Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment

Identification of MYCN non-amplified neuroblastoma subgroups points towards molecular signatures for precision prognosis and therapy stratification

BACKGROUND

Despite the extensive study of MYCN-amplified neuroblastomas, there is a significant unmet clinical need in MYCN non-amplified cases. In particular, the extent of heterogeneity within the MYCN non-amplified population is unknown.

METHODS

A total of 1566 samples from 16 datasets were identified in Gene Expression Omnibus (GEO) and ArrayExpress. Characterisation of the subtypes was analysed by ConsensusClusterPlus. Independent predictors for subgrouping were constructed from the single sample predictor based on the multiclassPairs package. Findings were verified using immunohistochemistry and CIBERSORTx analysis.

RESULTS

We demonstrate that MYCN non-amplified neuroblastomas are heterogeneous and can be classified into 3 subgroups based on their transcriptional signatures. Within these groups, subgroup_2 has the worst prognosis and this group shows a 'MYCN' signature that is potentially induced by the overexpression of Aurora Kinase A (AURKA); whilst subgroup_3 is characterised by an 'inflamed' gene signature. The clinical implications of this subtype classification are significant, as each subtype demonstrates a unique prognosis and vulnerability to investigational therapies. A total of 420 genes were identified as independent subgroup predictors with average balanced accuracy of 0.93 and 0.84 for train and test datasets, respectively.

CONCLUSION

We propose that transcriptional subtyping may enhance precision prognosis and therapy stratification for patients with MYCN non-amplified neuroblastomas.

PPARβ/δ-ANGPTL4 axis mediates the promotion of mono-2-ethylhexyl phthalic acid on MYCN-amplified neuroblastoma development

Di-2-ethylhexyl phthalic acid (DEHP) is one of the most widely used plasticizers in the industry, which can improve the flexibility and durability of plastics. It is prone to migrate from various daily plastic products through wear and leaching into the surrounding environment and decompose into the more toxic metabolite mono-2-ethylhexyl phthalic acid (MEHP) after entering the human body. However, the impacts and mechanisms of MEHP on neuroblastoma are unclear. We exposed MYCN-amplified neuroblastoma SK-N-BE(2)C cells to an environmentally related concentration of MEHP and found that MEHP increased the proliferation and migration ability of tumor cells. The peroxisome proliferator-activated receptor (PPAR) β/δ pathway was identified as a pivotal signaling pathway in neuroblastoma, mediating the effects of MEHP through transcriptional sequencing analysis. Because MEHP can bind to the PPARβ/δ protein and initiate the expression of the downstream gene angiopoietin-like 4 (ANGPTL4), the PPARβ/δ-specific agonist GW501516 and antagonist GSK3787, the recombinant human ANGPTL4 protein, and the knockdown of gene expression confirmed the regulation of the PPARβ/δ-ANGPTL4 axis on the malignant phenotype of neuroblastoma. Based on the critical role of PPARβ/δ and ANGPTL4 in the metabolic process, a non-targeted metabolomics analysis revealed that MEHP altered multiple metabolic pathways, particularly lipid metabolites involving fatty acyls, glycerophospholipids, and sterol lipids, which may also be potential factors promoting tumor progression. We have demonstrated for the first time that MEHP can target binding to PPARβ/δ and affect the progression of neuroblastoma by activating the PPARβ/δ-ANGPTL4 axis. This mechanism confirms the health risks of plasticizers as tumor promoters and provides new data support for targeted prevention and treatment of neuroblastoma.

Identification of a novel gene signature for neuroblastoma differentiation using a Boolean implication network

Although induction of differentiation represents an effective strategy for neuroblastoma treatment, the mechanisms underlying neuroblastoma differentiation are poorly understood. We generated a computational model of neuroblastoma differentiation consisting of interconnected gene clusters identified based on symmetric and asymmetric gene expression relationships. We identified a differentiation signature consisting of series of gene clusters comprised of 1251 independent genes that predicted neuroblastoma differentiation in independent datasets and in neuroblastoma cell lines treated with agents known to induce differentiation. This differentiation signature was associated with patient outcomes in multiple independent patient cohorts and validated the role of MYCN expression as a marker of neuroblastoma differentiation. Our results further identified novel genes associated with MYCN via asymmetric Boolean implication relationships that would not have been identified using symmetric computational approaches and that were associated with both neuroblastoma differentiation and patient outcomes. Our differentiation signature included a cluster of genes involved in intracellular signaling and growth factor receptor trafficking pathways that is strongly associated with neuroblastoma differentiation, and we validated the associations of UBE4B, a gene within this cluster, with neuroblastoma cell and tumor differentiation. Our findings demonstrate that Boolean network analyses of symmetric and asymmetric gene expression relationships can identify novel genes and pathways relevant for neuroblastoma tumor differentiation that could represent potential therapeutic targets.

Comparative epigenomics by machine learning approach for neuroblastoma

BACKGROUND

Neuroblastoma (NB) is the second most common pediatric solid tumor. Because the number of genetic mutations found in tumors are small, even in some patients with unfavorable NB, epigenetic variation is expected to play an important role in NB progression. DNA methylation is a major epigenetic mechanism, and its relationship with NB prognosis has been a concern. One limitation with the analysis of variation in DNA methylation is the lack of a suitable analytical model. Therefore, in this study, we performed a random forest (RF) analysis of the DNA methylome data of NB from multiple databases.

RESULTS

RF is a popular machine learning model owing to its simplicity, intuitiveness, and computational cost. RF analysis identified novel intermediate-risk patient groups with characteristic DNA methylation patterns within the low-risk group. Feature selection analysis based on probe annotation revealed that enhancer-annotated regions had strong predictive power, particularly for MYCN-amplified NBs. We developed a gene-based analytical model to identify candidate genes related to disease progression, such as PRDM8 and FAM13A-AS1. RF analysis revealed sufficient predictive power compared to other machine learning models.

CONCLUSIONS

RF is a useful tool for DNA methylome analysis in cancer epigenetic studies, and has potential to identify a novel cancer-related genes.

Characterization of m6A-related lncRNA signature in neuroblastoma

N6-methyladenosine (m6A) constitutes one of the most common modifications in mRNA, rRNA, tRNA, microRNA, and long-chain noncoding RNA. The influence of modifications of m6A on the stability of RNA depends upon the expression of methyltransferase ("writer") and demethylase ("eraser") and m6A binding protein ("reader"). In this study, we identified a set of m6A-related lncRNA expression profiles in neuroblastoma (NBL) based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program. Thereupon, we identified two subgroups of neuroblastoma (high-risk group and low-risk group) by applying consensus clustering to m6A RNA methylation regulators ("Readers,", "Writer," and "Erase"). Relative to the low-risk group, the high-risk group correlates with a poorer prognosis. Moreover, the present study also revealed that the high-risk group proves to be significantly positively enriched in the tumor-related signaling pathways, including the P53 signaling pathway, cell cycle, and DNA repair. This finding indicates that these molecular prognostic markers may also be potentially valuable in early diagnosis, which provides a new research direction for the study of molecular mechanisms underlying the development of NBL. In conclusion, this study constructed a new model of NBL prognosis based on m6a-associated lncRNAs. Ultimately, this model is helpful for stratification of prognosis and development of treatment strategies.

Advanced Minimal Residual Disease Monitoring for Acute Lymphoblastic Leukemia with Multiplex Mediator Probe PCR

Acute lymphoblastic leukemia (ALL) is the most frequent malignancy in childhood. Minimal residual disease (MRD) monitoring is an important prognostic factor for treatment response and patient stratification. It uses personalized real-time PCR to measure the amount of cancer cells among normal cells. Due to clonal tumor evolution or secondary rearrangement processes, MRD markers can disappear during treatment, leading to false-negative MRD results and wrong decision-making in personalized treatments. Therefore, monitoring of multiple MRD markers per patient is required. For the first time, the authors present personalized multiplex mediator probe PCR (MP PCR) for MRD monitoring in ALL. These assays can precisely quantify more MRD markers in less sample material. Therefore, clinical outcomes will be less affected by clonal tumor evolution. Personalized duplex MP PCR assays were developed for different genomic MRD markers, including immunoglobulin/T-cell receptor gene rearrangements, gene fusions, and gene deletions. One duplex assay was successfully applied in a prospective patient case and compared with hydrolysis probes. Moreover, the authors increased the multiplex level from duplex to 4-plex and still met the EuroMRD requirements for reliable quantification. In addition, the authors' MRD-MP design guidelines and multiplex workflow facilitate and accelerate MP PCR assay development. This helps the standardization of personal diagnostics.

Establishment and Validation of a Prognostic Immune Signature in Neuroblastoma

BACKGROUND

Neuroblastoma (NBL) is the most common extracranial solid tumor in childhood, and patients with high-risk neuroblastoma had a relatively poor prognosis despite multimodal treatment. To improve immunotherapy efficacy in neuroblastoma, systematic profiling of the immune landscape in neuroblastoma is an urgent need.

METHODS

RNA-seq and according clinical information of neuroblastoma were downloaded from the TARGET database and GEO database (GSE62564). With an immune-related-gene set obtained from the ImmPort database, Immune-related Prognostic Gene Pairs for Neuroblastoma (IPGPN) for overall survival (OS) were established with the TARGET-NBL cohort and then verified with the GEO-NBL cohort. Immune cell infiltration analysis was subsequently performed. The integrated model was established with IPGPN and clinicopathological parameters. Immune cell infiltration was analyzed with the XCELL algorithm. Functional enrichment analysis was performed with clusterProfiler package in R.

RESULTS

Immune-related Prognostic Gene Pairs for Neuroblastoma was successfully established with seven immune-related gene pairs (IGPs) involving 13 unique genes in the training cohort. In the training cohort, IPGPN successfully stratified neuroblastoma patients into a high and low immune-risk groups with different OS (HR=3.92, P = 2 × 10^-8) and event-free survival (HR=3.66, P=2 × 10^-8). ROC curve analysis confirmed its predictive power. Consistently, high IPGPN also predicted worse OS (HR=1.84, P = .002) and EFS in validation cohort (HR=1.38, P = .06) Moreover, higher activated dendritic cells, M1 macrophage, Th1 CD4⁺, and Th2 CD4⁺ T cell enrichment were evident in low immune-risk group. Further integrating IPGPN with age and stage demonstrated improved predictive performance than IPGPN alone.

CONCLUSION

Herein, we presented an immune landscape with IPGPN for prognosis prediction in neuroblastoma, which complements the present understanding of the immune signature in neuroblastoma.

FOXR2 Stabilizes MYCN Protein and Identifies Non-MYCN-Amplified Neuroblastoma Patients With Unfavorable Outcome

Clinical outcomes of patients with neuroblastoma range from spontaneous tumor regression to fatality. Hence, understanding the mechanisms that cause tumor progression is crucial for the treatment of patients. In this study, we show that FOXR2 activation identifies a subset of neuroblastoma tumors with unfavorable outcome and we investigate the mechanism how FOXR2 relates to poor outcome in patients.

Neuroblastoma: the association of anatomical tumour site, molecular biology and patient outcomes

BACKGROUND

Numerous factors have been identified as carrying prognostic value in neuroblastoma (NB) and therefore incorporated in risk stratification of disease. Here, we investigate the association of anatomical site of NB with molecular biology and clinical outcomes.

METHODS

A total of 117 patients with NB were studied over a 30-year period. Tumour location was confirmed with computed tomography/magnetic resonance imaging. Data on molecular biology were obtained as testing became available. Chi-squared, Fisher's exact test and Kaplan-Meier log-rank tests were used for statistical analysis.

RESULTS

Tumour originated in the thoracic region (thoracic NB, TNB) in 15 patients (13%), adrenal gland (adrenal NB, ANB) in 88 patients (75%) and abdominal/paravertebral chain (paravertebral NB, PVNB) in 14 patients (12%). Overall survival (OS) for ANB was significantly lower (38%; P = 0.015). ANB cases were more frequently diagnosed at stage IV (69%; P = 0.001). MYCN amplification was noted in 33% of ANB cases and associated with lower OS (17% versus 62% MYCN non-amplified ANB; P = 0.01). The vast majority of TNB and PVNB were non-MYCN amplified (100% and 86%, respectively) and carried better prognosis (OS 86% and 83%, respectively). Forty-two percent of ANB cases were diploid and had lower OS (20% versus 71% hyperdiploid ANB; P = 0.079). TNB and PVNB were found to be mostly hyperdiploid (86% and 100%, respectively) with better OS (83% and 33%, respectively). Segmental chromosomal alterations had prognostic significance in those with PVNB (P = 0.03).

CONCLUSION

TNB tumours have better outcomes than adrenal tumours. This may be due to varied factors reported here including non-metastatic disease at presentation, non-amplification of the MYCN oncogene and overall favourable molecular biology characteristics.

MYCN-Amplified Neuroblastoma Is Addicted to Iron and Vulnerable to Inhibition of the System Xc-/Glutathione Axis

MYCN is amplified in 20% to 25% of neuroblastoma, and MYCN-amplified neuroblastoma contributes to a large percent of pediatric cancer-related deaths. Therapy improvements for this subtype of cancer are a high priority. Here we uncover a MYCN-dependent therapeutic vulnerability in neuroblastoma. Namely, amplified MYCN rewires the cell through expression of key receptors, ultimately enhancing iron influx through increased expression of the iron import transferrin receptor 1. Accumulating iron causes reactive oxygen species (ROS) production, and MYCN-amplified neuroblastomas show enhanced reliance on the system Xc- cystine/glutamate antiporter for ROS detoxification through increased transcription of this receptor. This dependence creates a marked vulnerability to targeting the system Xc-/glutathione (GSH) pathway with ferroptosis inducers. This reliance can be exploited through therapy with FDA-approved rheumatoid arthritis drugs sulfasalazine (SAS) and auranofin: in MYCN-amplified, patient-derived xenograft models, both therapies blocked growth and induced ferroptosis. SAS and auranofin activity was largely mitigated by the ferroptosis inhibitor ferrostatin-1, antioxidants like N-acetyl-L-cysteine, or by the iron scavenger deferoxamine (DFO). DFO reduced auranofin-induced ROS, further linking increased iron capture in MYCN-amplified neuroblastoma to a therapeutic vulnerability to ROS-inducing drugs. These data uncover an oncogene vulnerability to ferroptosis caused by increased iron accumulation and subsequent reliance on the system Xc-/GSH pathway. SIGNIFICANCE: This study shows how MYCN increases intracellular iron levels and subsequent GSH pathway activity and demonstrates the antitumor activity of FDA-approved SAS and auranofin in patient-derived xenograft models of MYCN-amplified neuroblastoma.

Development and Internal Validation of Model Predicting Postoperative Blood Loss Risk Among Children with Pulmonary Atresia Undergoing Cardiopulmonary Bypass

To develop and internally validate nomogram predicting postoperative blood loss risk among pediatric patients with pulmonary atresia (PA) undergoing cardiopulmonary bypass (CPB). All patients aged from 6 months to 6 years with PA who underwent surgery at Fuwai Hospital from June 2015 to December 2019 were selected. And the prediction nomogram model was developed in the training set based on the selected patients. The demographic characteristics and laboratory data from each enrolled patient were gathered. Postoperative blood loss was defined as a blood loss exceeding 20.0 ml/kg within the first 24 postoperative hours. The least absolute shrinkage and selection operator (LASSO) method was used to optimize feature selection for multivariate logistic regression analysis that was applied to build a nomogram composed of all the features selected in the LASSO algorithm. The concordance index (C-index), calibration plot, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical net benefit of the nomogarm, respectively. Finally, internal validation was performed using the bootstrap technique. Of the 66 pediatric patients in the training set, 21 (31.82%) and 45 (68.18%) patients were assigned into bleeding group and non-bleeding group, respectively. The first postoperative 24-h blood loss in the bleeding group was significantly higher than that in the non-bleeding group during ICU stay (P = 0.000). Multivariate logistic regression analysis showed that, the immediate postoperative prothrombin time (odds ratio = 1.419, 95% confidence interval: 1.094-1.841, P = 0.008), the immediate postoperative platelet count (odds ratio = 0.985, 95% confidence interval: 0.973-0.997, P = 0.015) and the immediate postoperative red blood cell (RBC) count (odds ratio = 0.335, 95% confidence interval: 0.166-0.667, P = 0.002) were independent predictors of postoperative blood loss risk. The model presented favorable calibration and good discrimination with satisfactory calibration curve and a C-index of 0.858 (95% confidence interval: 0.758-0.958). High C-index value of 0.837 was achieved in the internal validation. The DCA revealed that the nomogram was great clinical effect when intervention was decided among nearly the entire range of threshold probabilities. We developed and internally validated an accurate nomogram to assist in the clinical decision-making concerning the presence of postoperative blood loss in pediatric patients with PA undergoing CPB. However, the nomogram should be endorsed by external validation before it can be recommended for routine practice.

Prp19 Is an Independent Prognostic Marker and Promotes Neuroblastoma Metastasis by Regulating the Hippo-YAP Signaling Pathway

Pre-mRNA processing factor 19 (Prp19) was previously reported to be involved in tumor progression. However, Prp19 expression and its functions remain elusive in neuroblastoma. Here, we aim to identify the functions and mechanisms of Prp19 in neuroblastoma. Neuroblastic tumor tissue microarrays and two independent validation data sets indicate that Prp19 is associated with high-risk markers and bone marrow metastasis and serves as a prognostic marker for worse clinical outcomes with neuroblastoma. Gain- and loss-of-expression assays reveal that Prp19 promotes invasion, migration, and epithelial-mesenchymal transition (EMT) of neuroblastoma cells in vitro. Bioinformatics analysis of RNA-seq data shows that the expressions of YAP and its downstream genes are significantly inhibited after downregulation of Prp19. Prp19 and YAP expression in metastatic lymph nodes is higher than in situ neuroblastoma tissue. Further experiments show that Prp19 regulates YAP expression and consequently affects cell invasion, migration, and EMT in neuroblastoma by pre-mRNA splicing of YAP. In conclusion, our findings provide the first evidence that Prp19 is a potential therapeutic target and prognostic biomarker for patients with neuroblastoma.

Hypoxia Predicts Poor Prognosis in Neuroblastoma Patients and Associates with Biological Mechanisms Involved in Telomerase Activation and Tumor Microenvironment Reprogramming

The biological and clinical heterogeneity of neuroblastoma (NB) demands novel biomarkers and therapeutic targets in order to drive the most appropriate treatment for each patient. Hypoxia is a condition of low-oxygen tension occurring in poorly vascularized tumor tissues. In this study, we aimed to assess the role of hypoxia in the pathogenesis of NB and at developing a new clinically relevant hypoxia-based predictor of outcome. We analyzed the gene expression profiles of 1882 untreated NB primary tumors collected at diagnosis and belonging to four existing data sets. Analyses took advantage of machine learning methods. We identified NB-hop, a seven-gene hypoxia biomarker, as a predictor of NB patient prognosis, which is able to discriminate between two populations of patients with unfavorable or favorable outcome on a molecular basis. NB-hop retained its prognostic value in a multivariate model adjusted for established risk factors and was able to additionally stratify clinically relevant groups of patients. Tumors with an unfavorable NB-hop expression showed a significant association with telomerase activation and a hypoxic, immunosuppressive, poorly differentiated, and apoptosis-resistant tumor microenvironment. NB-hop defines a new population of NB patients with hypoxic tumors and unfavorable prognosis and it represents a critical factor for the stratification and treatment of NB patients.

The effect of age distribution on the prognosis of retroperitoneal neuroblastoma

Retroperitoneal neuroblastoma is a rare subtype of neuroblastoma and the role of age in its clinical prognosis is still unknown.To describe the age distribution and investigate the association between age and survival outcomes in patients diagnosed with retroperitoneal neuroblastoma.We retrospectively analyzed patients registered for retroperitoneal neuroblastoma in the Surveillance, Epidemiology, and End Results (SEER) national database from 1973 to 2015. Age distribution was described and Cox proportional hazard regression was used to evaluate the measured effect of age on overall survival and disease-specific survival.A total of 399 retroperitoneal neuroblastoma patients with a median follow-up of 53.0 (interquartile range 17.0-133.5) months were included. We found a unimodal distribution of age with a median age of diagnosis to be 1.0 (interquartile range 0.0-4.0) years. Univariate analysis suggested that transformed age was associated with an increased risk of total death and disease-specific death (OR = 4.2, 95% CI 3.0-5.9; OR = 4.7, 95% CI 3.2-6.8). Adjusted smoothed plots showed a nonlinear correlation between age and disease-specific death. The risk of disease-specific death did not increase sharply as the age increased until reaching the inflection point (age < 3 years, OR = 0.4, 95% CI 0.2-1.0; age ≥ 3 years, OR = 1.2, 95% CI 0.9-1.5). There was, however, a linear relationship between age and total deaths (OR = 1.0, 95% CI 0.7-1.2). Adjusted multivariate Cox regression analysis showed that ages ≥ 3 years were associated with a significant increased risks of disease-specific death and total death (OR = 2.5, 95% CI 1.7-3.8; OR = 2.3, 95% CI 1.6-3.3, respectively).There was a unimodal age distribution of retroperitoneal neuroblastoma usually presented in infants or younger child. Older age was associated with a lower chance of overall survival and the risk of disease-specific death increased sharply after 3 years of age.

Gene signatures associated with genomic aberrations predict prognosis in neuroblastoma

BACKGROUND

Neuroblastoma (NB) is a heterogeneous disease with respect to genomic abnormalities and clinical behaviors. Despite recent advances in our understanding of the association between the genetic aberrations and clinical features, it remains one of the major challenges to predict prognosis and stratify patients for determining personalized therapy in this disease. The aim of this study was to develop an effective prognosis prediction model for NB patients.

METHODS

We integrated diverse computational analyses to define gene signatures that reflect MYCN activity and chromosomal aberrations including deletion of chromosome 1p (Chr1p_del) and chromosome 11q (Chr11q_del) as well as chromosome 11q whole loss (Chr11q_wls). We evaluated the prognostic and predictive values of these signatures in seven NB gene expression datasets (the number of samples ranges from 94 to 498, with a total of 2120) generated from both RNA sequencing and microarray platforms.

RESULTS

MYCN signature was a more effective prognostic marker than MYCN amplification status and MYCN expression. Similarly, the Chr1p_del score was more prognostic than Chr1p status. The activity scores of MYCN, Chr1p_del and Chr11q_del were associated with poor prognosis, while the Chr11q_wls score was linked to good outcome. We integrated the activity scores of MYCN, Chr1p_del, Chr11q_del, and Chr11q_wls and clinical variables into an integrative prognostic model, which displayed significant performance over the clinical variables or each genomic aberration alone.

CONCLUSIONS

Our integrative gene signature model shows a significantly improved forecast performance with prognostic and predictive information, and thereby can be served as a biomarker to stratify NB patients for prognosis evaluation and surveillance programs.

Telomerase Is a Prognostic Marker of Poor Outcome and a Therapeutic Target in Neuroblastoma

PURPOSE

Telomere maintenance is a hallmark of high-risk neuroblastoma; however, the contribution of telomerase and alternative lengthening of telomeres (ALT) to clinical phenotypes has remained unclear. We aimed to determine the clinical relevance of telomerase activation versus ALT as biomarkers in pretreatment neuroblastoma and to assess the potential value of telomerase as a therapeutic target.

MATERIALS AND METHODS

The genomic status of TERT and MYCN was assessed in 457 pretreatment neuroblastomas by fluorescence in situ hybridization. ALT was examined in 273 of 457 tumors by detection of ALT-associated promyelocytic leukemia nuclear bodies, and TERT expression was determined by microarrays in 223 of these. Cytotoxic effects of telomerase-interacting compounds were analyzed in neuroblastoma cell lines in vitro and in vivo.

RESULTS

We detected TERT rearrangements in 46 of 457 cases (10.1%), MYCN amplification in 93 of 457 cases (20.4%), and elevated TERT expression in tumors lacking TERT or MYCN alterations in 10 of 223 cases (4.5%). ALT activation was found in 49 of 273 cases (17.9%). All these alterations occurred almost mutually exclusively and were associated with unfavorable prognostic variables and adverse outcome. The presence of activated telomerase (ie, TERT rearrangements, MYCN amplification, or high TERT expression without these alterations) was associated with poorest overall survival and was an independent prognostic marker in multivariable analyses. We also found that the telomerase-interacting compound 6-thio-2'-deoxyguanosine effectively inhibited viability and proliferation of neuroblastoma cells bearing activated telomerase. Similarly, tumor growth was strongly impaired upon 6-thio-2'-deoxyguanosine treatment in telomerase-positive neuroblastoma xenografts in mice.

CONCLUSION

Our data suggest telomerase activation and ALT define distinct neuroblastoma subgroups with adverse outcome and that telomerase may represent a promising therapeutic target in many high-risk neuroblastomas.