Measurable impact of RNA quality on gene expression results from quantitative PCR.

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5'-3' difference in quantification cycle (Cq) and HPRT1 3' Cq value based on a 5'/3' ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality.

The microRNA body map: dissecting microRNA function through integrative genomics.

While a growing body of evidence implicates regulatory miRNA modules in various aspects of human disease and development, insights into specific miRNA function remain limited. Here, we present an innovative approach to elucidate tissue-specific miRNA functions that goes beyond miRNA target prediction and expression correlation. This approach is based on a multi-level integration of corresponding miRNA and mRNA gene expression levels, miRNA target prediction, transcription factor target prediction and mechanistic models of gene network regulation. Predicted miRNA functions were either validated experimentally or compared to published data. The predicted miRNA functions are accessible in the miRNA bodymap, an interactive online compendium and mining tool of high-dimensional newly generated and published miRNA expression profiles. The miRNA bodymap enables prioritization of candidate miRNAs based on their expression pattern or functional annotation across tissue or disease subgroup. The miRNA bodymap project provides users with a single one-stop data-mining solution and has great potential to become a community resource.

A 6-gene signature identifies four molecular subgroups of neuroblastoma.

BACKGROUND: There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. RESULTS: The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). CONCLUSIONS: Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.

External oligonucleotide standards enable cross laboratory comparison and exchange of real-time quantitative PCR data.

The quantitative polymerase chain reaction (qPCR) is widely utilized for gene expression analysis. However, the lack of robust strategies for cross laboratory data comparison hinders the ability to collaborate or perform large multicentre studies conducted at different sites. In this study we introduced and validated a workflow that employs universally applicable, quantifiable external oligonucleotide standards to address this question. Using the proposed standards and data-analysis procedure, we obtained a perfect concordance between expression values from eight different genes in 366 patient samples measured on three different qPCR instruments and matching software, reagents, plates and seals, demonstrating the power of this strategy to detect and correct inter-run variation and to enable exchange of data between different laboratories, even when not using the same qPCR platform.

Accurate prediction of neuroblastoma outcome based on miRNA expression profiles.

For neuroblastoma, the most common extracranial tumour of childhood, identification of new biomarkers and potential therapeutic targets is mandatory to improve risk stratification and survival rates. MicroRNAs are deregulated in most cancers, including neuroblastoma. In this study, we analysed 430 miRNAs in 69 neuroblastomas by stem-loop RT-qPCR. Prediction of event-free survival (EFS) with support vector machines (SVM) and actual survival times with Cox regression-based models (CASPAR) were highly accurate and were independently validated. SVM-accuracy for prediction of EFS was 88.7% (95% CI: 88.5-88.8%). For CASPAR-based predictions, 5y-EFS probability was 0.19% (95% CI: 0-38%) in the CASPAR-predicted short survival group compared with 0.78% (95%CI: 64-93%) in the CASPAR-predicted long survival group. Both classifiers were validated on an independent test set yielding accuracies of 94.74% (SVM) and 5y-EFS probabilities as 0.25 (95% CI: 0.0-0.55) for short versus 1 ± 0.0 for long survival (CASPAR), respectively. Amplification of the MYCN oncogene was highly correlated with deregulation of miRNA expression. In addition, 37 miRNAs correlated with TrkA expression, a marker of excellent outcome, and 6 miRNAs further analysed in vitro were regulated upon TrkA transfection, suggesting a functional relationship. Expression of the most significant TrkA-correlated miRNA, miR-542-5p, also discriminated between local and metastatic disease and was inversely correlated with MYCN amplification and event-free survival. We conclude that neuroblastoma patient outcome prediction using miRNA expression is feasible and effective. Studies testing miRNA-based predictors in comparison to and in combination with mRNA and aCGH information should be initiated. Specific miRNAs (e.g., miR-542-5p) might be important in neuroblastoma tumour biology, and qualify as potential therapeutic targets.

Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study.

BACKGROUND: More accurate prognostic assessment of patients with neuroblastoma is required to better inform the choice of risk-related therapy. The aim of this study is to develop and validate a gene-expression signature to improve outcome prediction. METHODS: 59 genes were selected using an innovative data-mining strategy, and were profiled in the largest neuroblastoma patient series (n=579) to date using real-time quantitative PCR starting from only 20 ng of RNA. A multigene-expression signature was built using 30 training samples, tested on 313 test samples, and subsequently validated in a blind study on an independent set of 236 tumours. FINDINGS: The signature has a performance, sensitivity, and specificity of 85.4% (95% CI 77.7-93.2), 84.4% (66.5-94.1), and 86.5% (81.1-90.6), respectively, to predict patient outcome. Multivariate analysis indicates that the signature is a significant independent predictor of overall survival and progression-free survival after controlling for currently used risk factors: patients with high molecular risk have a higher risk of death from disease and higher risk of relapse or progression than patients with low molecular risk (odds ratio 19.32 [95% CI 6.50-57.43] and 3.96 [1.97-7.97] for overall survival and progression-free survival, respectively, both p<0.0001). Patients at an increased risk of an adverse outcome can also be identified in the current treatment groups, showing the potential of this signature for improved clinical management. These results were confirmed in the validation study, in which the signature was also independently statistically significant in a model adjusted for MYCN status, age, International Neuroblastoma Staging System stage, ploidy, International Neuroblastoma Pathology Classification grade of differentiation, and mitosis karyorrhexis index (odds ratios between 4.81 and 10.53 depending on the model for overall survival and 3.68 [95% CI 2.01-6.71] for progression-free survival). INTERPRETATION: The 59-gene expression signature is an accurate predictor of outcome in patients with neuroblastoma. The signature is an independent risk predictor, identifying patients with an increased risk of poor outcome in the current clinical-risk groups. The method and signature is suitable for routine laboratory testing, and should be evaluated in prospective studies. FUNDING: The Belgian Foundation Against Cancer, the Children Cancer Fund Ghent, the Belgian Society of Paediatric Haematology and Oncology, the Belgian Kid's Fund and the Fondation Nuovo-Soldati (JV), the Fund for Scientific Research Flanders (KDP, JH), the Fund for Scientific Research Flanders, the Institute for the Promotion of Innovation by Science and Technology in Flanders, Strategisch basisonderzoek, the Fondation Fournier Majoie pour l'Innovation, the Instituto Carlos III, the Italian Neuroblastoma Foundation, the European Community under the FP6, and the Belgian programme of Interuniversity Poles of Attraction.

Circulating microRNA biomarkers for metastatic disease in neuroblastoma patients.

In this study, the circulating miRNome from diagnostic neuroblastoma serum was assessed for identification of noninvasive biomarkers with potential in monitoring metastatic disease. After determining the circulating neuroblastoma miRNome, 743 miRNAs were screened in 2 independent cohorts of 131 and 54 patients. Evaluation of serum miRNA variance in a model testing for tumor stage, MYCN status, age at diagnosis, and overall survival revealed tumor stage as the most significant factor impacting miRNA abundance in neuroblastoma serum. Differential abundance analysis between patients with metastatic and localized disease revealed 9 miRNAs strongly associated with metastatic stage 4 disease in both patient cohorts. Increasing levels of these miRNAs were also observed in serum from xenografted mice bearing human neuroblastoma tumors. Moreover, murine serum miRNA levels were strongly associated with tumor volume. These findings were validated in longitudinal serum samples from metastatic neuroblastoma patients, where the 9 miRNAs were associated with disease burden and treatment response.

Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers.

BACKGROUND: Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers. RESULTS: To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2'-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival. CONCLUSIONS: This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.

miRNA expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples.

PURPOSE: More accurate assessment of prognosis is important to further improve the choice of risk-related therapy in neuroblastoma (NB) patients. In this study, we aimed to establish and validate a prognostic miRNA signature for children with NB and tested it in both fresh frozen and archived formalin-fixed paraffin-embedded (FFPE) samples. EXPERIMENTAL DESIGN: Four hundred-thirty human mature miRNAs were profiled in two patient subgroups with maximally divergent clinical courses. Univariate logistic regression analysis was used to select miRNAs correlating with NB patient survival. A 25-miRNA gene signature was built using 51 training samples, tested on 179 test samples, and validated on an independent set of 304 fresh frozen tumor samples and 75 archived FFPE samples. RESULTS: The 25-miRNA signature significantly discriminates the test patients with respect to progression-free and overall survival (P < 0.0001), both in the overall population and in the cohort of high-risk patients. Multivariate analysis indicates that the miRNA signature is an independent predictor of patient survival after controlling for current risk factors. The results were confirmed in an external validation set. In contrast to a previously published mRNA classifier, the 25-miRNA signature was found to be predictive for patient survival in a set of 75 FFPE neuroblastoma samples. CONCLUSIONS: In this study, we present the largest NB miRNA expression study so far, including more than 500 NB patients. We established and validated a robust miRNA classifier, able to identify a cohort of high-risk NB patients at greater risk for adverse outcome using both fresh frozen and archived material.

Predicting outcomes for children with neuroblastoma.

One of the main challenges in clinical cancer research remains to be accurate outcome prediction at the time of diagnosis. Although not frequent in absolute terms, neuroblastoma represents an important clinical challenge, as it is fatal in almost half of the patients despite advances in multimodal anti-cancer therapies. Four major risk stratification systems for neuroblastoma patients are currently being used in various parts of the world. Systems are based on a combination of various clinical, histopathological, and biological factors. Accordingly, different therapeutic schemes exist ranging from wait-and-see approaches to intensive multimodal therapies. Clinical experience with the currently used risk stratification systems suggests that the stratification of patients for treatment is useful, but patients with the same clinico-pathological parameters, receiving the same treatment, can have markedly different clinical courses. Therefore, the challenge remains to identify additional tumor-specific and sensitive prognostic markers for improved risk estimation at the time of diagnosis and to improve the choice of risk-related therapy. Various studies have put forward new prognostic markers, including copy number aberrations, gene expression signatures, and epigenetic markers.

Accurate outcome prediction in neuroblastoma across independent data sets using a multigene signature.

PURPOSE: Reliable prognostic stratification remains a challenge for cancer patients, especially for diseases with variable clinical course such as neuroblastoma. Although numerous studies have shown that outcome might be predicted using gene expression signatures, independent cross-platform validation is often lacking. EXPERIMENTAL DESIGN: Using eight independent studies comprising 933 neuroblastoma patients, a prognostic gene expression classifier was developed, trained, tested, and validated. The classifier was established based on reanalysis of four published studies with updated clinical information, reannotation of the probe sequences, common risk definition for training cases, and a single method for gene selection (prediction analysis of microarray) and classification (correlation analysis). RESULTS: Based on 250 training samples from four published microarray data sets, a correlation signature was built using 42 robust prognostic genes. The resulting classifier was validated on 351 patients from four independent and unpublished data sets and on 129 remaining test samples from the published studies. Patients with divergent outcome in the total cohort, as well as in the different risk groups, were accurately classified (log-rank P < 0.001 for overall and progression-free survival in the four independent data sets). Moreover, the 42-gene classifier was shown to be an independent predictor for survival (odds ratio, >5). CONCLUSION: The strength of this 42-gene classifier is its small number of genes and its cross-platform validity in which it outperforms other published prognostic signatures. The robustness and accuracy of the classifier enables prospective assessment of neuroblastoma patient outcome. Most importantly, this gene selection procedure might be an example for development and validation of robust gene expression signatures in other cancer entities.

Meta-analysis of neuroblastomas reveals a skewed ALK mutation spectrum in tumors with MYCN amplification.

PURPOSE: Activating mutations of the anaplastic lymphoma kinase (ALK) were recently described in neuroblastoma. We carried out a meta-analysis of 709 neuroblastoma tumors to determine their frequency and mutation spectrum in relation to genomic and clinical parameters, and studied the prognostic significance of ALK copy number and expression. EXPERIMENTAL DESIGN: The frequency and type of ALK mutations, copy number gain, and expression were analyzed in a new series of 254 neuroblastoma tumors. Data from 455 published cases were used for further in-depth analysis. RESULTS: ALK mutations were present in 6.9% of 709 investigated tumors, and mutations were found in similar frequencies in favorable [International Neuroblastoma Staging System (INSS) 1, 2, and 4S; 5.7%] and unfavorable (INSS 3 and 4; 7.5%) neuroblastomas (P = 0.087). Two hotspot mutations, at positions R1275 and F1174, were observed (49% and 34.7% of the mutated cases, respectively). Interestingly, the F1174 mutations occurred in a high proportion of MYCN-amplified cases (P = 0.001), and this combined occurrence was associated with a particular poor outcome, suggesting a positive cooperative effect between both aberrations. Furthermore, the F1174L mutant was characterized by a higher degree of autophosphorylation and a more potent transforming capacity as compared with the R1275Q mutant. Chromosome 2p gains, including the ALK locus (91.8%), were associated with a significantly increased ALK expression, which was also correlated with poor survival. CONCLUSIONS: ALK mutations occur in equal frequencies across all genomic subtypes, but F1174L mutants are observed in a higher frequency of MYCN-amplified tumors and show increased transforming capacity as compared with the R1275Q mutants.

Prognostic impact of gene expression-based classification for neuroblastoma.

PURPOSE: To evaluate the impact of a predefined gene expression-based classifier for clinical risk estimation and cytotoxic treatment decision making in neuroblastoma patients. PATIENTS AND METHODS: Gene expression profiles of 440 internationally collected neuroblastoma specimens were investigated by microarray analysis, 125 of which were examined prospectively. Patients were classified as either favorable or unfavorable by a 144-gene prediction analysis for microarrays (PAM) classifier established previously on a separate set of 77 patients. PAM classification results were compared with those of current prognostic markers and risk estimation strategies. RESULTS: The PAM classifier reliably distinguished patients with contrasting clinical courses (favorable [n = 249] and unfavorable [n = 191]; 5-year event free survival [EFS] 0.84 +/- 0.03 v 0.38 +/- 0.04; 5-year overall survival [OS] 0.98 +/- 0.01 v 0.56 +/- 0.05, respectively; both P < .001). Moreover, patients with divergent outcome were robustly discriminated in both German and international cohorts and in prospectively analyzed samples (P

Aberrant methylation of candidate tumor suppressor genes in neuroblastoma.

CpG island hypermethylation has been recognized as an alternative mechanism for tumor suppressor gene inactivation. In this study, we performed methylation-specific PCR (MSP) to investigate the methylation status of 10 selected tumor suppressor genes in neuroblastoma. Seven of the investigated genes (CD44, RASSF1A, CASP8, PTEN, ZMYND10, CDH1, PRDM2) showed high frequencies (> or =30%) of methylation in 33 neuroblastoma cell lines. In 42 primary neuroblastoma tumors, the frequencies of methylation were 69%, CD44; 71%, RASSF1A; 56%, CASP8; 25%, PTEN; 15%, ZMYND10; 8%, CDH1; and 0%, PRDM2. Furthermore, CASP8 and CDH1 hypermethylation was significantly associated with poor event-free survival. Meta-analysis of 115 neuroblastoma tumors demonstrated a significant correlation between CASP8 methylation and MYCN amplification. In addition, there was a correlation between ZMYND10 methylation and MYCN amplification. The MSP data, together with optimized mRNA re-expression experiments (in terms of concentration and time of treatment and use of proper reference genes) further strengthen the notion that epigenetic alterations could play a significant role in NB oncogenesis. This study thus warrants the need for a global profiling of gene promoter hypermethylation to identify genome-wide aberrantly methylated genes in order to further understand neuroblastoma pathogenesis and to identify prognostic methylation markers.

The emerging molecular pathogenesis of neuroblastoma: implications for improved risk assessment and targeted therapy.

Neuroblastoma is one of the most common solid tumors of childhood, arising from immature sympathetic nervous system cells. The clinical course of patients with neuroblastoma is highly variable, ranging from spontaneous regression to widespread metastatic disease. Although the outcome for children with cancer has improved considerably during the past decades, the prognosis of children with aggressive neuroblastoma remains dismal. The clinical heterogeneity of neuroblastoma mirrors the biological and genetic heterogeneity of these tumors. Ploidy and MYCN amplification have been used as genetic markers for risk stratification and therapeutic decision making, and, more recently, gene expression profiling and genome-wide DNA copy number analysis have come into the picture as sensitive and specific tools for assessing prognosis. The applica tion of new genetic tools also led to the discovery of an important familial neuroblastoma cancer gene, ALK, which is mutated in approximately 8% of sporadic tumors, and genome-wide association studies have unveiled loci with risk alleles for neuroblastoma development. For some of the genomic regions that are deleted in some neuroblastomas, on 1p, 3p and 11q, candidate tumor suppressor genes have been identified. In addition, evidence has emerged for the contribution of epigenetic disturbances in neuroblastoma oncogenesis. As in other cancer entities, altered microRNA expression is also being recognized as an important player in neuroblastoma. The recent successes in unraveling the genetic basis of neuroblastoma are now opening opportunities for development of targeted therapies.

RNA pre-amplification enables large-scale RT-qPCR gene-expression studies on limiting sample amounts.

BACKGROUND: The quantitative polymerase chain reaction (qPCR) is a widely utilized method for gene-expression analysis. However, insufficient material often compromises large-scale gene-expression studies. The aim of this study is to evaluate an RNA pre-amplification method to produce micrograms of cDNA as input for qPCR. FINDINGS: The linear isothermal Ribo-SPIA pre-amplification method (WT-Ovation; NuGEN) was first evaluated by measuring the expression of 20 genes in RNA samples from six neuroblastoma cell lines and of 194 genes in two commercially available reference RNA samples before and after pre-amplification, and subsequently applied on a large panel of 738 RNA samples extracted from neuroblastoma tumours. All RNA samples were evaluated for RNA integrity and purity. Starting from 5 to 50 nanograms of total RNA the sample pre-amplification method was applied, generating approximately 5 microgams of cDNA, sufficient to measure more than 1000 target genes. The results obtained from this study show a constant yield of pre-amplified cDNA independent of the amount of input RNA; preservation of differential gene-expression after pre-amplification without introduction of substantial bias; no co-amplification of contaminating genomic DNA; no necessity to purify the pre-amplified material; and finally the importance of good RNA quality to enable pre-amplification. CONCLUSION: Application of this unbiased and easy to use sample pre-amplification technology offers great advantage to generate sufficient material for diagnostic and prognostic work-up and enables large-scale qPCR gene-expression studies using limited amounts of sample material.

Overall genomic pattern is a predictor of outcome in neuroblastoma.

PURPOSE: For a comprehensive overview of the genetic alterations of neuroblastoma, their association and clinical significance, we conducted a whole-genome DNA copy number analysis. PATIENTS AND METHODS: A series of 493 neuroblastoma (NB) samples was investigated by array-based comparative genomic hybridization in two consecutive steps (224, then 269 patients). RESULTS: Genomic analysis identified several types of profiles. Tumors presenting exclusively whole-chromosome copy number variations were associated with excellent survival. No disease-related death was observed in this group. In contrast, tumors with any type of segmental chromosome alterations characterized patients with a high risk of relapse. Patients with both numerical and segmental abnormalities clearly shared the higher risk of relapse of segmental-only patients. In a multivariate analysis, taking into account the genomic profile, but also previously described individual genetic and clinical markers with prognostic significance, the presence of segmental alterations with (HR, 7.3; 95% CI, 3.7 to 14.5; P < .001) or without MYCN amplification (HR, 4.5; 95% CI, 2.4 to 8.4; P < .001) was the strongest predictor of relapse; the other significant variables were age older than 18 months (HR, 1.8; 95% CI, 1.2 to 2.8; P = .004) and stage 4 (HR, 1.8; 95% CI, 1.2 to 2.7; P = .005). Finally, within tumors showing segmental alterations, stage 4, age, MYCN amplification, 1p and 11q deletions, and 1q gain were independent predictors of decreased overall survival. CONCLUSION: The analysis of the overall genomic pattern, which probably unravels particular genomic instability mechanisms rather than the analysis of individual markers, is essential to predict relapse in NB patients. It adds critical prognostic information to conventional markers and should be included in future treatment stratification.

ArrayCGH-based classification of neuroblastoma into genomic subgroups.

High-resolution array comparative genomic hybridization (arrayCGH) profiling was performed on 75 primary tumors and 29 cell lines to gain further insight into the genetic heterogeneity of neuroblastoma and to refine genomic subclassification. Using a novel data-mining strategy, three major and two minor genomic subclasses were delineated. Eighty-three percent of tumors could be assigned to the three major genomic subclasses, corresponding to the three known clinically and biologically relevant subsets in neuroblastoma. The remaining subclasses represented (1) tumors with no/few copy number alterations or an atypical pattern of aberrations and (2) tumors with 11q13 amplification. Inspection of individual arrayCGH profiles showed that recurrent genomic imbalances were not exclusively associated with a specific subclass. Of particular notice were tumors with numerical imbalances typically observed in subtype 1 neuroblastoma, in association with genomic features of subtype 2A or 2B. A search for prognostically relevant genomic alterations disclosed 1q gain as a predictive marker for therapy failure within the group of subtype 2A and 2B tumors. In cell lines, a high incidence of 6q loss was observed, with a 3.87-5.32 Mb region of common loss within 6q25.1-6q25.2. Our study clearly illustrates the importance of genomic profiling in relation to tumor behavior in neuroblastoma. We propose that genome-wide assessment of copy number alterations should ideally be included in the genetic workup of neuroblastoma. Further multicentric studies on large tumor series are warranted in order to improve therapeutic stratification in conjunction with other features such as age at diagnosis, tumor stage, and gene expression signatures.

Small-molecule MDM2 antagonists as a new therapy concept for neuroblastoma.

Circumvention of the p53 tumor suppressor barrier in neuroblastoma is rarely caused by TP53 mutation but might arise from inappropriately increased activity of its principal negative regulator MDM2. We show here that targeted disruption of the p53-MDM2 interaction by the small-molecule MDM2 antagonist nutlin-3 stabilizes p53 and selectively activates the p53 pathway in neuroblastoma cells with wild-type p53, resulting in a pronounced antiproliferative and cytotoxic effect through induction of G(1) cell cycle arrest and apoptosis. A nutlin-3 response was observed regardless of MYCN amplification status. Remarkably, surviving SK-N-SH cells adopted a senescence-like phenotype, whereas CLB-GA and NGP cells underwent neuronal differentiation. p53 dependence of these alternative outcomes of nutlin-3 treatment was evidenced by abrogation of the effects when p53 was knocked down by lentiviral-mediated short hairpin RNA interference. The diversity of cellular responses reveals pleiotropic mechanisms of nutlins to disable neuroblastoma cells and exemplifies the feasibility of exploiting, by a single targeted intervention, the multiplicity of anticancer activities exerted by a key tumor suppressor as p53. The observed treatment effects without the need of imposing a genotoxic burden suggest that selective MDM2 antagonists might be beneficial for treatment of neuroblastoma patients with and without MYCN amplification.