High genomic instability predicts survival in metastatic high-risk neuroblastoma

17q Gain in Neuroblastoma: A Review of Clinical and Biological Implications

Neuroblastoma (NB) is the most frequent extracranial solid childhood tumor. Despite advances in the understanding and treatment of this disease, the prognosis in cases of high-risk NB is still poor. 17q gain has been shown to be the most frequent genomic alteration in NB. However, the significance of this remains unclear because of its high frequency and association with other genetic modifications, particularly segmental chromosomal aberrations, 1p and 11q deletions, and MYCN amplification, all of which are also associated with a poor clinical prognosis. This work reviewed the evidence on the clinical and biological significance of 17q gain. It strongly supports the significance of 17q gain in the development of NB and its importance as a clinically relevant marker. However, it is crucial to distinguish between whole and partial chromosome 17q gains. The most important breakpoints appear to be at 17q12 and 17q21. The former distinguishes between whole and partial chromosome 17q gain; the latter is a site of IGF2BP1 and NME1 genes that appear to be the main oncogenes responsible for the functional effects of 17q gain.

ViLoN-a multi-layer network approach to data integration demonstrated for patient stratification

With more and more data being collected, modern network representations exploit the complementary nature of different data sources as well as similarities across patients. We here introduce the Variation of information fused Layers of Networks algorithm (ViLoN), a novel network-based approach for the integration of multiple molecular profiles. As a key innovation, it directly incorporates prior functional knowledge (KEGG, GO). In the constructed network of patients, patients are represented by networks of pathways, comprising genes that are linked by common functions and joint regulation in the disease. Patient stratification remains a key challenge both in the clinic and for research on disease mechanisms and treatments. We thus validated ViLoN for patient stratification on multiple data type combinations (gene expression, methylation, copy number), showing substantial improvements and consistently competitive performance for all. Notably, the incorporation of prior functional knowledge was critical for good results in the smaller cohorts (rectum adenocarcinoma: 90, esophageal carcinoma: 180), where alternative methods failed.

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.

Circular RNA circKIF2A Contributes to the Progression of Neuroblastoma Through Regulating PRPS1 Expression by Sponging miR-377-3p

Neuroblastoma is a malignant tumor originating from the primitive neural crest. Circular RNA (circRNA) Kinesin Superfamily Protein 2A (circKIF2A, also known as hsa_circ_0129276) has been reported to be upregulated in neuroblastoma. However, the molecular mechanism of circKIF2A participated in neuroblastoma is poorly defined. We analyzed the expression levels of circKIF2A, microRNA-377-3p (miR-377-3p), and phosphoribosyl pyrophosphate synthetase 1 (PRPS1) in neuroblastoma tissues and cell lines (SK-N-AS and LAN-6) and explored their roles. The expression levels of CircKIF2A and PRPS1 were increased and that of miR-377-3p were decreased in 21 neuroblastoma tissues and cells. Functionally, the silencing of circKIF2A inhibited cell proliferation, migration, invasion, and glycolysis, boosted apoptosis in neuroblastoma cells in vitro, and blocked the growth of subcutaneously transplanted tumors in nude mice. Mechanically, circKIF2A could work as a sponge of miR-377-3p to enhance PRPS1 expression. CircKIF2A knockdown impedes cell proliferation, metastasis, and glycolysis partly by regulating the miR-377-3p/PRPS1 axis, suggesting that targeting circKIF2A can be a feasible therapeutic strategy for neuroblastoma.

Imbalance between genomic gain and loss identifies high-risk neuroblastoma patients with worse outcomes

Survival in high-risk neuroblastoma (HR-NB) patients remains poor despite multimodal treatment. We aimed to identify HR-NB patients with worse outcomes by analyzing the genomic instability derived from segmental chromosomal aberrations. We calculated 3 genomic instability indexes for primary tumor SNP array profiles from 127 HR-NB patients: (1) Copy number aberration burden (%gains_length+%losses_length), (2) copy number load (CNL) (%gains_length-%losses_length) and (3) net genomic load (NGL) (%gains_amount-%losses_amount). Tumors were classified according to positive or negative CNL and NGL genomic subtypes. The impact of the genomic instability indexes on overall survival (OS) was assessed with Cox regression. We identified 38% of HR-NB patients with poor 5-year OS. A negative CNL genomic background was related to poor prognosis in patients ≥18 months showing tumors with homogeneous MYCN amplification (9.5% survival probability, P < 0.05) and patients with non-MYCN amplified NB (18.8% survival probability related to >2.4% CNL, P < 0.01). A positive CNL genomic background was associated with worse outcome in patients with heterogeneous MYCN amplification (22.5% survival probability, P < 0.05). We conclude that characterizing a tumor genomic background according to predominance of genome gained or lost contributes toward improved outcome prediction and brings greater insight into the tumor biology of HR-NB patients.

Genetic predisposition and chromosome instability in neuroblastoma

Neuroblastoma (NB) is a pediatric tumor of embryonic origin. About 1-2% of all NBs are familial cases, and genetic predisposition is suspected for the remaining cases. During the last decade, genome-wide association studies (GWAS) and high-throughput sequencing approaches have been used to identify associations among common and rare genetic variants and NB risk. Substantial data has been produced by large patient cohorts that implicate various genes in NB tumorigenesis, such as CASC15, BARD1, CHEK2, LMO1, LIN28B, AXIN2, BRCA1, TP53, SMARCA4, and CDK1NB. NB, as well as other pediatric cancers, has few recurrent mutations but several copy number variations (CNVs). Almost all NBs show both numerical and structural CNVs. The proportion between numerical and structural CNVs differs between localized and metastatic tumors, with a greater prevalence of structural CNVs in metastatic NB. This genomic chaos frequently identified in NBs suggests that chromosome instability (CIN) could be one of the major actors in NB oncogenesis. Interestingly, many NB-predisposing variants occur in genes involved in the control of genome stability, mitosis, and normal chromosome separation. Here, we discuss the relationship between genetic predisposition and CIN in NB.

Should we keep rocking? Portraits from targeting Rho kinases in cancer

Cancer targeted therapy, either alone or in combination with conventional chemotherapy, could allow the survival of patients with neoplasms currently considered incurable. In recent years, the dysregulation of the Rho-associated coiled-coil kinases (ROCK1 and ROCK2) has been associated with increased metastasis and poorer patient survival in several tumor types, and due to their essential roles in regulating the cytoskeleton, have gained popularity and progressively been researched as targets for the development of novel anti-cancer drugs. Nevertheless, in a pediatric scenario, the influence of both isoforms on prognosis remains a controversial issue. In this review, we summarize the functions of ROCKs, compile their roles in human cancer and their value as prognostic factors in both, adult and pediatric cancer. Moreover, we provide the up-to-date advances on their pharmacological inhibition in pre-clinical models and clinical trials. Alternatively, we highlight and discuss detrimental effects of ROCK inhibition provoked not only by the action on off-targets, but most importantly, by pro-survival effects on cancer stem cells, dormant cells, and circulating tumor cells, along with cell-context or microenvironment-dependent contradictory responses. Together these drawbacks represent a risk for cancer cell dissemination and metastasis after anti-ROCK intervention, a caveat that should concern scientists and clinicians.

Hormones Secretion and Rho GTPases in Neuroendocrine Tumors

Neuroendocrine tumors (NETs) belong to a heterogeneous group of neoplasms arising from hormone secreting cells. These tumors are often associated with a dysfunction of their secretory activity. Neuroendocrine secretion occurs through calcium-regulated exocytosis, a process that is tightly controlled by Rho GTPases family members. In this review, we compiled the numerous mutations and modification of expression levels of Rho GTPases or their regulators (Rho guanine nucleotide-exchange factors and Rho GTPase-activating proteins) that have been identified in NETs. We discussed how they might regulate neuroendocrine secretion.

Sjögren syndrome/scleroderma autoantigen 1 is a direct Tankyrase binding partner in cancer cells

Sjögren syndrome/scleroderma autoantigen 1 (SSSCA1) was first described as an auto-antigen over-expressed in Sjögren’s syndrome and in scleroderma patients. SSSCA1 has been linked to mitosis and centromere association and as a potential marker candidate in diverse solid cancers. Here we characterize SSSCA1 for the first time, to our knowledge, at the molecular, structural and subcellular level. We have determined the crystal structure of a zinc finger fold, a zinc ribbon domain type 2 (ZNRD2), at 2.3 Å resolution. We show that the C-terminal domain serves a dual function as it both behaves as the interaction site to Tankyrase 1 (TNKS1) and as a nuclear export signal. We identify TNKS1 as a direct binding partner of SSSCA1, map the binding site to TNKS1 ankyrin repeat cluster 2 (ARC2) and thus define a new binding sequence. We experimentally verify and map a new nuclear export signal sequence in SSSCA1.

Perdreau-Dahl et al. systematically characterise Sjögren syndrome/scleroderma autoantigen 1 at the molecular, structural and subcellular level. They show that the C-terminal domain serves a dual function as it both behaves as the interaction site to Tankyrase 1 and as a nuclear export signal.

Gene signatures associated with genomic aberrations predict prognosis in neuroblastoma

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Role of Surgery in High-risk Neuroblastoma

Although intensive multimodal treatment has improved outcomes for patients with high-risk neuroblastoma, the specific role of primary tumor resection remains controversial. Many studies have been designed to determine whether the extent of surgical resection impacts survival; however, these reports have demonstrated conflicting results. There is also ongoing debate regarding the timing of primary tumor resection, with subtle differences in the approach between the large pediatric oncology cooperative consortia. Most of the published literature to date has been approached from a surgical viewpoint. Although most evidence supports surgery as part of the local control approach for high-risk neuroblastoma, recommendations for timing and extent of surgical resection are not consistent. This review summarizes our current understanding from the perspectives of both the pediatric oncologist and pediatric surgeons and discusses how the objectives of neuroblastoma primary surgical resection are different from that of other malignancies. Furthermore, this commentary will address how retrospective surgical outcome data may be interpreted in the setting of modern era high-risk neuroblastoma treatment.

Bootstrap Bias Corrected Cross Validation Applied to Super Learning

Super learner algorithm can be applied to combine results of multiple base learners to improve quality of predictions. The default method for verification of super learner results is by nested cross validation; however, this technique is very expensive computationally.

It has been proposed by Tsamardinos et al., that nested cross validation can be replaced by resampling for tuning hyper-parameters of the learning algorithms. The main contribution of this study is to apply this idea to verification of super learner. We compare the new method with other verification methods, including nested cross validation.

Tests were performed on artificial data sets of diverse size and on seven real, biomedical data sets. The resampling method, called Bootstrap Bias Correction, proved to be a reasonably precise and very cost-efficient alternative for nested cross validation.

Chromosome band 11q23 deletion predicts poor prognosis in bone marrow metastatic neuroblastoma patients without MYCN amplification

Background

Interphase fluorescence in situ hybridization (FISH) of bone marrow cells has been confirmed to be a direct and valid method to assess the v-myc avian myelocytomatosis viral oncogene neuroblastoma derived homolog (MYCN) amplification in patients with bone marrow metastatic neuroblastoma. MYCN amplification alone, however, is insufficient for pretreatment risk stratification. Chromosome band 11q23 deletion has recently been included in the risk stratification of neuroblastoma. In the present study, we aimed to evaluate the biological characteristics and prognostic impact of 11q23 deletion and MYCN amplification in patients with bone marrow metastatic neuroblastoma.

Methods

We analyzed the MYCN and 11q23 statuses of 101 patients with bone marrow metastatic neuroblastoma using interphase FISH of bone marrow cells. We specifically compared the biological characteristics and prognostic impact of both aberrations.

Results

MYCN amplification and 11q23 deletion were seen in 12 (11.9%) and 40 (39.6%) patients. The two markers were mutually exclusive. MYCN amplification occurred mainly in patients with high lactate dehydrogenase (LDH) and high neuron-specific enolase (NSE) levels (both P < 0.001), and MYCN-amplified patients had more events (tumor relapse, progression, or death) than MYCN-normal patients (P = 0.004). 11q23 deletion was associated only with age (P = 0.001). Patients with MYCN amplification had poorer outcomes than those with normal MYCN (3-year event-free survival [EFS] rate: 8.3 ± 8.0% vs. 43.8 ± 8.5%, P < 0.001; 3-year overall survival [OS] rate: 10.4 ± 9.7% vs. 63.5% ± 5.7%, P < 0.001). 11q23 deletion reflected a poor prognosis only for patients with normal MYCN (3-year EFS rate: 34.3 ± 9.5% vs. 53.4 ± 10.3%, P = 0.037; 3-year OS rate: 42.9 ± 10.4% vs. 75.9 ± 6.1%, P = 0.048). Those with both MYCN amplification and 11q23 deletion had the worst outcome (P < 0.001).

Conclusions

Chromosome band 11q23 deletion predicts poor prognosis only in bone marrow metastatic neuroblastoma patients without MYCN amplification. Combined assessment of the two markers was much superior to single-marker assessment in recognizing the patients at a high risk of disease progression.

Patient-derived organoids (PDOs) as a novel in vitro model for neuroblastoma tumours

BACKGROUND

Neuroblastoma (NB) is a paediatric tumour of the sympathetic nervous system. Half of all cases are defined high-risk with an overall survival less than 40% at 5 years from diagnosis. The lack of in vitro models able to recapitulate the intrinsic heterogeneity of primary NB tumours has hindered progress in understanding disease pathogenesis and therapy response.

METHODS

Here we describe the establishment of 6 patient-derived organoids (PDOs) from cells of NB tumour biopsies capable of self-organising in a structure resembling the tissue of origin.

RESULTS

PDOs recapitulate the histological architecture typical of the NB tumour. Moreover, PDOs expressed NB specific markers such as neural cell adhesion molecules, NB84 antigen, synaptophysin (SYP), chromogranin A (CHGA) and neural cell adhesion molecule NCAM (CD56). Analyses of whole genome genotyping array revealed that PDOs maintained patient-specific chromosomal aberrations such as MYCN amplification, deletion of 1p and gain of chromosome 17q. Furthermore, the PDOs showed stemness features and retained cellular heterogeneity reflecting the high heterogeneity of NB tumours.

CONCLUSIONS

We were able to create a novel preclinical model for NB exhibiting self-renewal property and allowing to obtain a reservoir of NB patients' biological material useful for the study of NB molecular pathogenesis and to test drugs for personalised treatments.

Unfavorable Outcome of Neuroblastoma in Patients With 2p Gain

Background: Amplification of the MYCN oncogene is the most unfavorable genetic factor in neuroblastoma patients. However, knowledge about the clinical impact of low-level multiplication of MYCN is still insufficient. Therefore, we aimed to investigate the disease course in patients with different copy number status of MYCN. Materials and Methods: We examined 105 children diagnosed with neuroblastoma from 2010 to 2018 in five pediatric oncology centers in Poland. We determined the MYCN status at diagnosis by the interphase FISH examination and assessed the clinical outcome in patients. Results: A total of 35% of tumors presented with chromosome 2 numerical changes, 20% had MYCN amplification and 16% revealed 2p gain. Unexpectedly, we observed very low overall survival and event free survival (EFS) rates in neuroblastomas with 2p gain, which were comparable with patients with MYCN amplification. Conclusions: The 2p gain alteration should be reported as a strong unfavorable prognostic marker in neuroblastoma patients.

Neuroblastoma by chance

Neuroblastoma is a pediatric cancer of embryonic origin from neural crest cells. Neuroblastoma has a great medical and social impact because it is occurring with major frequency in pre-scholar age with metastatic disease showing less than 40% of survival at 5-years. In children, metastatic neuroblastoma has very few recurrent mutations but several chromosome structural copy variations. The tumorigenesis of neuroblastoma is still largely unknown; however recently, genomic wide association studies have shown that several gene allelic variants are associated with neuroblastoma predisposition. Many of these gene variants are related to maintaining the chromatin and mitosis integrity. In the present report, I suggest that neuroblastoma predisposing alleles may match by chance influencing the chromatin structure already during the early phases of embryonic life and inducing chromosome instability and structural damages.

The challenge of defining "ultra-high-risk" neuroblastoma

Given the biological and clinical heterogeneity of neuroblastoma, risk stratification is vital to determining appropriate treatment. Historically, most patients with high-risk neuroblastoma (HR-NBL) have been treated uniformly without further stratification. Attempts have been made to identify factors that can be used to risk stratify these patients and to characterize an "ultra-high-risk" (UHR) subpopulation with particularly poor outcome. However, among published data, there is a lack of consensus in the definition of the UHR population and heterogeneity in the endpoints and statistical methods used. This review summarizes our current understanding of stratification of HR-NBL and discusses the complex issues in defining UHR neuroblastoma.

Integrative analysis based on survival associated co-expression gene modules for predicting Neuroblastoma patients' survival time

Background

More than 90% of neuroblastoma patients are cured in the low-risk group while only less than 50% for those with high-risk disease can be cured. Since the high-risk patients still have poor outcomes, we need more accurate stratification to establish an individualized precise treatment plan for the patients to improve the long-term survival rate.

Results

We focus on extracting features and providing a workflow to improve survival prediction for neuroblastoma patients. With a workflow for gene co-expression network (GCN) mining in microarray and RNA-Seq datasets, we extracted molecular features from each co-expressed module and summarized them into eigengenes. Then we adopted the lasso-regularized Cox proportional hazards model to select the most informative eigengene features regarding association to the risk of metastasis. Nine eigengenes were selected which show strong association with patient survival prognosis. All of the nine corresponding gene modules also have highly enriched biological functions or cytoband locations. Three of them are unique modules to RNA-Seq data, which complement the modules from microarray data in terms of survival prognosis. We then merged all eigengenes from these unique modules and used an integrative method called Similarity Network Fusion to test the prognostic power of these eigengenes for prognosis. The prognostic accuracies are significantly improved as compared to using all eigengenes, and a subgroup of patients with very poor survival rate was identified.

Conclusions

We first compared GCNs mined from microarray and RNA-seq data. We discovered that each data modality yields unique GCNs, which are enriched with clear biological functions. Then we do module unique analysis and use lasso-cox model to select survival-associated eigengenes. Integration of unique and survival-associated eigengenes from both data types provides complementary information that leads to more accurate survival prognosis.

Reviewers

Reviewed by Susmita Datta, Marco Chierici and Dimitar Vassilev.

Electronic supplementary material

The online version of this article (10.1186/s13062-018-0229-2) contains supplementary material, which is available to authorized users.

Chromosome instability in neuroblastoma

Neuroblastoma is a neural crest-derived tumor that accounts for 7-10% of all malignancies in children and ~15% of all childhood cancer-associated mortalities. Approximately 50% of patients are characterized as high-risk (HR) and have an overall survival of <40% at 5 years from diagnosis. HR patients with unfavorable prognosis exhibit several structural copy number variations (CNVs), whereas localized tumors belonging to patients in the low- and intermediate-risk classes, have favorable outcomes and display several numerical CNVs. Taken together these results are indicative of chromosome instability (CIN) in neuroblastoma tumor cells. The present review discusses multiple aspects of CIN including methods of measuring CIN, CIN targeting as a therapeutic strategy in cancer and the effects of CIN in neuroblastoma development and aggressiveness with particular emphasis on the CIN gene signature associated with HR neuroblastoma patients.

Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma

High-risk neuroblastoma is a very aggressive disease, with excessive tumor growth and poor outcomes. A proper stratification of the high-risk patients by prognostic outcome is important for treatment. However, there is still a lack of survival stratification for the high-risk neuroblastoma. To fill the gap, we adopt a deep learning algorithm, Autoencoder, to integrate multi-omics data, and combine it with K-means clustering to identify two subtypes with significant survival differences. By comparing the Autoencoder with PCA, iCluster, and DGscore about the classification based on multi-omics data integration, Autoencoder-based classification outperforms the alternative approaches. Furthermore, we also validated the classification in two independent datasets by training machine-learning classification models, and confirmed its robustness. Functional analysis revealed that MYCN amplification was more frequently occurred in the ultra-high-risk subtype, in accordance with the overexpression of MYC/MYCN targets in this subtype. In summary, prognostic subtypes identified by deep learning-based multi-omics integration could not only improve our understanding of molecular mechanism, but also help the clinicians make decisions.

Integration of multiple types of genetic markers for neuroblastoma may contribute to improved prediction of the overall survival

Background

Modern experimental techniques deliver data sets containing profiles of tens of thousands of potential molecular and genetic markers that can be used to improve medical diagnostics. Previous studies performed with three different experimental methods for the same set of neuroblastoma patients create opportunity to examine whether augmenting gene expression profiles with information on copy number variation can lead to improved predictions of patients survival. We propose methodology based on comprehensive cross-validation protocol, that includes feature selection within cross-validation loop and classification using machine learning. We also test dependence of results on the feature selection process using four different feature selection methods.

Results

The models utilising features selected based on information entropy are slightly, but significantly, better than those using features obtained with t-test. The synergy between data on genetic variation and gene expression is possible, but not confirmed. A slight, but statistically significant, increase of the predictive power of machine learning models has been observed for models built on combined data sets. It was found while using both out of bag estimate and in cross-validation performed on a single set of variables. However, the improvement was smaller and non-significant when models were built within full cross-validation procedure that included feature selection within cross-validation loop. Good correlation between performance of the models in the internal and external cross-validation was observed, confirming the robustness of the proposed protocol and results.

Conclusions

We have developed a protocol for building predictive machine learning models. The protocol can provide robust estimates of the model performance on unseen data. It is particularly well-suited for small data sets. We have applied this protocol to develop prognostic models for neuroblastoma, using data on copy number variation and gene expression. We have shown that combining these two sources of information may increase the quality of the models. Nevertheless, the increase is small and larger samples are required to reduce noise and bias arising due to overfitting.

Reviewers

This article was reviewed by Lan Hu, Tim Beissbarth and Dimitar Vassilev.

Somatic mutations in specific and connected subpathways are associated with short neuroblastoma patients' survival and indicate proteins targetable at onset of disease

Neuroblastoma (NB) is an embryonic malignancy of the sympathetic nervous system with heterogeneous biological, morphological, genetic and clinical characteristics. Although genomic studies revealed the specific biological features of NB pathogenesis useful for new therapeutic approaches, the improvement of high-risk (HR)-NB patients overall survival remains unsatisfactory. To further clarify the biological basis of disease aggressiveness, we used whole-exome sequencing to examine the genomic landscape of HR-NB patients at stage M with short survival (SS) and long survival (LS). Only a few genes, including SMARCA4, SMO, ZNF44 and CHD2, were recurrently and specifically mutated in the SS group, confirming the low recurrence of common mutations in this tumor. A systems biology approach revealed that in the two patient groups, mutations occurred in different pathways. Mutated genes (ARHGEF11, CACNA1G, FGF4, PTPRA, PTK2, ANK3, SMO, NTNG2, VCL and NID2) regulate the MAPK pathway associated with the organization of the extracellular matrix, cell motility through PTK2 signaling and matrix metalloproteinase activity. Moreover, we detected mutations in LAMA2, PTK2, LAMA4, and MMP14 genes, impairing MET signaling, in SFI1 and CHD2 involved in centrosome maturation and chromosome remodeling, in AK7 and SPTLC2, which regulate the metabolism of nucleotides and lipoproteins, and in NALCN, SLC12A1, SLC9A9, which are involved in the transport of small molecules. Notably, connected networks of somatically mutated genes specific for SS patients were identified. The detection of mutated genes present at the onset of disease may help to address an early treatment of HR-NB patients using FDA-approved compounds targeting the deregulated pathways.

Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach

BACKGROUND

One of the main current challenges in computational biology is to make sense of the huge amounts of multidimensional experimental data that are being produced. For instance, large cohorts of patients are often screened using different high-throughput technologies, effectively producing multiple patient-specific molecular profiles for hundreds or thousands of patients.

RESULTS

We propose and implement a network-based method that integrates such patient omics data into Patient Similarity Networks. Topological features derived from these networks were then used to predict relevant clinical features. As part of the 2017 CAMDA challenge, we have successfully applied this strategy to a neuroblastoma dataset, consisting of genomic and transcriptomic data. In particular, we observe that models built on our network-based approach perform at least as well as state of the art models. We furthermore explore the effectiveness of various topological features and observe, for instance, that redundant centrality metrics can be combined to build more powerful models.

CONCLUSION

We demonstrate that the networks inferred from omics data contain clinically relevant information and that patient clinical outcomes can be predicted using only network topological data.

REVIEWERS

This article was reviewed by Yang-Yu Liu, Tomislav Smuc and Isabel Nepomuceno.

Multi-omics integration for neuroblastoma clinical endpoint prediction

BACKGROUND

High-throughput methodologies such as microarrays and next-generation sequencing are routinely used in cancer research, generating complex data at different omics layers. The effective integration of omics data could provide a broader insight into the mechanisms of cancer biology, helping researchers and clinicians to develop personalized therapies.

RESULTS

In the context of CAMDA 2017 Neuroblastoma Data Integration challenge, we explore the use of Integrative Network Fusion (INF), a bioinformatics framework combining a similarity network fusion with machine learning for the integration of multiple omics data. We apply the INF framework for the prediction of neuroblastoma patient outcome, integrating RNA-Seq, microarray and array comparative genomic hybridization data. We additionally explore the use of autoencoders as a method to integrate microarray expression and copy number data.

CONCLUSIONS

The INF method is effective for the integration of multiple data sources providing compact feature signatures for patient classification with performances comparable to other methods. Latent space representation of the integrated data provided by the autoencoder approach gives promising results, both by improving classification on survival endpoints and by providing means to discover two groups of patients characterized by distinct overall survival (OS) curves.

REVIEWERS

This article was reviewed by Djork-Arné Clevert and Tieliu Shi.

Whole exome sequencing identified sixty-five coding mutations in four neuroblastoma tumors

Neuroblastoma is a pediatric tumor characterized by histologic heterogeneity, and accounts for ~15% of childhood deaths from cancer. The five-year survival for patients with high-risk stage 4 disease has not improved in two decades. We used whole exome sequencing (WES) to identify mutations present in three independent high-risk stage 4 neuroblastoma tumors (COA/UAB-3, COA/UAB -6 and COA/UAB -8) and a stage 3 tumor (COA/UAB-14). Among the four tumors WES analysis identified forty-three mutations that had not been reported previously, one of which was present in two of the four tumors. WES analysis also corroborated twenty-two mutations that were reported previously. No single mutation occurred in all four tumors or in all stage 4 tumors. Three of the four tumors harbored genes with CADD scores ≥20, indicative of mutations associated with human pathologies. The average depth of coverage ranged from 39.68 to 90.27, with >99% sequences mapping to the genome. In summary, WES identified sixty-five coding mutations including forty-three mutations not reported previously in primary neuroblastoma tumors. The three stage 4 tumors contained mutations in genes encoding protein products that regulate immune function or cell adhesion and tumor cell metastasis.

Rho-associated kinase is a therapeutic target in neuroblastoma

Neuroblastoma is a peripheral neural system tumor that originates from the neural crest and is the most common and deadly tumor of infancy. Here we show that neuroblastoma harbors frequent mutations of genes controlling the Rac/Rho signaling cascade important for proper migration and differentiation of neural crest cells during neuritogenesis. RhoA is activated in tumors from neuroblastoma patients, and elevated expression of Rho-associated kinase (ROCK)2 is associated with poor patient survival. Pharmacological or genetic inhibition of ROCK1 and 2, key molecules in Rho signaling, resulted in neuroblastoma cell differentiation and inhibition of neuroblastoma cell growth, migration, and invasion. Molecularly, ROCK inhibition induced glycogen synthase kinase 3β-dependent phosphorylation and degradation of MYCN protein. Small-molecule inhibition of ROCK suppressed MYCN-driven neuroblastoma growth in TH-MYCN homozygous transgenic mice and MYCN gene-amplified neuroblastoma xenograft growth in nude mice. Interference with Rho/Rac signaling might offer therapeutic perspectives for high-risk neuroblastoma.

Growth, progression and chromosome instability of Neuroblastoma: a new scenario of tumorigenesis?

BACKGROUND

Neuroblastoma is a pediatric cancer with a low survival rate of patients with metastatic stage 4 disease. Tumor aggressiveness and progression have been associated with structural copy number variations (CNVs) that are observed in malignant cells. In contrast, localized Neuroblastomas, which are associated with a low number of structural CNVs but frequent numerical CNVs, are less aggressive, and patients have good outcomes. Finally, whole-genome and whole-exome sequencing of Neuroblastoma tissues have shown few damaging mutations in these tumors.

CONCLUSIONS

In the present report it is proposed that chromosome instability (CIN) plays a major role in Neuroblastoma tumorigenesis and that CIN is already present in the early phases of tumor development. High CIN can promote several types of chromosomal damage including chromothripsis, gene deletion, amplification and rearrangements, which deregulate gene expression. Indeed, gene rearrangements have been reported as a new scenario in the development of Neuroblastoma, which supports the hypothesis that CIN is an early step preliminary to the late catastrophic events leading to tumor development.

Neuroblastoma (Peripheral neuroblastic tumours)

Peripheral neuroblastic tumours (PNTs), a family of tumours arising in the embryonal remnants of the sympathetic nervous system, account for 7-10% of all tumours in children. In two-thirds of cases, PNTs originate in the adrenal glands or the retroperitoneal ganglia. At least one third present metastases at onset, with bone and bone marrow being the most frequent metastatic sites. Disease extension, MYCN oncogene status and age are the most relevant prognostic factors, and their influence on outcome have been considered in the design of the recent treatment protocols. Consequently, the probability of cure has increased significantly in the last two decades. In children with localised operable disease, surgical resection alone is usually a sufficient treatment, with 3-year event-free survival (EFS) being greater than 85%. For locally advanced disease, primary chemotherapy followed by surgery and/or radiotherapy yields an EFS of around 75%. The greatest problem is posed by children with metastatic disease or amplified MYCN gene, who continue to do badly despite intensive treatments. Ongoing trials are exploring the efficacy of new drugs and novel immunological approaches in order to save a greater number of these patients.

Genome instability model of metastatic neuroblastoma tumorigenesis by a dictionary learning algorithm

Background

Metastatic neuroblastoma (NB) occurs in pediatric patients as stage 4S or stage 4 and it is characterized by heterogeneous clinical behavior associated with diverse genotypes. Tumors of stage 4 contain several structural copy number aberrations (CNAs) rarely found in stage 4S. To date, the NB tumorigenesis is not still elucidated, although it is evident that genomic instability plays a critical role in the genesis of the tumor. Here we propose a mathematical approach to decipher genomic data and we provide a new model of NB metastatic tumorigenesis.

Method

We elucidate NB tumorigenesis using Enhanced Fused Lasso Latent Feature Model (E-FLLat) modeling the array comparative chromosome hybridization (aCGH) data of 190 metastatic NBs (63 stage 4S and 127 stage 4). This model for aCGH segmentation, based on the minimization of functional dictionary learning (DL), combines several penalties tailored to the specificities of aCGH data. In DL, the original signal is approximated by a linear weighted combination of atoms: the elements of the learned dictionary.

Results

The hierarchical structures for stage 4S shows at the first level of the oncogenetic tree several whole chromosome gains except to the unbalanced gains of 17q, 2p and 2q. Conversely, the high CNA complexity found in stage 4 tumors, requires two different trees. Both stage 4 oncogenetic trees are marked diverged, up to five sublevels and the 17q gain is the most common event at the first level (2/3 nodes). Moreover the 11q deletion, one of the major unfavorable marker of disease progression, occurs before 3p loss indicating that critical chromosome aberrations appear at early stages of tumorigenesis. Finally, we also observed a significant (p = 0.025) association between patient age and chromosome loss in stage 4 cases.

Conclusion

These results led us to propose a genome instability progressive model in which NB cells initiate with a DNA synthesis uncoupled from cell division, that leads to stage 4S tumors, primarily characterized by numerical aberrations, or stage 4 tumors with high levels of genome instability resulting in complex chromosome rearrangements associated with high tumor aggressiveness and rapid disease progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0132-y) contains supplementary material, which is available to authorized users.

Neuroblastoma after childhood: prognostic relevance of segmental chromosome aberrations, ATRX protein status, and immune cell infiltration

Neuroblastoma (NB) is a common malignancy in children but rarely occurs during adolescence or adulthood. This subgroup is characterized by an indolent disease course, almost uniformly fatal, yet little is known about the biologic characteristics. The aim of this study was to identify differential features regarding DNA copy number alterations, α-thalassemia/mental retardation syndrome X-linked (ATRX) protein expression, and the presence of tumor-associated inflammatory cells. Thirty-one NB patients older than 10 years who were included in the Spanish NB Registry were considered for the current study; seven young and middle-aged adult patients (range 18-60 years) formed part of the cohort. We performed single nucleotide polymorphism arrays, immunohistochemistry for immune markers (CD4, CD8, CD20, CD11b, CD11c, and CD68), and ATRX protein expression. Assorted genetic profiles were found with a predominant presence of a segmental chromosome aberration (SCA) profile. Preadolescent and adolescent NB tumors showed a higher number of SCA, including 17q gain and 11q deletion. There was also a marked infiltration of immune cells, mainly high and heterogeneous, in young and middle-aged adult tumors. ATRX negative expression was present in the tumors. The characteristics of preadolescent, adolescent, young adult, and middle-aged adult NB tumors are different, not only from childhood NB tumors but also from each other. Similar examinations of a larger number of such tumor tissues from cooperative groups should lead to a better older age–dependent tumor pattern and to innovative, individual risk-adapted therapeutic approaches for these patients.

Influence of segmental chromosome abnormalities on survival in children over the age of 12 months with unresectable localised peripheral neuroblastic tumours without MYCN amplification

Background:

The prognostic impact of segmental chromosome alterations (SCAs) in children older than 1 year, diagnosed with localised unresectable neuroblastoma (NB) without MYCN amplification enrolled in the European Unresectable Neuroblastoma (EUNB) protocol is still to be clarified, while, for other group of patients, the presence of SCAs is associated with poor prognosis.

Methods:

To understand the role of SCAs we performed multilocus/pangenomic analysis of 98 tumour samples from patients enrolled in the EUNB protocol.

Results:

Age at diagnosis was categorised into two groups using 18 months as the age cutoff. Significant difference in the presence of SCAs was seen in tumours of patients between 12 and 18 months and over 18 months of age at diagnosis, respectively (P=0.04). A significant correlation (P=0.03) was observed between number of SCAs per tumour and age. Event-free (EFS) and overall survival (OS) were calculated in both age groups, according to both the presence and number of SCAs. In older patients, a poorer survival was associated with the presence of SCAs (EFS=46% vs 75%, P=0.023; OS=66.8% vs 100%, P=0.003). Moreover, OS of older patients inversely correlated with number of SCAs (P=0.002). Finally, SCAs provided additional prognostic information beyond histoprognosis, as their presence was associated with poorer OS in patients over 18 months with unfavourable International Neuroblastoma Pathology Classification (INPC) histopathology (P=0.018).

Conclusions:

The presence of SCAs is a negative prognostic marker that impairs outcome of patients over the age of 18 months with localised unresectable NB without MYCN amplification, especially when more than one SCA is present. Moreover, in older patients with unfavourable INPC tumour histoprognosis, the presence of SCAs significantly affects OS.

N-Myc differentially regulates expression of MXI1 isoforms in neuroblastoma

Amplification of the MYCN proto-oncogene is associated with a poor prognosis in patients with metastatic neuroblastoma (NB). MYCN encodes the N-Myc protein, a transcriptional regulator that dimerizes with the Max transcription factor, binds to E-box DNA sequences, and regulates genes involved in cell growth and apoptosis. Overexpression of N-Myc leads to transcriptional activation and an increase in NB cell proliferation. Mxi1, a member of the Myc family of transcriptional regulators, also binds to Max. However, Mxi1 is a transcriptional repressor and inhibits proliferation of NB cells, suggesting that Mxi1 functions as an N-Myc antagonist. Our laboratory previously identified Mxi1-0, an alternatively transcribed Mxi1 isoform. Mxi1-0 has properties distinct from those of Mxi1; in contrast to Mxi1, Mxi1-0 is unable to suppress c-Myc-dependent transcription. We now show that Mxi1-0 expression increases in response to MYCN overexpression in NB cells, with a positive correlation between MYCN and MXI1-0 RNA levels. We also show that N-Myc expression differentially regulates the MXI1 and MXI1-0 promoters: Increased MYCN expression suppresses MXI1 promoter activity while enhancing transcription through the MXI1-0 promoter. Finally, induction of Mxi1-0 leads to increased proliferation, whereas expression of Mxi1 inhibits cell growth, indicating differential roles for these two proteins. These data suggest that N-Myc differentially regulates the expression of MXI1 and MXI1-0 and can alter the balance between the two transcription factors. Furthermore, MXI1-0 appears to be a downstream target of MYCN-dependent signaling pathways and may contribute to N-Myc-dependent cell growth and proliferation.

Cancer subclonal genetic architecture as a key to personalized medicine

The future of personalized oncological therapy will likely rely on evidence-based medicine to integrate all of the available evidence to delineate the most efficacious treatment option for the patient. To undertake evidence-based medicine through use of targeted therapy regimens, identification of the specific underlying causative mutation(s) driving growth and progression of a patient's tumor is imperative. Although molecular subtyping is important for planning and treatment, intraclonal genetic diversity has been recently highlighted as having significant implications for biopsy-based prognosis. Overall, delineation of the clonal architecture of a patient's cancer and how this will impact on the selection of the most efficacious therapy remain a topic of intense interest.

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.

Epidemiological and clinical characteristics of neuroblastoma in southern iran

BACKGROUND

Neuroblastoma is the third most common malignancy in children with a very heterogeneous feature. In this study, the epidemiological and clinical characteristics of children with neuroblastoma treated in a referral oncology hospital in Shiraz, Southern Iran, were investigated.

MATERIAL AND METHOD

In this historical cohort study, the medical files of 36 children under 18 years old with neuroblastoma were reviewed, who were admitted to Amir Oncology Hospital in Shiraz, Iran from 2006 to 2013. Overall survival and event free survival (EFS) curves were demonstrated by Kaplan Meier methods. Also the effects of demographic and clinical characteristics of the patients on survival were evaluated by Cox regression model.

RESULTS

The median age of diagnosis was 30 months (age range: from 4 to144 months), with M/F ratio of 63.9%. Over 70% of the patients had stage 4 of neuroblastoma at their initial presentations. Adrenal gland comprised 72.2% of the primary tumor site. The most common presenting symptoms were gastrointestinal and constitutional symptoms. The mean overall survival and EFS were 30.75 and 20.56 months, respectively. Among the different variables analyzed, only liver metastasis had an adverse effect on EFS (p=0.025 Hazard ratios 2.83, CI: 1.14-7.02).

CONCLUSION

This study revealed that the majority of children suffering from neuroblastoma in our center are high stage with disseminated disease at the time of detection. It also warns us about an urgent necessity for holding a re-educational program for general practitioners and pediatricians to review the warning signs of common pediatric cancers such as neuroblastoma.

Fractal dimension of chromatin: potential molecular diagnostic applications for cancer prognosis

Fractal characteristics of chromatin, revealed by light or electron microscopy, have been reported during the last 20 years. Fractal features can easily be estimated in digitalized microscopic images and are helpful for diagnosis and prognosis of neoplasias. During carcinogenesis and tumor progression, an increase of the fractal dimension (FD) of stained nuclei has been shown in intraepithelial lesions of the uterine cervix and the anus, oral squamous cell carcinomas or adenocarcinomas of the pancreas. Furthermore, an increased FD of chromatin is an unfavorable prognostic factor in squamous cell carcinomas of the oral cavity and the larynx, melanomas and multiple myelomas. High goodness-of-fit of the regression line of the FD is a favorable prognostic factor in acute leukemias and multiple myelomas. The nucleus has fractal and power-law organization in several different levels, which might in part be interrelated. Some possible relations between modifications of the chromatin organization during carcinogenesis and tumor progression and an increase of the FD of stained chromatin are suggested. Furthermore, increased complexity of the chromatin structure, loss of heterochromatin and a less-perfect self-organization of the nucleus in aggressive neoplasias are discussed.

Overcoming intratumor heterogeneity of polygenic cancer drug resistance with improved biomarker integration

Improvements in technology and resources are helping to advance our understanding of cancer-initiating events as well as factors involved with tumor progression, adaptation, and evasion of therapy. Tumors are well known to contain diverse cell populations and intratumor heterogeneity affords neoplasms with a diverse set of biologic characteristics that can be used to evolve and adapt. Intratumor heterogeneity has emerged as a major hindrance to improving cancer patient care. Polygenic cancer drug resistance necessitates reconsidering drug designs to include polypharmacology in pursuit of novel combinatorial agents having multitarget activity to overcome the diverse and compensatory signaling pathways in which cancer cells use to survive and evade therapy. Advances will require integration of different biomarkers such as genomics and imaging to provide for more adequate elucidation of the spatially varying location, type, and extent of diverse intratumor signaling molecules to provide for a rationale-based personalized cancer medicine strategy.

Genetic instability and intratumoral heterogeneity in neuroblastoma with MYCN amplification plus 11q deletion

Background/Aim

Genetic analysis in neuroblastoma has identified the profound influence of MYCN amplification and 11q deletion in patients’ prognosis. These two features of high-risk neuroblastoma usually occur as mutually exclusive genetic markers, although in rare cases both are present in the same tumor. The purpose of this study was to characterize the genetic profile of these uncommon neuroblastomas harboring both these high-risk features.

Methods

We selected 18 neuroblastomas with MNA plus 11q loss detected by FISH. Chromosomal aberrations were analyzed using Multiplex Ligation-dependent Probe Amplification and Single Nucleotide Polymorphism array techniques.

Results and Conclusion

This group of tumors has approximately the same high frequency of aberrations as found earlier for 11q deleted tumors. In some cases, DNA instability generates genetic heterogeneity, and must be taken into account in routine genetic diagnosis.