.3
`
`58.3
`
`7
`
`60
`
`60
`
`8.6
`
`Min-max
`
`37.3-83
`
`41-82
`
`PSA at Diagnosis (ng/ml)
`
`Median
`
`<4
`
`4–10
`
`>10
`
`6 (IQR 4.4, 9)
`
`17 (IQR 8.6, 46.6)
`
`31 (17.2%)
`
`105 (58.3%)
`
`44 (24.5%)
`
`4 (12.5%)
`
`6 (18.75%)
`
`22 (68.75%)
`
`Initial Biopsy Gleason Score
`
`5
`
`6
`
`7
`
`8
`
`9
`
`Initial Clinical Stage
`
`cT1c
`
`cT2
`
`cT3
`
`cT4
`
`Not available
`
`Ethnicity
`
`Black
`
`Asian
`
`White Hispanic
`
`2 (1%)
`
`101 (56%)
`
`61 (34%)
`
`11 (6%)
`
`6 (3%)
`
`95 (52.4%)
`
`76 (42%)
`
`9 (5%)
`
`–
`
`–
`
`29 (16.1%)
`
`4 (2.2%)
`
`0 (0%)
`
`–
`
`2 (6%)
`
`16 (46%)
`
`8 (23%)
`
`9 (25%)
`
`8 (22%)
`
`12 (33%)
`
`3 (8%)
`
`1 (3%)
`
`9 (25%)
`
`2 (5.6%)
`
`0 (0%)
`
`2 (5.6%)
`
`White non-Hispanic
`
`142 (78.5%)
`
`32 (88.9%)
`
`Unknown
`
`6 (3.3%)
`
`0 (0%)
`
`The cohort is composed of
`a primary tumors (n = 181; one patient with metastasis and primary
`analyzed) and
`b metastases (n = 37; one patient with two metastases analyzed), cell
`lines (n = 7; CWR22RV1, DU145, PC3, VCaP, LNCaP, LNCaP104R,
`LNCaP104S), and xenografts (n = 5; LAPC9, LNM971, LuCaP35,
`LAPC3, and LAPC4 [for both, two samples at different passages]). See
`also Figure S1 and Table S1.
`
`possibility that our stringent tumor selection criteria might bias
`our data set toward larger, more aggressive prostate cancers,
`we compared the clinical outcome of the 181 primary tumors
`(Table S1) in this data set with 3437 consecutive men with pros-
`tate cancer treated by prostatectomy at MSKCC from 2000 to
`2006. The time to biochemical relapse, defined as an increase
`in serum prostate-specific antigen, was somewhat shorter in
`this study cohort (Table 1; Figure S1A). While this indicates
`that genomic findings from these samples may be biased toward
`larger, more aggressive prostate cancers (selected to ensure
`sufficient nucleic acid yield), this cohort nevertheless includes
`patients with favorable long-term clinical outcome (24% of
`patients have >5 years of recurrence-free survival).
`Global analysis of CNA data from 194 tumors and 12 cell
`lines/xenografts revealed broad diversity in alteration levels.
`
`numbers of tumors (50–100 samples) or with lower resolution
`platforms (Kim et al., 2007; Lapointe et al., 2004, 2007; Lieber-
`farb et al., 2003; Perner et al., 2006; Singh et al., 2002). Con-
`sistent and common findings from these reports include the
`TMPRSS2-ERG fusion in 50%, 8p loss in 30%–50%, and
`8q gain in 20%–40% of cases. The data implicating ERG as
`a prostate cancer gene are clear (Tomlins et al., 2005), but there
`has been less progress in defining specific genes targeted by
`various common amplifications and deletions, in part due to
`limited availability of complementary transcriptome and exon
`resequencing data on sufficient patients to narrow the focus to
`a small list of candidate genes. Numerous transcriptome studies
`have defined general prostate cancer signatures, but, unlike
`breast cancer (Paik et al., 2004; van de Vijver et al., 2002), these
`analyses have not identified robust subtypes of prostate cancer
`with different prognoses (Febbo and Sellers, 2003; Lapointe
`et al., 2004; Singh et al., 2002).
`Here, we adopted a comprehensive approach to define tran-
`scriptomes and CNAs in 218 prostate tumors (181 primaries,
`37 metastases) and 12 prostate cancer cell lines and xenografts,
`as well as complete exon resequencing and/or focused mutation
`detection for 157 high interest genes in 80 tumors and 11 cell/
`xenograft lines (Table 1). After generating a map of CNAs across
`the data set, we used matching mRNA and microRNA transcrip-
`tome and exon resequencing data to define the frequency of
`alterations in several common signal transduction pathways,
`explore various candidate genes within a few selected regions
`of copy-number gain and loss, and correlate genomic alter-
`ations to clinical outcome. These data serve as a valuable
`resource for the cancer genomics community, prostate cancer
`scientists and clinicians and is readily and freely available
`through a user-friendly web-based portal
`(http://cbio.mskcc.
`org/prostate-portal/).
`
`RESULTS
`
`Global Copy-Number and Transcriptome Profiles Define
`Core Pathway Alterations
`We applied rigorous criteria for selecting tumors for genomic
`analysis that have become the standard in large genomic studies
`(Cancer Genome Atlas Research Network, 2008) but adapted to
`address unique challenges posed by prostate cancers. All 218
`samples had at least 70% tumor content (Table 1; Figure S1
`and Table S1 available online). Transcriptome (mRNA and micro-
`RNA) and CNA profiling were conducted without amplification,
`with the exception of exon resequencing, which required
`whole-genome amplification. Because we did not
`impose
`a stringent tumor size requirement, the small size of some tumors
`precluded concurrent analysis across all four platforms (Table 2;
`Table S2).
`Analysis of known prostate cancer alterations in our data set
`indicates successful tumor selection criteria (Figure S1). For
`example, the frequency of ERG alteration was 52% (see Exper-
`imental Procedures), consistent with other studies, and chromo-
`some 8p loss and 8q gain were easily detected (Figure 1A). Overt
`CNAs were observed in 89% of tumors, also indicative of high
`tumor content. Additional histologic and molecular analysis of
`those tumors without CNA confirmed high tumor content (e.g.,
`detection of TMPRSS2-ERG translocations). To address the
`
`12 Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc.
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`

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`Cancer Cell
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`Genomic Characterization of Human Prostate Cancers
`
`Table 2. Number of Primary and Metastatic Tumors Analyzed by
`Each Platform
`
`Data Type
`
`aCGH
`
`mRNA
`
`miRNA
`Sequencingb
`aCGH, mRNAc
`aCGH, mRNA, miRNAc
`
`aCGH, miRNA,
`sequencingb,c
`
`aCGH, mRNA, miRNA,
`sequencingb,c
`
`Primariesa Metastases
`
`Cell Lines/
`Xenografts
`
`157
`
`131 (29)
`
`99 (28)
`
`75
`
`109
`
`79
`
`72
`
`61
`
`37
`
`19
`
`14
`
`5
`
`19
`
`13
`
`2
`
`1
`
`13
`
`6
`
`0
`
`11
`
`5
`
`2
`
`0
`
`0
`
`All
`
`207
`
`156
`
`113
`
`98
`
`133
`
`94
`
`74
`
`62
`
`Summary of tumors and characterization platforms:
`a number of samples in parentheses refers to the count of matching
`normal prostate expression;
`b sequencing category includes only tumors with matched normals and
`cell/xenografts lines; and
`c mRNA and miRNA refers to expression profiling data. See also
`Tables S2 and S5.
`
`Metastatic tumors and cell/xenograft lines harbored the greatest
`number of whole chromosome, chromosome arm, and focal
`amplifications and deletions, but primary tumors also displayed
`a wide range of alteration levels, from tumors appearing meta-
`static-like in profile to those with fundamentally diploid genomes
`(Figure S1B). Regions of recurrent CNA were identified using the
`statistical method RAE (Taylor et al., 2008), revealing 30 focal
`amplifications and 36 focal deletions as well as recurrent gains
`and losses of seven chromosome arms (Figure 1A; Tables S3
`and S4). The most frequent alteration in the prostate oncoge-
`nome was loss of chromosome 8p, a common abnormality in
`many epithelial tumors that harbors NKX3.1 (He et al., 1997).
`Interestingly, NKX3.1 mRNA expression did not correlate with
`copy-number loss, suggesting the possibility of alternative tumor
`suppressors in this region. Consistent with prior studies, we also
`found peaks of deletion targeting PTEN on 10q23.31, RB1 on
`13q14.2, TP53 on 17p31.1, and the interstitial 21q22.2-3 deletion
`spanning ERG and TMPRSS2. Other broader deletions included
`12p13.31-p12.3, which spans ETV6 and DUSP16 in addition to
`CDKN1B, the previously reported target of this genomic deletion
`(Lapointe et al., 2007). The most common amplified loci included
`MYC on 8q24.21 and a previously unreported NCOA2 amplifica-
`tion on 8q13.3 (discussed further below). Focal amplifications of
`AR (Xq12) were also common but restricted to metastatic
`tumors. Other gains span discontinuous regions of 7q, including
`genes such as BRAF and EZH2, for which we were unable to
`localize individual target genes. We observed less frequent gains
`of 5p13.3-p13.1 spanning AMACR, RICTOR, and SKP2 as well
`as 47 other genes and two microRNAs.
`Eighty tumors were examined for somatic mutations in 138
`genes by exon sequencing (Figure 1A; Tables S5 and S6). These
`and an additional 76 tumors were also profiled for well-known
`oncogenic mutations in 22 genes by mass spectrometry using
`the iPLEX Sequenom assay (Table S5). In total, 84 confirmed
`somatic mutations were detected in 57 different genes
`
`(Table S6). Thirty-seven percent of the missense mutations we
`detected are predicted to affect protein function (Table S6)
`based on an algorithm that uses a combination of evolutionary
`information from protein-family sequence alignments and
`residue placement
`in known or homology-deduced three-
`dimensional protein and complex structures (B.R., Y.A., C.S.,
`unpublished data; http://www.mutationassessor.org/). Among
`all mutated genes, including those bearing previously known
`mutations, the most commonly mutated gene was the androgen
`receptor (AR), with four samples, all metastases. Mutations in 21
`other genes were detected in two or more samples, but no single
`gene other than AR had mutations in more than three samples.
`We also confirmed prior data suggesting that common, broadly
`mutated oncogenes such as PIK3CA, KRAS, and BRAF are
`not commonly mutated in prostate cancer (two tumors had
`H1047R and E545K PIK3CA mutations, two had G12V and
`Q61H/L KRAS mutations, and one tumor had a BRAF V600E
`mutation). Mutations in other more recently identified oncogenes
`such as IDH1 and IDH2 were similarly rare, with only one tumor
`bearing an IDH2 R172K mutation. Curiously, one tumor with
`a mutation in the mismatch repair gene MSH6 (V250A) had 11
`confirmed somatic mutations versus an average of two somatic
`mutations per
`tumor, suggestive of a mutator phenotype.
`Mutations in two other DNA repair genes, BLM and XPC, were
`each found in a single tumor, but not in association with an
`increased number of other mutations. Only two tumors had
`missense mutations in TP53 and none had mutations in PTEN,
`but both tumor suppressors were commonly altered through
`hetero- or homozygous copy-number loss (24% and 21%,
`respectively). Comparison of synonymous and nonsynonymous
`changes detected in these samples suggests a low mutation rate
`in prostate cancer (0.31 mutations/Mb). Consistent with this
`notion, the frequency of mutations recovered in our analysis
`did not exceed the expected background rate (Ding et al.,
`2008), although the modest number of genes and samples
`sequenced limits this analysis.
`We next integrated the CNA, transcriptome, and mutation data
`to conduct a core pathway analysis, based on the success of
`this approach in revealing common pathway alterations in glio-
`blastoma (Cancer Genome Atlas Research Network, 2008).
`Three well-known cancer pathways were commonly altered,
`PI3K, RAS/RAF, and RB, with frequencies ranging from 34% to
`43% in primary tumors versus 74% to 100% in metastases
`(Figure 1B). In this analysis, a tumor was considered altered if
`one or more genes in the pathway were mutated or significantly
`deregulated at the expression level (outlier expression compared
`to the distribution of expression in normal prostate samples, see
`Experimental Procedures). As in glioblastoma, the extremely
`high frequency of alteration in these pathways became evident
`only through examination of multiple genes in each pathway
`since individual genes are affected less commonly. Of particular
`interest is the PI3K pathway, which was altered in nearly half of
`primaries and all metastases examined. Loss of PTEN function,
`through deletion, mutation, or reduced expression, has been
`well documented in prostate cancer with an estimated frequency
`of 40% (Pourmand et al., 2007), consistent with our findings
`here. The frequency of PI3K pathway alteration rises substan-
`tially when PTEN alterations are considered together with alter-
`ations in the INPP4B and PHLPP phosphatases recently
`
`Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc. 13
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`

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`Genomic Characterization of Human Prostate Cancers
`
`Cancer Cell
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`A
`
`B
`
`AKT
`
`Figure 1. A Global View of the Prostate Cancer Genome
`(A) Significant genomic aberrations in the prostate oncogenome. Regions of amplification (red) or deletion (blue) with FDR %10% are plotted, with chromosomes
`indicated at the center and centromeres in red. Genes in which we detected somatic nonsynonymous mutations are listed on top (black). Additional genes of
`interest targeted by copy-number alterations alone are also indicated (gray).
`(B) Three of the most commonly altered pathways in both primary and metastatic prostate cancers: RB, PI3K, and RAS/RAF signaling. Alteration frequencies are
`shown for individual genes and for the entire pathway in primary and metastatic tumors. Alterations are defined as those having outlier expression (significant up-
`or downregulation) compared with the distribution of expression in normal prostate samples (outlier analysis described in further detail in Experimental Proce-
`dures), or by somatic mutations, and are interpreted as activation (red) or inactivation (blue) of protein function. See also Figure S1 and Tables S3 and S6.
`
`implicated in PI3K regulation, the PIK3CA gene itself, and the
`PIK3CA regulatory subunits PIK3R1 and PIK3R3 (Cancer
`Genome Atlas Research Network, 2008; Gao et al., 2005; Gewin-
`ner et al., 2009; Jaiswal et al., 2009; Ueki et al., 2003). These data
`provide strong rationale for exploring the clinical activity of PI3K
`pathway inhibitors, many of which are now in early clinical devel-
`opment, in prostate cancer.
`
`Common Genomic Alterations in Androgen Receptor
`Signaling Pathway Members
`We also conducted a core pathway analysis of AR, which is
`essential for growth and differentiation of the normal prostate
`and is responsible for treatment failure in castration-resistant,
`metastatic disease (Chen et al., 2004; Tran et al., 2009). As
`expected, alteration of AR through mutation, gene amplification,
`
`14 Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc.
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`Cancer Cell
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`Genomic Characterization of Human Prostate Cancers
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`A
`
`C
`
`B
`
`100%100%
`
`D
`
`E
`
`Figure 2. Diversity of Androgen Signaling Pathway Alterations in Primary and Metastatic Prostate Cancers
`(A) Alterations in androgen signaling components where frequencies are shown for AR and selected modulators in primary and metastatic tumors. Alterations are
`defined as those having outlier expression (as described in Figure 1B and Experimental Procedures), or by somatic mutations, and interpreted as activation (red)
`or inactivation (blue).
`(B) Overall genomic alteration rates in androgen signaling genes. The 11 genes in the AR pathway (A) had somatic mutations (black, red) and/or outlier expression
`(over- or underexpression, see Experimental Procedures), a subset of which was the result of copy-number alterations (gray, broad and focal gain or loss of one or
`more copies, see the Supplemental Information). Primary tumors show moderate levels of alteration in at least one of these 11 AR pathway genes (left), preceding
`the generally higher alteration rates in metastatic tumors (right).
`(C) The steroid receptor coactivator NCOA2 had two novel somatic point mutations in primary tumors. These clustered near sites of known NCOA2 point muta-
`tions in melanoma (G435S in the serine/threonine-rich [S/T] regulatory domain) and lung cancer (S1024N in the transcriptional activation domain 1 [AD1]).
`(D) Increasing levels of NCOA2 induce increasing androgen-dependent AR transcriptional activity. Increasing amounts of NCOA2 plasmid were transfected into
`LNCaP cells, resulting in NCOA2 protein expression (inset western blot) and ARE-luciferase reporter activity. Error bars representing the SEM (standard error of
`the mean) are displayed but represent a very small portion of the signal and are therefore not visible.
`(E) Noncastrate primary tumors with NCOA2 gain (defined as copy-number amplification greater than single-copy gain, outlier overexpression, or mutation) have
`higher androgen signaling (Student’s t test, p < 0.0001), as assessed by an independent signature of 29 androgen-responsive genes (Hieronymus et al., 2006).
`See also Figure S2.
`
`and/or overexpression was common but occurred exclusively in
`metastatic samples (58%, Figure 2A). However, AR pathway
`analysis (including several known AR coactivators and corepres-
`sors) revealed alteration in 56% of primaries and 100% in metas-
`tases (Figure 2A; Figure S2). Among AR pathway genes, the most
`striking finding was a peak of copy-number gain on 8q13.3
`(57 Mb away from the peak at 8q24 commonly attributed to
`MYC, and of even greater significance) that spans the nuclear
`receptor coactivator gene NCOA2 (also known as SRC2/TIF2/
`GRIP1). Seventeen percent of tumors had broad gains of the
`region spanning NCOA2 on 8q, whereas 6.2% of tumors (1.9%
`and 24.3% of primary and metastases, respectively) harbored
`focal or high-level amplifications of the locus and these were
`
`significantly correlated with elevated NCOA2 transcript levels
`(p < 1016, Figure S2A). In addition to copy-number and expres-
`sion changes, AR pathway alterations included mutations in
`NCOA2 (two confirmed somatic) as well as in NCOR2 (three
`tumors), NRIP1, TNK2, and EP300 (one tumor each). Overall,
`8% of primary tumors and 37% of metastases had NCOA2
`gain of expression (determined to be outlier expression as
`described in Experimental Procedures) or mutation (Figures 2A
`and 2B).
`Including broader gains of 8q,
`the frequency of
`NCOA2 alteration may be as high as 20% and 63% in primary
`and metastatic tumors, respectively. Of note, NCOA2 mutations
`have also been reported in melanoma and lung cancer and, in
`conjunction with the prostate mutations detected here, cluster
`
`Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc. 15
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`Genomic Characterization of Human Prostate Cancers
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`Cancer Cell
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`ERG in transgenic mice and in a prostate tissue reconstitution
`model (Carver et al., 2009; King et al., 2009; Zong et al., 2009).
`The 3p14 deletion, whose association with TMPRSS2-ERG
`was even more significant, has not been previously reported
`and spans only eight genes. Further interrogation of 2550 tumors
`and cell
`lines spanning 14 tumor types (acute lymphoid leu-
`kemia, breast, colorectal, esophageal, glioma, hepatocellular,
`non-small cell
`lung, squamous lung, medulloblastoma, mela-
`noma, myeloproliferative, ovarian, renal, and prostate) for CNAs
`in this region suggests this deletion is only found in prostate
`cancer (Beroukhim et al., 2010). Indeed, the only other focal
`signal found in this region is an amplicon in melanoma that
`includes microphthalmia-associated transcription factor (MITF),
`a previously reported finding (Garraway et al., 2005).
`Closer inspection of the 3p14 deletion in our prostate cohort
`revealed two distinct peaks of association within the region that,
`together with expression data and the focal deletion patterns,
`implicates only three genes: FOXP1, RYBP, and SHQ1 (Figures
`3B and 3C). Deletions in some tumors spanned FOXP1 only,
`whereas others included RYBP and SHQ1, but spared FOXP1.
`FOXP1 encodes a forkhead box transcription factor and functions
`in motor neuron specification in the spinal cord, as well as early
`thymocyte development, in collaboration with various HOX genes
`(Arber, 2008; Pfaff, 2008). A role for FOXP1 in cancer has been
`proposed based on reduced expression in breast and other
`cancers, increased expression in some lymphoid malignancies
`and, remarkably, by translocation-mediated fusion to the ERG
`homolog ETV1 in at least one prostate cancer (Goatly et al.,
`2008; Hermans et al., 2008; Koon et al., 2007). Furthermore,
`recent evidence implicates the FoxP family member FOXP3 as
`a potential tumor suppressor in prostate cancer (Wang et al.,
`2009). RYBP (Ring and YY1 Binding Protein) encodes a polycomb
`group transcriptional repressor implicated in homeotic develop-
`ment and, potentially, as a tumor suppressor through inhibition
`of MDM2 and subsequent p53 stabilization (Chen et al., 2009).
`SHQ1 encodes an accessory factor for the assembly of H/ACA
`ribonucleoproteins (RNP)
`through direct binding to NAP57,
`a core RNP subunit. Missense mutations in NAP57 that disrupt
`interaction with SHQ1 are associated with the bone marrow
`failure syndrome dyskeratosis congenita, raising a potential link
`to precancer syndromes (Grozdanov et al., 2009).
`To gather further evidence for a potential tumor suppressor
`role of either of these genes, we searched for point mutations
`through exon resequencing. We found no mutations in FOXP1
`or RYBP, but detected a confirmed somatic mutation in SHQ1
`(P22S) in a highly conserved region of the CS domain that is
`required for SHQ1 function (Singh et al., 2009). A second tumor
`had a deletion targeting the middle of the SHQ1 gene that,
`consequently, resulted in production of an aberrant mRNA
`species truncated at exon 6 (Figure 3D). Although these data
`further implicate SHQ1 as a tumor suppressor in this locus, the
`fact that some tumors with 3p14 loss spare SHQ1 (Figure 3B) rai-
`ses the possibility of multiple tumor suppressors in this region.
`
`Unsupervised Clustering of CNAs Reveals Distinct
`Subgroups with Differing Risk of Relapse
`after Prostatectomy
`Given the pressing need for biomarkers that distinguish indolent
`from aggressive prostate cancer, we also examined the genomic
`
`in two highly conserved regions. These include a serine/threo-
`nine-rich stretch (S/T) known to be phosphorylated and an acti-
`vation domain (AD1) that mediates binding with histone acetyl-
`transferases such as CBP and p300 (Huang and Cheng, 2004)
`(Figure 2C). A third patient had an A407S NCOA2 substitution
`that was potentially germline (detected at low frequency in adja-
`cent normal prostate). Interestingly, noncastrate patients with
`primary tumors harboring NCOA2 mutation, overexpression, or
`high-level amplification had significantly higher rates of recur-
`rence (Figure S2B).
`The combination of the high frequency of NCOA2 gain in
`primary tumors and its known role as an AR coactivator (Agoulnik
`et al., 2005) suggests that these two genes might collaborate in
`early prostate cancer progression by enhancing AR transcrip-
`tional output. We addressed this possibility by expressing
`increasing levels of NCOA2 in prostate cancer cells with a fixed
`endogenous level of nonamplified AR. The range in NCOA2
`protein levels is shown by Western blot (Figure 2D) and is
`similar to the 2- to 4-fold increase in NCOA2 mRNA levels
`over the mean level seen in the overall prostate cancer cohort.
`As expected from other work, AR transcriptional output (mea-
`sured using an androgen-responsive reporter construct) was
`increased when cells were treated with dihydrotestosterone
`(DHT)
`in a dose-dependent fashion, but reached a plateau
`between 1 and 10 mM (Figure 2D). Increasing levels of NCOA2
`shifted the DHT dose-response curve leftward and upward, indi-
`cating that NCOA2 can not only prime AR to respond to lower
`androgen concentrations but can also boost the total magnitude
`of AR transcriptional output. One prediction from these in vitro
`data is that the AR transcriptional output in prostate cancers
`with NCOA2 gene amplification should be greater than those
`without. Based on a 29-gene signature of AR transcriptional
`output previously used to conduct small molecule screens for
`novel antiandrogens (Hieronymus et al., 2006), NCOA2-ampli-
`fied primary tumors displayed an increase in AR signaling (Fig-
`ure 2E). Collectively, the genomic and functional data suggest
`that NCOA2 functions as a driver oncogene in primary tumors
`by increasing AR signaling, which is known to play a critical
`role in early and late stage prostate cancer. In contrast, AR
`amplification, which is largely restricted to castration-resistant
`metastatic disease, is more likely a mechanism of drug resis-
`tance rather than a natural step in tumor progression. We also
`propose that NCOA2 and MYC both function as driver onco-
`genes on the 8q13 and 8q24 amplicons, respectively.
`
`Genetic Alterations Highly Associated
`with TMPRSS2-ERG
`The TMPRSS2-ERG fusion is the single most prevalent molec-
`ular lesion in prostate cancer (Tomlins et al., 2005). Functional
`studies of TMPRSS2-ERG, including transgenic expression in
`the mouse prostate, have shown modest evidence of oncogenic
`activity (Carver et al., 2009; King et al., 2009; Klezovitch et al.,
`2008; Tomlins et al., 2008), which raises the possibility that coop-
`erating events are required.
`Analysis of 194 tumors for CNAs associated with TMPRSS2-
`ERG fusion revealed three significant regions of copy-number
`loss: two spanning the tumor suppressors PTEN and TP53 and
`a third spanning the multigenic region at 3p14 (Figure 3A).
`PTEN loss was recently shown to cooperate with TMPRSS2-
`
`16 Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc.
`
`

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`Cancer Cell
`
`Genomic Characterization of Human Prostate Cancers
`
`A
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`C
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`B
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`D
`
`Figure 3. TMPRSS2-ERG-Associated Deletion of 3p14.1-p13
`(A) TMPRSS2-ERG gene fusion co-occurs with genomic aberrations in the prostate cancer genome including deletions of loci encoding TP53 (17p13.1) and PTEN
`(10q23.31), as well as focal deletion of 3p14.1-p13 (genes listed in genomic order; green lines represent statistically significant associations, FDR %1%). Chro-
`mosomes are shown around the ring.
`(B) Diverse genomic deletions (heterozygous and homozygous deletions, light and dark blue, respectively) target a 2.2 Mb region of 3p14.1-p13 encoding eight
`genes (indicated at bottom). Tumors are rows and those harboring TMPRSS2-ERG fusion or PTEN/TP53 deletion (heterozygous and homozygous deletions are
`black and gray, respectively) are identified at right. Tumors are sorted according to their locus of deletion with focal losses preferentially affecting FOXP1 (top),
`RYBP and the adjacent gene SHQ1 (bottom), or both loci simultaneously (middle). Inset indicates the pattern of significance of total genomic deletion juxtaposed
`to the significance of TMPRSS2-ERG-associated deletion (black and dotted blue, respectively).
`(C) Transcript expression according to copy-number status for the three genes targeted by the 3p14.1-p13 deletion: FOXP1, RYBP, and SHQ1, all three of which
`are correlated (p values as indicated, ANOVA). EIF4E3 and PPP4R2 expression and copy-number loss were also correlated, but neither of these two genes was
`focally targeted by 3p14.1-p13 deletion.
`(D) Along with whole-gene deletions of SHQ1 (B), we detected a single tumor with a P22S somatic mutation of the CS domain, indicated in red in the three-dimen-
`sional structure of the SHQ1 yeast homolog (3eud) and in linear representation of the protein (top right). Also, intragenic deletions (shown here in metastatic
`sample PCA0187) confer exon-specific loss of expression indicating a truncation event (bottom right).
`
`data for prognostic significance. It is estimated that 30%–50% of
`men diagnosed with prostate cancer could avoid surgery or radi-
`ation (and instead be followed by watchful waiting) because they
`have good-prognosis tumors that are unlikely to progress (Coop-
`erberg et al., 2005). Whereas transcriptome analysis defines
`breast cancer subgroups with distinct prognoses and treatment
`outcomes that have changed clinical practice (Paik et al., 2004;
`van de Vijver et al., 2002), similar studies in prostate cancer have
`been less clinically useful (Mucci et al., 2008a, 2008b). The 5 year
`median clinical follow-up linked to this tumor set provided an
`opportunity to address the prognosis question using various
`
`forms of oncogenomic data. While unsupervised hierarchical
`clustering of mRNA and microRNA data failed to identify robust
`clusters of patients with significant differences in prognosis, the
`CNA data revealed distinct subgroups with substantial differ-
`ences in time to biochemical (PSA) relapse (Figures 4A and 4B;
`Figure S3A–S3C). Further attempts to identify individual genes
`whose expression has prognostic impact through outlier anal-
`ysis (1766 genes with over- or underexpressing outliers relative
`to normal prostate) were only modestly successful and these
`associations were weak relative to those observed using the
`CNA data.
`
`Cancer Cell 18, 11–22, July 13, 2010 ª2010 Elsevier Inc. 17
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`

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`Genomic Characterization of Human Prostate Cancers
`
`Cancer Cell
`
`A
`
`B
`
`C
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`*
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`Figure 4. Genomic Aberrations Identify Clinically Distinct Subtypes of Prostate Cancer
`(A) Unsupervised hierarchical clustering of copy-number alterations (heat map; red represents amplification, white represents copy-neutral, blue represents dele-
`tion) indicates six groups of prostate cancers exist. Samples are ordered on the basis of their group membership (dendrogram, groups are colored; metastatic
`samples are indicated by hashes). Selected genomic regi