Translating expression profiling into a clinically feasible test to predict neuroblastoma outcome

Transcript signatures that predict outcome and identify targetable pathways in MYCN-amplified neuroblastoma

BACKGROUND

In the pediatric cancer neuroblastoma (NB), patients are stratified into low, intermediate or high-risk subsets based in part on MYCN amplification status. While MYCN amplification in general predicts unfavorable outcome, no clinical or genomic factors have been identified that predict outcome within these cohorts of high-risk patients. In particular, it is currently not possible at diagnosis to determine which high-risk neuroblastoma patients will ultimately fail upfront therapy.

EXPERIMENTAL DESIGN

We analyzed the prognostic potential of most published gene expression signatures for NB and developed a new prognostic signature to predict outcome for patients with MYCN amplification. Network and pathway analyses identified candidate therapeutic targets for this MYCN-amplified patient subset with poor outcome.

RESULTS

Most signatures have a high capacity to predict outcome of unselected NB patients. However, the majority of published signatures, as well as most randomly generated signatures, are highly confounded by MYCN amplification, and fail to predict outcome in subpopulations of high-risk patients with MYCN-amplified NB. We identify a MYCN module signature that predicts patient outcome for those with MYCN-amplified tumors, that also predicts potential tractable therapeutic signaling pathways and targets including the DNA repair enzyme Poly [ADP-ribose] polymerase 1 (PARP1).

CONCLUSION

Many prognostic signatures for NB are confounded by MYCN amplification and fail to predict outcome for the subset of high-risk patients with MYCN amplification. We report a MYCN module signature that is associated with distinct patient outcomes, and predicts candidate therapeutic targets in DNA repair pathways, including PARP1 in MYCN-amplified NB.

A Cre-conditional MYCN-driven neuroblastoma mouse model as an improved tool for preclinical studies

Neuroblastoma, a childhood cancer that originates from neural crest-derived cells, is the most common deadly solid tumor of infancy. Amplification of the MYCN oncogene, which occurs in approximately 20–25% of human neuroblastomas, is the most prominent genetic marker of high-stage disease. The availability of valid preclinical in vivo models is a prerequisite to develop novel targeted therapies. We here report on the generation of transgenic mice with Cre-conditional induction of MYCN in dopamine β-hydroxylase-expressing cells, termed LSL-MYCN;Dbh-iCre. These mice develop neuroblastic tumors with an incidence of >75%, regardless of strain background. Molecular profiling of tumors revealed upregulation of the MYCN-dependent miR-17–92 cluster as well as expression of neuroblastoma marker genes, including tyrosine hydroxylase and the neural cell adhesion molecule 1. Gene set enrichment analyses demonstrated significant correlation with MYC-associated expression patterns. Array comparative genome hybridization showed that chromosomal aberrations in LSL-MYCN;Dbh-iCre tumors were syntenic to those observed in human neuroblastomas. Treatment of a cell line established from a tumor derived from a LSL-MYCN;Dbh-iCre mouse with JQ1 or MLN8237 reduced cell viability and demonstrated oncogene addiction to MYCN. Here we report establishment of the first Cre-conditional human MYCN-driven mouse model for neuroblastoma that closely recapitulates the human disease with respect to tumor localization, histology, marker expression and genomic make up. This mouse model is a valuable tool for further functional studies and to assess the effect of targeted therapies.

Clinical significance of NTRK family gene expression in neuroblastomas

BACKGROUND

Neuroblastomas (NBs) are characterized by clinical heterogeneity, from spontaneous regression to relentless progression. The pattern of NTRK family gene expression contributes to these disparate behaviors. TrkA/NTRK1 is expressed in favorable NBs that regress or differentiate, whereas TrkB/NTRK2 and its ligand brain-derived neurotrophic factor (BDNF) are co-expressed in unfavorable NBs, representing an autocrine survival pathway. We determined the significance of NTRK family gene expression in a large, representative set of primary NBs.

PATIENTS AND METHODS

We analyzed the expression of the following genes in 814 NBs using quantitative real-time reverse transcriptase polymerase chain reaction (RT-PCR): NTRK1, NTRK2, NTRK3, P75/NGFR, nerve growth factor (NGF), BDNF, IGFR1, and EGFR. Expression (high vs. low) was dichotomized by median expression value and compared to clinical and biological variables as well as outcome.

RESULTS

High NTRK1 expression was strongly correlated with favorable age, stage, MYCN status, histology, ploidy, risk group, and outcome (P < 0.0001 for all). However, it did not add significantly to the panel of prognostic variables currently used for cooperative group trials. NTRK2 expression was associated with risk factors but not with outcome. High NGF expression was also associated with most risk factors and weakly with unfavorable outcome.

CONCLUSIONS

High expression of NTRK1 is strongly associated with favorable risk factors and outcome in a large, representative population of NB patients. It did not add significantly to the current risk prediction algorithm, but it may contribute to future expression classifiers. Indeed, prospective assessment of NTRK1 and NTRK2 expression will identify tumors that would be candidates for NTRK-targeted therapy, either alone or in combination with conventional agents.

New aspects of neuroblastoma treatment: ASPHO 2011 symposium review

Neuroblastoma is the most common extracranial solid tumor of childhood, and the outcomes for children with high-risk and relapsed disease remain poor. However, new international strategies for risk stratification and for treatment based on novel tumor targets and including immunotherapy are being employed in attempts to improve the outcomes of children with neuroblastoma. A new international neuroblastoma risk classification system has been developed which is being incorporated into cooperative group clinical trials in North America, Japan, and Europe, resulting in standardized approaches for the initial evaluation and treatment stratification of neuroblastoma patients. Furthermore, novel treatment regimens are being developed based on improved understanding of neuroblastoma biology and on the recruitment of the immune system to specifically target neuroblastoma tumors. These approaches will lead to new therapeutic strategies that likely will improve the outcomes for children with neuroblastoma worldwide.

Design of a multi-signature ensemble classifier predicting neuroblastoma patients' outcome

Background

Neuroblastoma is the most common pediatric solid tumor of the sympathetic nervous system. Development of improved predictive tools for patients stratification is a crucial requirement for neuroblastoma therapy. Several studies utilized gene expression-based signatures to stratify neuroblastoma patients and demonstrated a clear advantage of adding genomic analysis to risk assessment. There is little overlapping among signatures and merging their prognostic potential would be advantageous. Here, we describe a new strategy to merge published neuroblastoma related gene signatures into a single, highly accurate, Multi-Signature Ensemble (MuSE)-classifier of neuroblastoma (NB) patients outcome.

Methods

Gene expression profiles of 182 neuroblastoma tumors, subdivided into three independent datasets, were used in the various phases of development and validation of neuroblastoma NB-MuSE-classifier. Thirty three signatures were evaluated for patients' outcome prediction using 22 classification algorithms each and generating 726 classifiers and prediction results. The best-performing algorithm for each signature was selected, validated on an independent dataset and the 20 signatures performing with an accuracy > = 80% were retained.

Results

We combined the 20 predictions associated to the corresponding signatures through the selection of the best performing algorithm into a single outcome predictor. The best performance was obtained by the Decision Table algorithm that produced the NB-MuSE-classifier characterized by an external validation accuracy of 94%. Kaplan-Meier curves and log-rank test demonstrated that patients with good and poor outcome prediction by the NB-MuSE-classifier have a significantly different survival (p < 0.0001). Survival curves constructed on subgroups of patients divided on the bases of known prognostic marker suggested an excellent stratification of localized and stage 4s tumors but more data are needed to prove this point.

Conclusions

The NB-MuSE-classifier is based on an ensemble approach that merges twenty heterogeneous, neuroblastoma-related gene signatures to blend their discriminating power, rather than numeric values, into a single, highly accurate patients' outcome predictor. The novelty of our approach derives from the way to integrate the gene expression signatures, by optimally associating them with a single paradigm ultimately integrated into a single classifier. This model can be exported to other types of cancer and to diseases for which dedicated databases exist.

Differential toxicity of copper (II) oxide nanoparticles of similar hydrodynamic diameter on human differentiated intestinal Caco-2 cell monolayers is correlated in part to copper release and shape

The potential toxic effects of copper oxide (CuO) nanoparticles (NPs) were studied on differentiated Caco-2 cell monolayers, a classical in vitro model of human small intestine epithelium. Two types of CuO NPs, with different specific surface area, different sizes as raw material but the same hydrodynamic diameter in suspension, differentially disturbed the monolayer integrity, were cytotoxic and triggered an increase of the abundance of several transcripts coding for pro-inflammatory cytokines and chemokines. Specific surface area was not a major variable explaining the increased toxicity when intestinal epithelium is exposed to rod-shaped CuO NPs, compared with spherical CuO NPs. The results suggest that release of Cu(II) cations and shape of these CuO NPs are likely to be implicated in the toxicity of these CuO NPs.

Pro-inflammatory effects of different MWCNTs dispersions in p16(INK4A)-deficient telomerase-expressing human keratinocytes but not in human SV-40 immortalized sebocytes

We tested whether multi-walled carbon nanotubes (MWCNTs) induce oxidative stress and a pro-inflammatory response in human N-hTERT telomerase-immortalized keratinocytes, in human SZ95 SV-40 immortalized sebocytes and in in vitro reconstructed epidermises. MWCNTS were tested in various dispersion states, from raw and agglomerated particles to isolated entities obtained by sonication in the presence of dispersive agents (hydroxypropylcellulose and Pluronic F108). It was observed that: (a) Contrary to individualized MWCNTs, agglomerated particles prepared by suspension into pure water increased the intracellular levels of reactive oxygen species as well as the expression and secretion of interleukin-8 in N-hTERT cells; (b) the inflammatory signature of MWCNTs in N-hTERT cells, drawn by transcriptomic analysis with low-density microfluidic cards, included various other cytokines such as interleukin-6 or C-C motif ligand 3; (c) the pro-inflammatory effects of MWCNTs, as assessed by interleukin-8 transcript level and protein release, were not observed in SZ95 cells; and (d) the secretion of interleukins-1α and -8 from in vitro reconstructed epidermal tissues, used as specific markers for skin irritation and sensitization, was unaffected in presence of MWCNTs, confirming that the cornified layer is an efficient barrier against MWCNTs.

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.

Global genomic and RNA profiles for novel risk stratification of neuroblastoma

Neuroblastoma is one of the most common solid tumors in children. Its clinical behavior ranges widely from spontaneous regression to life-threatening aggressive growth. The molecular etiology of neuroblastoma is still enigmatic and the overall cure rate of advanced disease is still very poor. Recent microarray-based technology provided us with important information such as comprehensive genomic alterations and gene expression profiles to help us understand the molecular characteristics of each tumor in detail. Several retrospective studies have revealed that these signatures are strongly correlated with patient prognoses and led to the construction of new risk stratification systems, some of which are considered for evaluation in upcoming clinical studies in a prospective way. Large-scale analyses using a variety of genetic tools also discovered a major familial neuroblastoma predisposition gene ALK, as well as new candidate susceptibility genes at 6q22 and 2q35 for sporadic neuroblastoma. Of note, ALK is mutated in 6-9% of sporadic cases, and is either amplified or constitutively activated through mutations mainly within the kinase domain, promoting the possibility of new therapeutic strategies using ALK inhibitors. Additional candidates for outcome predictors such as the methylation phenotype of tumor DNA and expression profiles of microRNA have also been proposed. Such variety of information will help us understand the heterogeneity of neuroblastoma biology and further, the combined use of these signatures will be beneficial in predicting prognosis with high accuracy, as well as choosing a suitable therapy for the individual patient.

A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

BACKGROUND

Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome.

RESULTS

We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo) taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification.

CONCLUSIONS

Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

Proteomic approaches in neuroblastoma: a complementary clinical platform for the future

Neuroblastoma (NB) is one of the most common solid tumors of childhood and displays a remarkable diversity in both biologic characteristics and clinical outcomes. Availability of high-throughput 'omics technologies and their subsequent application towards oncology has provided insight into the complex pathways of tumor formation and progression. Investigation of NB 'omics profiles may better define tumor behavior and provide targeted therapy with the goal of improving outcomes in patients with high-risk disease. Utilization of these technologies in NB has already led to advances in classification and risk stratification. The gradual emergence of NB-directed proteomics adds a layer of intricacy to the analysis of biologic organization but may ultimately provide a better comprehension of this complex disease. In this review, we cite specific examples of how NB-directed proteomics has provided information regarding novel biomarkers and possible therapeutic targets. We finish by examining the impact of high-throughput 'omics in the field of NB and speculate on how these emerging technologies may further be incorporated into the discipline.

Reanalysis of neuroblastoma expression profiling data using improved methodology and extended follow-up increases validity of outcome prediction

Neuroblastoma is the most common extracranial childhood tumor, comprising 15% of all childhood cancer deaths. In an initial study, we used Affymetrix oligonucleotide microarrays to analyse gene expression in 68 primary neuroblastomas and compared different data mining approaches for prediction of early relapse. Here, we performed re-analyses of the data including prolonged follow-up and applied support vector machine (SVM) algorithms and outer cross-validation strategies to improve reliability of expression profiling based predictors. Accuracy of outcome prediction was significantly improved by the use of innovative SVM algorithms on the updated data. In addition, CASPAR, a hierarchical Bayesian approach, was used to predict survival times for the individual patient based on expression profiling data. CASPAR reliably predicted event-free survival, given a cut-off time of three years. Differential expression of genes used by CASPAR to predict patient outcome was validated in an independent cohort of 117 neuroblastomas. In conclusion, we show here for the first time that reanalysis of microarray data using improved methodology, state-of-the-art performance tests and updated follow-up data improves prognosis prediction, and may further improve risk stratification of individual patients.

Lysine-specific demethylase 1 is strongly expressed in poorly differentiated neuroblastoma: implications for therapy

Aberrant epigenetic changes in DNA methylation and histone acetylation are hallmarks of most cancers, whereas histone methylation was previously considered to be irreversible and less versatile. Recently, several histone demethylases were identified catalyzing the removal of methyl groups from histone H3 lysine residues and thereby influencing gene expression. Neuroblastomas continue to remain a clinical challenge despite advances in multimodal therapy. Here, we address the functional significance of the chromatin-modifying enzyme lysine-specific demethylase 1 (LSD1) in neuroblastoma. LSD1 expression correlated with adverse outcome and was inversely correlated with differentiation in neuroblastic tumors. Differentiation of neuroblastoma cells resulted in down-regulation of LSD1. Small interfering RNA-mediated knockdown of LSD1 decreased cellular growth, induced expression of differentiation-associated genes, and increased target gene-specific H3K4 methylation. Moreover, LSD1 inhibition using monoamine oxidase inhibitors resulted in an increase of global H3K4 methylation and growth inhibition of neuroblastoma cells in vitro. Finally, targeting LSD1 reduced neuroblastoma xenograft growth in vivo. Here, we provide the first evidence that a histone demethylase, LSD1, is involved in maintaining the undifferentiated, malignant phenotype of neuroblastoma cells. We show that inhibition of LSD1 reprograms the transcriptome of neuroblastoma cells and inhibits neuroblastoma xenograft growth. Our results suggest that targeting histone demethylases may provide a novel option for cancer therapy.

Identification of potential therapeutic targets in malignant mesothelioma using cell-cycle gene expression analysis

Cell-cycle defects are responsible for cancer onset and growth. We studied the expression profile of 60 genes involved in cell cycle in a series of malignant mesotheliomas (MMs), normal pleural tissues, and MM cell cultures using a quantitative polymerase chain reaction-based, low-density array. Nine genes were significantly deregulated in MMs compared with normal controls. Seven genes were overexpressed in MMs, including the following: CDKN2C, cdc6, cyclin H, cyclin B1, CDC2, FoxM1, and Chk1, whereas Ube1L and cyclin D2 were underexpressed. Chk1 is a principal mediator of cell-cycle checkpoints in response to genotoxic stress. We confirmed the overexpression of Chk1 in an independent set of 87 MMs by immunohistochemistry using tissue microarrays. To determine whether Chk1 down-regulation would affect cell-cycle control and cell survival, we transfected either control or Chk1 siRNA into two mesothelioma cell lines and a nontumorigenic (Met5a) cell line. Results showed that Chk1 knockdown increased the apoptotic fraction of MM cells and induced an S phase block in Met5a cells. Furthermore, Chk1 silencing sensitized p53-null MM cells to both an S phase block and apoptosis in the presence of doxorubicin. Our results indicate that cell-cycle gene expression analysis by quantitative polymerase chain reaction can identify potential targets for novel therapies. Chk1 knockdown could provide a novel therapeutic approach to arrest cell-cycle progression in MM cells, thus increasing the rate of cell death.

Whole chromosome alterations predict survival in high-risk neuroblastoma without MYCN amplification

PURPOSE

Patients with stage IV neuroblastoma over the age of 500 days without MYCN amplification have a survival rate of <30% and there are currently no reliable means of predicting which of these patients will survive or succumb to the disease. The goal of this study is to develop a DNA copy number-based prognostic profile for these patients.

EXPERIMENTAL DESIGN

We have used comparative genomic hybridization to identify genome copy number changes that can predict outcome in patients with stage IV neuroblastoma without MYCN amplification.

RESULTS

A strong correlation of patient survival with the presence of whole chromosome changes (WCC >or=2) was observed, even in the group of patients older than 500 days at time of diagnosis. This novel prognostic marker showed a significant dependence on the date of diagnosis; patients with WCC >or=2 diagnosed after 1998 had a significantly higher probability of survival compared with those diagnosed earlier. At the same time, no such time dependence was found among the samples with WCC <2, suggesting that medical progress patients in recent years has particularly benefited those patients with a stage IV non-MYCN-amplified disease if WCC >or=2 were present.

CONCLUSIONS

In this pilot study, we present a novel prognostic marker for survival of high-risk neuroblastoma patients over the age of 500 days without MYCN amplification and diagnosed after 1998. Further validation study is required to establish this risk stratification for these patients.

A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative real-time PCR

Background

Based upon defining a common reference point, current real-time quantitative PCR technologies compare relative differences in amplification profile position. As such, absolute quantification requires construction of target-specific standard curves that are highly resource intensive and prone to introducing quantitative errors. Sigmoidal modeling using nonlinear regression has previously demonstrated that absolute quantification can be accomplished without standard curves; however, quantitative errors caused by distortions within the plateau phase have impeded effective implementation of this alternative approach.

Results

Recognition that amplification rate is linearly correlated to amplicon quantity led to the derivation of two sigmoid functions that allow target quantification via linear regression analysis. In addition to circumventing quantitative errors produced by plateau distortions, this approach allows the amplification efficiency within individual amplification reactions to be determined. Absolute quantification is accomplished by first converting individual fluorescence readings into target quantity expressed in fluorescence units, followed by conversion into the number of target molecules via optical calibration. Founded upon expressing reaction fluorescence in relation to amplicon DNA mass, a seminal element of this study was to implement optical calibration using lambda gDNA as a universal quantitative standard. Not only does this eliminate the need to prepare target-specific quantitative standards, it relegates establishment of quantitative scale to a single, highly defined entity. The quantitative competency of this approach was assessed by exploiting "limiting dilution assay" for absolute quantification, which provided an independent gold standard from which to verify quantitative accuracy. This yielded substantive corroborating evidence that absolute accuracies of ± 25% can be routinely achieved. Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.

Conclusion

Called "linear regression of efficiency" or LRE, this novel kinetic approach confers the ability to conduct high-capacity absolute quantification with unprecedented quality control capabilities. The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis. This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions.