Research HDAC5 and HDAC9 in Medulloblastoma: Novel ......Medulloblastoma is the most common...

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Published OnlineFirst April 22, 2010; DOI: 10.1158/1078-0432.CCR-10-0395

Imaging, Diagnosis, Prognosis Clinical
Cancer
Research

HDAC5 and HDAC9 in Medulloblastoma: Novel Markers forRisk Stratification and Role in Tumor Cell Growth

Till Milde1, Ina Oehme1, Andrey Korshunov2,5, Annette Kopp-Schneider3, Marc Remke4,6,Paul Northcott7, Hedwig E. Deubzer1,6, Marco Lodrini1,6, Michael D. Taylor7,Andreas von Deimling2,5, Stefan Pfister4,6, and Olaf Witt1,6

Abstract

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Purpose: Medulloblastomas are the most common malignant brain tumors in childhood. Survivorssuffer from high morbidity because of therapy-related side effects. Thus, therapies targeting tumors in aspecific manner with small molecules such as histone deacetylase (HDAC) inhibitors are urgently war-ranted. This study investigated the expression levels of individual human HDAC family members in pri-mary medulloblastoma samples, their potential as risk stratification markers, and their roles in tumor cellgrowth.Experimental Design: Gene expression arrays were used to screen for HDAC1 through HDAC11. Using

quantitative real time reverse transcriptase-PCR and immunohistochemistry, we studied the expression ofHDAC5 and HDAC9 in primary medulloblastoma samples. In addition, we conducted functional studiesusing siRNA-mediated knockdown of HDAC5 and HDAC9 in medulloblastoma cells.Results: HDAC5 and HDAC9 showed the highest expression in prognostically poor subgroups. This

finding was validated in an independent set of medulloblastoma samples. High HDAC5 and HDAC9expression was significantly associated with poor overall survival, with high HDAC5 and HDAC9 expres-sion posing an independent risk factor. Immunohistochemistry revealed a strong expression of HDAC5and HDAC9 proteins in most of all primary medulloblastomas investigated. siRNA-mediated knockdownof HDAC5 or HDAC9 in medulloblastoma cells resulted in decreased cell growth and cell viability.Conclusion: HDAC5 and HDAC9 are significantly upregulated in high-risk medulloblastoma in com-

parison with low-risk medulloblastoma, and their expression is associated with poor survival. Thus,HDAC5 and HDAC9 may be valuable markers for risk stratification. Because our functional studies pointtoward a role in medulloblastoma cell growth, HDAC5 and HDAC9 may potentially be novel drug targets.Clin Cancer Res; 16(12); 3240–52. ©2010 AACR.

Medulloblastoma is the most common malignant intra-cranial tumor in childhood (1) and represents a very het-erogeneous group as far as outcome is concerned. 5-Yearevent-free survival can be as low as 34.7% in patients withmetastasized disease (2) compared with 81% in patientswith localized disease (3). Traditionally, clinical para-

ffiliations: 1Clinical Cooperation Unit Pediatric Oncology,Cooperat ion Unit Neuropathology, 3Department ofs, 4Division Molecular Genetics, German Cancer Researchpartments of 5Neuropathology and 6Pediatric Oncology,gy and Immunology, University Hospital Heidelberg,, Germany; and 7Division of Neurosurgery, Program inntal and Stem Cell Biology, Arthur and Sonia Labatt Brainesearch Centre, Hospital for Sick Children, University ofronto, Ontario, Canada

lementary data for this article are available at Clinical Cancernline (http://clincancerres.aacrjournals.org/).

ding Author: Till Milde, Clinical Cooperation Unit Pediatric(G340), German Cancer Research Center, Im Neuenheimer9120 Heidelberg, Germany. Phone: 49-6221-423388; Fax:3277; E-mail: [email protected].

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meters, such as age, dissemination at diagnosis, and extentof surgical resection, are used for risk stratification. Recent-ly, novel molecular markers, most notably DNA copy-number variations of chromosomal regions 6q and 17q,and MYC/MYCN have been proposed for risk stratifica-tion, which clearly separate prognostic subgroups (4).Many of the surviving patients suffer from therapy-relatedside effects, especially if radiotherapy is included in thetreatment regimen during infancy (5, 6). It is thereforemost important to develop novel treatment strategies thathelp to increase the survival of high-risk patients and atthe same time induce less side effects.One of the strategies that have been followed to achieve

this goal is the use of small molecules inhibiting histonedeacetylases (HDAC; ref. 7). A wide body of literature pro-vides evidence for effective treatment of different tumorcells using HDAC inhibitors (HDACi) in vitro and in vivo,such as leukemia (8), lymphoma (9), lung cancer (10, 11),retinoblastoma (12), and neuroblastoma (13, 14). Braintumor cells seem to be susceptible to treatment withHDACi as has been shown for glioblastoma (15, 16),

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Translational Relevance

Patients with medulloblastoma experience pooroutcomes, especially in metastasized disease, and treat-ment of all stages is associated with strong side effects,resulting in impaired quality of life. Specific therapiesfor such high-risk patients are therefore urgently need-ed to resolve this unsatisfactory situation. Histone dea-cetylase (HDAC) inhibitors are a promising novel classof targeted therapeutics. Our group and others have pre-viously shown that differential expression of singleHDAC familymembers is associatedwith poor outcomein solid tumors and that selective targeting of the identi-fied HDACs could be a successful strategy. Here, we de-scribe HDAC5 and HDAC9 as independent prognosticmarkers for overall survival in primary medulloblasto-ma, and we show a functional role of HDAC5 andHDAC9 in tumor cell growth in medulloblastoma celllines. This finding is of general interest in oncology be-cause class I HDACs, especially HDAC1 and HDAC2,have thus far been considered to be the most relevantHDAC family members to be targeted in cancer.

HDAC5 and HDAC9 in Medulloblastoma


atypical teratoid/rhabdoid tumor (17), and medulloblas-toma (17–19). HDACis have only recently been introducedin the clinical setting of cancer treatment, with Vorinostatbeing the first HDACi approved for the treatment of cutane-ous T-cell lymphoma by the Food andDrug Administration(20). However, most of the HDACis target either all or atleast a wide range of HDACs (21). This creates the problemof unspecific inhibition of several HDACs, whereas thetargeted blockade of specific single HDACs might be moredesirable instead. Class-specific side effects of pan-HDACishave been reported (22), supporting the requirement ofselective inhibitor development.The zinc-dependent HDAC1 through HDAC11 com-

prise 11 members grouped into four classes (I, IIa, IIb,and IV; ref. 21). Knockout studies in mice suggest nonre-dundant and specific functions of single HDACs in thephysiologic setting. For example, HDAC1 and HDAC3knockouts are early embryonic lethal in accordance withtheir essential und ubiquitous function as componentsof repressor complexes and cell cycle progression; HDAC2,HDAC5, and HDAC9 control myocardial developmentand function; HDAC4 is involved in bone and chondro-cyte development; HDAC7 plays a central role in endothe-lial cell adhesion and HDAC6 in tubulin acetylation; andHDAC8 knockouts show a distinct neural crest cell pheno-type (23). Thus, these data already point to distinct andspecific functions of individual HDAC family members.It can be expected that tissue- and time-specific disruptionof single HDAC will uncover even more physiologic func-tions of particular HDACs since liver-specific disruption ofHDAC3 causes deregulation of carbohydrate and lipidmetabolism (24). In cancer, deregulated HDACs also

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seem to have nonredundant and specific functions con-trolling hallmarks of cancer biology, such as proliferation,apoptosis, differentiation, migration, resistance to chemo-therapy, and angiogenesis (25, 26).The specific functions of single HDAC family members

furthermore seem to be tumor specific, and accordingly,our group has started to dissect the function of individualHDAC family members in distinct tumor entities. Forexample, HDAC8 expression was found to correlate withpoor outcome of neuroblastoma tumors, a highly ma-lignant childhood cancer derived from neural crest pro-genitor cells. Specific inhibition of HDAC8 inducesdifferentiation of neuroblastoma cells (14, 27). Of note,HDAC8 disruption in mice impairs neural crest cell fate(28). Class I HDAC1, HDAC2, and HDAC3 have beenshown to be highly expressed in colorectal and gastric can-cers (29, 30). The expression of some of the isoenzymescan be associated with prognosis (29, 30), and in the caseof colorectal carcinomas, targeting of the specific isoen-zymes was a successful strategy in cell culture models (30).Here, we examined the expression patterns and functions

of HDAC isoenzymes in medulloblastoma and correlatedisoenzyme expression with clinical course. For the firsttime, we provide evidence for a role of the class IIa HDACs,HDAC5 and HDAC9 in medulloblastoma cell growth andpropose HDAC5 and HDAC9 as novel prognostic markers.

Materials and Methods

PatientsMaterial from patients from the first set (n = 37 snap

frozen samples in liquid nitrogen at -196°C), as well asthe paraffin embedded medulloblastoma samples, wererandomly collected at the Department of Neuropathology,Burdenko Neurosurgical Institute (Moscow, Russia) be-tween 1993 and 2003. Approval to link laboratory datato clinical data was obtained by the Institutional ReviewBoard. Two neuropathologists confirmed the diagnoses ac-cording to the 2000 WHO classification. None of the pa-tients had received irradiation or chemotherapy beforecollection of specimens. Metastatic state (M stage) wasdetermined by magnetic resonance imaging and cerebro-spinal fluid cytopathology at diagnosis. Clinical andhistopathologic data are summarized in SupplementaryTable S1.Material from patients from the second set (n = 103

samples) was obtained in accordance with the ResearchEthics Board at the Hospital for Sick Children (Toronto,Ontario, Canada), from the Co-operative Human TissueNetwork (Columbus, OH), and the Brain Tumor TissueBank (London, Ontario, Canada) as described (31).

DNA extraction and array-based comparativegenomic hybridizationExtraction of high–molecular weight DNA and RNA from

frozen tumor samples was carried as previously described(32). Selection of genomic clones, isolation of bacterialartificial chromosome DNA, performance of degenerate

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oligonucleotide primer-PCR, and preparation of microar-rays were done as described (33). Labeling, hybridization,and washing procedure were done as reported (34).

RNA extraction, cDNA synthesis, and quantitativereal-time reverse transcriptase-PCR (RT-PCR)RNA was extracted from biopsy samples after milling of

the frozen primary medulloblastoma sample in a Mikro-Dismembrator S (B. Braun). RNA from primary medullo-blastoma samples was extracted using Trizol (Invitrogen),and RNA from cell culture experiments was extractedusing the RNeasy Mini Kit (Qiagen), both according tomanufacturer's instructions. cDNA was synthesized usingthe First Strand cDNA Synthesis Kit (Fermentas) accordingto manufacturer's instructions. Quantitative real-timePCR was done using an ABI Prism 7700 thermal cycler(Applied Biosystems) in standard mode with PlatinumSYBR Green qPCR SuperMix-UDG (Invitrogen). The quan-titative real-time PCR conditions were 50°C (2 min), 95°C(10 min), 40 cycles of 95°C (15 s), and 60°C (1 min).Primers were obtained through Thermo Electron (se-quences in Supplementary Table S2). The software usedto analyze the data was SDS v. 1.3.1 (Applied Biosystems).The ΔΔCt method was used to obtain relative quantifica-tion. ACTB was used as a control gene whereas normal cer-ebellum RNA as a control sample. Normal cerebellumRNA was purchased from Clontech.

Gene expression microarrayHybridizedmicroarrays were scanned at 5-μm resolution

in a two-color Agilent Scanner G25505B (Agilent) with au-tomatically adjusted photomultiplier tube (PMT) voltagesaccording to manufacturer's specification. Array raw datawere generated from scanned images using Axon GenePix-Pro Software (version 6.1.0.2). The data was preprocessed,quality controlled, and analyzed with our in-house-devel-oped ChipYard framework for microarray data analysis(http://www.dkfz.de/genetics/ChipYard/) using R (35)and Bioconductor (36) software packages. Feature signalshad to fulfill the following criteria to be considered for anal-ysis: minimal signal to background ratio ≥1.2 in at least onechannel; mean to median spot intensity ≤75% quartile + 3times the interquartile range of all features on the array; andfeature replicate SD ≤ 0.25 per array. Normalization of rawsignals was done using variance stabilization normalization(37). Probes with >40% missing values across all sampleswere removed. Based on BLASTing the probes sequence in-formation against the genome, biological annotations wereretrieved from EnsEMBL (version 54; NCBI Build 36 of thehuman genome reference sequence). Sample preparation,hybridization, and data analysis of the second separate me-dulloblastoma patient set was done as described (31).

Preparation of medulloblastoma tissue microarray,immunohistochemical staining, and fluorescencein situ hybridizationThe medulloblastoma tissue microarray was prepared

from blocks of patient material as described (4). All

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immunohistochemical stainings were done on 5-μm-thicksections of formalin-fixed, paraffin-embedded microdis-sected specimens. The antibodies used were obtained fromAbcam: HDAC5, ab55403 (1:500); and HDAC9, ab59718(1:20). Immunohistochemistry for HDAC5 and HDAC9was done with an automated stainer (Benchmark XT, Ven-tana) following the protocols of the manufacturer. Allanalyses of immunohistochemical stainings were carriedout by two investigators (A. Korshunov and M. Remke)who were blinded to clinical and molecular variables us-ing a scoring system. Fluorescence in situ hybridization wascarried out as described (38).

Cell culture and siRNA-mediated knockdownDaoy cells were obtained through American Type Cul-

ture Collection, UW228-2 cells were a friendly gift fromJohn Silber (Seattle, WA), UW228-3 cells were a friendlygift from Steven Clifford (Newcastle, United Kingdom),ONS76 was obtained from the Institute for Fermentation(Japan), and Med8A were a friendly gift from R. Gilbertson(Memphis, TN). Cells were tested for mycoplasma,viral, and cell contamination using the in-house Multi-plex cell Contamination Testing Service (39).For siRNA-mediated knockdown, cells were- seeded in 6-wellplates on the day before transfection. On day 0, cellswere transfected with siRNA at 25 nmol/L concen-trations using HiPerfect transfection reagent (Qiagen)according to manufacturer's instructions. siRNAs wereobtained through Qiagen and Dharmacon/Thermo FisherScientific (catalog numbers in Supplementary Table S3).RNA was extracted at indicated time points as describedabove.

Western blot analysis and image processingProtein concentrations of cell lysates were determined

using the Bradford assay (Bio-Rad) according to manufac-turer's instructions. The following antibodies were used:polyclonal rabbit anti-human HDAC5 (1:500; catalogno. 2082; Cell Signaling), polyclonal rabbit anti-humanHDAC9 (1:500; catalog no. ab53102; Abcam), and mousemonoclonal anti–β-actin (clone AC-15; Sigma-Aldrich).Detection was done using Amersham ECL Western Blot-ting Detection System (GE Healthcare) and AmershamHyperfilm ECL (GE Healthcare). Developed films werescanned using an Epson Perfection V700 Photo (Seiko Ep-son Corp.). Uncropped images were contrast enhancedand subsequently cropped using Photoshop CS2 Version9.0 (Adobe Systems).

Cell number, cell growth kinetic, and viabilityCells were seeded in 6-well plates 24 h before transfec-

tion. Transfection was done as described above. Cells werecollected at indicated time points, and cell numbers weremeasured using a Z2 Series Coulter Counter (BeckmanCoulter). Growth kinetic curves were plotted and doublingtimes calculated using GraphPad Prism version 3.03 forWindows (GraphPad Software). Viability was determinedusing trypan blue exclusion staining.

Clinical Cancer Research





Measurement of the sub-G0 fraction andcaspase-3–like activityThe sub-G0 fraction of cultured cells was measured

as described (13) using Nicoletti stain and the flowcytometer FACS Canto II (Beckman Coulter). For dataanalysis, FACSDiva (version 6.1.2; Beckman Coulter)was used. Caspase-3–like activity of cultured cells wasmeasured using the Caspase-3 Fluorometric Assay Kit(Biovision, Inc.) according to manufacturer's instruc-tions. The positive control for caspase-3–like activitymeasurements consisted of untransfected cells treatedwith UV light (35 mJ/cm2) 16 h before caspase-3–likeactivity measurement.

Statistical analysisStatistical analysis was done using GraphPad Prism

version 3.03 for Windows (GraphPad Software) and R(R version 2.4.1, 2006; The R Foundation for StatisticalComputing) with the package maxstat (40) as follows:GraphPad Prism, nonparametric Mann-Whitney U test ofquantitative real-time RT-PCR measurements of HDAC5and HDAC9 in patient samples and of gene expressionmeasurements in the validation cohort; and R, Kaplan-Meier survival analysis and log-rank statistics, cut-pointanalysis of quantitative real-time RT-PCR measurementsof HDAC5 and HDAC9 in patient samples using maximal-ly selected rank statistics to determine the value separatinga group into two groups with the most significant differ-ence when used as a cut-point, and ANOVA analysis of cellnumbers, sub-G0 fraction, and caspase-3 activity afterknockdown of HDAC5 and HDAC9 using a linear mixedmodel with fixed factors (“siRNA against” and “no. ofsiRNA,” and random intercept for the “number of mea-surement”). Grouping of patients according to medianof quantitative real-time RT-PCR measurements was doneas follows: HDAC5 ≤ 0.33, HDAC5 low; HDAC5 > 0.33,HDAC5 high; HDAC9 ≤ 0.87, HDAC9 low; and HDAC9 >0.87, HDAC9 high. Grouping according to calculatedoptimal cut-points was done as follows: HDAC5 ≤ 0.5,HDAC5 low; HDAC5 > 0.5, HDAC5 high; HDAC9 ≤ 1.3,HDAC9 low; and HDAC9 > 1.3, HDAC9 high. CombinedHDAC5 and HDAC9 grouping according to calculated op-timal cut-points was done as follows: HDAC5 ≤ 0.5 andHDAC9 ≤ 1.3 (group A), HDAC5 ≤ 0.5 and HDAC9 >1.3 or HDAC5 > 0.5 and HDAC9 ≤ 1.3 (group B), andHDAC5 > 0.5 and HDAC9 > 1.3 (group C). The stratifiedCox-regression model was calculated in R (R version2.7.1, 2008-06-23; The R Foundation for StatisticalComputing). A stratified Cox-model analysis was usedto determine prognostic factors in a multivariate analysiswith HDAC5 and HDAC9 dichotomized at the previous-ly determined cut-points. Because no deaths were ob-served in the group with chromosome 6q loss or withdesmoplastic histology, the Cox-regression model strati-fied for chromosome 6 and histology was fitted. Thisapproach allows for different baseline hazards functionsfor the combinations of chromosome 6 and histologycategories.



Results

High HDAC5 and HDAC9 mRNA expression isassociated with poor prognosis in medulloblastomaTo determine the expression of HDAC family members

in medulloblastoma with unfavorable versus favorableclinical outcome in a screening approach, we did anmRNA expression profiling of a small set of pooled patientsamples with either chromosome 6q loss (a marker for fa-vorable prognosis; n = 5 samples) or gain of chromosome6q (a marker for poor prognosis; n = 4 samples; Fig. 1A) orpools of patients with balanced chromosome 17 status(correlating with favorable prognosis; n = 11 samples) or17q gain (defined as having either an isochromosomei17q or a gain of chromosome arm 17q, correlating withpoor prognosis; n = 10 samples; Fig. 1B). These molecularmarkers on chromosome 6 and 17 have recently beenidentified as powerful outcome predictors of prognosisin medulloblastoma patients (4). Our screening revealedHDAC5 and HDAC9 to be highly expressed in the prog-nostic unfavorable groups (Fig. 1A and B). HDACs thatwere found downregulated in the prognostic unfavorablegroups are HDAC4 and HDAC1 to a lesser extent.To confirm the mRNA expression of HDAC5 and

HDAC9 in a set of 37 individual samples of patients withmedulloblastoma, we used quantitative real time RT-PCR.Tumors harboring a gain of chromosome 6q again showeda significantly higher mRNA expression of HDAC5 and ofHDAC9 when compared with tumors with 6q deletion(P < 0.05 and P < 0.05; Fig. 1C and D). Tumors with bal-anced 6q also showed a significantly higher HDAC5 andHDAC9 mRNA expression level when compared with tu-mors with 6q deletion (P < 0.05 and P < 0.005; Fig. 1Cand D). The same was true when patients were groupedusing the DNA copy-number status of chromosome 17q;tumors exhibiting gain of 17q revealed a significantlyhigher expression of HDAC5 and of HDAC9 mRNA whencompared with tumors displaying a balanced chromo-some 17 status (P < 0.05 and P < 0.005; Fig. 1E and F).We therefore conclude that medulloblastoma with eitherbalanced chromosome 6 or gain of chromosome 6q or17q have a higher HDAC5 and higher HDAC9 mRNA ex-pression level than tumors with chromosome 6q deletionor balanced status of 17q.To investigate the potential of HDAC5 and HDAC9

mRNA expression to predict the survival of medulloblasto-ma patients, we did a log-rank analysis. When analyzed foroverall survival using the median as a cut-point, the groupsdisplayed statistically significant differences in overall sur-vival probability forHDAC5 andHDAC9 (P < 0.05 and P <0.005; log-rank test; Supplementary Fig. S1). Therefore, ei-ther HDAC5 or HDAC9 mRNA expression separates thepatients into two groups with distinct overall survival.To analyze the potential of combined HDAC5 and

HDAC9 expression data to separate groups of patientswith distinct overall survival probabilities, we combinedHDAC5 and HDAC9 expression data, separating thepatients into three groups. First, we used optimal cut-point




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Fig. 1. Increased HDAC5 and HDAC9mRNA expression in primary medulloblastoma samples with unfavorable prognosis. A, a pool of n = 4 patient sampleswith gain of chromosome 6q (chr 6q gain) was compared with a pool of n = 5 patient samples with loss of chromosome 6q (chr 6q loss). The log 2ratios for each HDAC represented on the array chip were calculated by expression value of chr 6q gain pool divided by the expression value of chr 6q losspool. HDACs shown to the left are upregulated in the pool with poorer prognosis; HDACs shown to the right are downregulated in the pool withpoorer prognosis. B, a pool of n = 10 patient samples with 17q gain (chr 17q gain) was compared with a pool of n = 11 patient samples with balancedchromosome 17 status (chr 17 bal); log 2 ratios for each HDAC represented on the array chip were calculated by expression value of 17q gain pooldivided by expression value of chromosome 17 balanced pool. HDACs shown to the left are upregulated in the pool with poor prognosis; HDACs shownto the right are downregulated in the pool with poor prognosis. C-F, HDAC5 and HDAC9 mRNA expression was measured by quantitative real timeRT-PCR in n = 37 individual samples of medulloblastoma patients, which were grouped according to chromosome 6q (C and D) and chromosome17 status (E and F). Relative expression is normalized to normal cerebellum RNA. C and D, patients grouped according to chromosome 6q showed asignificantly higher expression of HDAC5 (C) and of HDAC9 (D) in the prognostically unfavorable group with gain of chromosome 6q when compared withpatients with loss of chromosome 6q (P = 0.0152 for HDAC5 and P = 0.0260 for HDAC9; Mann-Whitney U test). HDAC5 and HDAC9 expression was alsosignificantly higher in the group with balanced chromosome 6 status when compared with the prognostically favorable group with loss of chromosome 6q(P = 0.0108 for HDAC5 and P = 0.0025 for HDAC9; Mann-Whitney U test). E and F, when patients were grouped according to the status of chromosome17q, the prognostically unfavorable group with 17q gain (either gain on 17q or i17q) exhibited a significantly higher expression of HDAC5 (E) and HDAC9(F; P = 0.0051 for HDAC5 and P = 0.0024 for HDAC9; Mann-Whitney U test). Chr, chromosome; bal, balanced. *, P < 0.05; **, P < 0.001; ***, P < 0.0001.

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analysis to identify the optimal cut-point separating thepatients in two groups with high or low expression levelsof either HDAC5 or HDAC9. For overall survival, the op-timal cut-point for HDAC5 was 0.5, however, withoutreaching statistical significance in separating the twogroups after correction for overfitting (Fig. 2A). ForHDAC9, the optimal cut-point for overall survival was1.3, dividing the two groups with high statistical signifi-cance after correction for overfitting (P < 0.001; log-ranktest; Fig. 2B). In a second step, patients were grouped ac-cording to optimal cut-points as follows (Fig. 2C): a,HDAC5 and HDAC9 low; b, HDAC5 low and HDAC9 highor HDAC5 high and HDAC9 low; and c, HDAC5 high andHDAC9 high. Kaplan-Meier analysis revealed significantdifferences about survival probabilities upon subgrouping(P < 0.0001; log-rank test). In summary, patients expres-sing low HDAC5 and- low HDAC9 had a significantlyhigher overall survival probability than patients with ei-ther HDAC5 or HDAC9 high expression, especially thanpatients with HDAC5 and HDAC9 high expression. Wetherefore conclude that the level of mRNA expression ofHDAC5 and HDAC9 may be a candidate for risk stratifica-tion of patients with medulloblastoma.Using a stratified Cox-regression analysis, we deter-

mined independent prognostic factors in a multivariateanalysis in our patient cohort, including the parametersage, metastatic stage at diagnosis, extent of surgicalresection, histology, DNA copy-number status of chromo-some 6 and 17, and HDAC5 and HDAC9 mRNA expres-sion (Table 1). Combined analysis of HDAC5 andHDAC9 was carried out in the same manner as done inthe survival analysis. High expression of HDAC5 andHDAC9 (group c) proved to be a significant independentrisk factor when compared with the group with low ex-pression for HDAC5 and HDAC9 (group a; P < 0.005),as well as when compared with the group with high ex-pression of only HDAC5 or HDAC9 (group b; P < 0.05;Table 1). Thus, we conclude that the combination of highexpression of HDAC5 and HDAC9 may be of prognosticsignificance in medulloblastoma.

HDAC5 and HDAC9 expression correlates withprognostic markers in an independent large cohort ofmedulloblastoma patientsTo test if HDAC5 and HDAC9 expression correlates with

prognostic markers in a separate validation set of medul-loblastoma samples, we measured HDAC5 and HDAC9expression in an independent set of n = 103 medulloblas-toma samples using gene expression arrays (31). Tumorswith balanced chromosome 6 status showed a signifi-cantly higher mRNA expression for HDAC5 and HDAC9when compared with patients with 6q deletion (P < 0.05and P < 0.0005; Supplementary Fig. S2A and B). Tumorswith a gain of chromosome 6q showed a significantlyhigher mRNA expression of HDAC9 when comparedwith tumors with 6q deletion (P < 0.05; SupplementaryFig. S2B). For HDAC5, expression was also higher intumors with gain of chromosome 6q when compared with

Fig. 2. HDAC5 and HDAC9 mRNA expression is associated with survivalprobability in medulloblastoma patients. Kaplan-Meier analysis ofsurvival of medulloblastoma patients grouped according to HDAC5 andHDAC9 expression as measured by quantitative real-time RT-PCR.A and B, after doing optimal cut-point analysis for HDAC5 and for HDAC9using maximally selected rank statistics, patients were grouped into twogroups for eachHDAC5 (cut-point = 0.5) andHDAC9 (cut-point = 1.3). Thedifference in overall survival probability between HDAC5 low versusHDAC5 high expressing patients (A) showed a trend toward significanceafter correction for overestimation (P = 0.08; log rank). The difference inoverall survival probability between HDAC9 low and HDAC9 highexpressing patients (B) was statistically significant after correction foroverfitting (P = 0.0008; log rank). C, when three groups were formed usingthe optimal cut-points for HDAC5 and HDAC9 as determined bycut-point analysis, the group with patients expressing HDAC5 andHDAC9 at low levels (group a) showed a significantly better overall survivalprobability compared with the two other groups (P = 0.00004; log rank).




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loss of chromosome 6q, however, without reaching statis-tical significance (Supplementary Fig. S2A). Tumorsexhibiting a gain of 17q showed a significantly higherexpression of HDAC5mRNA when compared with tumorsdisplaying a balanced chromosome 17 status (P < 0.0001;Supplementary Fig. S2C). However, no difference inHDAC9 mRNA expression was found between these twogroups (Supplementary Fig. S2D). These data confirm theassociation of high HDAC5 expression with prognosti-cally unfavorable chromosome 17q gain and highHDAC9 expression with prognostically unfavorable gainon chromosome 6.Previous publications have shown that, in medullo-

blastoma, monosomy 6 is concurrent with activatingmutations of CTNNB1 (41) and all of the tumors withchromosome 6 loss investigated have an activation ofthe WNT pathway (42). We therefore went on to grouppatients according to their gene expression signatures, thatis, WNT and sonic hedgehog (SHH) pathway signaturesand signatures C and D as published previously (31, 41).HDAC5 expression correlated significantly with molecularsubgroups, that is, it was lowest in the groups with WNTand SHH signatures and highest in groups C andD (Supple-mentary Fig. S2E). HDAC9 expression showed a similartrend, with the expression being significantly lowest inthe WNT group when compared with group C or D butshowed no statistically significant difference between theSHH group and group C or D (Supplementary Fig. S2F).In conclusion,these data show a statistically significantassociation of highHDAC5 expression with chromosome17q gain and of high HDAC9 expression with chromo-some 6 gain, both correlating with poor prognosis, in asecond independent sample set. Furthermore, HDAC5and HDAC9 expression significantly correlates with mo-lecular subgroups characterized by distinct gene expres-sion signatures.



HDAC5 and HDAC9 protein expression and cellularlocalization in primary medulloblastoma samplesTo investigate if HDAC5 and HDAC9 are also expressed

at the protein level and could thus represent potential drugtargets, we stained sections of a medulloblastoma tissuemicroarray for HDAC5 and HDAC9. In addition, we stud-ied the cellular localization because both proteins belongto class IIa HDACs known to shuttle between nucleus andcytoplasm. HDAC5 was predominantly located in thenucleus (Fig. 3A; Supplementary Table S4); HDAC9 wasprimarily located in the cytoplasm (Fig. 3B; Supplemen-tary Table S4). Overall, >95% of cells stained positivefor either HDAC5 or HDAC9 protein (SupplementaryTable S4). For n = 125 samples, both HDAC5 and HDAC9staining was available. Samples were evaluated for nuclearHDAC5 staining and cytosolic HDAC9 staining. More than74% of the tumor samples showed a strong immunoreac-tivity for HDAC5 and HDAC9 (Supplementary Table S4).Of note, staining for HDAC5 and HDAC9 was stronger indesmoplastic nodules than in the surrounding tissue inmost patients with desmoplastic medulloblastoma (4 of 7tumors and 6 of 8 tumors, respectively; Fig. 3A and B). Insummary, we were able to show strong HDAC5 andHDAC9 protein levels in most primary medulloblastomasamples and show HDAC5 to be localized predominantlyin the nucleus, whereas HDAC9 is mostly localized in thecytoplasm. Considering HDAC5 andHDAC9 as potentially“druggable” proteins, >95% of the medulloblastomatumors are positive for these targets.

siRNA-mediated knockdown of HDAC5 and HDAC9in medulloblastoma cell lines reduces cell growthand viabilityTo investigate whether HDAC5 and HDAC9 are of

functional relevance in medulloblastoma cells, we chosean in vitro cell culture model using siRNA-mediated

Table 1. Stratified Cox regression model and hazard ratio (n = 37)

Variable (multivariate analysis)
Effect
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Hazard ratio

Clinical Cancer R

Association for Can

P

Age
<4 vs ≥4 y 6.26 NS Metastasis M2 or M3 vs M0 or M1 1.40 NS Level of resection STR vs GTR 28.12 <0.05 Histology Large cell anaplastic vs classic or desmoplastic 1.99 NS Chromosome 6 6 Bal vs monosomy 6 n/a n/a
6 Gain vs monosomy 6
n/a n/a Chromosome 17 17q gain vs 17q bal 10.79 NS HDAC5 and HDAC9 expression Group c (high/high) vs group a (low/low) 0.02 <0.005
Group c (high/high) vs group b (high/low)
0.02 <0.05
NOTE: Hazard ratio prediction using a stratified Cox regression model revealed that high expression of HDAC5 and HDAC9 is asignificant risk factor. The only other significant risk factor found in this model using the combined analysis proved to be level ofresection. Because no deaths were observed in the groups with 6q loss and the group with M stage 0, no HR can be estimated forthese groups.Abbreviations: STR, subtotal resection; GTR, gross total resection; bal, balanced; NS, not significant; n/a, not available.

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knockdown of HDAC5 or HDAC9 expression in estab-lished medulloblastoma cell lines Daoy, UW228-2,UW228-3, ONS76, and Med8A. After transient transfec-tion with three different siRNAs against each HDAC5 orHDAC9, medulloblastoma cell lines showed a knockdownof up to 80% of HDAC5 and HDAC9 mRNA expressionafter 72 hours (Supplementary Fig. S3A). Western blotconfirmed the knockdown of HDAC5 and HDAC9 proteinexpression at 72-hour exemplary in Daoy cells (Supple-mentary Fig. S3B). When cell counts were measured forDaoy cells over the course of 0 to 5 days after transfection,



a reduction in cell growth was seen, with the strongest ef-fect seen in all cell populations with knockdown ofHDAC5 but also in two out of three populations withknockdown of HDAC9 (Fig. 4A). Accordingly, the dou-bling time was increased up to 2.04-fold (Fig. 4B). Becausewe did not observe p21WAF1/CIP1 mRNA induction (datanot shown), a marker typically associated with cell cycleinhibition upon HDAC inhibition, we went on to investi-gate viability and cell death after knockdown of HDAC5 orHDAC9. Following knockdown of HDAC5 or HDAC9, weobserved a significant increase of up to 5-fold in trypan

Fig. 3. HDAC5 and HDAC9protein expression in primarymedulloblastoma samples.A and B, two representativemedulloblastoma samples areshown for each of the threestandard histologic categories:classical, large cell anaplastic(LCA) and desmoplasticmedulloblastoma. Originalmagnification, ×100 (left) and×400× (right). Pink staining,HDAC5 (A) or HDAC9 (B); bluestaining, nuclei. The cellularstaining pattern for HDAC5 waspredominantly nuclear, and forHDAC9, it was predominantlycytoplasmic.




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blue–positive cells (P < 0.005 to P < 0.0001; Fig. 5A). Ofnote, knockdown efficacy paralleled the extent of viabilitydecrease, that is, Med8A cell exhibiting the highest remain-ing HDAC5 and HDAC9 mRNA levels after knockdown al-so showed the least increase in trypan blue-positive cells.Flow-cytometric analysis of propidium iodide–stainedDaoy cells showed a significant increase in sub-G0 fractionfollowing knockdown of HDAC5 or HDAC9 (up to 34%and 31%; P < 0.05 and P < 0.05; Fig. 5B), suggestive ofapoptosis. We therefore determined caspase-3–like activityin Daoy cells as an indicator for apoptosis. Knockdown ofHDAC5 and HDAC9 resulted in increased caspase-3–likeactivity up to 2.65-fold, suggestive of apoptosis induction(P < 0.05; Fig. 5C). Of note, HDAC9 siRNA 2, which



induced the weakest reduction in HDAC9 protein level,also showed the least effects on subsequent cell counts,sub-G0, and caspase-3–like activity analyses, indicating adose-response relationship. In summary, knockdown ofHDAC5 or HDAC9 reduces cell growth and viability ofmedulloblastoma cells in vitro, associated with inductionof apoptosis.

Discussion

The treatment of medulloblastoma patients is stillchallenging in terms of long-term survival, as well as neu-rologic, cognitive, and endocrinological sequelae of che-motherapy- and radiation-based treatment protocols. To

Fig. 4. Knockdown of HDAC5 and HDAC9 reduces cell population growth and increases doubling time. A, cell counts of Daoy cells were measured at0 hour and every 24 hours for 5 days after transfection with three different siRNAs against HDAC5 (HDAC5 siRNA 1-3) or HDAC9 (HDAC9 siRNA 1-3),two different siRNA controls (negative ctrl 1 and 2) and transfection reagent only (transfection ctrl; representative plot). Cell population growth wasdecreased in cells with knockdown of either HDAC5 or HDAC9. B, doubling times (days; means and SD from four independent measurements) werecalculated for Daoy cells after siRNA-mediated knockdown of HDAC5 and HDAC9. The increase in doubling time was significant for cells with knockdownof HDAC5 (P = 0.0361) but not for cells with knockdown of HDAC9 (P = 0.0592; ANOVA). However, when only the two HDAC9 siRNAs with sufficientreduction of HDAC9 protein (HDAC9 siRNAs 1 and 3; Supplementary Fig. S3B) were compared with the negative controls; the difference in doubling timewas statistically significant (P = 0.0272; ANOVA). ctrl, control; NS, not significant; n/a, not available.






Fig. 5. Knockdown of HDAC5 and HDAC9 decreases viability in medulloblastoma cell lines. A, the percentage of dead cells as determined by trypanblue exclusion staining was increased in a statistically significant manner 72 hours after transfection with three different siRNAs against HDAC5(HDAC5 siRNA 1-3) or HDAC9 (HDAC9 siRNA 1-3) compared with two different siRNA controls (negative ctrl 1 and 2) in five different cell lines (P = 0.0014 toP < 0.0001; ANOVA). B, measurement of sub-G0 fraction 72 hours after knockdown of HDAC5 or HDAC9 (Nicoletti method) in Daoy cells. The sub-G0

fraction is significantly increased (P = 0.0092 and P = 0.0266; ANOVA). C, caspase-3–like activity is significantly increased in Daoy cells 72 hours afterknockdown of HDAC5 (P = 0.0115; ANOVA), Daoy cells with knockdown of HDAC9 showed an increase in caspase-3 activity 72 hours after knockdown,however, without reaching statistical significance, because of the lack of caspase-3–like activity increase in one of three siRNAs against HDAC9. Whenonly the two HDAC9 siRNAs with sufficient reduction of HDAC9 protein (HDAC9 siRNAs 1 and No.3; Supplementary Fig. S3B) were compared with thenegative controls, the difference in caspase-3–like activity was statistically significant (P < 0.005; ANOVA). Bars in A-C, averages from at least threeindependent measurements; error bars, SD. *, P < 0.05; **, P < 0.001; ***, P < 0.0001.

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explore the possibility of treatment with selective HDACi,we studied the expression of individual HDAC familymembers in medulloblastoma and found HDAC5 andHDAC9 to be highly expressed in prognostically unfavor-able subgroups. Of note, because HDAC5 is located onchromosome arm 17q, the most frequently gainedgenomic region in medulloblastoma, this might wellcontribute to a higher expression of HDAC5 through agene-dosage effect. Significant upregulation of HDAC5 intumors harboring a 17q gain as revealed by our studyunderlines the functional relevance of this candidate genein medulloblastoma biology. With regard to HDAC9, wedid not see a significant difference in mRNA levels be-tween tumors exhibiting 17q gain and balanced chromo-some 17 status in the second cohort as opposed to the firstcohort. We believe this is due to the difference in the com-position of the two 17q balanced groups; the first patientcohort contains more patients with activated WNT path-way than the second cohort. Because low HDAC9 expres-sion seems to be mostly attributable to the WNT group,the comparison of 17q balanced versus 17q gain in thefirst cohort shows a difference, whereas the second cohortdoes not.All classic HDACs (HDAC1-HDAC11) are widely ex-

pressed in the vertebrate developing and adult brain ashas been shown in rats and mice (43–45), with HDAC1being expressed in neural stem cells (45). Thus far, onlya few studies have systematically examined the expressionof all 11 classic HDAC family members in primary tumorsin general and tumors of neural origin in particular. Incancers of the gastrointestinal system, high HDAC1,HDAC2, and HDAC3 expression correlated with poor clin-ical outcome (29, 30). In neuroblastoma, among allHDAC family members investigated, only HDAC8 was as-sociated with advanced-stage disease and poor prognosis(14). Recently, class II and IV HDACs were found down-regulated in glioblastoma compared with low-grade astro-cytoma and normal brain (46). Therefore, expression ofindividual HDAC family members seems to be tumorspecific. In our study, we show for the first time that theHDAC class IIa isoenzymes HDAC5 and HDAC9 areassociated with clinical outcome in a malignant disease,not only correlating with survival but furthermore posingan independent risk factor. Prospective studies will beneeded to confirm the prospective value of HDAC5 andHDAC9 mRNA expression levels in the risk stratificationof medulloblastoma patients.Thus far, little is known about the physiologic function

of HDAC5 and HDAC9 in normal cells and in develop-ment. Both HDACs seem to play central roles in modula-tion of cardiac stress signals and cardiac development.Mouse knockout models of HDAC5 and HDAC9 producecardiac phenotypes similar to each other (47, 48), suggest-ing similar functions of the two isoenzymes in the physi-ologic setting. Furthermore, HDAC5 shuttles from thenucleus to the cytoplasm when myoblasts differentiate(49), and in fibroblasts, HDAC5 repressed the transcrip-tion of cyclin D3, a cell cycle activator (50), suggesting



physiologic roles in differentiation and cell cycle regula-tion. Data about HDAC5 and HDAC9 function in cancerhowever are scarce. In mouse erythroleukemia cells,HDAC5 interacts with the transcription factor GATA bind-ing protein 1 (GATA1) and shuttles from the nucleus tothe cytoplasm upon erythroid differentiation of leukemiccells (51), indicating a role of HDAC5 in differentiationprocesses of malignant cells as well. Our data suggestthat HDAC5 and HDAC9 harbor oncogenic function inmedulloblastoma cells because knockdown inhibits cellgrowth and reduces viability in these cells. On the pro-tein level, HDAC5 and HDAC9 were widely expressed inprimary medulloblastoma, with a nodular pattern in asubset of desmoplastic tumors. This and our data fromcell culture experiments indicate that the higher HDAC5and HDAC9 expression in the nodular area may have anantiapoptotic function.Based on our observation that (a) high HDAC5 and

HDAC9 expression correlates with poor prognostic sub-groups and is associated with poor overall survival, (b)high expression of HDAC5 and HDAC9 is an independentrisk factor, and (c) knockdown of HDAC5 or HDAC9 re-duces cell number, decreases viability, and induces apopto-sis in medulloblastoma cells, we propose that HDAC5 andHDAC9 play amajor role in medulloblastoma biology. It iscurrently under debate whether class IIa HDACs functionthrough their own enzymatic activity or display a ratherlow enzymatic activity (52, 53) and act in complex onlywith class I HDACs (23). The lack of specific HDAC5 orHDAC9 inhibitors currently prevents the testing of strate-gies involving selective targeting of these HDACs.In summary, we have identified HDAC5 and HDAC9 as

potential novel prognostic markers for medulloblastoma.Our functional data furthermore warrants further investi-gation of selective targeting of HDAC5 and HDAC9 as anovel strategy for medulloblastoma treatment.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Acknowledgments

We thank Sandra Riedinger, Carina Konrad, Sarah Engelhardt, CorneliaRütz, and Diana Jäger for the excellent technical assistance.

Grant Support

The NGFNplus program by a grant of the Bundesministerium für Bil-dung und Forschung, Germany (H.E. Deubzer and O. Witt), the Universityof Heidelberg through the FRONTIER and the OLYMPIA MORATA pro-grams (H.E. Deubzer), and a grant from the Wilhelm Sander Foundation(T. Milde and I. Oehme).

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely toindicate this fact.

Received 02/13/2010; revised 04/14/2010; accepted 04/15/2010;published OnlineFirst 04/22/2010.






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2010;16:3240-3252. Published OnlineFirst April 22, 2010.Clin Cancer Res Till Milde, Ina Oehme, Andrey Korshunov, et al. Risk Stratification and Role in Tumor Cell GrowthHDAC5 and HDAC9 in Medulloblastoma: Novel Markers for

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