Integrative Genome-Scale Analysis Identifies Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas

Published OnlineFirst September 7, 2016; DOI: 10.1158/0008-5472.CAN-15-2507 Cancer Tumor and Stem Cell Biology Research

Integrative Genome-Scale Analysis Identiﬁes Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas Kai-Oliver Henrich1, Sebastian Bender2, Maral Saadati3, Daniel Dreidax1, Moritz Gartlgruber1, Chunxuan Shao4, Carl Herrmann5, Manuel Wiesenfarth3, Martha Parzonka1, Lea Wehrmann1, Matthias Fischer6, David J. Duffy7, Emma Bell8, Alica Torkov1, Peter Schmezer9, Christoph Plass9, Thomas Hofer€ 4, Axel Benner3, Stefan M. Pﬁster2, and Frank Westermann1

Abstract

The broad clinical spectrum of neuroblastoma ranges from MYCN. Transcriptome integration and histone modification– spontaneous regression to rapid progression despite intensive based definition of enhancer elements revealed intragenic multimodal therapy. This diversity is not fully explained by enhancer methylation as a mechanism for high-risk–associated known genetic aberrations, suggesting the possibility of epige- transcriptional deregulation. Furthermore, in high-risk neuro- netic involvement in pathogenesis. In pursuit of this hypothesis, blastomas, we obtained evidence for cooperation between we took an integrative approach to analyze the methylomes, PRC2 activity and DNA methylation in blocking tumor-sup- transcriptomes, and copy number variations in 105 cases of pressive differentiation programs. Notably, these programs neuroblastoma, complemented by primary tumor- and cell could be re-activated by combination treatments, which tar- line–derived global histone modification analyses and epigenetic geted both PRC2 and DNA methylation. Overall, our results drug treatment in vitro. We found that DNA methylation pat- illuminate how epigenetic deregulation contributes to neuro- terns identify divergent patient subgroups with respect to blastoma pathogenesis, with novel implications for its diagnosis survival and clinicobiologic variables, including amplified and therapy. Cancer Res; 76(18); 1–15. 2016 AACR.

Introduction DNA methylation, an epigenetic modification via methylation of cytosin carbon 5, is a major mechanism in cell differentiation Neuroblastoma originates from precursor cells of the sympa- and neoplastic transformation. Promoter-associated CpG islands thetic nervous system. It is the most frequent solid tumor of early have been identified as frequent targets of transcriptionally relevant childhood with a remarkable variation in clinical and biological methylation events. Accumulating evidence, however, suggests that behavior ranging from spontaneous regression to rapid progres- nonpromoter methylation may be also actively involved in gene sion in spite of intensive multimodal chemotherapy. The molec- regulatory processes and is an abundant phenomenon among ular basis of neuroblastoma pathogenesis is still poorly under- somatically acquired methylation changes in human cancer stood. Genetic alterations seen in high-risk tumors include ampli- (4, 5). In neuroblastoma, candidate-based approaches revealed fication of the proto-oncogene MYCN, activation of the ALK gene, methylation of several genes including CASP8 (6), which plays an heterozygous deletions of 1p or 11q and gain of 17q. However, important role in the TNF-related apoptosis pathway. Global the molecular etiology of a substantial portion of aggressive approaches based on epigenetic drug-induced re-expression anal- neuroblastomas remains largely enigmatic. Recurrent somatic yses and/or affinity-based capture methods in neuroblastoma cell mutations are rare (1–3), suggesting that epigenetic mechanisms lines revealed further potential mechanisms and targets of DNA may drive neuroblastoma development and progression. methylation in neuroblastoma (7, 8). Further reports suggested the

1Neuroblastoma Genomics B087, German Cancer Research Center, Hei- Note: Supplementary data for this article are available at Cancer Research 2 delberg, Germany. Division of Pediatric Neurooncology, German Can- Online (http://cancerres.aacrjournals.org/). cer Consortium (DKTK), German Cancer Research Center, Heidelberg, Germany & Department of Pediatric Oncology, Hematology and Immu- K.-O. Henrich, S. Bender, and M. Saadati contributed equally as co-first authors to nology, Heidelberg University Hospital, Germany. 3Division of Biostatis- this article. tics, German Cancer Research Center, Heidelberg, Germany. 4Division of fi Theoretical Systems Biology, German Cancer Research Center, Heidel- A. Benner, S.M. P ster, and F. Westermann contributed equally as co-senior berg, Germany. 5Division of Theoretical Bioinformatics, German Cancer authors to this article. Research Center, Institute of Pharmacy and Molecular Biotechnology, Corresponding Authors: Kai-Oliver Henrich, German Cancer Research Center Bioquant, University of Heidelberg, Germany. 6Department of Pediatric (DKFZ), Im Neuenheimer Feld 280, Heidelberg 69120, Germany. Phone: 4962- Oncology, University Children's Hospital, and Center for Molecular Med- icine Cologne (CMMC), University of Cologne, Cologne, Germany. 7Sys- 2142-3279; Fax: 4962-2142-3277; E-mail: k.henrich@dkfz; and Frank Wester- tems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland. mann, [email protected] 8 Department of Pathology, University of Cambridge, Cambridge, United doi: 10.1158/0008-5472.CAN-15-2507 Kingdom. 9Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center, Heidelberg, Germany. 2016 American Association for Cancer Research.

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presence of a CpG island methylator phenotype (CIMP), defined MYCN levels, stable neuroblastoma cell models were used as widespread simultaneous CpG island methylation, which is where MYCN can be either up- or downregulated upon addition significantly associated with poor outcome (9, 10). Genome-wide of tetracycline [SH-SY5Y-MYCN and IMR5-75-shMYCN (small DNA methylation analyses in primary neuroblastomas using hairpin RNA targeting MYCN), respectively; refs. 16, 17]. IMR5- methylated DNA immunoprecipitation (MeDIP) or DNA meth- 75-shMYCN with and without MYCN knockdown (Tet) were ylation arrays identified methylation events representing new synchronized via thymidine (2 mmol/L) block for 18 hours candidate epigenetic biomarkers (11–14). An integrated approach, before release by wash out. combining methylome, transcriptome, and genome data from a large cohort of primary neuroblastomas with chromatin modifi- Array-based gene expression and DNA methylation profiling cation analyses has, however, not yet been applied. Expression profiles were generated using customized 4 44 Here, we analyzed DNA methylation in 105 neuroblastomas K oligonucleotide microarrays (Agilent Technologies) and using the Illumina 450k methylation array, which covers pro- genome-wide DNA methylation was assessed using Infinium moter and gene body sites of 99% of Refseq-annotated genes. HumanMethylation450 (450k) BeadChips (Illumina). See These data were complemented by expression profiles and copy Supplementary Materials and Methods for details. number information from the same tumors and combined with Genomic annotation of CpGs was done using the assign- primary neuroblastoma- and cell line–derived global histone GenomeAnnotation program of the HOMER tool suite (http:// modification data. We identified functional programs targeted homer.salk.edu/homer). GpGs with gene context annotations by epigenetic mechanisms in high-risk neuroblastomas and pro- "EXON", "INTRON", "3UTR" and "TTS" (transcription termina- vide evidence for methylation of intragenic enhancers being a tion site) were defined as intragenic (gene body), whereas CpGs mechanism of high-risk–associated transcriptional dysregulation. with annotations "PROMOTER-TSS" and "5UTR" were defined as Furthermore, our data suggest an active contribution of PRC2 50-associated. For association of DNA methylation and gene components to the downregulation of tumor-suppressive genes expression data, only CpGs with gene context annotation were that are hypermethylated in high-risk patients. In line with this, a considered. MassARRAY analysis (Sequenom) at two selected combination of drugs targeting the repressive effect of both DNA CpGs within CDKN2D revealed strong correlation with methyl- methylation and PRC2 efficiently reinduced programs epigenet- ation levels assessed by 450k arrays [Pearson correlation coeffi- ically impaired in high-risk disease. Our results provide funda- cients: 0.85 (95% confidence interval (CI), 0.79–0.90) and 0.89 mental new insights into epigenetic deregulation of aggressive (95% CI, 0.84–0.92; ref. 18]. neuroblastoma and may open new diagnostic and therapeutic avenues for children with high-risk disease. Detection of copy number alterations Copy number alterations were assessed in the 450k Infinium Patients and Methods array data using a previously described custom approach inte- Patients grating both methylated and unmethylated signals (19). Result- fi All patients were enrolled in the German Neuroblastoma Trial ing pro les were manually curated and overall genomic patterns fi (NB97þNB2004) and diagnosed between 1998 and 2011. Treat- used for patient risk strati cation according to Janoueix-Lerosey ment was according to the trial guidelines. Informed consent was and colleagues (20). obtained from the patients' parents and risk stratification was according to the German trial protocol for risk adapted treatment ChIP-seq and deep mRNA-sequencing of children with neuroblastoma; our cohort for methylation and ChIP-seq was performed as described previously (21) with expression analysis included 40 low-risk, 9 intermediate-risk, and changes as described in Supplementary Materials and Methods. 56 high-risk patients. Clinical disease stage was assessed according RNA-seq was performed as described in Supplementary Materials to the International Neuroblastoma Staging System (INSS): stage and Methods. 1, n ¼ 10; stage 2, n ¼ 9; stage 3, n ¼ 10; stage 4, n ¼ 56; stage 4S, – n ¼ 20. Age at diagnosis ranged from 0 to 24.6 years (median age 1 Data analysis DNA methylation and gene expression year) and amplified MYCN was seen in 33 neuroblastomas. Patients were clustered on the basis of DNA methylation and Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) resulting patient clusters were analyzed for MYC(N) activity and was done for two additional stage 4 high-risk neuroblastomas, survival probability as described in Supplementary Materials and one MYCN-nonamplified (termed HR neuroblastoma I), one Methods. To identify correlations between DNA methylation and MYCN-amplified (HR neuroblastoma II). Tumor cell content was gene expression we used maximally selected Wilcoxon rank-sum >60% for all samples used. statistics estimating CpG methylation cut-off points that separate patient groups with differential expression of the corresponding Cell culture and treatments gene (22). Oligonucleotide probes annotated to the same gene All cell lines were kindly provided by Larissa Savelyeva (Ger- were analyzed separately. To identify CpGs whose expression- man Cancer Research Center) in 2012–2015 and authenticated associated methylation is associated with patient subgroups of via multiplex-FISH karyotyping and short tandem repeat DNA differential disease risk, ORs for high-risk disease were estimated. typing at the DSMZ (German Collection of Microorganisms and To identify GpGs whose methylation levels are robustly associ- Cell Cultures). Culture conditions and treatment with all-trans ated with both expression of the corresponding gene and high-risk retinoic acid (ATRA) were as described previously (15). Be(2)-C disease, the following filters were applied: (i) P value 0.05 for and IMR5-75 were treated with 5-aza-20-deoxycytidine (DAC; maximally selected Wilcoxon rank-sum statistics for methylation 1 mmol/L, 72 hours) and EPZ-6438 (1 mmol/L 96 hours) in cut-off point selection, (ii) minimum 2-fold change in expression combination or alone. DAC was resubstituted every 24 hours. between cut-off point separated patient subgroups, (iii) mini- Controls were treated with solvent (DMSO). For modulation of mum mean methylation difference between cut-off point

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separated patient subgroups: 0.1 (b-values), and (iv) P value as well as ArrayExpress accession E-MTAB- 2691 were used. UCSC 0.05 for testing the null hypothesis that the OR estimating the accession IDs for ENCODE ChIP-seq tracks from the neuroblas- association of methylation separated patient subgroups with toma cell line SK-N-SH were: wgEncodeEH003373 (Mx1), wgEn- high-risk disease is 1 (Fisher exact test). Gene sets associated with codeEH003393 (p300, SC-584), wgEncodeEH003227 (TCF12), the identified CpGs were investigated as described in Supplemen- wgEncodeEH003249 (GATA3), wgEncodeEH003302 (RXRA), tary Materials and Methods. To identify differential DNA meth- wgEncodeEH003237 (NFIC), wgEncodeEH003226 (JunD), ylation in drug-treated cell lines, after filtering out CpGs with a wgEncodeEH003297 (FOSL2), wgEncodeEH003243 (FOXM1), delta b-value <0.1 across all samples, a linear regression model wgEncodeEH003298 (MEF2A), wgEncodeEH003286 (TEAD4), was used and significant transcripts were selected on the basis of wgEncodeEH003270 (p300, SC-585), wgEncodeEH003261 the moderated t statistic (23). Benjamini–Hochberg procedure (ZBTB33), wgEncodeEH003242 (ELF1), wgEncodeEH002269 was applied to estimate the false discovery rate (FDR). A low- (NRSF), wgEncodeEH003375 (RFX5), wgEncodeEH003300 stringency P value threshold (FDR < 0.2) in combination with (Pbx3), wgEncodeEH003376 (Rad21), wgEncodeEH003377 ranking by M-value fold changes (corresponding to delta b-values (SMC3), wgEncodeEH003269 (USF-1), wgEncodeEH003371 > 0.1) was used to identify differential CpG methylation (24). (CTCF), wgEncodeEH003374 (Nrf1), wgEncodeEH003228 Statistical analyses were performed using the R/Bioconductor (YY1), wgEncodeEH003248 (GABP), wgEncodeEH002271 software environment. (Sin3Ak-20), wgEncodeEH002270 (Pol2), wgEncodeEH002301 (TAF1) and wgEncodeEH003299 (Max). UCSC accession IDs Data analysis – ChIP-seq and mRNA-seq for ENCODE ChIP-seq tracks from the neuroblastoma cell ChIP-seq single-end reads were aligned to the hg19 genome line SH-SY5Y were: wgEncodeEH002031 (GATA3, SC269) and using Bowtie and only uniquely aligned reads were kept. BAM- wgEncodeEH001770 (GATA2). Files of aligned reads were further processed using the deepTools suite. Input files were subtracted from the treatment files using the bamCompare tool, applying the SES method for normalization of Results signal to noise. Resulting signals were normalized to an average Genome-wide DNA methylation patterns in neuroblastomas 1 coverage to produce signal (bigWig) files. H3K4me1, are associated with clinicobiological variables and patient H3K27ac, and H3K4me3 peaks were called using the MACS outcome 1.4 tool using default parameters. Enhancers were defined as Genome-wide DNA methylation patterns of 105 neuroblasto- overlapping H3K4me1 and H3K27ac peaks with a minimal mas were assessed using the Illumina 450k methylation array distance of 2 kb to the closest H3K4me3 peak, a criterion imposed interrogating > 485,000 methylation sites per sample at single- to rule out selection of (unannotated) promoters. We tested for nucleotide resolution. Hierarchical clustering based on the 1,000 enriched colocalization of CpG subsets with enhancer elements or most variable probes identified two distinct patient clusters, ENCODE-derived ChIP-seq peaks using hypergeometric test and termed cluster 1 and cluster 2 (Fig. 1A and Supplementary Fig. all 450k array-represented CpGs with corresponding gene context S1). DNA methylation patterns suggested subgroups in both annotation as background population. The HOMER tool suite clusters, such as 2s, a large group within cluster 2 displaying a (version 4.6) was used for H3K27me3 bedgraph file generation. remarkably homogeneous methylation pattern. Subgroup 2s was Differential H3K27me3 coverage in treated versus nontreated strongly enriched with low-risk patients, as stratified according to cells was estimated by SICER (25) using a window size of 400 the German NB2004 trial criteria. Subgroup 2s patients were and a gap size of 400. Candidate H3K27me3 islands with an FDR diagnosed at <1.5 years of age and had mainly localized (INSS < 0.01 were considered as significantly differentially covered and 1-3) or 4s tumors that lacked amplified MYCN. Segmental chro- were annotated to the nearest transcription start site. mosomal aberrations, as assessed by interpretation of copy num- mRNA-seq raw data were mapped to hg19 by Tophat (2.0.5). ber data derived from 450k arrays, were rare in subgroup 2s. When Number of reads per gene was calculated using HTSeq (0.5.3p9). overall genomic alteration pattern was used to stratify into risk Normalization was done using DESeq2 (R/Bioconductor). groups (20), 32 of the 34 patients with tumors harboring only Fold changes were calculated from normalized data. A Wald numerical aberrations (Type A, associated with good prognosis) test (DESeq2) was used to test for differential expression in treated mapped to subgroup 2s. The remaining patients of cluster 2 had versus nontreated cell lines and P values were adjusted by Benja- MYCN-nonamplified tumors, similar to patients in subgroup 2s, mini–Hochberg procedure. An adjusted P value < 0.05 was but were otherwise characterized by high-risk disease and considered to indicate differential expression. For time course enriched for other variables associated with poor patient out- data in synchronized IMR5-75 shMYCN cells, a likelihood ratio come, including age at diagnosis >1.5 years, stage 4 disease, 11q test (DESeq2) was used. RNA-seq expression data from 498 deletions, or other segmental chromosomal alterations (poor primary neuroblastomas (26) were analyzed using the R2 Geno- prognosis types BþD = segmental alterations and MYCN-non- mics Analysis and Visualization Platform (http://r2.amc.nl). amplified). Of the 40 patients in cluster 1, 37 were high-risk (NB2004), and stage 4 disease and an age at diagnosis of >1.5 Accession codes years were strongly enriched. All MYCN-amplified tumors RNA-seq, ChIP-seq, as well as expression and methylation mapped to cluster 1, being in line with an impact of MYCN on array data were deposited in Gene Expression Omnibus (GEO) DNA methylation patterns. MYCN-nonamplified cluster 1 tumors under accession numbers GSE73518, GSE80197, GSE80397, had significantly higher MYC(N) target gene activity (defined in GSE79859, GSE80243, and GSE80445. ChIP-seq data from pri- Supplementary Materials and Methods) than cluster 2 tumors mary tumors were deposited at the DKFZ data management (Fig. 1B), which might be partially due to c-MYC activity as platform and may be accessed upon request. Public expression indicated by elevated MYC mRNA levels in a subgroup of the data submitted under GEO accessions GSE35218 and GSE62564 nonamplified cluster 1 tumors (Fig. 1A). This may suggest that

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Neuroblastoma samples (n = 105) A

Methylation High

Low

INSS Stage 4 4s 1–3

Survival status Death Progression No event No event / = 1,000) n = Follow-up <3 yrs

Current risk category High risk Intermediate risk Low risk

Genomic subtype A Numerical only B+D Segmental C+E MYCN Amp.

MYC(N) Activity High

Low MYCN Expression

High ( probes methylation DNA

Low MYC Expression High

Low Methylation cluster 1 2 2s INSS Stage Survival status Current risk category Age at diagnosis >1.5 yrs CIMP Positive (PCDHB) 1p Deletion 11q Deletion 17q Gain Genomic subtype MYC(N) Activity MYCN Amplified * MYCN Expression MYC Expression

B C

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MYC(N) deregulation affects DNA methylation even in the Methylation levels of 4,074 CpGs were significantly associated absence of genomic amplification. Testing the association with expression of the corresponding genes (P < 0.05). Of these, between DNA methylation-based subgroups and patient survival hypermethylation of 1,462 and hypomethylation of 1,283 CpGs revealed poor outcome for cluster 1 patients and intermediate were significantly associated with high-risk disease (P 0.05, outcome for cluster 2 patients (Fig. 1C) with excellent outcome for Supplementary Table S2). Four CpG categories were identified subgroup 2s patients (Supplementary Fig. S2). Multivariate sur- within this high-risk (HR) disease-associated methylation/expres- vival analysis suggested methylation-based clustering as an inde- sion (Fig. 3A; Supplementary Table S2): (i) 860 CpGs representing pendent predictor of outcome (P ¼ 0.036), with variance inflation 341 genes exhibited hypermethylation with downregulation of factors for MYCN status and methylation cluster indicating a the corresponding gene (HyperDownHR), (ii) 396 CpGs repre- moderate degree of collinearity (Supplementary Table S1), prob- senting 167 genes exhibited hypomethylation with upregulation ably due to a correlation between these two predictors (Spearman of the corresponding gene (HypoUpHR), (iii) 602 CpGs repre- r ¼ 0.86). Together, global DNA methylation can identify senting 178 genes exhibited hypermethylation with upregulation groups of neuroblastoma patients, which are strongly associated of the corresponding gene (HyperUpHR), and (iv) 887 CpGs with differential outcome and either presence or absence of representing 273 genes exhibited hypomethylation with down- amplified MYCN. regulation of the corresponding gene (HypoDownHR). CpGs whose methylation was negatively associated with gene PCDHB gene family methylation reflects global methylation expression (HyperDownHR and HypoUpHR) mapped closer to patterns the transcription start site (TSS; median distance: þ2.9 kb and þ3.4 Previous analyses suggest that CpG island methylation in the kb, respectively) compared with CpGs with a positive association gene body of protocadherin beta family (PCDHB) members is (HyperUpHR and HypoDownHR; median distance to TSS: þ15.5 closely associated with the presence of a high-risk-associated kb and þ38.8 kb, respectively; Fig. 3B). With respect to gene neuroblastoma CIMP (9, 10). To investigate whether the global context annotation, CpGs whose methylation was negatively methylation patterns identified in our study are synonymous with associated with expression of the corresponding gene had a higher 0 this PCDHB-defined CIMP, we performed hierarchical clustering fraction of TSS and 5 -UTR-annotated CpGs (HyperDownHR and of the 105 patients using only 450k data representing gene body HypoUpHR; 27% and 28%, respectively) compared with CpGs methylation of PCDHB family members 2–18 (119 CpGs). Of the whose methylation was positively associated with expression of two clusters identified, one was defined as CIMP-positive by the corresponding gene (HyperUpHR and HypoDownHR; 13% PCDHB hypermethylation, which was corroborated by hyper- and 8%, respectively). Conversely, CpG categories with a positive methylation of two additional CIMP marker genes, CYP26C1 and association between methylation and expression had a higher HLP (Fig. 2; refs. 9, 10). The CIMP cluster contained 32 predom- fraction of gene body-annotated CpGs (HyperUpHR and Hypo- inantly high-risk patients and was strongly associated with vari- DownHR; 87% and 92%, respectively) compared with CpG cat- ables of unfavorable tumor biology, including amplified MYCN, egories with a negative association (HyperDownHR and higher age at diagnosis and advanced tumor stage. While not all HypoUpHR; 73% and 72%, respectively; P < 0.001, Fig. 3A). patients with poor outcome were detected, the majority of patients These results are in line with the established role of promoter/ that died from disease mapped to the CIMP cluster. Of the 32 CIMP TSS-associated DNA methylation in transcriptional repression and patients, the majority mapped to global methylation-defined agree with previous genome-wide epigenomic studies linking gene patient groups associated with high-risk (Fig. 1), supporting that body methylation to active transcription (5). Together, we iden- PCDHB family methylation status may help estimate global meth- tified subgroups of CpGs whose methylation is significantly asso- ylation patterns associated with high-risk neuroblastoma biology. ciated with expression of corresponding genes in neuroblastomas of differential risk groups. The nature of this association is strongly DNA methylation correlates with gene expression and disease dependent on gene context and relative distance to the TSS. risk To estimate the effect of differential DNA methylation on gene Methylation of intragenic enhancers as a regulator of disease expression in neuroblastomas, we integrated 450k methylome risk–associated gene expression data with mRNA expression profiles derived from customized 44 Despite gene body methylation being largely positively associ- k oligonucleotide microarrays (Agilent Technologies) of the same ated with expression, a substantial fraction of negatively associated 105 tumors. Maximally selected Wilcoxon rank-sum statistics CpGs (HyperDownHR and HypoUpHR) mapped to the gene were used to estimate CpG methylation cut-off points separating body. To investigate whether this negative association is due to patient groups with differential expression of coannotated genes. DNA methylation targeting specific intragenic regulatory DNA

Figure 1. Genome-wide DNA methylation patterns in neuroblastomas are associated with clinicobiological variables and patient outcome. A, heatmap of DNA methylation levels in neuroblastoma subgroups identified by hierarchical clustering with average linkage and noncentralized correlation distance function using the 1,000 most variable probes (clustering based on the 5,000 or 10,000 most variable probes revealed similar results). Each row represents a probe and each column represents a sample. The level of DNA methylation (m-values) is represented with the color scale depicted. For each sample (n ¼ 105), genomic aberrations, transcriptional MYC(N) activity as estimated by the median expression of 155 MYC(N) target genes (56), CpG island methylator phenotype (CIMP) as monitored by exon 1 methylation of PCDHB gene family members, survival status, INSS stage, risk category according to the German neuroblastoma trial NB2004, age at diagnosis, genomic MYCN status, and MYCN and MYC expression are indicated. Prognostic genomic subtypes (A–E) where identified based on genetic alterations according to Janoueix-Lerosey and colleagues (20). , heterogeneous MYCN status. B, MYC(N) activity of MYCN-nonamplified neuroblastomas in methylation clusters 1 and 2. P value was calculated by Wilcoxon rank-sum test. C, Kaplan–Meier estimates of overall survival for neuroblastoma clusters defined by DNA methylation profiling.

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Neuroblastoma samples (n = 105)

PCDHB2

PCDHB3

PCDHB4

PCDHB5 Methylation High

PCDHB6

Low PCDHB7

family exon 1 Methylation additional CIMP markers PCDHB8 High PCDHB9 Low PCDHB10 PCDHB PCDHB11 Survival status Death PCDHB12 Progression PCDHB13 No event No event / PCDHB14 Follow-up <3 yrs Current risk category PCDHB15 High risk Intermediate risk Low risk

PCDHB16 INSS Stage 4 4s 1–3 DNA Methylation probes PCDHB17

PCDHB18

CIMP Negative CIMP Positive Methylation cluster HLP cg12660439 CYP26C1 cg19305681 CYP26C1 cg05193369 Survival status Current risk category INSS Stage Age at diagnosis >1.5 yrs MYCN Amplified

Figure 2. PCDHB family methylation patterns in neuroblastomas reflect global methylation patterns and are associated with clinicobiological variables and patient outcome. Heatmap of DNA methylation levels in two neuroblastoma subgroups identified by hierarchical clustering with average linkage and noncentralized correlation distance function using probes representing exon 1 of PCDHB2-18 family members. Clusters were termed "CpG island methylator phenotype (CIMP) Positive" and "CIMP Negative" in line with the PCDHB-methylation-based CIMP definition described in Abe and colleagues (9, 10). Each row represents a probe and each column represents a sample. The level of DNA methylation (m-values) is represented with the color scale depicted. For each sample (n ¼ 105), INSS stage, risk category according to the German NB2004 trial, age at diagnosis, genomic MYCN status, and methylation levels of CpGs representing additional CIMP marker loci within HLP and CYP26C1 are shown.

elements, we mined ChIP-seq data from neuroblastoma cell lines ation was negatively associated with gene expression (Hyper- deposited in the ENCODE (Encyclopedia of DNA Elements, DownHR and HypoUpHR) were significantly enriched with UCSC) database. These analyses revealed a highly significant enhancer elements in both cell lines and primary tumors (Fig. enrichment of intragenic HyperDownHR and HypoUpHR CpGs 4B; all P < 0.02, except HypoUpHR CpGs with primary HR NB I with sites bound by enhancer-associated protein p300 in the SK-N- enhancers P ¼ 0.1). These data suggest that methylation of intra- SH neuroblastoma cell line (Fig. 4A; P < 0.001), indicating that genic enhancer elements may regulate expression of genes relevant methylation of intragenic enhancers might be relevant for the for high-risk neuroblastoma development, highlighting a role of negative association between gene body methylation and gene nonpromoter DNA methylation in neuroblastoma pathogenesis. expression seen in these CpG subgroups. To investigate the role of intragenic enhancers in additional neuroblastoma models, we Deregulated expression/methylation of neuroblastoma-related used ChIP-seq for defining enhancers (H3K4me1/H3K27ac pos- genetic programs itive, H3K4me3 negative) in two stage 4 primary high-risk neu- To elucidate the biology of genetic programs regulated by roblastomas and three high-risk neuroblastoma-derived cells lines, promoter and/or enhancer methylation in neuroblastomas of Be(2)-C, SH-SY5Y and IMR5-75. Intragenic CpGs whose methyl- differential risk, we further investigated the HypoUpHR and

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HyperDownHR gene groups. Among genes that where highly entiate via retinoic acid treatment (Supplementary Fig. S3). expressed in high-risk neuroblastomas with concomitant CpG Intriguingly, genes occupied by Polycomb repressive complex 2 demethylation (HypoUpHR), we identified several genes previ- (PRC2) components EED and SUZ12 and marked by H3K27me3 ously described to be involved in the biology of aggressive in embryonic stem cells (ESC; ref. 40) were significantly enriched neuroblastoma including CXCR4 (27), GAL (28), LRRN1 (29), in the HyperDownHR group (all P < 1 10 10, Table 1), ODC1 (30), TWIST1 (31), and WHSC1 (32). Notably, the indicating that silencing HyperDownHR genes may contribute HypoUpHR genes included four members (DDX43, PRAME, to cell stemness. Overall, investigation of HyperDownHR genes TEX14, TMEM108) of the Cancer/Testis Antigens and genes for revealed a strong representation of established tumor suppressors two proteins previously suggested as neuroblastoma antigens or and genes previously found to be impaired in neuroblastomas by therapy targets, NEK2 (33) and NPY (34). This suggests that genetic events, together with a significant enrichment of ESC aberrant demethylation in aggressive neuroblastomas is associ- PRC2 targets and genes involved in neuronal differentiation. ated with (i) upregulation of genes contributing to neuroblastoma progression and (ii) induction of possible targets for immu- DNA hypermethylation in high-risk neuroblastomas is notherapeutic intervention. associated with PRC2 hyperactivity The 341 genes downregulated in high-risk patients with con- Enrichment of HyperDownHR genes with ESC PRC2 targets comitant CpG hypermethylation (HyperDownHR) represented corresponds to the idea that genes silenced in ESCs by Poly- the largest group of genes among all possible expression/meth- comb group proteins are prone to hypermethylation in cancer ylation association combinations. Some of these HyperDownHR (41). To estimate whether the PRC2-mediated H3K27 trimethy- genes have been previously implicated in neuroblastoma-relevant lation of HyperDownHR genes is a transient developmental aberrant methylation, including ABCB1, CACNA1G, CD44, feature or whether it contributes to silencing of HyperDownHR DUSP23, PRDM2, RBP1, SFRP1 (reviewed in ref. 35), CHD5 genes in established neuroblastoma cells, H3K27me3 ChIP-seq (36), and NTRK1 (37). Four genes (KRT19, PRPH, CNR1, QPCT) was performed in two stage 4 primary high-risk neuroblasto- were part of an eight-gene DNA methylation-based prognostic mas and two high-risk neuroblastoma-derived cells lines, Be biomarker (8), substantiating that the prognostic value of these (2)-C and SH-SY5Y. H3K27me3 was strongly enriched at methylation markers is tightly linked to downregulation of the HyperDownHR genes compared with global gene-associated corresponding genes. Mapping of HyperDownHR genes to the H3K27me3 occupancy in both cell lines and primary tumors catalog of nonsilent mutations identified via global neuroblas- (Fig. 5A–D). Integration of H3K27me3 and DNA methylation toma sequencing approaches (1–3) revealed an overlap of 85 data (450k array) in Be(2)-C identified several H3K27me3- genes that are likely to be targeted in neuroblastoma by rare covered HyperDownHR genes with high methylation levels at somatic mutations and epigenetic silencing (Supplementary putative regulatory regions. Among these, promoter methyla- Table S3). These include DLC1, a tumor suppressor gene recur- tion as exemplified by HENMT1 (Supplementary Fig. S4A) was rently mutated in neuroblastomas (2, 3) and involved in Rac/Rho less frequent than methylation of intragenic enhancers as signaling, a pathway essential for neuritogenesis that is frequently exemplified by SPOCK2 (Supplementary Fig. S4B) and impaired in high-risk neuroblastomas (3). HyperDownHR genes SLC18A2 (Supplementary Fig. S4C). Our data suggest that also included direct targets of neuroblastoma-specific structural PRC2 activity contributes to the ongoing repression of hyper- aberrations, such as the neurotransmission-associated ASIC2, methylated genes in established high-risk neuroblastomas, whose disruption by a constitutional translocation has been which needs to be considered for therapeutic approaches aim- shown (38), and RGS5, reported to be downregulated via ing at derepression of HyperDownHR genes. MYCN-activated miRNAs and affected by focal homozygous deletion (39). Chromosomal distribution analysis of Hyper- MYCN is a repressor of genes that are silenced in high-risk DownHR genes revealed significant enrichment of two cytogenet- neuroblastomas ic regions, 5q31 (P < 0.006), encompassing the neuroblastoma c-MYC has been shown to induce expression of PRC2 com- CIMP-predictive PCDHB gene family cluster, and 1p36 (P ¼ ponents by various mechanisms including direct transcription- 0.018, Table 1), which is frequently deleted in neuroblastoma al activation (42, 43), and expression of the PRC2 component and other cancers. To provide further insight into molecular gene EZH2 is elevated in high-risk neuroblastomas (44). To processes mediated by HyperDownHR genes, we performed GO investigate the influence of amplified MYCN on PRC2 compo- term and pathway enrichment analysis using the Database for nent expression in primary neuroblastomas, we analyzed tran- Annotation, Visualization and integrated Discovery tool scriptomes from 498 tumors. Unsupervised clustering based on (DAVID, Table 1; Supplementary Table S4). Significantly enriched expression of the PRC2 core genes EED, EZH2, SUZ12 and GO terms included terms like "regulation of apoptosis" and RBBP7 (RbAp46) identified a group of tumors characterized by "positive regulation of lymphocyte differentiation", with the latter PRC2 hyperactivity and strong prevalence of amplified MYCN likely reflecting differential lymphocytic infiltration among neu- (Supplementary Fig. S5A). In line with this,EED,EZH2,and roblastoma subtypes. A predominant fraction of significantly RBBP7 were significantly higher expressed in MYCN-amplified enriched GO terms, however, related to neuronal differentiation versus -nonamplified neuroblastomas (all P < 0.001, Supple- or function (e.g., "neuron projection", "synapse", "axon", "syn- mentary Fig. S5B). Analyzing the impact of MYCN on PRC2 aptic vesicle", "nervous system development"). In line with this, component expression in neuroblastoma cells, we found sig- the Reactome pathway most strongly overrepresented among nificantly higher expression of EED, EZH2, and RBBP7 in HyperDownHR genes was "Synaptic Transmission" synchronized MYCN-amplified IMR5-75 S-phase cells com- (REACT_13685, P < 0.008). Involvement of HyperDownHR pared with MYCN-knockdown IMR5-75 cells at equivalent time genes in neuronal differentiation is further supported by their points (all P < 0.05, Supplementary Fig. S5C). To estimate time-dependent upregulation in Be(2)-C cells induced to differ- whether a MYCN-associated PRC2 component induction

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Gene context distribution Example A PRAME

HypoUpHR 396 CpGs 167 Genes

E M

NCAN

HyperUpHR 602 CpGs 178 Genes

E M

Promoter_TSS 5UTR Exon Intron CDH22 3UTR TTS

HypoDownHR 887 CpGs 273 Genes

E M

KRT19

HyperDownHR 860 CpGs 341 Genes

E M

E M HypoUpHR

E M HyperUpHR

E M HypoDownHR

E M HyperDownHR

0 50,000 100,000 150,000 200,000 Distance to TSS (bp)

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Figure 4. Intragenic CpG methylation that is negatively associated with expression (HyperDownHR, HypoUpHR) maps preferentially to enhancer elements. Test for colocalization of intragenic CpGs of the HypoDownHR, HyperUpHR, HypoUpHR, and HyperDownHR subgroups (see Fig. 3) with ENCODE-deposited neuroblastoma ChIP-seq peaks (A) and enhancer elements defined in neuroblastoma cell lines and primary high-risk neuroblastomas by H3K27ac þ H3K4me1 in the absence of H3K4me3 (B). Colocalization enrichment was tested for by a hypergeometric test using all CpGs represented on the 450k array with corresponding gene- context annotation as the background population. log10 of P values is represented with the color scale depicted. Graph pictograms indicate negative (green) or positive (red) association between CpG methylation (M) and expression (E) of the corresponding gene. SH-SY5Y cells were uninduced SH-SY5Y-MYCN cells. IMR5-75 cells were uninduced IMR5-75-shMYCN cells. Primary high-risk neuroblastoma (HR NB) I was MYCN-nonamplified, primary HR NB II MYCN-amplified. might contribute to the observed H3K27me3 enrichment at bottom). In line with this, MYCN knockdown in IMR5-75 cells HyperDownHR genes, ChIP-seq was performed in neuroblas- led to decreased H3K27me3 coverage at HyperDownHR genes, toma cells upon MYCN modulation. In SH-SY5Y cells, MYCN which was accompanied by a specific induction of Hyper- induction led to increased H3K27me3 coverage at Hyper- DownHR gene expression (Supplementary Fig. S6 and Fig. DownHR genes (Fig. 6A), which was accompanied by a 6C; Supplementary Table S5). The activation of PRC2 compo- time-dependent repression of HyperDownHR gene expression nents by MYCN, together with our observation that global DNA (Fig. 6B; Supplementary Table S5). The remaining global tran- methylation is strongly associated with genomic MYCN status scriptome was affected to a substantially lesser extend as in primary neuroblastomas, indicates that MYCN may prime demonstrated by strong enrichment of HyperDownHR genes a subset of genes for epigenetic silencing in high-risk among genes downregulated upon MYCN induction (Fig. 6B, neuroblastomas.

Figure 3. Association with expression is preferentially negative for 50-associated CpG methylation and preferentially positive for gene body CpG methylation. A, gene context distribution of CpGs whose methylation is significantly associated with expression and patient risk. Four CpG/gene categories are defined by differential high-risk disease-associated methylation/expression as estimated by maximally selected Wilcoxon rank-sum statistics. Example CpGs for each category and illustration of their methylation with respect to expression of the corresponding gene are shown at the right. High-risk patients are marked by orange dots. Dashed lines indicate CpG methylation cut-off points defining patient subgroups with differential expression of the corresponding gene as determined by maximally selected Wilcoxon rank-sum statistics. Hyper, hypermethylated; Hypo, hypomethylated; Up, upregulated expression; Down, downregulated expression; HR, high-risk patients. B, distance distribution within defined CpG categories relating to the transcription start site (TSS). Intergenic CpGs without gene annotation are not considered. Graph pictograms indicate negative (green) or positive (red) association between CpG methylation (M) and expression (E) of the corresponding gene.

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Table 1. Representative GO terms, pathways, and gene sets enriched in genes tively rare with three HyperDownHR genes in Be(2)-C and two whose hypermethylation and downregulation are associated with high-risk HyperDownHR genes in IMR5-75 (exemplified by DPP6 in Be disease (HyperDownHR) (2)-C, Supplementary Fig. S7). To further investigate the idea of Term category preferential HyperDownHR induction by combination treat- (platform) Enriched term Adjusted P GO Terms (DAVID) Nervous system development 5.4 108 ment in a larger neuroblastoma panel, we reanalyzed genome- Positive regulation of lymphocyte 6.3 104 wide expression data assessed in 17 neuroblastoma cell lines differentiation treated with DAC and trichostatin A (TSA; ref. 45), a histone Regulation of apoptosis 8.5 104 deacetylase (HDAC) inhibitor previously shown to restore 3 Neuron projection 3.4 10 expression of PRC2-repressed genes (46). After genome-wide Synapse 4.4 103 2 testing for differential expression upon treatment across all 17 Axon 1.4 10 fi Synaptic vesicle 3.7 102 cell lines, gene-set enrichment analysis revealed signi cant enrichment of HyperDownHR genes among DAC/TSA-induced 3 Reactome Pathway Synaptic Transmission (REACT_13685) 8.0 10 genes (P ¼ 0.039, Supplementary Fig. S8, Supplementary Table (DAVID) S8). Together, these data suggest that genetic programs silenced 3 Gene sets (MSigDB) Cytogenetic band 5q31 5.7 10 in high-risk neuroblastoma can be efficiently and preferentially Cytogenetic band 1p36 1.8 102 derepressed in a broad range of neuroblastoma subtypes by SUZ12-occupied in ES cells <1 10 10 H3K27me3-marked in ES cells <1 1010 combining epigenetic drugs that target both PRC2- and DNA EED-occupied in ES cells <1 1010 methylation-mediated repression. NOTE: P values are FDR or Benjamini–Hochberg adjusted as implemented in the MSigDB and DAVID platforms, respectively. For an extended list of enriched GO terms, see Supplementary Table S4. Discussion Abbreviations: DAVID, Database for Annotation, Visualization and Integrated In an integrative approach, we investigated methylomes, tran- Discovery tool; ES cells, embryonic stem cells; GO, gene ontology; MSigDB, scriptomes, and copy number aberrations of 105 neuroblastomas Molecular Signatures Database. together with tumor- and cell line-derived chromatin modification data. Clustering based on DNA methylation profiles identified patient clusters and subgroups strongly associated with key Genetic programs silenced in high-risk neuroblastomas are clinical parameters and specific genetic alterations in the tumors, derepressed by combination treatment targeting both DNA which suggests that deregulated methylation is a fundamental methylation and PRC2 feature of high-risk neuroblastomas. Multivariate survival analy- As reinducing genetic programs silenced in high-risk neuro- sis suggested that 450k methylome data contain prognostic blastoma is likely to be therapeutically beneficial, we investigated information that could complement current risk stratification. the potential of epigenetically active drugs to derepress Hyper- Further studies in an extended patient cohort need to refine (i) DownHR genes in the neuroblastoma cell lines Be(2)-C and which loci are most informative as predictive biomarkers, (ii) to 0 IMR5-75. In both cell lines, treatment with the 5-aza-2 -deoxy- which extend DNA methylation can complement the correlated cytidine (DAC) DNA-demethylating agent led to a preferential predictive factor MYCN status, and (iii) which patient subgroups induction of HyperDownHR genes compared with global gene would benefit most from DNA methylation-based stratification. induction (Fig. 6D; Supplementary Table S6). The overall potency Clustering based on methylation of PCDHB family members of DAC to significantly induce gene transcription, however, was largely reflected global DNA methylation, suggesting that PCDHB substantially higher in IMR5-75 compared with Be(2)-C (induced methylation could function as a marker for genome-wide DNA gene fraction HyperDownHR 25.2% vs. 5%, global 7.9% vs. 1.4%, methylation patterns associated with high-risk neuroblastoma. respectively). Preferential induction of HyperDownHR genes was Detection platform differences may contribute to the observed also seen upon treatment with EPZ-6438, a specific inhibitor of limitation of PCDHB methylation-based clustering to detect all the H3K27 methyltransferase EZH2. With EPZ-6438, the overall patients with poor outcome, as the 450k probe design only effect on gene transcription was more pronounced in Be(2)-C incompletely covers the CIMP marker sites previously identified compared with IMR5-75 (induced gene fraction HyperDownHR (9, 10). PCDHB family methylation has, until now, been generally 11.7% vs. 6.5%, global 2.7% vs. 0.9%, respectively). Most efficient thought to be a surrogate marker for synchronized methylation and preferential HyperDownHR reinduction (P < 0.001 in both events acting on other genes that contribute to neuroblastoma cell lines), however, was achieved by combined treatment with development, instead of having a direct regulatory role (47). DAC and EPZ-6438, supporting the notion that DNA methylation Of note, we identified hypermethylation of several PCDHB family and H3K27 trimethylation cooperate to repress HyperDownHR members to be associated with downregulation of their transcripts genes (fraction of HyperDownHR genes induced: 24.6% vs. 5.7% in high-risk neuroblastomas, which argues for a more direct role of global in Be(2)-C, 34.3% vs. 10.9% global in IMR5-75). To PCDHB impairment in neuroblastoma pathogenesis. monitor the epigenetic changes associated with this induction, As expected, we frequently observed methylation in the pro- we investigated gene-associated H3K27me3 coverage (ChIP- moter and surrounding regions that was negatively associated seq) and DNA methylation (450k arrays) in Be(2)-C and IMR5- with expression. Positive correlation between DNA methylation 75 cells after DAC/EPZ-6438 combination treatment (Fig. 6E; and expression was predominantly associated with the gene body, Supplementary Table S7). Of 81 HyperDownHR genes induced a phenomenon detected in various biological contexts, including in Be(2)-C, 47 (58%) lost either K27me3 methylation, DNA development, differentiation and cancer (5). A surprisingly large methylation or both. Of 114 HyperDownHR genes induced in fraction of negatively associated DNA methylation sites, however, IMR5-75, 51 (45%) lost either K27me3 methylation, DNA also mapped to the gene body. This might be partially due to methylation, or both. Loss of both repressive marks was rela- methylation of promoter downstream correlating regions

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Figure 5. Genes whose hypermethylation and downregulation are associated with high-risk disease (HyperDownHR) are occupied by H3K27me3 in established high-risk neuroblastoma cells. Composite H3K27me3 proﬁle of HyperDownHR genes versus genome-wide gene-associated H3K27me3 occupancy in SH-SY5Y (SH-SY5Y-MYCN/OFF; A), Be(2)-C (B), and two primary high-risk (HR) neuroblastomas (C and D) with respect to transcription start site (TSS) and transcription termination site (TTS).

(pdCR), which were recently shown to extend up to tens of Our analysis identified a catalog of genes that are strong candi- kilobases downstream of the transcriptional start site (4), a gene dates for being transcriptionally deregulated by aberrant methyl- context not annotated as promoter-associated in our analysis. ation in high-risk neuroblastomas. The substantial overlap with However, we revealed another likely regulatory mechanism to be genes that are targeted by genetic events in neuroblastomas indi- transcriptional inhibition via intragenic enhancer methylation. A cates that epigenetic and genetic mechanisms converge partially on growing body of evidence suggests that enhancer methylation the same targets to contribute to neuroblastoma pathogenesis. may be a pivotal element in both physiologic transcriptional Given the low incidence of most somatic mutations identified by regulation and disease-associated dysregulation, and, strikingly, genome-wide sequence analyses in neuroblastomas (1–3), our expression variation in a large fraction of genes appears to be data may be used to prioritize candidates for future analyses. exclusively associated with enhancer methylation while promoter From the subgroup of genes hypomethylated and upregulated methylation remains unaffected (5, 48). Modulation of intragenic in high-risk neuroblastomas (HypoUpHR), several were previ- enhancer methylation has also been described to be the dominant ously shown to be activated in aggressive neuroblastomas, but methylome change during cell differentiation (5). We conclude little was known about the mechanisms of their deregulation. Our that the high prevalence of expression-associated intragenic data suggest that these mechanisms include aberrant demethyl- enhancer methylation being differential across neuroblastomas ation during high-risk neuroblastoma development. HypoUpHR of varying biology suggests that this epigenetic event accounts for genes should be strongly enriched for potential therapeutic tar- a significant proportion of subtype-specific intertumor diversity gets. Of special interest in this context is the high-risk–specific and contributes to high-risk neuroblastoma development. hypomethylation and overexpression of DDX43, PRAME, TEX14,

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Figure 6. Genes whose hypermethylation and downregulation are associated with high-risk disease (HyperDownHR) are repressed by MYCN in vitro. HyperDownHR genes are preferentially induced by treatment with epigenetically active drugs in neuroblastoma cells. A, composite H3K27me3 proﬁle of HyperDownHR genes vs. genome- wide gene-associated H3K27me3 occupancy in MYCN-induced and -uninduced SH-SY5Y cells with respect to transcription start site (TSS) and transcription termination site (TTS). B, time-dependent expression fold change (RNA-seq) of global and HyperDownHR genes in SH-SY5Y cells upon MYCN induction.

Reference for fold change was solvent control at 0 h. HyperDownHR genes retained after ﬁltering for low read count: n ¼ 251. Bottom, log2-fold changes of HyperDownHR genes (black lines) within the log2-fold range of the global transcriptome (gray). Smoothed local frequency graph illustrates enrichment of the HyperDownHR gene set. C, time-dependent expression fold change (RNA-seq) of global and HyperDownHR genes in IMR5-75 cells upon shMYCN induction. Reference for fold change was solvent control at respective time points. HyperDownHR genes retained after ﬁltering for low read count: n ¼ 220. Bottom,

log2-fold changes of HyperDownHR genes (black lines) within the log2-fold range of the global transcriptome (gray). Smoothed local frequency graph illustrates enrichment of the HyperDownHR gene set. D, total numbers (left) and fractions (right) of genes signiﬁcantly induced (adjusted P < 0.05) in Be(2)-C and IMR5-75 cells after treatment with epigenetically active drugs 5-aza-20-deoxycytidine (DAC) and EPZ-6438 alone or in combination. Reference total numbers for

fractions were 341 (HyperDownHR) and 23,118 (Global ¼ hg19 annotated genes-341). RNA-seq was done in duplicates. For log2-fold changes versus solvent of individual genes see Supplementary Table S6. E, total numbers of genes that signiﬁcantly (i) lost H3K27me3 coverage, (ii) lost DNA methylation, and/or (iii) gained expression in Be(2)-C and IMR5-75 cells upon combination treatment with DAC and EPZ-6438. H3K27me3 was analyzed by ChIP-seq, DNA methylation by 450k arrays (duplicates) and expression by RNA-seq (duplicates). Only genes with information on all three parameters are depicted (n ¼ 330 for HyperDownHR). For status of individual genes see Supplementary Table S7.

and TMEM108, of which PRAME has been previously identiﬁed as gulation of genes (HyperDownHR). A subset of this gene group a candidate for therapeutic intervention in neuroblastoma (49). has been previously reported to mediate tumor-suppressive func- These genes all encode Cancer/Testis Antigens, proteins whose tions and/or be targeted in neuroblastomas by methylation or expression is typically restricted to the testis but that are aberrantly genetic events including point mutation and structural aberrations expressed in many cancers, constituting attractive targets for (1–3, 8, 35–39). Positional gene enrichment analysis revealed an biomarkers and immunotherapy. Our results support the idea overrepresentation of 1p36 genes, which included the well-estab- that DNA hypomethylation is a driver of Cancer/Testis Antigen lished dosage-dependent neuroblastoma suppressor candidates derepression in neuroblastoma as has been previously proposed CAMTA1, CHD5, and KIF1B (51), suggesting that DNA methyl- for other tumor entities (50). ation may cooperate with genomic deletion to shift gene product The most prominent high-risk–associated phenomenon was dosage to levels below those needed for oncosuppression. Strong hypermethylation in combination with transcriptional downre- enrichment of neuron-speciﬁc pathways and GO terms, together

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with the observed induction of HyperDownHR genes in differ- lated MYCN guides DNA methylation via setting PRC2-defined entiating neuroblastoma cells, indicates that these genes contrib- pre-marks for permanent silencing of a set of genes whose expres- ute to neuronal development and function. Together, this suggests sion is incompatible with progression to high-risk neuroblasto- that hypermethylation and concomitant downregulation of the ma. Together, our integrative analysis has uncovered a wealth of identified gene group provides a selective advantage during high- epigenetic alterations that enhance the understanding of neuro- risk neuroblastoma development by facilitating circumvention of blastoma heterogeneity and shed light on potential regulatory tumor suppressive and prodifferentiation programs. mechanisms involved in neuroblastoma development and pro- A subset of genes targeted by PRC2 in ESCs and undifferentiated gression. The strikingly subtype-specific methylation patterns are early cell compartments is thought to be transferred to a tighter promising points of departure for prognostic purposes whereas repressive state by methylation during tumor development. This the deregulated genetic programs and particularly the epigenetic gene subset, previously termed "DNA methylation module", often mechanisms involved in their deregulation are attractive targets comprises developmental regulators that may differ across tumor for therapeutic intervention. entities, and whose silencing may contribute to the stem-like state of cancer cells (52). Enrichment of both PRC2 ESC targets and Disclosure of Potential Conflicts of Interest neuronal development genes among HyperDownHR genes indi- No potential conflicts of interest were disclosed. cates that we identified the neuroblastoma-specific DNA hypermethylation module, which defines stem cell qualities such as Authors' Contributions unlimited self-renewal and evasion from differentiation. We Conception and design: K.-O. Henrich, S. Bender, E. Bell, S.M. Pfister, identified overrepresentation of H3K27me3 at HyperDownHR F. Westermann genes in established neuroblastoma cells, suggesting that PRC2 Development of methodology: K.-O. Henrich, D. Dreidax, M. Gartlgruber, continues to contribute to silencing of these genes, a phenomenon C. Plass, A. Benner, F. Westermann Acquisition of data (provided animals, acquired and managed patients, of great therapeutic implication also recently acknowledged in provided facilities, etc.): K.-O. Henrich, S. Bender, D. Dreidax, M. Gartlgruber, other cancer entities (53, 54). In line with this, combined treat- M. Parzonka, L. Wehrmann, M. Fischer, D.J. Duffy, E. Bell, A. Torkov, ment targeting both DNA methylation and PRC2 (EPZ-6438/ P. Schmezer, F. Westermann DAC) efficiently and preferentially reinduced this gene group, Analysis and interpretation of data (e.g., statistical analysis, biostatistics, while the potency of EPZ-6438 and DAC alone was lower and computational analysis): K.-O. Henrich, S. Bender, M. Saadati, M. Gartlgruber, diverged in the tested cell lines. This suggests that the efficiency of C. Shao, C. Herrmann, M. Wiesenfarth, M. Parzonka, D.J. Duffy, P. Schmezer, C. Plass, T. Hofer,€ A. Benner, S.M. Pfister, F. Westermann such combined treatment is robust with respect to the (epi)genetic Writing, review, and/or revision of the manuscript: K.-O. Henrich, S. Bender, fi background of cells, which is further supported by signi cant M. Saadati, D. Dreidax, M. Gartlgruber, M. Parzonka, M. Fischer, C. Plass, reexpression of HyperDownHR genes in a diverse panel of 17 A. Benner, S.M. Pfister, F. Westermann neuroblastoma cell lines by TSA/DAC combination. A large Administrative, technical, or material support (i.e., reporting or organizing fraction of EPZ-6438/DAC-induced genes lost H3K27me3 cover- data, constructing databases): M. Gartlgruber, M. Parzonka, F. Westermann age or DNA methylation but loss of both marks was not common, Study supervision: K.-O. Henrich, S. Bender, F. Westermann which may suggest that on the level of individual genes, either Acknowledgments H3K27me3 or DNA methylation is the main repressive mecha- We thank the tumor bank team of the University Hospital of Cologne nism. However, on the level of cancer-silenced gene groups, (Germany) for providing primary tumor samples, Steffen Bannert, Jochen Kreth, fi fi targeting both modi cations seems to be required for ef cient Elisa Hess, and Young-Gyu Park for excellent technical assistance and Kathy induction of the genetic program. We propose that combining Astrahantseff for critical reading of the manuscript. drugs targeting PRC2- and DNA methylation–mediated repression could be a rational strategy for high-risk neuroblastoma Grant Support therapy. This concept is strengthened by recent data showing that This work was supported by the German Cancer Aid (grant no. 110122 to a modification by both of these marks is strongly overrepresented F. Westermann), the German Ministry of Science and Education (BMBF) as part in cancer cells compared with their normal counterparts and, thus, of the e:Med initiative (grant no. 01ZX1307D to M. Fischer and F. Westermann), fi may serve as a cancer-specific target (54). the BMBF MYC-NET (grant no. 0316076A to F. Westermann, S.M. P ster, and S. Bender), the European Union grant no. 259348 (F. Westermann), the German c-MYC stimulates PRC2 components in ESCs to keep bivalent Cancer Research Center (DKFZ) intramural program for interaction projects genes silent, maintaining ESCs in an undifferentiated state (43), (F. Westermann and S.M. Pfister), the DKFZ – Heidelberg Center for Person- and it was shown to activate the PRC2 component EZH2 in cancer alized Oncology (HIPO) & National Center for Tumor Diseases (NCT) cells (42). Our data indicate that MYCN plays a similar role in Precision Oncology Program (S.M. Pfister), and intramural funding neuroblastoma cells by directly or indirectly activating the expres- through NCT 3.0: ENHANCE – Enhancers and non-coding (epi-)mutations fi sion of PRC2 components, which adds to MYCN's function as (F. Westermann, C. Herrmann, C. Plass, S.M. P ster). The costs of publication of this article were defrayed in part by the payment of recruiter of EZH2 to the promoter of target genes (55). Consid- page charges. This article must therefore be hereby marked advertisement in ering the observed increase in H3K27me3 coverage at Hyper- accordance with 18 U.S.C. Section 1734 solely to indicate this fact. DownHR genes in MYCN-overexpressing neuroblastoma cells and the established functional crosstalk between PRC2 activity Received September 11, 2015; revised May 3, 2016; accepted May 29, 2016; and DNA methylation, our data point to a model where deregu- published OnlineFirst September 6, 2016.

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www.aacrjournals.org Cancer Res; 76(18) September 15, 2016 OF15

Integrative Genome-Scale Analysis Identifies Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas

Kai-Oliver Henrich, Sebastian Bender, Maral Saadati, et al.

Cancer Res Published OnlineFirst September 7, 2016.

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