Microarray-based gene expression profiling of benign, atypical and anaplasticmeningiomas identifies novel genes associated with meningioma progressionGunnar Wrobel1, Peter Roerig2, Felix Kokocinski1, Kai Neben1, Meinhard Hahn1, Guido Reifenberger2 and Peter Lichter1*1Division of Molecular Genetics, German Cancer Research Center, Heidelberg, Germany2Department of Neuropathology, Heinrich-Heine-University, Dusseldorf, Germany

To identify gene expression profiles associated with human me-ningiomas of different World Health Organization (WHO) malig-nancy grades, we analyzed 30 tumors (13 benign meningiomas,WHO grade I; 12 atypical meningiomas, WHO grade II; 5 ana-plastic meningiomas, WHO grade III) for the expression of 2,600genes using cDNA-microarray technology. Receiver operatorcurve (ROC) analysis with a cutoff value of 45% selection prob-ability identified 37 genes with decreased and 27 genes with in-creased expression in atypical and anaplastic meningiomas, com-pared to benign meningiomas. Supervised classification of thetumors did not reveal specific expression patterns representativeof each WHO grade. However, anaplastic meningiomas could bedistinguished from benign meningiomas by differential expressionof a distinct set of genes, including several ones associated with cellcycle regulation and proliferation. Investigation of potential cor-relations between microarray expression data and genomic aber-rations, detected by comparative genomic hybridization (CGH),demonstrated that losses on chromosomes 10 and 14 were associ-ated with distinct expression profiles, including increased expres-sion of several genes related to the insulin-like growth factor (IGF)(IGF2, IGFBP3 and AKT3) or wingless (WNT) (CTNNB1,CDK5R1, ENC1 and CCND1) pathways. Taken together, our mi-croarray-based expression profiling revealed interesting novelcandidate genes and pathways that may contribute to meningiomaprogression.© 2004 Wiley-Liss, Inc.

Key words: meningioma; tumor progression; cDNA microarrays;gene expression profiling; WNT pathway; IGF pathway

Meningiomas are common central nervous system tumors thatoriginate from the meningeal coverings of the brain and spinalcord. They account for about 25% of all primary brain tumors,with an estimated annual incidence of 6 per 100,000 individuals.1The World Health Organization (WHO) classification of tumors ofthe nervous system distinguishes meningiomas of 3 malignancygrades: benign meningiomas of WHO grade I, atypical meningi-omas of WHO grade II and anaplastic (malignant) meningiomas ofWHO grade III.1 About 90% of all meningiomas are slowlygrowing benign tumors of WHO grade I.1 Atypical meningiomasconstitute about 6–8% of the cases and are histologically definedby increased mitotic activity, i.e., 4 or more mitoses per 10microscopic high-power fields and/or 3 or more of the followingcriteria: increased cellularity, high nucleus/cytoplasm ratio, prom-inent nucleoli, uninterrupted patternless or sheet-like growth andnecrosis.1 Clinically, atypical meningiomas have a significantlyhigher risk of local tumor recurrence than benign meningiomas,even after gross total resection. Approximately 2–3% of all me-ningiomas show histologic features of frank malignancy, includinga high mitotic activity (20 or more mitoses per 10 microscopichigh-power fields) and/or a histologic appearance similar to sar-coma, carcinoma or melanoma.1 These rare anaplastic meningio-mas are associated with a poor prognosis, as indicated by a mediansurvival time of less than 2 years after diagnosis.2 In addition tohigher histologic grade, certain clinical factors, such as incompletesurgical resection and a patient age of �40 years, are associatedwith an increased likelihood of tumor recurrence.3

The molecular mechanisms underlying the development andprogression of meningiomas remain poorly understood. Mutationsin the neurofibromatosis type 2 gene (NF2) on chromosome 22q12were identified as the important initial event in about half of all

meningiomas.4,5 The NF2 gene product (merlin/schwannomin)belongs to the highly conserved protein 4.1 family that links cellsurface glycoproteins to the actin cytoskeleton.6 Certain membersof this family, including merlin/schwannomin and protein 4.1B,also known as DAL-1 (differentially expressed in adenocarcinomaof the lung), exhibit growth-inhibitory and tumor-suppressiveproperties.6 Besides NF2 mutation, loss of protein 4.1B expressionwas identified as a common aberration in meningiomas of allWHO grades.7,8 Furthermore, a third protein 4.1 molecule, protein4.1R, is frequently downregulated in primary meningiomas andwas shown to inhibit meningioma cell growth in vitro.9 Thus,meningioma initiation appears to be closely linked to the inacti-vation of 1 or more protein 4.1 family members.

The genetic alterations leading to atypical and anaplastic me-ningiomas are complex and appear to involve genomic losses,gains and amplifications on multiple different chromosomes.10

Atypical meningiomas carry frequent losses on chromosomes 1p,6q, 10, 14q, 18q and 22q, as well as gains on 1q, 9q, 12q, 15q, 17qand 20q.10 Anaplastic meningiomas share these chromosomal ab-errations but show more frequent losses on 6q, 10 and 14q,additional losses on 9p and gene amplification on 17q23.10,11 Thelosses on 9p affect the tumor suppressor genes CDKN2A, p14ARF

and CDKN2B at 9p21, which are inactivated by homozygousdeletion or mutation in the majority of anaplastic meningiomas.12

Relevant genes on the other aberrant chromosomes are mostlyunknown. Mutations in the phosphatase and tensin homolog geneon chromosome 10 (PTEN, 10q23)13,14 or the cyclin-dependentkinase inhibitor 2c gene (CDKN2C, 1p32)12 were detected in rarecases of atypical or anaplastic meningiomas, while amplification ofthe ribosomal protein S6 kinase gene (RPS6KB1, 17q23) wasfound in a minor fraction of anaplastic meningiomas.15

In contrast to these genetic alterations, relatively little is knownabout the changes at the transcript level that are associated with thedifferent meningioma malignancy grades. To better understand themolecular basis of meningioma progression, we performed mi-croarray-based expression profiling of 30 meningiomas of differ-ent malignancy grades using cDNA arrays representing 2,600different genes with relevance to mitosis, cell cycle control, on-cogenesis and apoptosis. Thereby, we intended to identify novelgenes associated with meningioma progression as well as geneexpression patterns that may be helpful for the distinction of thedifferent meningioma malignancy grades. In addition, we corre-lated the expression data with the genomic imbalances detected in

Abbreviations: CGH, comparative genomic hybridization; GO, geneontology; IGF, insulin-like growth factor; PCNA, proliferating cell nuclearantigen; ROC, receiver-operator curve; RT, reverse transcription; WHO,World Health Organization; WNT, wingless.

Grant sponsor: Deutsche Forschungsgemeinschaft; Grant number:SFB503, B7; Grant sponsor: Wilhelm Sander-Stiftung; Grant number:2000.039.1; Grant sponsor: Medical Faculty of the Heinrich-Heine-Uni-versity; Grant number: 9772182; Grant sponsor: Bundesministerium furBildung und Wissenschaft; Grant number: NGFN-1, 01 GR 0101.

*Correspondence to: Abteilung Molekulare Genetik (B060), DeutschesKrebsforschungszentrum, Im Neuenheimer Feld 280, D-69120 Heidelberg,Germany. Fax: �49-6221-42-4639. E-mail: M.MacLeod@dkfz.de

Received 17 June 2004; Accepted 10 September 2004DOI 10.1002/ijc.20733Published online 11 November 2004 in Wiley InterScience (www.

interscience.wiley.com).

Int. J. Cancer: 114, 249–256 (2005)© 2004 Wiley-Liss, Inc.

Publication of the International Union Against Cancer

the same tumors using comparative genomic hybridization (CGH)analysis.

Material and methodsTumor samples

Tumor tissue specimens from 30 sporadic meningiomas wereselected from the archives of the Department of Neuropathology,Heinrich-Heine-University, Dusseldorf, Germany, as approved bythe local institutional review board. The cases were selected on thebasis that data from CGH analysis10 and sufficient amounts oftumor RNA were available. The tumors were from 30 adult pa-tients (9 males and 21 females, mean age at operation � 62.6years, range � 38–84 years) who were operated on between 1991and 1998 at the Department of Neurosurgery, Heinrich-Heine-University, Dusseldorf, Germany. All tumors were histologicallyreclassified according to the WHO classification of tumors of thenervous system.1 Thirteen tumors corresponded to benign menin-giomas of WHO grade I (3 meningothelial, 6 fibrous, 4 transi-tional), 12 tumors were atypical meningiomas of WHO grade IIand 5 were anaplastic meningiomas of WHO grade III. Parts ofeach tumor were snap-frozen immediately after operation andstored at –80°C. Extraction of RNA from frozen tumor tissue wasperformed by ultracentrifugation as described elsewhere.16 Histo-logic evaluation of these pieces revealed an estimated tumor cellcontent of 90% or more for all cases.

Microarray analysisMicroarrays containing replicate spots of 4,211 different gene-

specific fragments, representing 2,600 different genes with rele-vance to mitosis, cell cycle control, oncogenesis and apoptosis,were generated and processed as described elsewhere.17–20 TumorRNA was cohybridized with a pool of commercially availableRNA from 8 different human tissues, i.e., heart, spleen, placenta,kidney, skeletal muscle, liver, brain and lung (Stratagene, La Jolla,CA, USA). From each tumor and the control RNA pool, poly-A-RNA was extracted from 10 �g of total RNA using Oligotex resinpurification (Qiagen, Hilden, Germany), followed by labeling withCy3 or Cy5 dUTP using the Omniscript Reverse Transcriptase kit(Qiagen). The combined samples, together with 10 �g of C0tIDNA, 30 �g of bovine liver tRNA and 10 �g of oligo-dT, werehybridized to the microarrays in an automated GeneTac hybrid-ization chamber (Genomic Solutions, Ann Arbor, MI, USA). Allsamples were hybridized to 2 microarrays, with the only differencebeing an inverted dye labeling for the repeated experiment. Hy-bridized microarrays were scanned and fluorescence was detectedusing a GenePix 4000B microarray scanner (Axon Instruments,Union City, CA, USA).

Biomathematic analysesAll relevant microarray data were analyzed for each slide using

the software GenePix Pro 3.0 (Axon Instruments). Individual datareports for all conducted experiments were exported and furtheranalyzed using the R-software environment for statistical comput-ing (http://www.r-project.org). Data sets for spots not recognizedby the GenePix Pro 3.0 software were excluded from furtherconsiderations. In addition, all remaining data sets were rankedaccording to spot homogeneity (as assayed by the ratio of medianand mean fluorescence intensities), spot intensity and the standarddeviation of log ratios for replicate spots. Data points rankingamong the lower 20%, and thus possessing the lowest reliability,were eliminated, based on the criteria just described. For eachhybridization, the intensities were normalized by variance stabili-zation.21 To combine experiments with switched dye labeling, theratios of 1 experiment were inverted and averaged with the ratiosof the corresponding spots on the second array. Features lackingthe corresponding spot after the filtering described above werecompletely eliminated.

All processings from raw data to the final tables and figures areprovided as supplemental material (http://www.dkfz.de/kompl_ge-

nome/Script/modules.php?name�Downloads). The analysis pro-cedures have been formulated in Sweave22 and can be downloadedin conjunction with the raw data. The Sweave file provides code inthe R-programming language23 combined with comments in La-TeX format. By processing the file using R, the code itself can beextracted or a portable document format (PDF) document provid-ing an overview of the analysis can be generated. Thus, the entireprocess of analysis is completely transparent.

ROC24 analysis was used to identify genes that show a differ-ential expression between benign meningiomas and atypical oranaplastic meningiomas. In comparison to a t-test, the ROCmethod has the advantage of being able to select differentiallyexpressed genes even if only a subset of tumors within each groupshows a strong differential expression, while a t-test is solely basedon mean value and standard deviation. The stability of the selec-tion was increased by choosing only genes that were among the100 genes with the highest ROC (0.1) value in more than 45% of200 bootstrapped samples (selection probability �45%).

The resulting lists were analyzed using the tool EASE.25 Thecorresponding functional annotations of the Gene Ontology (GO)Consortium26 were searched for a significant overrepresentation ofterms. For statistical evaluation, this tool uses a modified Fisherscore.

The method of shrunken centroids was employed to classifysamples on the basis of specific expression signatures.27 For eachsample class, a separate centroid (mean vector over gene expres-sion) was generated. Each centroid was then reduced toward zeroby a value proportional to the standard deviation of gene expres-sion over the samples of the centroid’s class. All genes demon-strating a mean value reduced to zero or below zero in thisprocedure were removed from the centroid. This shrunken centroidcan then be used for classification by determining the distancesbetween each sample and centroid. The optimal amount of shrink-age is determined by cross-validation. This cross-validation alsoallows a judgment of the classification quality. For the exactmathematic procedures, see Tibshirani et al.27

Real-time RT-PCR analysisTo verify selected microarray data, the expression levels of 9

genes (AKT3, CDK5R1, CENPF, ELF3, IGF2, IGFBP3, MDM4,PTPRF and VASP) were determined for all 30 meningiomas byreal-time reverse transcription (RT) PCR analysis using the ABIPRISM 5700 sequence detection system (Applied Biosystems,Darmstadt, Germany). Continuous quantitative measurement ofthe PCR product was achieved by incorporation of SYBR Green Ifluorescent dye (Applied Biosystems) into the double-strandedPCR products. The transcript level of each gene was normalized tothe transcript level of the housekeeping gene ARF1 (ADP-ribosy-lation factor 1). The respective primer sequences are availableupon request. RNA extracted from normal meningeal tissue sam-ples obtained at autopsy was used as the reference. Both microar-ray and real-time RT-PCR data were tested for differential expres-sion using independent t-tests for each gene. In addition, thecorrelation between both data sets was determined genewise.

ResultsMeningioma signature and results of ROC analyses

A characteristic signature of the meningioma samples was iden-tified by selecting the 10 genes with the highest median expressionover all samples relative to the pool reference tissues (Fig. 1).Receiver operator curve (ROC) analysis was performed to identifygenes differentially expressed between benign meningiomas(WHO grade I, n � 13) and the combined group of atypical andanaplastic meningiomas (WHO grades II and III, n � 17). Thegenes that were expressed at significantly lower levels in atypical/anaplastic meningiomas, compared to benign meningiomas, arelisted in Table I. Table II shows the list of genes that wereexpressed at significantly higher levels in atypical/anaplastic me-ningiomas. Both lists were cut off at a value of 45% selection

250 WROBEL ET AL.

probability, which resulted in 37 candidate genes with decreasedand 27 candidate genes with increased expression in atypical/anaplastic meningiomas, compared to benign meningiomas.

To identify functional groups among these candidate genes, bothlists were analyzed with regard to the frequency of GO termsassociated with the respective genes, compared to the frequencywithin the list of all genes present on the microarray, using the toolEASE.25 While there was no significant enrichment of GO termsfound in the list of genes downregulated in higher-grade menin-giomas (data not shown), the list of genes upregulated in atypical/anaplastic meningiomas showed a significant enrichment of pro-liferation-associated genes. The “biological process” branch of theGO hierarchy dominated this list of overrepresented terms andamong the most frequent categories were “regulation of cell cy-cle,” “mitotic cell cycle” and “G1/S transition of mitotic cellcycle,” with 9, 7 and 4 associated genes, respectively.

Classification according to WHO gradeSupervised classification of the samples, based on tumor grade,

was performed using shrunken centroid analysis. However, thisanalysis did not identify specific expression patterns representativefor each grade (see supplementary information at http://www.dkfz.de/kompl_genome/Script/modules.php?name�Downloads).The cross-validated error over all samples was in the range of 40%.By limiting the comparison to the benign tumors of WHO grade I(n � 13) and the anaplastic meningiomas of WHO grade III (n �5), the method was able to provide a stable centroid that allowedfor the classification of the samples (Fig. 2). The cross-validationstill yielded 1 wrongly classified anaplastic tumor, but the totalerror of the classification was reduced. The resulting centroid wascomposed of the genes IGFBP3, AKT3, LDHB, CENPF, CDK5R1,CCND1 and ENC1 (in the order of their significance). All thesegenes were expressed at higher levels in anaplastic meningiomas.

Correlation of expression data with genomic imbalancesShrunken centroid analysis was additionally used to identify

potential associations between the mRNA expression data andtumor-associated genomic changes as detected by CGH analysis.10

The resolution of CGH aberrations had to be lowered to fullchromosomes to get a reasonable number of patient samples withineach group. Thus, dim14 represents a loss of genomic material thatoccurred anywhere on chromosome 14, while enh17 signifies again of genomic material anywhere on chromosome 17. Testingeach chromosome and each type of aberration (gain or loss)separately, the analysis aimed at identifying gene expression pat-terns that could be used to determine the CGH status for a partic-ular chromosome. The analysis was restricted to chromosomesshowing an aberration in at least 4 tumors. Centroids that provideda low amount of misclassifications were identified for loss ofgenomic material on chromosome 10 (dim10) and chromosome 14(dim14) (Fig. 3a and b). The total rate of misclassification was10% (dim10) and 20% (dim14) using a shrinkage of 1.9 and 1.5,respectively.

Identification of signaling pathways potentially involved inmeningioma progression

ROC analysis of microarray data revealed increased expressionof 2 members of the insulin-like growth factor (IGF) pathway(IGFBP3 and AKT3) in atypical and anaplastic meningiomas (Ta-ble II). Both genes were also at the top of the WHO grade I vs.WHO grade III centroid (Fig. 2) and were included in the dim10centroid (Fig. 3a). Another gene related to this pathway, IGF2,was at the top of the dim14 centroid (Fig. 3b) and showed in-creased mRNA levels in atypical and anaplastic tumors, comparedto benign meningiomas (Table III). The centroid generated for theclassification according to chromosome 14 status included 4 genes(CTNNB1, CCND1, ENC1 and CDK5R1) that can be linked to thewingless (WNT) signaling pathway (Fig. 3b). Two of these genes(CCND1 and ENC1) were also upregulated in anaplastic menin-giomas, compared to benign meningiomas (Fig. 2).

Analysis of selected genes by real-time RT-PCRSeven genes were selected for further analysis by real-time

RT-PCR from the list of genes identified by microarray analysis asbeing differentially expressed between benign meningiomas andatypical/anaplastic meningiomas (Tables I and II). These included4 genes (AKT3, CDK5R1, CENPF and IGFBP3) with higher and3 genes (ELF3, PTPRF and VASP) with lower expression in theatypical/anaplastic tumors. In addition, we performed real-timeRT-PCR analyses for IGF2, which was of high relevance for thedim14 centroid and MDM4, which was represented in both dim10and dim14 centroids (Fig. 3). The real-time RT-PCR data con-firmed significantly higher mRNA levels of CENPF, IGFBP3 andMDM4 in atypical/anaplastic meningiomas, compared to benignmeningiomas (Table III). The increased expression of CENPF andIGFBP3 in tumors with loss of chromosome 10 and the increasedexpression of CENPF, IGF2, AKT3 and MDM4 in tumors withloss of chromosome 14 were also corroborated (Table IV). In linewith the microarray data, real-time RT-PCR showed a significantincrease in the mean expression levels of CDK5R1 in anaplasticmeningiomas (Table III). Similarly, real-time RT-PCR showedhigher CDK5R1 expression in meningiomas with losses on chro-mosomes 10 or 14, compared to meningiomas without theselosses, but the differences in mean values were not significant(Table IV). The differential expression of AKT3, ELF3, PTPRFand VASP in benign vs. atypical/anaplastic meningiomas, as sug-gested by ROC analyses (Tables I and II), was not corroborated bythe real-time RT-PCR analyses of these genes (Table III).

Discussion

Among the 10 genes showing the highest expression in ourtumor series, 6 were already known to be expressed in meningi-oma. These include PTGDS,28 CLU,29 MGP,30 MMP12,31 VIM1

FIGURE 1 – Highly expressed genes in the meningioma samplesrelative to a reference representing 8 different human tissues (heart,spleen, placenta, kidney, skeletal muscle, liver, brain and lung). Thebox plot represents expression of each gene over all 30 tumors. Thecentral line denotes the median of expression over all samples, whilethe box is drawn from the upper to the lower quartile. The linesextending from the boxes represent the first value below the lowerquartile plus 1.5 times the interquartile range and the first value abovethe upper quartile plus 1.5 times the interquartile range, respectively.The dots refer to individual outliers.

251EXPRESSION PROFILING OF MENINGIOMAS

and TIMP1.31 It is difficult to assess the biologic impact of theseexpression levels due to the nature of the reference population ofdifferent human tissues used for reference. Nevertheless, the cor-rect identification of genes known to be expressed in meningiomasunderlines the reliability of the data. The other 4 genes that werestrongly expressed in meningiomas (ANXA2, BAD, CCND1 andLIG1) have not been investigated in these tumors so far.

Expression profiles in relation to WHO gradeWe assumed that meningiomas of different WHO grade may be

distinguishable by distinct expression profiles using statisticalmethods like hierarchical clustering or shrunken centroids. Thelatter method was used here to identify a classifier for the 3different WHO grades. Unfortunately, this classifier provided anunacceptable fraction of misclassifications, and thus did not allowfor a reliable distinction of the different meningioma grades. Asimilar observation was made in a previous oligonucleotide mi-croarray study of a smaller number of meningiomas.32 Severalreasons may contribute to the fact that the histologic grading couldnot be matched to specific, diagnostically useful expression pro-

files. For example, the group of WHO grade I meningiomasincluded different morphologic subtypes (meningothelial, fibro-blastic and transitional). The group of atypical meningiomas wasalso quite heterogeneous and comprised tumors with a consider-able variability in mitotic activity and/or other histologic featuresof atypia. Thus, the considerable morphologic and biologic heter-ogeneity of meningiomas may require the analysis of larger casenumbers in order to identify expression profiles that may differ-entiate the various meningioma types as well as malignancygrades.

Nevertheless, to identify single genes that may be associatedwith tumor progression, we employed ROC analysis for the com-parison of 13 benign meningiomas with 17 atypical and anaplasticmeningiomas included in our series. The ROC method is compa-rable to a parametric Mann-Whitney test, but preferentially selectsgenes that show strong differential expression in a subset ofpatients of 1 class, instead of genes that mainly differ in their meanvalue between 2 classes.24 Thus, the pathologic grading can betaken as a classifier without requesting an absolutely stringentseparation of expression values between these classes. However,

TABLE I – GENES IDENTIFIED BY ROC ANALYSIS AS BEING DOWNREGULATED IN ATYPICAL AND ANAPLASTIC MENINGIOMASAS COMPARED TO BENIGN MENINGIOMAS1

No. Gene Localization Gene name ROCvalue

1 VASP 19q13.2-q13.3 Vasodilator-stimulated phosphoprotein 0.892 ICSBP1 16q24.1 Interferon consensus sequence binding protein 1 0.813 ALOX5AP 13q12 Arachidonate 5-lipoxygenase-activating protein 0.794 NOS1 12q24.2-q24.31 Nitric oxide synthase 1 (neuronal) 0.795 PPARG 3p25 Peroxisome proliferative activated receptor � 0.7756 PBX2 6p21.3 Pre-B-cell leukemia transcription factor 2 0.777 ARHC 1p21-p13 Ras homolog gene family, member C 0.738 UMP-CMPK 1p33 UMP-CMP kinase 0.719 HOXB2 17q21-q22 Homeo box B2 0.70510 HLA-DRA 6p21.3 Major histocompatibility complex, class II DR� 0.69511 CHC1 1p36.1 Chromosome condensation 1 0.6512 FGF12B 3 Fibroblast growth factor 12B 0.64513 LTBP2 14q24 Latent transforming growth factor � binding protein 2 0.6214 LILRA2 19q13.4 Leukocyte immunoglobulin-like receptor subfamily A

(with TM domain) member 20.605

15 CCNG2 4q13.3 Cyclin G2 0.60516 TAGLN 11q23.2 Transgelin 0.617 GPRK6 5q35 G protein-coupled receptor kinase 6 0.58518 CDKN2C 1p32 Cyclin-dependent kinase inhibitor 2C (p18) 0.5519 CYP2A6 19q13.2 Cytochrome P450, subfamily IIA (Phenobarbital-

inducible polypeptide 6)0.55

20 GAPCENA 9q34.11 Rab6 GTPase activating protein (GAP and centrosome-associated)

0.54

21 SELPLG 12q24 Selectin P ligand 0.53522 CYP1B1 2p21 Cytochrome P450, subfamily I (dioxin-inducible

polypeptide 1)0.535

23 CASP8 2q33-q34 Caspase 8, apoptosis-related cysteine protease 0.5324 PTPRF 1p34 Protein tyrosine phosphatase, receptor type F 0.5325 ImageID: 632001 0.49526 EFEMP1 2p16 EGF-containing fibulin-like extracellular matrix protein

10.49

27 ARHG 11p15.5-p15.4 Ras homolog gene family, member G (rho 6) 0.4928 ARHB 2pter-p12 Ras homolog gene family, member B 0.48529 STAT2 12q12 Signal transducer and activator of transcription 2 0.4830 TAF2J 1p35.3 TAF12 RNA polymerase II 0.4831 NEDD8 14q11.2 Neural precursor cell expressed, developmentally

downregulated 80.47

32 GADD45B 19p13.3 Growth arrest and DNA-damage-inducible � 0.4733 ELF3 1q32.2 E74-like factor 3 (ets domain transcription factor,

epithelial-specific)0.47

34 LRP8 1p34 Low density lipoprotein receptor-related protein 8,apolipoprotein e receptor

0.46

35 CDC25B 20p13 Cell division cycle 25B 0.4636 SERPINH2 11q13.5 Serine (or cysteine) proteinase inhibitor clade H (heat

shock protein 47), member 10.46

37 MAP3K11 11q13.1-q13.3 Mitogen-activated protein kinase kinase kinase 11 0.4551A higher ROC value indicates a stronger downregulation of the respective gene. The gene HLA-DRA was represented by 2 clones and only

the average value of both clones is given. Clones without localization information are identified by their Image ID number.

252 WROBEL ET AL.

any selection of genes based on techniques that are applied pergene will also identify false positives because of the high numberof data points per sample that are obtained from microarray ex-periments. This fact is confirmed by the results of our real-timeRT-PCR analyses of selected genes, which did not confirm differ-

ential expression in all instances. Thus, although the ROC methodhas been shown to result in a list of genes that is strongly enrichedwith genes being truly differentially expressed,24 the list alsoincludes a minor amount of falsely identified genes. To excludesuch genes, we will focus our discussion on those genes that aremembers of certain functional pathways and have been addition-ally identified by the shrunken centroid analyses and/or have beenconfirmed by real-time RT-PCR analysis. However, this selectiondoes not preclude many of the other genes identified by ROCanalysis, which are not discussed in detail here, that may still beimportant for meningioma progression.

Increased expression of proliferation-associated genes inatypical/anaplastic meningiomas

Within the list of genes that were differentially expressed be-tween benign meningiomas and atypical/anaplastic meningiomas,EASE analysis25 identified a number of proliferation-associatedgenes, with the most specific theme being related to the “G1/Stransition of mitotic cell cycle.” This is not too surprising for 2reasons: (i) our microarrays were enriched for genes related tomitosis and cell cycle regulation and (ii) increased mitotic activityis the major histologic criterion for the diagnosis of atypical andanaplastic meningioma. Furthermore, we showed previously that 1or more genes involved in the control of G1/S-phase transition, inparticular CDKNA, p14ARF, CDKN2B and CDKN2C, are altered inthe majority of anaplastic meningiomas.12 The present study indi-cates that CDK4 mRNA levels are frequently upregulated in atyp-ical and anaplastic meningiomas. CDK4 gene amplification, how-ever, is rare in these tumors.12 We also found that atypical/anaplastic meningiomas show higher expression of the growtharrest and the DNA damage-inducible GADD45A gene, which isimportant for p53-dependent cell cycle control and DNA excisionrepair. Similar to meningiomas, expression of GADD45A wasfound to increase with tumor grade in pancreatic carcinomas.33

CKS2 is yet another cell cycle regulatory gene that we identified to

TABLE II – GENES IDENTIFIED BY ROC ANALYSIS AS BEING UPREGULATED IN ATYPICAL AND ANAPLASTIC MENINGIOMASAS COMPARED TO BENIGN MENINGIOMAS1

No. Gene Localization Gene name ROCvalue

1 CKS2 9q22 CDC28 protein kinase 2 0.7432 IGFBP3 7p13-p12 Insulin-like growth factor binding protein 3 0.713 AKT3 1q43-q44 V-akt murine thymoma viral oncogene homolog 3 0.684 TEAD4 12p13.2-p13.3 TEA domain family member 4 0.6155 E4F1 16p13.3 E4F transcription factor 1 0.6056 STK15 20q13.2-q13.3 Serine/threonine kinase 15 0.67 CDK5R1 17q11.2 Cyclin-dependent kinase 5, regulatory subunit 1 (p35) 0.598 LILRB5 19q13.4 Leukocyte immunoglobulin-like receptor subfamily B (with

TM and ITIM domains), member 50.565

9 E2F6 22q11 E2F transcription factor 6 0.5510 CYP3A5 7q21.1 Cytochrome P450, subfamily IIIA (niphedipin oxidase)

polypeptide 50.535

11 SOX9 17q24.3-q25.1 SRY (sex determining region Y)-box 9 (campomelicdysplasia, autosomal sex-reversal)

0.525

12 ImageID: 77723 0.52513 RAD52 12p13-p12.2 RAD52 homolog (S. cerevisiae) 0.5214 TFPI2 7q22 Tissue factor pathway inhibitor 2 0.5115 PLAG1 8q12 Pleiomorphic adenoma gene 1 0.516 HINT 5q31.2 Histidine triad nucleotide binding protein 1 0.4917 ImageID: 42156 0.4718 CCT2 12q13.2 Chaperonin containing TCP1, subunit 2 (�) 0.4719 CENPF 1q32-q41 Centromere protein F (350/400 kD, mitosin) 0.46520 EP300 22q13.2 E1A binding protein p300 0.46521 PER2 2q37.3 Period homolog 2 (Drosophila) 0.46522 FBL 19q13.1 Fibrillarin 0.4623 TC10 2p21 Likely ortholog of mouse TC10-alpha 0.4624 TUBA2 13q11 Tubulin, alpha 2 0.4625 GADD45A 1p31.2-p31.1 Growth arrest and DNA-damage-inducible, � 0.4526 CDK4 12q14 Cyclin-dependent kinase 4 0.4527 STK12 17p13.1 Serine/threonine kinase 12 0.451A higher ROC value indicates a stronger upregulation of the respective gene. The gene CSK2 was represented by 2 clones and only the

average value of both clones is given. Clones without localization information are identified by their Image ID number.

FIGURE 2 – Shrunken centroid classification of meningioma expres-sion data according to WHO grade, i.e., benign meningiomas (WHOgrade I) vs. anaplastic (WHO grade III) meningiomas. The orientationof the bars in regard to the central line represents down- (left) orupregulation (right) of the gene in the corresponding class. The lengthof the bars represents the difference in mean expression over samplesof 1 class, compared to the mean over all samples. Thus, it alsovisualizes the significance of the gene for this classification.

253EXPRESSION PROFILING OF MENINGIOMAS

be upregulated in atypical/anaplastic meningiomas. Previous mi-croarray studies showed increased expression of this gene inadvanced pancreatic and breast cancers.34,35 The CDK5R1 gene,whose gene product is associated with the “G1/S transition ofmitotic cell cycle,” is discussed below.

Moving along the GO hierarchy to “mitotic cell cycle,” therewere 3 additional genes that were more strongly expressed inatypical and anaplastic meningiomas than in benign meningio-mas. These included the genes for proliferating cell nuclearantigen (PCNA), which interacts with GADD45 and functionsas a cofactor of DNA polymerase delta;36 STK15, whose geneproduct functions as a centrosome-associated serine/threoninekinase;37 and CENPF, which encodes mitosin, a protein of thekinetochore that is involved in cell cycle progression.38 In linewith our mRNA findings, immunohistochemical studies docu-mented an increase in the fraction of PCNA and mitosin-

positive tumor cells with advancing WHO grade of meningio-mas.39,40

Increased expression of IGF pathway genes in meningiomaswith losses on chromosomes 10 and 14

Correlation between genomic alterations detected by CGH anal-ysis and mRNA expression profiles using shrunken centroid anal-ysis revealed 2 sets of genes whose expression discriminatedbetween meningiomas with and without genomic losses on chro-mosomes 10 and 14, respectively. The fact that none of thediscriminating genes mapped to chromosome 10 or 14 suggeststhat the identified profiles likely represent downstream effectsoccurring as a result of aberrations in yet unknown genes onchromosomes 10 or 14, respectively. Strikingly, most of the geneswhose expression correlated with losses on chromosomes 10 and14 demonstrated increased expression in the group of tumors with

FIGURE 3 – Shrunken centroid classification of meningioma expression data according to losses on chromosomes 10 (a) and 14 (b). Theorientation of the bars in regard to the central line represents down- (left) or upregulation (right) of the gene in the corresponding class. Thedim14 centroid (b) has been cut at 27 genes. The full centroid is available as supplementary information (http://www.dkfz.de/kompl_genome/Script/modules.php?name�Downloads).

TABLE III – COMPARISON OF mRNA EXPRESSION DATA OF 10 SELECTED GENES AS DETERMINED BY MICROARRAY ANALYSISOR REAL-TIME RT-PCR ANALYSIS, RESPECTIVELY1

Gene

Microarray data Real-time RT-PCR data

WHO Grade I 3 IIp-val

II 3 IIIp-val

I 3 II � IIIp-val

WHO Grade I 3 IIp-val

II 3 IIIp-val

I 3 II � IIIp-valI II III I II III

IGF2 �0.22 0.58 0.78 0.0723 0.3730 0.0307 0.32 0.63 0.73 0.3017 0.4640 0.2766MDM4 �0.07 0.19 0.52 0.1686 0.1100 0.0627 �0.20 0.14 0.69 0.1018 0.1705 0.0218AKT3 �0.14 0.14 0.54 0.0491 0.0346 0.0032 �0.96 �1.07 �0.82 0.6811 0.1793 0.5636IGFBP3 �0.48 �0.12 0.88 0.0767 0.0174 0.0045 �3.25 �2.06 �0.03 0.0423 0.0026 0.0009CENPF �0.13 0.31 0.69 0.0418 0.0511 0.0075 0.72 2.12 3.55 0.0025 0.0225 <0.0001CDK5R1 0.06 0.14 0.60 0.3200 0.0408 0.0651 �2.44 �2.36 �1.23 0.4379 0.0206 0.1462PTPRF 0.25 �0.11 �0.17 0.0150 0.3607 0.0015 1.10 0.92 0.89 0.3280 0.4852 0.3254VASP 0.13 �0.14 �0.13 0.0070 0.5613 0.0017 �0.23 �0.19 0.06 0.5709 0.7767 0.7207ELF3 �0.01 �0.16 �0.26 0.0380 0.2020 0.0105 �0.01 �0.03 2.00 0.4809 0.9981 0.92871The table shows the mean expression value calculated for each WHO grade by the 2 different methods. The p-values (p-val) correspond to

the difference in means between WHO grade I and II (I 3 II), WHO grade II and III (II 3 III) or WHO grade I and the combined group ofWHO grade II and III tumors (I 3 II � III). Significant p-values are printed in bold.

254 WROBEL ET AL.

losses, as opposed to the tumors without losses. The molecularmechanisms underlying these correlations remain to be investi-gated in more detail. However, it is important to note that losses onchromosomes 10 and 14 may possibly be related to activation ofIGF signaling, as indicated by increased mRNA expression ofseveral members from this pathway. Activation of IGF signalingand aberrant expression of IGF, IGF receptor and IGF-bindingproteins were demonstrated in a variety of different tumor types,including meningiomas.41,42 Increased IGF2 but decreased IGF-binding protein 2 (IGFBP2) mRNA levels in atypical/anaplasticmeningiomas, compared to benign meningiomas, were reported.43

The microarray study of Watson et al.32 listed IGF2 and IGFBP3among the genes that were found to be upregulated in atypical/anaplastic meningiomas. Our data are in line with these findingsand further show that losses on chromosomes 10 and 14 wereassociated with increased expression of IGFBP3 and IGF2 tran-scripts, respectively. Taken together, these data raise the hypoth-esis that activation of IGF signaling by upregulation of IGF2and/or IGFBP3 expression is important in meningioma progres-sion. Interestingly, it was reported that IGFBP3 may potentiateIGF1 action by altering protein kinase B/AKT’s sensitivity to IGFreceptor 1 signaling.44 The higher levels of AKT3 mRNA, detectedpreferentially in meningiomas with losses on chromosome 10 or14, might further contribute to aberrant IGF pathway activation inthese tumors. However, these speculations would require confir-mation by the demonstration of phosphorylated (activated) AKTproteins in the respective meningiomas.

Increased expression of WNT pathway genes in meningiomaswith losses on chromosome 14

The dim14 shrunken centroid contained several genes that canbe related to the WNT signaling pathway, including the genes for�-catenin (CTNNB1), the regulatory subunit of cyclin-dependentkinase 5 (CDK5R1), ectodermal-neural cortex 1 (ENC1) and cyclinD1 (CCND1) (Fig. 3b). The complex of CDK5R1 and CDK5 canbind to and phosphorylate �-catenin,45 and may cause the disso-ciation of �-catenin from cadherins.46 Since �-catenin stabilizescadherin-mediated cell-cell adhesion, upregulation of CDK5R1might reduce this interaction. Interestingly, an immunohistochem-ical study has demonstrated that anaplastic meningiomas have

frequently lost E-cadherin expression.47 However, increased CT-NNB1 and CDK5R1 mRNA levels may also result in aberrantWNT pathway activity due to increased levels of cytoplasmic�-catenin, which may translocate to the nucleus, where it functionsas a transcriptional activator of a number of genes, includingENC148 and CCND1,49 both members of the dim14 centroid (Fig.3b).

In conclusion, we report that the expression of several geneslinked to cell cycle regulation and cellular proliferation is upregu-lated in atypical and anaplastic meningiomas, compared to benignmeningiomas. This finding fits well to the higher mitotic activity inatypical and anaplastic meningiomas. In addition, we demonstrateincreased expression of several members of the IGF and WNTsignaling cascades in atypical and anaplastic meningiomas withlosses on chromosome 10 or 14, suggesting that aberrations ofthese pathways may play a role in meningioma progression. How-ever, the fact that the microarrays used in our study cover less than10% of all human genes indicates that we have missed detectingmany genes that are additionally involved in meningiomas. Inaddition, the relationship between expression profiles and malig-nancy grade of meningiomas appears to be complex, most likelydue to the pronounced phenotypic heterogeneity of these neo-plasms. Thus, to identify diagnostically useful gene signatures, itwill be important to investigate the expression profiles of moregenes in larger series of tumors, preferentially from patients withavailable clinical follow-up data.

Acknowledgements

The authors thank Ms. H. Kramer for her excellent technicalassistance. Ms. R.G. Weber is greatly acknowledged for leavingher CGH data to us. This work was supported by grants from theDeutsche Forschungsgemeinschaft (SFB503, B7) to G.R., the Wil-helm Sander-Stiftung (2000.039.1) to G.R. and P.L., the MedicalFaculty of the Heinrich-Heine-University (9772182) to G.R. andthe Bundesministerium fur Bildung und Wissenschaft (NationalesGenomforschungsnetzwerk, NGFN-1, 01 GR 0101) to P.L. K.N. isa scholar of the Deutsche Jose Carreras Leukamie Stiftung e.V.(DJCLS 2001/NAT-3).

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