Meta-Mining of Neuroblastoma and Neuroblast Gene Expression

Cancer Therapy: Preclinical

Meta-mining of Neuroblastoma and Neuroblast Gene Expression Profiles Reveals Candidate Therapeutic Compounds Katleen De Preter,1 Sara De Brouwer,1 Tom Van Maerken,1 Filip Pattyn,1 Alexander Schramm,2 Angelika Eggert,2 Jo Vandesompele,1 and Frank Speleman1

Abstract Purpose: Neuroblastoma is a heterogeneous childhood tumor with poor survival outcome for the aggressive type despite intensive multimodal therapies. In this study, we aimed to identify new treatment options for neuroblastoma based on integrative genomic analysis. Experimental Design: The Connectivity Map is a database comprisingexpression profiles in response to known therapeutic compounds. This renders it a useful tool in the search for potential therapeutic compounds based on comparison of gene expression profiles of diseased cells and a database of profiles in response to known therapeutic compounds. We have used this strategy in the search for new therapeutic molecules for neuroblastoma based on data of an integrative meta-analysis of gene copy number and expression profiles from 146 primary neuroblastoma tumors and normal fetal neuroblasts. Results: In a first step, a 132-gene classifier was established that discriminates three major genomic neuroblastoma subgroups, reflecting inherent differences in gene expression between these subgroups. Subsequently, we screened the Connectivity Map database using gene lists generated by comparing expression profiles of fetal adrenal neuroblasts and the genomic subgroups of neuroblastomas. A putative therapeutic effect was predicted for several compounds of which six were empirically tested. A significant reduction in cell viability was shown for five of these molecules: 17-allylamino- geldanamycin, monorden, fluphenazine, trichostatin, and rapamycin. Conclusions: This proof-of-principle study indicates that an integrative genomic meta- analysis approach with inclusion of neuroblast data enables the identification of prom- isingcompounds for treatment of children with neuroblastoma. Further studies are warranted to explore in detail the therapeutic potential of these compounds.

Neuroblastoma is the most common extracranial solid child- One possible approach toward development of more effective hood tumor with a remarkable variation in clinical presentation and less toxic therapies is to gain insight into the biochemical ranging from favorable localized tumors that can spontaneous- pathways that are deregulated in neuroblastoma and to use this ly regress to highly metastatic disease with unfavorable out- information for the design of molecular therapies. However, at come. Despite intensive multimodal therapies, survival rates present, only three genes, MYCN, PHOX2B, and ALK, have been for aggressive neuroblastomas are still disappointingly low. directly linked to neuroblastoma pathogenesis (i.e., MYCN amplification in a subgroup of aggressive metastasizing tumors, PHOX2B germ-line mutations in a subset of familial cases and ALK Authors' Affiliations: 1Center for Medical Genetics, Ghent University in a small percentage of sporadic cases, and mutations in Hospital, Ghent, Belgium and 2Division of Hematology and Oncology, ∼12% of high-stage sporadic cases; refs. 1–5). One of the chal- University Children's Hospital Essen, Essen, Germany lenges in unraveling the altered signaling in neuroblastoma cells Received 10/17/08; revised 2/3/09; accepted 3/3/09; published OnlineFirst 5/12/09. is the genetic heterogeneity of the tumor. Genome-wide DNA The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement copy number and transcriptome analysis are now offering the in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. possibility to investigate this genetic heterogeneity in much Note: Supplementary data for this article are available at Clinical Cancer more detail. Array comparative genomic hybridization (CGH) Research Online (http://clincancerres.aacrjournals.org/). studies identified three major genetic subgroups within sporadic This article presents research results of the Belgian program of Inter- university Poles of Attraction, initiated by the Belgian State, Prime Minis- neuroblastoma cases (i.e., triploid tumors without segmental al- ter's Office, Science Policy Programming. terations, MYCN-amplified neuroblastoma with 17q gain and Requests for reprints: Katleen De Preter, Center for Medical Genetics, 1p deletion, and MYCN single-copy neuroblastoma with 11q Ghent University Hospital, Medical Research Building, 2nd Floor, Room deletion and 17q gain; refs. 6, 7). The relationship between these 120.038, De Pintelaan 185, B-9000 Ghent, Belgium. Phone: 32-9-332-5533; subgroups and gene expression profiles has thus far not been Fax: 32-9-332-6549; E-mail: [email protected]. F 2009 American Association for Cancer Research. investigated thoroughly and most expression studies aimed par- doi:10.1158/1078-0432.CCR-08-2699 ticularly at the identification of prognostic genes (8–14).

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Materials and Methods Translational Relevance Data preprocessing. Raw data (.Cel files) of four published neuro- Despite intensive multimodal therapies, survival blastoma expression microarray studies obtained from two different rates for aggressive neuroblastoma are still disap- platforms were collected and reanalyzed [i.e., hgu95av2 Affymetrix pointingly low. Therefore, there is an urgent need (11, 19) and hgu133a with (17) and without (20) preamplification]. for alternative treatment options for this type of tu- The Bioconductor repository of the statistical language R was used to mor. The presented compound screeningapproach do gcRMA normalization (21). In the next step, probe IDs of both plat- 3 is of particular interest for pediatric tumors, such forms were matched using the array comparison spreadsheet. Signifi- as neuroblastoma, because numerous obstacles ex- cance analysis of microarrays (22) was used to identify probe IDs that ist in the development of therapies for these entities are differentially expressed between hgu133a with or without preamplification as well as probe IDs that are differentially expressed between not in the least the rare occurrence of this disease. hgu133a and hgu95av2 arrays. These probe IDs were omitted for fur- Typically little or no efforts are undertaken for drug ther meta-analysis (Supplementary Data 2). development for such rare disorders due to the lim- Statistical analysis. For the construction of a prediction analysis of ited expected return. With so few people affected by microarrays (PAM) classifier, the MCRestimate Bioconductor package neuroblastoma, there is a reduced market incentive (9) was used and rank products (RP) analysis was done with the Rank- for industry-based drugdevelopment. Therefore, it is Prod Bioconductor package (23). of interest to screen a list of small-molecule com- Neuroblastoma gene server analysis and positional gene enrichment 4,5 pounds of which the majority is already approved analysis were done using in-house developed tools (24). by the Food and DrugAdministration and which do For the Connectivity Map analysis, RP lists were loaded in the Con- not need further preclinical trials to evaluate toxicity. nectivity database (build 1). In the field for up-regulated genes, the lists that are higher expressed in the neuroblasts compared with the neuroblastomas were uploaded and vice versa for the down-regulated gene field. Using the gene set enrichment analysis algorithm (25), cmap cal- Disturbance of normal differentiation pathways is an impor- culates enrichment scores for the different compounds. Compounds tant event in oncogenesis of multiple tumor types, as exempli- with significant P values (<0.1) after permutation analysis were listed fied by disruption or mutation of hematopoietic differentiation in Table 3 (in this way, only compounds from the database that were genes in leukemia and implication of the patched-hedgehog tested more than twice were included). signaling pathway in brain tumors (15, 16). The proven role Cell viability assay. Cells were seeded in duplicate in 96-well plates PHOX2B ALK (10,000 per well), incubated for 6 h to allow adherence to the surface, of and , both involved in nervous tissue differen- and then treated in duplicate for 24 and 48 h with six-point dilution tiation, in the oncogenesis of familial neuroblastoma and the series of the compounds dissolved in either ethanol [trichostatin (Sig- ALK PHOX2B occurrence of somatic and mutations in sporadic ma-Aldrich) and rapamycin (LC Laboratories)] or DMSO [17-allylami- neuroblastoma tumors indicates that future data-mining efforts no-geldanamycin (17-AAG; Sigma-Aldrich), monorden (Calbiochem), for neuroblastoma gene expression profiles should ideally also fluphenazine (Sigma-Aldrich), and colforsin (Sigma-Aldrich)]. Con- include data from the normal fetal counterpart of neuroblasto- centration ranges were according to the literature for trichostatin A ma cells, such as the adrenal neuroblasts. The limited accessibil- (0-8 μmol/L; ref. 26), rapamycin (0-25 μmol/L; ref. 27), 17-AAG (0- ity to these fetal human neuroblasts has, however, precluded 8.1 μmol/L; ref. 28), and monorden (0-5 μmol/L; ref. 29). For fluphen- μ such studies in the past. Using dedicated protocols for isolation azine, we used a concentration range of 0 to 20 mol/L, as this compound and amplification of mRNA, we have been the first to deter- was not yet used for treatment of cancer cells. Cell viability was deter- mined using the CellTiter-Glo Luminescent Cell Viability Assay (Promega) mine the expression profiles of these normal neuroblasts, pres- with untreated cells as a reference (average signals were plotted). ent as small cell clusters in fetal adrenal glands (17). These data Quantitative PCR validation. Cell lines IMR-32, NGP, CLB-GA, and strongly supported the hypothesis that the neuroblasts are the SK-N-SH were treated with 2.5 μmol/L 17-AAG and harvested at 24, 48, “neuroblastoma cells of origin” and now open the way for and 72 h after treatment. In parallel, untreated cells were harvested at more powerful data mining of the available tumor expression each time point. profiles. In a first comparative expression analysis of the normal RNA was isolated from the cells using the miRNeasy kit (Qiagen). neuroblasts versus the malignant neuroblastomas, several neu- Subsequently, 2 μg RNA from each sample was treated with RQ1 DNase I roblastoma candidate genes, including ALK, were identified. (Promega) and desalted using a Microcon-100 spin column (Milli- In this study, we investigated whether the genetic heterogene- pore). cDNA synthesis was done on the eluate with the iScript cDNA ity, reflected in the three major genetic subgroups, of neuroblas- synthesis kit (Bio-Rad). All manipulations were conducted according to the manufacturer's instructions. Reverse transcription-PCR amplifica- toma tumors is also reflected in their expression profile. For tion reactions were carried out in a 384-well plate with a total reaction each subgroup, we could identify a signature with genes differ- volume of 8 μL, containing 10 ng of template cDNA, 4 μL of 2× SYBR entially expressed between normal progenitor neuroblasts and Green I reaction mix (Eurogentec), 4 μL nuclease-free water (Sigma- malignant neuroblastomas. Instead of looking for signaling Aldrich), and 250 nmol/L of each primer. Cycling conditions were as pathways with therapeutic potential that are enriched in these follows: 10 min at 95°C followed by 45 cycles of denaturation (10 s at gene lists, we directly submitted the lists to the Connectivity 95°C) and annealing (45 s at 60°C) and elongation (1 s at 72°C). Map database (18). This public resource contains gene signa- All reactions were done on LC480 (Roche). Primers for CLCN6 tures obtained after treatment of cells with several chemical (RTPrimerDB-ID7804), CYP1B1 (ID7805), DDIT4 (ID7806), EGR3 compounds and has pattern-matching tools to detect similarities between these signatures and gene lists uploaded by the 3 Available from http://www.affymetrix.com. user. Application of this tool on the subgroup-specific signa- 4 F. Pattyn et al., in preparation. tures directly allowed the identification of new candidate ther- 5 http://medgen.ugent.be/NBGS and http://homes.esat.kuleuven.be/ apeutic small molecules for neuroblastoma. ~bioiuser/pge.

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(ID7807), and HSPA6 (ID7808) were designed and validated using cross-validation process, as these genes are likely to be the ones RTPimerDB's batch primer design tool (30–32). LC480 Cq export files with the highest predictive value (9). We used an in-house de- Plus were imported into qBase (Biogazelle; ref. 33) and normalized using veloped neuroblastoma gene server4 to compare this gene list AluSq, HMBS HPRT1 five stably expressed reference genes: (ID4), (ID5), with genes that have been reported as differentially expressed SDHA (ID7), and UBC (ID8; ref. 34). in 29 published gene expression profiling studies on neuroblastoma (total of 2,864 genes after exclusion of the published gene Results lists from the four data sets used in this study). We found that as much as 67 of the 132 PAM genes (50%) are included in neu- Genomic subgroup classification of the neuroblastoma tumors. roblastoma gene server. The finding of these genes in other neu- For the integrative meta-analysis, mRNA expression microarray roblastoma expression profiling studies strongly suggests that data of four published studies were merged (11, 17, 19, 20). these genes are genuinely deregulated in neuroblastoma. Nine Integration of genomic and transcriptomic data of the tumors were included in the Cancer Gene Census list (ALK, ATIC, CBFB, was conducted through differential expression profiling of the ETV1, GMPS, IGL@, MYCN, NTRK1, and RET), 15 are nervous neuroblastoma tumors that belonged to the different genomic system development genes (Gene Ontology: 0007399; ALCAM, subclasses. Based on (array)CGH and fluorescence insitu hy- ALK, ASCL1, CDH4, DRD2, GAL, GAP43, NRCAM, NRG1, bridization data, neuroblastoma samples of these studies were NTRK1, PMP22, PTN, SH3GL3, SLIT3, and SPOCK2), 11 are cell classified in subtype 1 (no MYCN amplification, whole 17 gain, cycle genes (Gene Ontology: 0007049; BCAT1, BUB1, CADM1, no structural aberrations), subtype 2A (11q deletion, no MYCN CCNB1, CHEK1, CKS2, DLG7, DUSP4, E2F3, KIAA0367,and amplification, 17q gain or normal 17), and subtype 2B (MYCN PTN), and 5 are apoptosis genes (Gene Ontology: 0006915; amplification, no 11q deletion, no 3p deletion, 17q gain or CADM1, KIAA0367, IL7, PMAIP1, and SCG2). normal 17) tumors. One hundred forty-six of 207 tumors Using positional gene enrichment analysis (24), we searched (70%) could be unequivocally classified in one of the three pro- for chromosomal loci that are overrepresented in the classifier totype subgroups (Table 1). The remainder could not be classi- list. Significant enrichment was found for a region on 1p36 that fied as either the genomic information was incomplete or is frequently deleted in high-stage neuroblastoma tumors missing (6 from study 2 and 20 from study 3) or a genomic (ATP6V0B, CDC42, CLCN6, CLSTN1, FUCA1, GNB1, PINK1, aberration pattern was present characteristic for more than PRDM2, PTPRF, STX12, and VPS13D; adjusted P < 0.002). one subgroup, confirming previous studies (6, 35). For this In the next step, the performance of the established PAM clas- analysis, we included only tumors unequivocally assigned to sifier was tested on the remaining 110 samples. This resulted in the subgroups defined above. an accuracy of 91% (Table 2B), which is comparable with the Gene expression classification of genomic subgroups. We first estimated accuracy of 92%. The results showed that the gene examined whether the genomic aberration pattern of neuro- classifier most easily identified subtype 2B tumors, whereas dis- blastoma tumors is reflected in their mRNA expression profile. crimination of subtype 1 and 2A tumors was more difficult. Therefore, we established a classifier aiming to distinguish neu- These data clearly show that the genomic differences in neuro- roblastoma tumors of the three different genomic subgroups. A blastoma tumors are reflected in their expression profiles and complete 10-times repeated 10-fold cross-validation (9, 36) that the classification of neuroblastoma tumors in these three was done on the merged data sets to estimate the PAM classifi- different genomic subgroups might be relevant toward the cation accuracy of the patients in one of the three subgroups. biology of neuroblastoma and must be taken into account in This estimation reflects the validity of the expression data of downstream gene expression analysis. the different studies for prediction of the genomic subgroup us- Genes differentially expressed between neuroblasts and neuro- ing a PAM classifier. Three patients of each subgroup from each blastomas from different genomic subgroups. To gain further in- study (total = 36) were used in this training step and showed sights in the genes that play a role in the genetic subgroups of that the estimated performance of classification in one of the neuroblastoma, genes were identified that are differentially ex- three subgroups using PAM is very good (accuracy of 92% = pressed in the normal neuroblasts (17) versus the neuroblasto- 33 of 36; Table 2A). ma samples of three genomic subgroups using the RP algorithm We selected 136 probes (132 unique genes) that were includ- (P < 0.05; ref. 23). More detailed information on the gene lists ed in at least 95 of the 100 predictive gene lists generated in the can be found in Supplementary Data 1. Comparison of the

Table 1. Genomic classification of 210 samples from four published studies based on (array)CGH and fluorescence in situ hybridization data

Subtype 1 Subtype 2A Subtype 2B Not classified

Study 1 (De Preter et al.)*5 6 5 1 Study 2 (Wang et al.) 43 22 16 14 (+6) Study 3 (Schramm et al.) 18 4 6 19 (+20) Study 4 (McArdle et al.) 8 10 3 1 Total 74 42 30 35 (+26)

NOTE: For 26 samples, not enough genomic information was available for classification. *In this study, also three normal neuroblast samples were profiled.

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certain compound. It is hypothesized that a similar transition Table 2. Perfomance of the PAM classifier to profile indicates a potential therapeutic effect of the compound predict genomic subgroup on neuroblastoma growth. Table 3 summarizes the significant results (permuted results with P < 0.1) for the different gene 1 predicted 2A predicted 2B predicted lists (neuroblasts versus neuroblastoma type 1, neuroblasts versus neuroblastoma type 2A, and neuroblasts versus neuroblas- A. Estimation of the performance of a PAM classifier obtained using 10-times repeated 10-fold cross-validation toma type 2B) and ranks the compounds according to the mean Subtype 1 11 1 0 enrichment score across the different signatures. In the top list, Subtype 2A 1 11 0 there was a positive enrichment for four HSP90 inhibitors, Subtype 2B 1 0 11 three histone deacetylase inhibitor compounds, and three do- B. Predicted performance of the PAM classifier in 110 test samples pamine blocking agents. For functional screening, we selected Subtype 1 58 4 0 Subtype 2A 6 24 0 representative compounds of each of these classes (with the Subtype 2B 0 0 18 most significant P values; monorden and 17-AAG, trichostatin A, and fluphenazine) as well as the compound with the highest overall enrichment score (forskolin) and rapamycin that different gene lists showed a high overlap between the lists but showed a significant enrichment for all three signatures. The also indicated that there are many subgroup-specific genes added value of our strategy in which we contrasted tumoral ex- (Fig. 1). This analysis further confirms that tumors of subgroup pression profiles characteristic of the different genomic sub- 1 and 2A share more genes (86 + 11) differentially expressed groups with the normal neuroblast profiles is clear when compared with normal neuroblasts than subgroup 1 and sub- doing cmap analysis on the list of genes that are differentially group 2B tumors (26 + 9) or subgroup 2A and subgroup 2B expressed between the neuroblasts and all neuroblastoma sam- tumors (27 + 14). ples, irrespective of their genomic subgroup. This analysis pro- Connectivity Map analysis of differentially expressed genes and vided us with only six potential therapeutic compounds (data cell viability screening of candidate therapeutics. The RP gene not shown), of which four were in common with the com- lists were analyzed using the Connectivity Map (cmap) data- pounds listed in Table 3. This is in sharp contrast to the 9, base (build 1; ref. 18). This database contains genome-wide 14, and 13 compounds that are significantly enriched in the transcriptional data from cultured human cells treated with bio- 1, 2A, and 2B signatures, respectively. active small molecules. Submission of the gene lists to cmap Viability assays on five neuroblastoma cells [CLB-GA, IMR- allows to find similarities between the transition of the malig- 32, SKNBE (2c), NGP, and SK-N-SH] showed that five of six nant neuroblastoma phenotype to the normal neuroblast phe- selected compounds have indeed an effect on neuroblastoma notype and the change of cancer cells after treatment with a cell viability (Fig. 2). As a negative control, we observed that

Table 3. Results of cmap analysis of the 1, 2A, and 2B neuroblastoma subgroup signatures

Subtype 1 Subtype 2A Subtype 2B Mean Action signature signature signature enrichment

Colforsin = forskolin*0.903 (0.0183) 0.938 (0.009) 0.837 (0.0549) 0.893 Raise levels of cyclic AMP 5248896 0.909 (0.0162) 0.85 (0.043) 0.887 (0.0286) 0.882 Unknown action Trifluoperazine 0.876 (0.0039) 0.876 Dopamine blocking agent Pyrvinium 0.87 (0.0324) 0.870 Anthelmintic Vorinostat 0.863 (0.0387) 0.863 Histone deacetylase inhibitor Blebbistatin 0.815 (0.0665) 0.852 (0.0453) 0.834 Inhibitor of myosin II 17-Dimethylamino- 0.81 (0.0728) 0.810 HSP90 inhibitor geldanamycin Fluphenazine*0.781 (0.0059) 0.81 (0.0034) 0.796 Dopamine blocking agent Calmidazolium 0.79 (0.0848) 0.779 (0.0997) 0.785 Calmodulin inhibitor Prochlorperazine 0.797 (0.0179) 0.863 (0.0052) 0.664 (0.078) 0.775 Dopamine blocking agent Deferoxamine 0.647 (0.0892) 0.647 Chelating agent Trichostatin A*0.536 (0.0012) 0.497 (0.0045) 0.778 (<0.001) 0.604 Histone deacetylase inhibitor Resveratrol 0.558 (0.0539) 0.558 Antibacterial and antifungal Sirolimus = rapamycin*0.432 (0.0336) 0.611 (0.0007) 0.598 (0.0004) 0.547 Inhibitor of the AKT/mammalian target of rapamycin pathway Geldanamycin 0.523 (0.0443) 0.523 HSP90 inhibitor Troglitazone 0.476 (0.0865) 0.476 Activates peroxisome proliferator-activated receptors, α and γ Wortmannin 0.457 (0.0478) 0.467 (0.0405) 0.462 Inhibitor of phosphoinositide 3-kinases Monorden*0.41 (0.0505) 0.410 HSP90 inhibitor 17-AAG*0.474 (0.0003) 0.288 (0.082) 0.426 (0.0017) 0.396 HSP90 inhibitor Valproic acid 0.346 (0.0181) 0.346 Histone deacetylase inhibitor

NOTE: This table only contains compounds for which significant enrichment of one of the three neuroblastoma signatures in their expression profile was found using cmap (P < 0.1). Six of these compounds (*) were selected for a cell viability screening of neuroblastoma cells. As highlighted in bold, several of these compounds have similar modes of action.

www.aacrjournals.org 3693 Clin Cancer Res 2009;15(11) June 1, 2009 Downloaded from clincancerres.aacrjournals.org on September 30, 2021. © 2009 American Association for Cancer Research. Cancer Therapy: Preclinical two compounds (iloprost and estradiol) that were not signifi- therapeutically targeted. Third, we did a unique integrative cant according to the cmap analysis had no effect on neuroblas- genomics approach. In previous integrative genomics efforts, toma cell growth (Supplementary Data 3). tumors with and without a given genomic aberrations were To check whether the compounds are indeed acting via compared (19, 20, 37, 38). Here, we focused on the global activation or repression of genes from the gene lists (used for genomic landscape of the tumors. As previously described thecmapanalysis),weselectedthetoprankinggenesfrom (6, 7), three major genomic subgroups can be recognized the cmap results, that is, the highest median ranking score (i.e., a group of tumors with only numerical aberrations; a for the different cmap treatments for one compound (i.e., 17- group of tumors with MYCN amplification, 1p deletion, and AAG). Expression of five presumed differentially regulated 17q gain; and a group characterized by 11q and 3p deletion genes (three up-regulated and two down-regulated genes) was and 17q gain). In fact, also a fourth subgroup of patients with tested using real-time quantitative reverse transcription-PCR on few or no genomic aberrations can be recognized. This last four cell lines and three time points. It was observed that four subgroup might represent tumors with few or no genomic al- of the five genes (CLCN6, DDIT4, HSPA6, and CYP1B1) show terations, such as the acute myeloid leukemias with normal the expected effect (i.e., up-regulated or down-regulated for all karyotypes that carry nucleophosmin mutations (39). These three time points) in at least one of the four cell lines (Supple- neuroblastomas might also be characterized by specific muta- mentary Data 4). tion patterns. The possibility of normal cell contamination should also be considered but is less likely, as in most studies samples with >60% of tumor cell content were used. Based on Discussion (array)CGH and fluorescence insitu hybridization results, the Despite recent advances in chemotherapeutic and transplan- tumors were classified in one of the three major genomic sub- tation options, the overall prognosis for advanced neuroblas- groups. In a first step, we were able to establish a 132-gene tomas remains very poor. For those surviving, the intensive classifier that allows to distinguish tumors that belong to treatment schemes may lead to both short-term and long-term the different genomic subgroups based on mRNA expression side effects, including risk for secondary tumors. Therefore, data, in keeping with an assumed association of specific dif- more effective and less toxic drugs are urgently needed. In this ferential gene expression profiles for each of the three major study, we aimed to identify new therapeutic compounds for genomic neuroblastoma entities. Not surprisingly, this classifi- treatment of neuroblastoma patients through an integrative er contains numerous genes that have been reported in the genomic meta-analysis and comparative expression analysis context of neuroblastoma (e.g., MYCN, NTRK1, ALK, CADM1, with normal neuroblast cells. The success of this study is and ASCL1). In the next step, the neuroblast expression profile based on three important and innovative data-mining steps. was compared with the expression profiles of neuroblastomas First, we used publicly available expression data to allow a from the different subgroups. Instead of looking at genes and more robust statistical analysis. Four published expression mi- pathways that are disrupted and might be therapeutically tar- croarray data sets generated on two different Affymetrix plat- geted, we directly submitted the differentially expressed gene forms were merged and reanalyzed (11, 17, 19, 20). In this lists to the Connectivity Map database (cmap; build 1). In this way, more than 200 neuroblastoma tumors were analyzed. way, we were able to identify agents that may have therapeutic Second, in one of the studies, the transcriptome of fetal adre- potential in neuroblastoma. We showed that only by consid- nal neuroblasts, the normal counterpart cells of the malignant ering the genomic subgroup in which the tumors belong, we neuroblastomas, was profiled (17). Inclusion of these data is could identify many more potential therapeutic compounds. of particular interest as comparison with the expression pro- The finding of different compounds with the same mode of files from the malignant tumors may lead to the identification action further supported the validity of our approach. More- of developmental pathways that are disturbed and can be over, for several of these compounds, a therapeutic activity

Fig. 1. Comparison of the gene lists obtained after RP analysis of the neuroblast samples versus the different neuroblastoma subtypes shows that there is a large overlap between the neuroblastoma type 1 (NB1) and 2A (NB2A) signatures, whereas there are less genes in common between the neuroblastoma type 1 and 2B (NB2B) and between the neuroblastoma type 2A and 2B signatures. A, number of genes that are overexpressed in the neuroblasts compared with the different neuroblastoma subtypes. B, number of genes that are overexpressed in the neuroblastoma samples of a specific subtype compared with the neuroblasts.

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Fig. 2. Cell viability assays of five compounds on five neuroblastoma cell lines show that rapamycin, 17-AAG, trichostatin A, monorden, and fluphenazine have an effect on cell viability (results at 48 h). has been reported previously. Histone deacetylase inhibitors from the list in Table 3. This small discrepancy might be (e.g., trichostatin A) were shown to have promising therapeu- due to the different statistical algorithm that is used in the tic activity for different cancer entities (40). Several studies new version to identify significantly enriched compounds. have also shown the growth-suppressive activity of these inhi- One of the top five compounds from this analysis is quinosta- bitors on neuroblastoma (41, 42). In addition, two HSP90 in- tin, which is, like rapamycin, an inhibitor of the mammalian hibitors came up from the data-mining screen, of which the target of rapamycin pathway and might be an interesting ther- 17-AAG molecule was already shown to have therapeutic po- apeutic (49, 50). Further analysis is warranted to test this com- tential in neuroblastoma (43, 44). Moreover, this compound pound in neuroblastoma. was evaluated in a phase I study on pediatric tumors (45). The presented compound screening approach is of particular Another HSP90 inhibitor and macrocyclic antifungal antibiot- interest for pediatric tumors such as neuroblastoma because nu- ic, monorden (alias radicicol), with the ability to suppress merous obstacles exist in the development of therapies for these transformation by diverse oncogenes such as Src, Ras, and entities not in the least the rare occurrence of this disease. Typ- Mos (46), was not yet tested in neuroblastoma cells. In addi- ically little or no efforts are undertaken for drug development tion, the antiproliferative or antiapoptotic activity of rapamy- for such rare disorders due to the limited expected return. With cin, an inhibitor of mammalian target of rapamycin, and so few people affected by neuroblastoma, there is a reduced phenotiazines, such as fluphenazine, has been reported for market incentive for industry-based drug development. There- neuroblastoma (27, 47, 48). To evaluate invitro therapeutic fore,itisofinteresttoscreenalistofsmall-moleculecom- potential of the selected compounds, six of the strongest can- pounds of which the majority is already approved by the didate compounds were tested by assessing the viability of Food and Drugs Administration and which do not need further neuroblastoma cells on treatment. This analysis revealed that preclinical trials to evaluate toxicity. five of these compounds effectively reduced neuroblastoma cell viability using concentrations in the low micromolar Disclosure of Potential Conflicts of Interest range, suggesting that our approach provides a rational means for prioritization of small-molecule compounds for preclinical No potential conflicts of interest were disclosed. evaluation. Recently, cmap build 2 was released containing 6,100 expres- Acknowledgments sion profiles from 1,309 bioactive small molecules (only 164 compounds in the first build of cmap). Reanalysis of our We thank Nurten Yigit for technical assistance with cell culturing and gene lists in the new build leads to the identification of other reverse transcription-PCR analysis. European Community under the FP6 (project: STREP: EET-pipeline, promising compounds with therapeutic potential in neuro- number: 037260), “Kinderkankerfonds,”“StichtingtegenKanker, ” Fund blastoma (data not shown). Using the same criteria, 160 poten- for Scientific Research, and BOF. K. De Preter and T. Van Maerken are tially interesting compounds were identified, including 17 of 20 supported by the Fund for Scientific Research.

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Katleen De Preter, Sara De Brouwer, Tom Van Maerken, et al.

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