A three-gene expression signature model for risk stratification of patients with neuroblastoma

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.

Predicting Neuroblastoma Patient Risk Groups, Outcomes, and Treatment Response Using Machine Learning Methods: A Review

Neuroblastoma, a paediatric malignancy with high rates of cancer-related morbidity and mortality, is of significant interest to the field of paediatric cancers. High-risk NB tumours are usually metastatic and result in survival rates of less than 50%. Machine learning approaches have been applied to various neuroblastoma patient data to retrieve relevant clinical and biological information and develop predictive models. Given this background, this study will catalogue and summarise the literature that has used machine learning and statistical methods to analyse data such as multi-omics, histological sections, and medical images to make clinical predictions. Furthermore, the question will be turned on its head, and the use of machine learning to accurately stratify NB patients by risk groups and to predict outcomes, including survival and treatment response, will be summarised. Overall, this study aims to catalogue and summarise the important work conducted to date on the subject of expression-based predictor models and machine learning in neuroblastoma for risk stratification and patient outcomes including survival, and treatment response which may assist and direct future diagnostic and therapeutic efforts.

Target Genes of c-MYC and MYCN with Prognostic Power in Neuroblastoma Exhibit Different Expressions during Sympathoadrenal Development

Deregulation of the MYC family of transcription factors c-MYC (encoded by MYC), MYCN, and MYCL is prevalent in most human cancers, with an impact on tumor initiation and progression, as well as response to therapy. In neuroblastoma (NB), amplification of the MYCN oncogene and over-expression of MYC characterize approximately 40% and 10% of all high-risk NB cases, respectively. However, the mechanism and stage of neural crest development in which MYCN and c-MYC contribute to the onset and/or progression of NB are not yet fully understood. Here, we hypothesized that subtle differences in the expression of MYCN and/or c-MYC targets could more accurately stratify NB patients in different risk groups rather than using the expression of either MYC gene alone. We employed an integrative approach using the transcriptome of 498 NB patients from the SEQC cohort and previously defined c-MYC and MYCN target genes to model a multigene transcriptional risk score. Our findings demonstrate that defined sets of c-MYC and MYCN targets with significant prognostic value, effectively stratify NB patients into different groups with varying overall survival probabilities. In particular, patients exhibiting a high-risk signature score present unfavorable clinical parameters, including increased clinical risk, higher INSS stage, MYCN amplification, and disease progression. Notably, target genes with prognostic value differ between c-MYC and MYCN, exhibiting distinct expression patterns in the developing sympathoadrenal system. Genes associated with poor outcomes are mainly found in sympathoblasts rather than in chromaffin cells during the sympathoadrenal development.

Development and validation of a 21-gene prognostic signature in neuroblastoma

Survival outcomes for patients with neuroblastoma vary markedly and reliable prognostic markers and risk stratification tools are lacking. We sought to identify and validate a transcriptomic signature capable of predicting risk of mortality in patients with neuroblastoma. The TARGET NBL dataset (n = 243) was used to develop the model and two independent cohorts, E-MTAB-179 (n = 478) and GSE85047 (n = 240) were used as validation sets. EFS was the primary outcome and OS was the secondary outcome of interest for all analysis. We identified a 21-gene signature capable of stratifying neuroblastoma patients into high and low risk groups in the E-MTAB-179 (HR 5.87 [3.83-9.01], p < 0.0001, 5 year AUC 0.827) and GSE85047 (HR 3.74 [2.36-5.92], p < 0.0001, 5 year AUC 0.815) validation cohorts. Moreover, the signature remained independent of known clinicopathological variables, and remained prognostic within clinically important subgroups. Further, the signature was effectively incorporated into a risk model with clinicopathological variables to improve prognostic performance across validation cohorts (Pooled Validation HR 6.93 [4.89-9.83], p < 0.0001, 5 year AUC 0.839). Similar prognostic utility was also demonstrated with OS. The identified signature is a robust independent predictor of EFS and OS outcomes in neuroblastoma patients and can be combined with clinically utilized clinicopathological variables to improve prognostic performance.

Prognostic value of xenograft engraftment in patients with metastatic high-risk neuroblastoma

BACKGROUND

Successful engraftment of human cancer biopsies in immunodeficient mice correlates with the poor prognosis of patients. This was reported 30 years ago for children with neuroblastoma, but the standard of care treatment evolved significantly during the last 15 years, leading to improved survival of these patients. Here, we evaluated the association of patient-derived xenograft (PDX) engraftment and prognosis in patients receiving up-to-date treatments for cancers classified as metastatic (stage M) high-risk neuroblastoma (HR-NB) by the International Neuroblastoma Risk Group Staging System (INRGSS).

METHODS

We obtained biopsies from patients with stage M HR-NB. We inoculated biopsy fragments subcutaneously in mice. We studied the association of PDX engraftment with event-free survival (EFS) and overall survival (OS) of patients.

RESULTS

Since 2009, we established 17 PDX from 97 samples of 66 patients with stage M HR-NB, with a follow-up of at least two years. Factors associated with higher probability of engraftment were the death as outcome (p = .0006) and the amplification of the gene MYCN in tumors (p = .0271). Patients whose biopsies established a PDX had significantly shorter EFS and OS (p = .0039 and .0002, respectively) than patients whose samples did not engraft. The association of PDX engraftment and OS was significant in patients without MYCN amplification (p = .0041), but not in patients with MYCN amplification (p = .2707).

CONCLUSION

Positive PDX engraftment is a factor related to poor prognosis and fatal outcome in patients with stage M HR-NB treated with up-to-date therapies.

Contrast computed tomography-based radiomics is correlation with COG risk stratification of neuroblastoma

PURPOSE

Although a risk stratification strategy for neuroblastoma (NB) has been proposed, precise and convenient clinical risk estimation remains challenging. This study aimed to investigate the correlation of contrast computed tomography (CT)-based radiomics with NB risk stratification.

METHODS

Patients with NB (n = 289) from two centers (244 and 45 patients in the training/testing and external validation cohorts, respectively) were divided into nonhigh- and high-risk groups. A total of 1648 radiomics features were extracted from the arterial phase, and the radiomics signature was constructed using rad scores, whereas the clinical model was established based on clinical factors. Further, a combined nomogram was developed based on the clinical factors and radiomics signatures. Finally, receiver operating characteristic curve and decision curve analyses (DCA) were used to assess the performance of the established models.

RESULTS

Seventeen radiomics features were used to construct the radiomics signature. A significant difference was observed in the rad score between the two groups in the training (0.540 vs. 0.704, P < 0.001) and testing (0.563 vs. 0.969, P < 0.001) cohorts. The nomogram showed a higher area under the curve (AUC) in the training (AUC = 0.87), testing (AUC = 0.83), and external validation (AUC = 0.84) cohorts than other models. The Hosmer-Lemeshow test and calibration curves indicated that the nomogram fit perfectly. DCA demonstrated that the clinical-radiomics nomogram was more beneficial.

CONCLUSIONS

Contrast CT-based radiomics shows correlation with COG risk stratification of NB. Radiomics features combined with clinical factors showed the best performance, which may improve the management of patients with NB.

Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma

Neuroblastoma is a childhood neurological tumor which affects hundreds of thousands of children worldwide, and information about its prognosis can be pivotal for patients, their families, and clinicians. One of the main goals in the related bioinformatics analyses is to provide stable genetic signatures able to include genes whose expression levels can be effective to predict the prognosis of the patients. In this study, we collected the prognostic signatures for neuroblastoma published in the biomedical literature, and noticed that the most frequent genes present among them were three: AHCY, DPYLS3, and NME1. We therefore investigated the prognostic power of these three genes by performing a survival analysis and a binary classification on multiple gene expression datasets of different groups of patients diagnosed with neuroblastoma. Finally, we discussed the main studies in the literature associating these three genes with neuroblastoma. Our results, in each of these three steps of validation, confirm the prognostic capability of AHCY, DPYLS3, and NME1, and highlight their key role in neuroblastoma prognosis. Our results can have an impact on neuroblastoma genetics research: biologists and medical researchers can pay more attention to the regulation and expression of these three genes in patients having neuroblastoma, and therefore can develop better cures and treatments which can save patients' lives.

Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma

Background

Neuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients.

Methods

Multi-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated.

Results

We constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment.

Conclusion

This study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients.

Metabolic remodeling of pyrimidine synthesis pathway and serine synthesis pathway in human glioblastoma

Glioblastoma is the most common brain tumor with dismal outcomes in adults. Metabolic remodeling is now widely acknowledged as a hallmark of cancer cells, but glioblastoma-specific metabolic pathways remain unclear. Here we show, using a large-scale targeted proteomics platform and integrated molecular pathway-level analysis tool, that the de novo pyrimidine synthesis pathway and serine synthesis pathway (SSP) are the major enriched pathways in vivo for patients with glioblastoma. Among the enzymes associated with nucleotide synthesis, RRM1 and NME1 are significantly upregulated in glioblastoma. In the SSP, SHMT2 and PSPH are upregulated but the upstream enzyme PSAT1 is downregulated in glioblastoma. Kaplan–Meier curves of overall survival for the GSE16011 and The Cancer Genome Atlas datasets revealed that high SSP activity correlated with poor outcome. Enzymes relating to the pyrimidine synthesis pathway and SSP might offer therapeutic targets for new glioblastoma treatments.

Extracellular Vesicle-Mediated Metastasis Suppressors NME1 and NME2 Modify Lipid Metabolism in Fibroblasts

Simple Summary

Communication between cancer and stromal cells involves paracrine signalling mediated by extracellular vesicles (EVs). EVs transmit essential factors among cells of the tumour microenvironment. EVs derived from both cancer and stromal cells have been implicated in tumour progression. In this study, we focused on the first identified metastasis suppressor NME1, and on its close homolog NME2, and investigated their function in EVs in the interplay between cancer and stromal cells.

Abstract

Nowadays, extracellular vesicles (EVs) raise a great interest as they are implicated in intercellular communication between cancer and stromal cells. Our aim was to understand how vesicular NME1 and NME2 released by breast cancer cells influence the tumour microenvironment. As a model, we used human invasive breast carcinoma cells overexpressing NME1 or NME2, and first analysed in detail the presence of both isoforms in EV subtypes by capillary Western immunoassay (WES) and immunoelectron microscopy. Data obtained by both methods showed that NME1 was present in medium-sized EVs or microvesicles, whereas NME2 was abundant in both microvesicles and small-sized EVs or exosomes. Next, human skin-derived fibroblasts were treated with NME1 or NME2 containing EVs, and subsequently mRNA expression changes in fibroblasts were examined. RNAseq results showed that the expression of fatty acid and cholesterol metabolism-related genes was decreased significantly in response to NME1 or NME2 containing EV treatment. We found that FASN (fatty acid synthase) and ACSS2 (acyl-coenzyme A synthetase short-chain family member 2), related to fatty acid synthesis and oxidation, were underexpressed in NME1/2-EV-treated fibroblasts. Our data show an emerging link between NME-containing EVs and regulation of tumour metabolism.

Mechanisms involved in selecting and maintaining neuroblastoma cancer stem cell populations, and perspectives for therapeutic targeting

Pediatric neuroblastomas (NBs) are heterogeneous, aggressive, therapy-resistant embryonal tumours that originate from cells of neural crest (NC) origin and in particular neuroblasts committed to the sympathoadrenal progenitor cell lineage. Therapeutic resistance, post-therapeutic relapse and subsequent metastatic NB progression are driven primarily by cancer stem cell (CSC)-like subpopulations, which through their self-renewing capacity, intermittent and slow cell cycles, drug-resistant and reversibly adaptive plastic phenotypes, represent the most important obstacle to improving therapeutic outcomes in unfavourable NBs. In this review, dedicated to NB CSCs and the prospects for their therapeutic eradication, we initiate with brief descriptions of the unique transient vertebrate embryonic NC structure and salient molecular protagonists involved NC induction, specification, epithelial to mesenchymal transition and migratory behaviour, in order to familiarise the reader with the embryonic cellular and molecular origins and background to NB. We follow this by introducing NB and the potential NC-derived stem/progenitor cell origins of NBs, before providing a comprehensive review of the salient molecules, signalling pathways, mechanisms, tumour microenvironmental and therapeutic conditions involved in promoting, selecting and maintaining NB CSC subpopulations, and that underpin their therapy-resistant, self-renewing metastatic behaviour. Finally, we review potential therapeutic strategies and future prospects for targeting and eradication of these bastions of NB therapeutic resistance, post-therapeutic relapse and metastatic progression.

Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

The migrational propensity of neuroblastoma is affected by cell identity, but the mechanisms behind the divergence remain unknown. Using RNAi and time-lapse imaging, we show that ADRN-type NB cells exhibit RAC1- and kalirin-dependent nucleokinetic (NUC) migration that relies on several integral components of neuronal migration. Inhibition of NUC migration by RAC1 and kalirin-GEF1 inhibitors occurs without hampering cell proliferation and ADRN identity. Using three clinically relevant expression dichotomies, we reveal that most of up-regulated mRNAs in RAC1- and kalirin-GEF1-suppressed ADRN-type NB cells are associated with low-risk characteristics. The computational analysis shows that, in a context of overall gene set poverty, the upregulomes in RAC1- and kalirin-GEF1-suppressed ADRN-type cells are a batch of AU-rich element-containing mRNAs, which suggests a link between NUC migration and mRNA stability. Gene set enrichment analysis-based search for vulnerabilities reveals prospective weak points in RAC1- and kalirin-GEF1-suppressed ADRN-type NB cells, including activities of H3K27- and DNA methyltransferases. Altogether, these data support the introduction of NUC inhibitors into cancer treatment research.

Development of a stacked, porous silk scaffold neuroblastoma model for investigating spatial differences in cell and drug responsiveness

Development of in vitro, preclinical cancer models that contain cell-driven microenvironments remains a challenge. Engineering of millimeter-scale, in vitro tumor models with spatially distinct regions that can be independently assessed to study tumor microenvironments has been limited. Here, we report the use of porous silk scaffolds to generate a high cell density neuroblastoma (NB) model that can spatially recapitulate changes resulting from cell and diffusion driven changes. Using COMSOL modeling, a scaffold holder design that facilitates stacking of thin, 200 μm silk scaffolds into a thick, bulk millimeter-scale tumor model (2, 4, 6, and 8 stacked scaffolds) and supports cell-driven oxygen gradients was developed. Cell-driven oxygen gradients were confirmed through pimonidazole staining. Post-culture, the stacked scaffolds were separated for analysis on a layer-by-layer basis. The analysis of each scaffold layer demonstrated decreasing DNA and increasing expression of hypoxia related genes (VEGF, CAIX, and GLUT1) from the exterior scaffolds to the interior scaffolds. Furthermore, the expression of hypoxia related genes at the interior of the stacks was comparable to that of a single scaffold cultured under 1% O₂ and at the exterior of the stacks was comparable to that of a single scaffold cultured under 21% O₂. The four-stack scaffold model underwent further evaluation to determine if a hypoxia activated drug, tirapazamine, induced reduced cell viability within the internal stacks (region of reduced oxygen) as compared with the external stacks. Decreased DNA content was observed in the internal stacks as compared to the external stacks when treated with tirapazamine, which suggests the internal scaffold stacks had higher levels of hypoxia than the external scaffolds. This stacked silk scaffold system presents a method for creating a single culture model capable of generating controllable cell-driven microenvironments through different stacks that can be individually assessed and used for drug screening.

The Role of Autologous Stem-Cell Transplantation in High-Risk Neuroblastoma Consolidated by anti-GD2 Immunotherapy. Results of Two Consecutive Studies

Background: Treatment of HR-NB comprise induction, consolidation with autologous stem cell transplant (ASCT) followed by anti-GD2 immunotherapy and isotretinoin. Childrens Oncology Group and SIOPEN studies used dinutuximab and cytokines to treat patients in complete remission or refractory Bone/Bone marrow (B/BM) disease after ASCT.

Methods: HR-NB patients referred to Hospital Sant Joan de Déu for anti-GD2 immunotherapy were eligible for two consecutive studies (dinutuximab for EudraCT 2013–004864–69 and naxitamab for 017–001829–40) and naxitamab/Sargramostim CU with or without prior ASCT. Patients enrolled in first complete remission or with primary refractory B/BM disease. We accrued a study population of two groups whose therapy, aside from ASCT, was similar. This is a retrospective analysis of their outcome calculated from study entry.

Results: From December 2014–2019, 67 patients were treated with dinutuximab and cytokines (n = 21) in the Hospital Sant Joan de Déu-HRNB-Ch14.18 study or with naxitamab and Sargramostim either in the Ymabs study 201 (n = 12) or CU (n = 34). 23 patients were treated with primary refractory disease in the B/BM (11 with dinutuximab and 12 with naxitamab), and 44 in first CR (10 with dinutuximab and 34 with naxitamab). Study patients included 13 (19.4%) treated following single ASCT and 54 following conventional chemotherapy. Median follow-up for all patients is 16.2 months. Two-year rates for ASCT and non-ASCT patients were, respectively, EFS 64.1% vs. 54.2% (p = 0.28), and OS 66.7% vs. 84.1% (p = 0.81). For the 44 pts in first CR, 2-years rates for ASCT and non-ASCT patients were, respectively, EFS 65.5% vs. 58.7% (p = 0.48), and OS 71.4% vs. 85.4% (p = 0.63).

Conclusions: In this retrospective, single center study, ASCT did not provide survival benefit when anti-GD2 immunotherapy was used after induction chemotherapy.

Computational Identification of Gene Networks as a Biomarker of Neuroblastoma Risk

Neuroblastoma is a common cancer in children, affected by a number of genes that interact with each other through intricate but coordinated networks. Traditional approaches can only reconstruct a single regulatory network that is topologically not informative enough to explain the complexity of neuroblastoma risk. We implemented and modified an advanced model for recovering informative, omnidirectional, dynamic, and personalized networks (idopNetworks) from static gene expression data for neuroblastoma risk. We analyzed 3439 immune genes of neuroblastoma for 217 high-risk patients and 30 low-risk patients by which to reconstruct large patient-specific idopNetworks. By converting these networks into risk-specific representations, we found that the shift in patients from a low to high risk or from a high to low risk might be due to the reciprocal change of hub regulators. By altering the directions of regulation exerted by these hubs, it may be possible to reduce a high risk to a low risk. Results from a holistic, systems-oriented paradigm through idopNetworks can potentially enable oncologists to experimentally identify the biomarkers of neuroblastoma and other cancers.

Machine Learning Supports Long Noncoding RNAs as Expression Markers for Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is the second most common type of gynecological tumor. Several research studies have recently shown the potential of different ncRNAs as biomarkers for prognostics and diagnosis in different types of cancers, including UCEC. Thus, we hypothesized that long noncoding RNAs (lncRNAs) could serve as efficient factors to discriminate solid primary (TP) and normal adjacent (NT) tissues in UCEC with high accuracy. We performed an in silico differential expression analysis comparing TP and NT from a set of samples downloaded from the Cancer Genome Atlas (TCGA) database, targeting highly differentially expressed lncRNAs that could potentially serve as gene expression markers. All analyses were performed in R software. The receiver operator characteristics (ROC) analyses and both supervised and unsupervised machine learning indicated a set of 14 lncRNAs that may serve as biomarkers for UCEC. Functions and putative pathways were assessed through a coexpression network and target enrichment analysis.

The Potential Functional Roles of NME1 Histidine Kinase Activity in Neuroblastoma Pathogenesis

Neuroblastoma is the most common extracranial solid tumor in childhood. Gain of chromosome 17q material is found in >60% of neuroblastoma tumors and is associated with poor patient prognosis. The NME1 gene is located in the 17q21.3 region, and high NME1 expression is correlated with poor neuroblastoma patient outcomes. However, the functional roles and signaling activity of NME1 in neuroblastoma cells and tumors are unknown. NME1 and NME2 have been shown to possess histidine (His) kinase activity. Using anti-1- and 3-pHis specific monoclonal antibodies and polyclonal anti-pH118 NME1/2 antibodies, we demonstrated the presence of pH118-NME1/2 and multiple additional pHis-containing proteins in all tested neuroblastoma cell lines and in xenograft neuroblastoma tumors, supporting the presence of histidine kinase activity in neuroblastoma cells and demonstrating the potential significance of histidine kinase signaling in neuroblastoma pathogenesis. We have also demonstrated associations between NME1 expression and neuroblastoma cell migration and differentiation. Our demonstration of NME1 histidine phosphorylation in neuroblastoma and of the potential role of NME1 in neuroblastoma cell migration and differentiation suggest a functional role for NME1 in neuroblastoma pathogenesis and open the possibility of identifying new therapeutic targets and developing novel approaches to neuroblastoma therapy.

CAMKV Is a Candidate Immunotherapeutic Target in MYCN Amplified Neuroblastoma

We developed a computational pipeline designed to use RNA sequencing (n = 136) and gene expression profiling (n = 250) data from neuroblastoma tumors to identify cell surface proteins predicted to be highly expressed in MYCN amplified neuroblastomas and with little or no expression in normal human tissues. We then performed ChIP-seq in the MYCN amplified cell lines KELLY, NB-1643, and NGP to identify gene promoters that are occupied by MYCN protein to define the intersection with the differentially-expressed gene list. We initially identified 116 putative immunotherapy targets with predicted transmembrane domains, with the most significant differentially-expressed of these being the calmodulin kinase-like vesicle-associated gene (CAMKV, p = 2 × 10-6). CAMKV encodes a protein that binds calmodulin in the presence of calcium, but lacks the kinase activity of other calmodulin kinase family members. We confirmed that CAMKV is selectively expressed in 7/7 MYCN amplified neuroblastoma cell lines and showed that the transcription of CAMKV is directly controlled by MYCN. From membrane fractionation and immunohistochemistry, we verified that CAMKV is membranous in MYCN amplified neuroblastoma cell lines and patient-derived xenografts. Finally, immunohistochemistry showed that CAMKV is not expressed on normal tissues outside of the central nervous system. Together, these data demonstrate that CAMKV is a differentially-expressed cell surface protein that is transcriptionally regulated by MYCN, making it a candidate for targeting with antibodies or antibody-drug conjugates that do not cross the blood brain barrier.

The Function of NM23-H1/NME1 and Its Homologs in Major Processes Linked to Metastasis

Metastasis suppressor genes (MSGs) inhibit different biological processes during metastatic progression without globally influencing development of the primary tumor. The first MSG, NM23 (non-metastatic clone 23, isoform H1) or now called NME1 (stands for non-metastatic) was identified some decades ago. Since then, ten human NM23 paralogs forming two groups have been discovered. Group I NM23 genes encode enzymes with evolutionarily highly conserved nucleoside diphosphate kinase (NDPK) activity. In this review we summarize how results from NDPKs in model organisms converged on human NM23 studies. Next, we examine the role of NM23-H1 and its homologs within the metastatic cascade, e.g. cell migration and invasion, proliferation and apoptosis. NM23-H1 homologs are well known inhibitors of cell migration. Drosophila studies revealed that AWD, the fly counterpart of NM23-H1 is a negative regulator of cell motility by modulating endocytosis of chemotactic receptors on the surface of migrating cells in cooperation with Shibire/Dynamin; this mechanism has been recently confirmed by human studies. NM23-H1 inhibits proliferation of tumor cells by phosphorylating the MAPK scaffold, kinase suppressor of Ras (KSR), resulting in suppression of MAPK signalling. This mechanism was also observed with the C. elegans homolog, NDK-1, albeit with an inverse effect on MAPK activation. Both NM23-H1 and NDK-1 promote apoptotic cell death. In addition, NDK-1, NM23-H1 and their mouse counterpart NM23-M1 were shown to promote phagocytosis in an evolutionarily conserved manner. In summary, inhibition of cell migration and proliferation, alongside actions in apoptosis and phagocytosis are all mechanisms through which NM23-H1 acts against metastatic progression.

A 2-Protein Signature Predicting Clinical Outcome in High-Grade Serous Ovarian Cancer

OBJECTIVE

High-grade serous ovarian cancer (HGSOC) accounts for approximately 70% deaths in ovarian cancer. The overall survival (OS) of HGSOC is poor and still remains a clinical challenge. High-grade serous ovarian cancer can be divided into 4 molecular subtypes. The prognosis of different molecular subtypes is still unclear. We aimed to investigate the prognostic values of immunohistochemistry-based different molecular subtypes in patients with HGSOC.

METHODS

We analyzed the protein expression of representative biomarkers (CXCL11, HMGA2, and MUC16) of 3 different molecular subtypes in 110 formalin-fixed, paraffin-embedded HGSOC by tissue microarrays.

RESULTS

High CXCL11 expression predicted worse OS, not disease-free survival (DFS; P = 0.028 for OS, P = 0.191 for DFS). High HMGA2 expression predicted worse OS and DFS (P = 0.037 for OS, P = 0.021 for DFS). MUC16 expression was not associated with OS or DFS (P = 0.919 for OS, P = 0.517 for DFS). Multivariate regression analysis showed that CXCL11 combined with HMGA2 signature was an independent predictor for OS and DFS in patients with HGSOC.

CONCLUSIONS

CXCL11 combined with HMGA2 signature was a clinically applicable prognostic model that could precisely predict an HGSOC patient's OS and tumor recurrence. This model could serve as an important tool for risk assessment of HGSOC prognosis.

NDPKA is not just a metastasis suppressor - be aware of its metastasis-promoting role in neuroblastoma

NDPK-A, encoded by nm23-H1 (also known as NME1) was the first metastasis suppressor discovered. Much of the attention has been focused on the metastasis-suppressing role of NDPK-A in human tumors, including breast carcinoma and melanoma. However, compelling evidence points to a metastasis-promoting role of NDPK-A in certain tumors such as neuroblastoma and lymphoma. To balance attention on this contrariety of NDPK-A in different cancer types, this review addresses the metastasis-promoting role of NDPK-A in neuroblastoma. Neuroblastoma is an embryonic tumor, arising from neural crest cells that fail to differentiate into the sympathetic nervous system. We summarize and discuss nm23-H1 genetics and the prognosis of neuroblastoma, structural and functional changes associated with the S120G mutation of NDPK-A, as well as the evidence supporting the role of NDPK-A as a metastasis promoter. Also discussed are the NDPK-A relevant molecular determinants of neuroblastoma metastasis, and metastasis-relevant neural crest development. Because of NDPK-A's dichotomous role in tumor metastasis as both a suppressor and a promoter, tumor genome/exome profiles are necessary to identify the molecular drivers of metastasis in the NDPK-A network for developing tumor-specific therapies.

A three-gene signature from protein-protein interaction network of LOXL2- and actin-related proteins for esophageal squamous cell carcinoma prognosis

Current staging is inadequate for predicting clinical outcome of esophageal squamous cell carcinoma (ESCC). Aberrant expression of LOXL2 and actin-related proteins plays important roles in ESCC. Here, we aimed to develop a novel molecular signature that exceeds the power of the current staging system in predicting ESCC prognosis. We found that LOXL2 colocalized with filamentous actin in ESCC cells, and gene set enrichment analysis (GSEA) showed that LOXL2 is related to the actin cytoskeleton. An ESCC-specific protein-protein interaction (PPI) network involving LOXL2 and actin-related proteins was generated based on genome-wide RNA-seq in 15 paired ESCC samples, and the prognostic significance of 14 core genes was analyzed. Using risk score calculation, a three-gene signature comprising LOXL2, CDH1, and FN1 was derived from transcriptome data of patients with ESCC. The high-risk three-gene signature strongly correlated with poor prognosis in a training cohort of 60 patients (P = 0.003). In mRNA and protein levels, the prognostic values of this signature were further validated in 243 patients from a testing cohort (P = 0.001) and two validation cohorts (P = 0.021, P = 0.007). Furthermore, Cox regression analysis revealed that the signature was an independent prognostic factor. Compared with using the signature or TNM stage alone, the combined model significantly enhanced the accuracy in evaluating ESCC prognosis. In conclusion, our data reveal that the tumor-promoting role of LOXL2 in ESCC is mediated by perturbing the architecture of actin cytoskeleton through its PPIs. We generated a novel three-gene signature (PPI interfaces) that robustly predicts poor clinical outcome in ESCC patients.

Artificial neural network classifier predicts neuroblastoma patients' outcome

Background

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients’ outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease.

Methods

Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients’ outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with “Poor” or “Good” outcome.

Results

We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients’ outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors’ set. The NB-hypo classifier predicted the patients’ outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis.

Conclusions

We developed a robust classifier predicting neuroblastoma patients’ outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1194-3) contains supplementary material, which is available to authorized users.

Neuropeptide Y as a Biomarker and Therapeutic Target for Neuroblastoma

Neuroblastoma (NB) is a pediatric malignant neoplasm of sympathoadrenal origin. Challenges in its management include stratification of this heterogeneous disease and a lack of both adequate treatments for high-risk patients and noninvasive biomarkers of disease progression. Our previous studies have identified neuropeptide Y (NPY), a sympathetic neurotransmitter expressed in NB, as a potential therapeutic target for these tumors by virtue of its Y5 receptor (Y5R)-mediated chemoresistance and Y2 receptor (Y2R)-mediated proliferative and angiogenic activities. The goal of this study was to determine the clinical relevance and utility of these findings. Expression of NPY and its receptors was evaluated in corresponding samples of tumor RNA, tissues, and sera from 87 patients with neuroblastic tumors and in tumor tissues from the TH-MYCN NB mouse model. Elevated serum NPY levels correlated with an adverse clinical presentation, poor survival, metastasis, and relapse, whereas strong Y5R immunoreactivity was a marker of angioinvasive tumor cells. In NB tissues from TH-MYCN mice, high immunoreactivity of both NPY and Y5R marked angioinvasive NB cells. Y2R was uniformly expressed in undifferentiated tumor cells, which supports its previously reported role in NB cell proliferation. Our findings validate NPY as a therapeutic target for advanced NB and implicate the NPY/Y5R axis in disease dissemination. The correlation between elevated systemic NPY and NB progression identifies serum NPY as a novel NB biomarker.

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.

Enriched Bone Marrow Derived Disseminated Neuroblastoma Cells Can Be a Reliable Source for Gene Expression Studies-A Validation Study

BACKGROUND

Metastases in the bone marrow (BM) in form of disseminated tumor cells (DTCs) are frequent events at diagnosis and also at relapse in high-risk neuroblastoma patients. The frequently highly diluted occurrence of DTCs requires adequate enrichment strategies to enable their detailed characterization. However, to avoid methodical artifacts we tested whether pre-analytical processing steps-including transport duration, temperature and, importantly, tumor cell enrichment techniques-are confounding factors for gene expression analysis in DTCs.

METHODS

LAN-1 neuroblastoma cells were spiked into tumor free BM and/or peripheral blood and: i) kept at room temperature or at 4°C for 24, 48 and 72 hours; ii) frozen down at -80°C and thawed; iii) enriched via magnetic beads. The effect on the gene expression signature of LAN-1 cells was analyzed by qPCR arrays and gene expression microarrays.

RESULTS

Neither storage at -80°C in DMSO and subsequent thawing nor enrichment of spiked-in neuroblastoma cells changed the expression of the analyzed genes significantly. Whereas storage at 4°C altered the expression of analyzed genes (14.3%) only at the 72h-timepoint in comparison to the 0h-timepoint, storage at room temperature had a much more profound effect on gene expression by affecting 20% at 24h, 26% at 48h and 43% at 72h of the analyzed genes.

CONCLUSION

Using neuroblastoma as a model, we show that tumor cell enrichment by magnetic bead separation has virtually no effect on gene expression in DTCs. However, transport time and temperature can influence the expression profile remarkably. Thus, the expression profile of routinely collected BM samples can be analyzed without concern as long as the transport conditions are monitored.

Advances in Risk Classification and Treatment Strategies for Neuroblastoma

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations.

RNA Biosignatures in Adolescent Patients in a Pediatric Emergency Department With Pelvic Inflammatory Disease

BACKGROUND

Adolescents are at high risk for pelvic inflammatory disease (PID). Because accurate diagnosis of PID is difficult, and complications of untreated PID are significant, novel methods to improve diagnosis are essential.

OBJECTIVES

To determine if patients with PID have unique RNA expression patterns compared to controls.

METHODS

Peripheral blood was collected from adolescent females with PID in the emergency department, and from control patients in the operating room. RNA was isolated, and microarray analysis was performed. Initial analysis involved a training set of 18 patients (9 PID patients with either Neisseria gonorrhoeae or Chlamydia trachomatis infection and 9 control patients). Supervised and unsupervised cluster analyses were performed, followed by network analysis. The training set was used to classify a set of 15 additional PID patients and 2 controls.

RESULTS

Supervised cluster analysis of the training set revealed 170 genes which were differentially expressed in PID patients versus controls. Network analysis indicated that several differentially expressed genes are involved in immune activation. Analysis of additional PID patients based on the training set findings revealed that patients with positive testing for Trichomonas vaginalis partitioned with the PID group, whereas patients with no organism identified partitioned with both groups.

CONCLUSIONS

RNA sample collection from adolescents in the emergency department is feasible. Genes were identified which were differentially expressed in PID patients versus controls, many of which are involved in inflammation. Future studies should confirm the training set findings on a larger sample and may lead to improved accuracy of PID diagnosis.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction

Background

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model.

Results

We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models.

Conclusions

We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0694-1) contains supplementary material, which is available to authorized users.

The chromatin remodeler chd5 is necessary for proper head development during embryogenesis of Danio rerio

The chromatin remodeler CHD5 plays a critical role in tumor suppression and neurogenesis in mammals. CHD5 contributes to gene expression during neurogenesis, but there is still much to learn regarding how this class of remodelers contributes to differentiation and development. CHD5 remodelers are vertebrate-specific, raising the prospect that CHD5 plays one or more conserved roles in this phylum. Expression of chd5 in adult fish closely mirrors expression of CHD5 in adult mammals. Knockdown of Chd5 during embryogenesis suggests new roles for CHD5 remodelers based on resulting defects in craniofacial development including reduced head and eye size as well as reduced cartilage formation in the head. In addition, knockdown of Chd5 results in altered expression of neural markers in the developing brain and eye as well as a profound defect in differentiation of dopaminergic amacrine cells. Recombinant zebrafish Chd5 protein exhibits nucleosome remodeling activity in vitro, suggesting that it is the loss of this activity that contributes to the observed phenotypes. Our studies indicate that zebrafish is an appropriate model for functional characterization of CHD5 remodelers in vertebrates and highlight the potential of this model for generating novel insights into the role of this vital class of remodelers.

DNA methylation fingerprint of neuroblastoma reveals new biological and clinical insights

AIM

To define the DNA methylation landscape of neuroblastoma and its clinicopathological impact.

MATERIALS & METHODS

Microarray DNA methylation data were analyzed and associated with functional/regulatory genome annotation data, transcriptional profiles and clinicobiological parameters.

RESULTS

DNA methylation changes in neuroblastoma affect not only promoters but also intragenic and intergenic regions at cytosine-phosphate-guanine (CpG) and non-CpG sites, and target functional chromatin domains of development and cancer-related genes such as CCND1. Tumors with diverse clinical risk showed differences affecting CpG and, remarkably, non-CpG sites. Non-CpG methylation observed essentially in clinically favorable cases was associated with the differentiation status of neuroblastoma and expression of key genes such as ALK.

CONCLUSION

This epigenetic fingerprint of neuroblastoma provides new insights into the pathogenesis and clinical behavior of this pediatric tumor.

A three-protein signature and clinical outcome in esophageal squamous cell carcinoma

Current staging is inadequate to precisely predict clinical outcome of esophageal squamous cell carcinoma (ESCC) and determine treatment choices, which vary from operation alone to intensive multimodal regimens. The purpose of this study is to investigate the prognostic values of an immunohistochemistry-based three-protein signature model in patients with ESCC. We determined the protein expression of Annexin II, cofilin 1, ezrin, fascin, kindlin-2, moesin, MTSS1, myosin-9, profilin-1, Rac1, radixin, ROCK2, talin, tensin and villin 1 in a test cohort including 110 formalin-fixed, paraffin-embedded esophageal curative resection specimens by tissue microarrays (TMAs). A three-protein signature elicited from the protein cluster, Annexin II, kindlin-2, and myosin-9, was validated by TMAs on an independent cohort of 147 specimens. The expression of three-protein signature was highly predictive of ESCC overall survival (OS) and disease-free survival (DFS) in both generation and validation datasets. Regression analysis shows that this three-protein signature is an independent predictor for OS and DFS. Furthermore, the predictive ability of these 3 biomarkers in combination is more robust than that of each individual biomarker. This study demonstrates a clinically applicable prognostic model that accurately predicts ESCC patient survival and/or tumor recurrence, and thus could serve as a complement to current risk stratification approaches.

Individual patient risk stratification of high-risk neuroblastomas using a two-gene score suited for clinical use

Several gene expression-based prognostic signatures have been described in neuroblastoma, but none have successfully been applied in the clinic. Here we have developed a clinically applicable prognostic gene signature, both with regards to number of genes and analysis platform. Importantly, it does not require comparison between patients and is applicable amongst high-risk patients. The signature is based on a two-gene score (R-score) with prognostic power in high-stage tumours (stage 4 and/or MYCN-amplified diagnosed after 18 months of age). QPCR-based and array-based analyses of matched cDNAs confirmed cross platform (array-qPCR) transferability. We also defined a fixed cut-off value identifying prognostically differing subsets of high-risk patients on an individual patient basis. This gene expression signature independently contributes to the current neuroblastoma classification system, and if prospectively validated could provide further stratification of high-risk patients, and potential upfront identification of a group of patients that are in need of new/additional treatment regimens.

A molecular signature for the prediction of recurrence in colorectal cancer

BACKGROUND

Several clinical and pathological factors have an impact on the prognosis of colorectal cancer (CRC), but they are not yet adequate for risk assessment. We aimed to identify a molecular signature that can reliably identify CRC patients at high risk for recurrence.

RESULTS

Two hundred eighty-one CRC samples (stage II/III) were included in this study. A two-step gene expression profiling study was conducted. First, gene expression measurements from 81 fresh frozen CRC samples were obtained using Affymetrix Human Genome U133 Plus 2.0 Arrays. Second, a focused gene expression assay, including prognostic genes and genes of interest from literature reviews, was performed using 200 fresh frozen samples and a Taqman low-density array (TLDA) analysis. An optimal 31-gene expression classifier for the prediction of recurrence among patients with stage II/III CRC was developed using logistic regression analysis. This gene expression signature classified 58.5% of patients as low-risk and 41.5% as high-risk (P < 0.001). The signature was the strongest independent prognostic factor in the multivariate analysis. The five-year relapse-free survival (RFS) rates for the low-risk patients and the high-risk patients were 88.5% and 41.3% (P < 0.001), respectively.

CONCLUSION

We identified a 31-gene expression signature that is closely associated with the clinical outcome of stage II/III CRC patients.

Neuroblastoma: paradigm for precision medicine

Neuroblastoma (NB) is the third most common pediatric cancer. Although NB accounts for 7% of pediatric malignancies, it is responsible for more than 10% of childhood cancer-related mortality. Prognosis and treatment are determined by clinical and biological risk factors. Estimated 5-year survival rates for patients with non-high-risk and high-risk NB are more than 90% and less than 50%, respectively. Recent clinical trials have continued to reduce therapy for patients with non-high-risk NB, including the most favorable subsets who are often followed with observation approaches. In contrast, high-risk patients are treated aggressively with chemotherapy, radiation, surgery, and myeloablative and immunotherapies.

Regulatory functions of Nm23-H2 in tumorigenesis: insights from biochemical to clinical perspectives

Substantial effort has been directed at elucidating the functions of the products of the Nm23 tumor metastasis suppressor genes over the past two decades, with the ultimate goal of exploring their translational potentials in changing cancer patients' outcomes. Much attention has been focused on the better-known Nm23-H1, but despite having high sequence similarity, Nm23-H2 functions differently in many aspects. Besides acting as a metastasis suppressor, compelling data suggest that Nm23-H2 may modulate various tumor-associated biological events to enhance tumorigenesis in human solid tumors and hematological malignancies. Linkage to tumorigenesis may occur through the ability of Nm23-H2 to regulate transcription, cell proliferation, apoptosis, differentiation, and telomerase activity. In this review, we examine the linkages of Nm23-H2 to tumorigenesis in terms of its biochemical and structural properties and discuss its potential role in various tumor-associated events.

A molecular prognostic model predicts esophageal squamous cell carcinoma prognosis

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC.

METHODS

We developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR), phosphorylated Specificity protein 1 (p-Sp1), and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset) and validated using an independent cohort of 185 specimens (validation dataset).

RESULTS

The expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001). Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391-3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256-3.154], P = 0.003 in validation dataset). Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker.

CONCLUSIONS

This technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.

Recent insights into the biology of neuroblastoma

Neuroblastoma (NB) is an embryonal tumor of the sympathetic nervous system which accounts for 8-10% of pediatric cancers. It is characterized by a broad spectrum of clinical behaviors from spontaneous regression to fatal outcome despite aggressive therapies. Considerable progress has been made recently in the germline and somatic genetic characterization of patients and tumors. Indeed, predisposition genes that account for a significant proportion of familial and syndromic cases have been identified and genome-wide association studies have retrieved a number of susceptibility loci. In addition, genome-wide sequencing, copy-number and expression studies have been conducted on tumors and have detected important gene modifications, profiles and signatures that have strong implications for the therapeutic stratification of patients. The identification of major players in NB oncogenesis, including MYCN, ALK, PHOX2B and LIN28B, has enabled the development of new animal models. Our review focuses on these recent advances, on the insights they provide on the mechanisms involved in NB development and their applications for the clinical management of patients.

Validation of a prognostic multi-gene signature in high-risk neuroblastoma using the high throughput digital NanoString nCounter™ system

Microarray-based molecular signatures have not been widely integrated into neuroblastoma diagnostic classification systems due to the complexities of the assay and requirement for high-quality RNA. New digital technologies that accurately quantify gene expression using RNA isolated from formalin-fixed paraffin embedded (FFPE) tissues are now available. In this study, we describe the first use of a high-throughput digital system to assay the expression of genes in an "ultra-high risk" microarray classifier in FFPE high-risk neuroblastoma tumors. Customized probes corresponding to the 42 genes in a published multi-gene neuroblastoma signature were hybridized to RNA isolated from 107 FFPE high-risk neuroblastoma samples using the NanoString nCounter™ Analysis System. For classification of each patient, the Pearson's correlation coefficient was calculated between the standardized nCounter™ data and the molecular signature from the microarray data. We demonstrate that the nCounter™ 42-gene panel sub-stratified the high-risk cohort into two subsets with statistically significantly different overall survival (p = 0.0027) and event-free survival (p = 0.028). In contrast, none of the established prognostic risk markers (age, stage, tumor histology, MYCN status, and ploidy) were significantly associated with survival. We conclude that the nCounter™ System can reproducibly quantify expression levels of signature genes in FFPE tumor samples. Validation of this microarray signature in our high-risk patient cohort using a completely different technology emphasizes the prognostic relevance of this classifier. Prospective studies testing the prognostic value of molecular signatures in high-risk neuroblastoma patients using FFPE tumor samples and the nCounter™ System are warranted.

Role of CHD5 in human cancers: 10 years later

CHD5 was first identified because of its location on 1p36 in a region of frequent deletion in neuroblastomas. CHD5 (chromodomain-helicase-DNA-binding-5) is the fifth member of a family of chromatin remodeling proteins, and it probably functions by forming a nucleosome remodeling and deacetylation (NuRD) complex that regulates transcription of particular genes. CHD5 is preferentially expressed in the nervous system and testis. On the basis of its position, pattern of expression, and function in neuroblastoma cells and xenografts, CHD5 was identified as a tumor suppressor gene (TSG). Evidence soon emerged that CHD5 also functioned as a TSG in gliomas and a variety of other tumor types, including breast, colon, lung, ovary, and prostate cancers. Although one copy of CHD5 is deleted frequently, inactivating mutations of the remaining allele are rare. However, DNA methylation of the CHD5 promoter is found frequently, and this epigenetic mechanism leads to biallelic inactivation. Furthermore, low CHD5 expression is strongly associated with unfavorable clinical and biologic features as well as outcome in neuroblastomas and many other tumor types. Thus, based on its likely involvement as a TSG in neuroblastomas, gliomas, and many common adult tumors, CHD5 may play an important developmental role in many other tissues besides the nervous system and testis.

Therapeutic targets for neuroblastomas

INTRODUCTION

Neuroblastoma (NB) is the most common and deadly solid tumor in children. Despite recent improvements, the long-term outlook for high-risk NB is still < 50%. Further, there is considerable short- and long-term toxicity. More effective, less toxic therapy is needed, and the development of targeted therapies offers great promise.

AREAS COVERED

Relevant literature was reviewed to identify current and future therapeutic targets that are critical to malignant transformation and progression of NB. The potential or actual NB therapeutic targets are classified into four categories: i) genes activated by amplification, mutation, translocation or autocrine overexpression; ii) genes inactivated by deletion, mutation or epigenetic silencing; iii) membrane-associated genes expressed on most NBs but few other tissues; or iv) common target genes relevant to NB as well as other tumors.

EXPERT OPINION

Therapeutic approaches have been developed to some of these targets, but many remain untargeted at the present time. It is unlikely that single targeted agents will be sufficient for long-term cure, at least for high-risk NBs. The challenge will be how to integrate targeted agents with each other and with conventional therapy to enhance their efficacy, while simultaneously reducing systemic toxicity.

Recurrent pre-existing and acquired DNA copy number alterations, including focal TERT gains, in neuroblastoma central nervous system metastases

Stage 4 neuroblastomas have a high rate of local and metastatic relapse and associated disease mortality. The central nervous system (CNS) is currently one of the most common isolated relapse sites, yet the genomic alterations that contribute to these metastases are unknown. This study sought to identify recurrent DNA copy number alterations (CNAs) and target genes relating to neuroblastoma CNS metastases by studying 19 pre-CNS primary tumors and 27 CNS metastases, including 12 matched pairs. SNP microarray analyses revealed that MYCN amplified (MYCNA) tumors had recurrent CNAs different from non-MYCNA cohorts. Several CNAs known to be prevalent among primary neuroblastomas occurred more frequently in CNS metastases, including 4p-, 7q+, 12q+, and 19q- in non-MYCNA metastases, and 9p- and 14q- irrespective of MYCNA status. In addition, novel CNS metastases-related CNAs included 18q22.1 gains in non-MYCNA pre-CNS primaries and 5p15.33 gains and 15q26.1→tel losses in non-MYCNA CNS metastases. Based on minimal common regions, gene expression, and biological properties, TERT (5p), NR2F2 (15q), ALDH1A3 (15q), CDKN2A (9p), and possibly CDH7 and CDH19 (18q) were candidate genes associated with the CNS metastatic process. Notably, the 5p15 minimal common region contained only TERT, and non-MYCNA CNS metastases with focal 5p15 gains had increased TERT expression, similar to MYCNA tumors. These findings suggest that a specific genomic lesion (18q22.1 gain) predisposes to CNS metastases and that distinct lesions are recurrently acquired during metastatic progression. Among the acquired lesions, increased TERT copy number and expression appears likely to function in lieu of MYCNA to promote CNS metastasis.

Neuroblastoma tumorigenesis is regulated through the Nm23-H1/h-Prune C-terminal interaction

Nm23-H1 is one of the most interesting candidate genes for a relevant role in Neuroblastoma pathogenesis. H-Prune is the most characterized Nm23-H1 binding partner, and its overexpression has been shown in different human cancers. Our study focuses on the role of the Nm23-H1/h-Prune protein complex in Neuroblastoma. Using NMR spectroscopy, we performed a conformational analysis of the h-Prune C-terminal to identify the amino acids involved in the interaction with Nm23-H1. We developed a competitive permeable peptide (CPP) to impair the formation of the Nm23-H1/h-Prune complex and demonstrated that CPP causes impairment of cell motility, substantial impairment of tumor growth and metastases formation. Meta-analysis performed on three Neuroblastoma cohorts showed Nm23-H1 as the gene highly associated to Neuroblastoma aggressiveness. We also identified two other proteins (PTPRA and TRIM22) with expression levels significantly affected by CPP. These data suggest a new avenue for potential clinical application of CPP in Neuroblastoma treatment.

snoRNPs Regulate Telomerase Activity in Neuroblastoma and Are Associated with Poor Prognosis

Amplification of the MYCN oncogene is strongly associated with poor prognosis in neuroblastoma (NB). In addition to MYCN amplification, many studies have focused on identifying patients with a poor prognosis based on gene expression profiling. The majority of prognostic signatures today are comprised of large gene lists limiting their clinical application. In addition, although of prognostic significance, most of these signatures fail to identify cellular processes that can explain their relation to prognosis. Here, we determined prognostically predictive genes in a data set containing 251 NBs. Gene Ontology analysis was performed on significant genes with a positive hazard ratio to search for cellular processes associated with poor prognosis. An enrichment in ribonucleoproteins (RNPs) was found. Genes involved in the stabilization and formation of the central small nucleolar RNP (snoRNP) complex were scrutinized using a backward conditional Cox regression resulting in an snoRNP signature consisting of three genes: DKC1, NHP2, and GAR1. The snoRNP signature significantly and independently predicted prognosis when compared to the established clinical risk factors. Association of snoRNP protein expression and prognosis was confirmed using tissue micro-arrays. Knockdown of snoRNP expression in NB cell lines resulted in reduced telomerase activity and an increase in anaphase bridge frequency. In addition, in patient material, expression of the snoRNP complex was significantly associated with telomerase activity, occurrence of segmental aberrations, and expression-based measurements of chromosomal instability. Together, these results underscore the prognostic value of snoRNP complex expression in NB and suggest a role for snoRNPs in telomere maintenance and genomic stability.

Polymorphisms in the calcium-sensing receptor gene are associated with clinical outcome of neuroblastoma

Background

Neuroblastic tumors include the neuroblastomas, ganglioneuroblastomas, and ganglioneuromas. Clinical behavior of these developmental malignancies varies from regression to aggressive growth with metastatic dissemination. Several clinical, histological, genetic, and biological features are associated with this diversity of clinical presentations. The calcium-sensing receptor (CaSR) is a G-protein coupled receptor with a key role in calcium homeostasis. We have previously reported that it is expressed in benign, differentiated neuroblastic tumors, but silenced by genetic and epigenetic events in unfavorable neuroblastomas. We have now analyzed three functionally relevant polymorphisms clustered at the signal transduction region of the CaSR (rs1801725, rs1042636 and rs1801726) to assess if genetic variants producing a less active receptor are associated with more aggressive disease course.

Methods

Polymorphisms were analyzed in DNA samples from 65 patients using specific Taqman Genotyping Assays.

Results

Mildly inactivating variant rs1801725 was associated with clinical stage 4 (P = 0.002) and the histological subgroup of undifferentiated neuroblastomas (P = 0.046). Patients harboring this polymorphism had significantly lower overall (P = 0.022) and event-free survival (P = 0.01) rates than those who were homozygous for the most common allele among Caucasians. However, this single locus genotype was not independently associated with outcome in multivariate analyses. Conversely, the tri-locus haplotype TAC was independently associated with an increased risk of death in the entire cohort (Hazard Ratio = 2.45; 95% Confidence Interval [1.14–5.29]; P = 0.022) and also in patients diagnosed with neuroblastomas (Hazard Ratio = 2.74; 95% Confidence Interval [1.20–6.25]; P = 0.016).

Conclusions

The TAC haplotype includes the moderately inactivating variant rs1801725 and absence of the gain-of-function rs1042636 polymorphism. Thus, its association with metastatic disease and poor outcome would add to our previous data and further support that inactivation of the CaSR gene is a mechanism associated with neuroblastoma malignant behavior.

Chd5 requires PHD-mediated histone 3 binding for tumor suppression

Chromodomain Helicase DNA binding protein 5 (CHD5) is a tumor suppressor mapping to 1p36, a genomic region that is frequently deleted in human cancer. Although CHD5 belongs to the CHD family of chromatin-remodeling proteins, whether its tumor-suppressive role involves an interaction with chromatin is unknown. Here we report that Chd5 binds the unmodified N terminus of H3 through its tandem plant homeodomains (PHDs). Genome-wide chromatin immunoprecipitation studies reveal preferential binding of Chd5 to loci lacking the active mark H3K4me3 and also identify Chd5 targets implicated in cancer. Chd5 mutations that abrogate H3 binding are unable to inhibit proliferation or transcriptionally modulate target genes, which leads to tumorigenesis in vivo. Unlike wild-type Chd5, Chd5-PHD mutants are unable to induce differentiation or efficiently suppress the growth of human neuroblastoma in vivo. Our work defines Chd5 as an N-terminally unmodified H3-binding protein and provides functional evidence that this interaction orchestrates chromatin-mediated transcriptional programs critical for tumor suppression.