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

SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma

Neuroblastoma is the most devastating extracranial solid malignancy in children. Despite an intense treatment regimen, the prognosis for high-risk neuroblastoma patients remains poor, with less than 40% survival. So far, MYCN amplification status is considered the most prognostic factor but corresponds to only ∼25% of neuroblastoma patients. Therefore, it is essential to identify a better prognosis and therapy response marker in neuroblastoma patients. We applied robust bioinformatic data mining tools, such as weighted gene co-expression network analysis, cisTarget, and single-cell regulatory network inference and clustering on two neuroblastoma patient datasets. We found Sin3A-associated protein 30 (SAP30), a driver transcription factor positively associated with high-risk, progression, stage 4, and poor survival in neuroblastoma patient cohorts. Tumors of high-risk neuroblastoma patients and relapse-specific patient-derived xenografts showed higher SAP30 levels. The advanced pharmacogenomic analysis and CRISPR-Cas9 screens indicated that SAP30 essentiality is associated with cisplatin resistance and further showed higher levels in cisplatin-resistant patient-derived xenograft tumor cell lines. Silencing of SAP30 induced cell death in vitro and led to a reduced tumor burden and size in vivo. Altogether, these results indicate that SAP30 is a better prognostic and cisplatin-resistance marker and thus a potential drug target in high-risk neuroblastoma.

CD20highCD138low tumor-infiltrating lymphocytes predominantly related to cytokine‒cytokine receptor interactions are associated with favorable outcomes in neuroblastoma patients

Recent advances have revealed that the role of the immune system is prominent in the antitumor response. In the present study, it is aimed to provide an expression profile of tumor-infiltrating lymphocytes (TILs), including mature B cells, plasma cells, and their clinical relevance in neuroblastoma. The expression of CD20 and CD138 was analyzed in the Cangelosi786 dataset (n = 769) as a training dataset and in our cohort (n = 120) as a validation cohort. CD20 high expression was positively associated with favorable overall survival (OS) and event-free survival (EFS) (OS: P < 0.001; EFS: P < 0.001) in the training dataset, whereas CD138 high expression was associated with poor OS and EFS (OS: P < 0.001; EFS: P < 0.001) in both the training and validation datasets. Accordingly, a combined pattern of CD20 and CD138 expression was developed, whereby neuroblastoma patients with CD20highCD138low expression had a consistently favorable OS and EFS compared with those with CD20lowCD138high expression in both the training and validation cohorts (P < 0.0001 and P < 0.01, respectively). Examination of potential molecular functions revealed that signaling pathways, including cytokine‒cytokine receptor interactions, chemokine, and the NF-kappa B signaling pathways, were involved. Differentially expressed genes, such as BMP7, IL7R, BIRC3, CCR7, CXCR5, CCL21, and CCL19, predominantly play important roles in predicting the survival of neuroblastoma patients. Our study proposes that a new combination of CD20 and CD138 signatures is associated with neuroblastoma patient survival. The related signaling pathways reflect the close associations among the number of TILs, cytokine abundance and patient outcomes and provide therapeutic insights into neuroblastoma.

Hypoxia-associated markers in the prognosis of oral canine melanoma

Canine oral malignant melanoma (COMM) is the most common neoplasm in the oral cavity characterized by local invasiveness and high metastatic potential. Hypoxia represents a crucial feature of the solid tumor microenvironment promoting cancer progression and drug resistance. Hypoxia-inducible factor-1α (HIF-1α) and its downstream effectors, vascular endothelial growth factor A (VEGF-A), glucose transporter isoform 1 (GLUT1), C-X-C chemokine receptor type 4 (CXCR4), and carbonic anhydrase IX (CAIX), are the main regulators of the adaptive response to low oxygen availability. The prognostic value of these markers was evaluated in 36 COMMs using immunohistochemistry. In addition, the effects of cobalt chloride-mediated hypoxia were evaluated in 1 primary COMM cell line. HIF-1α expression was observed in the nucleus, and this localization correlated with the presence or enhanced expression of HIF-1α-regulated genes at the protein level. Multivariate analysis revealed that in dogs given chondroitin sulfate proteoglycan-4 (CSPG4) DNA vaccine, COMMs expressing HIF-1α, VEGF-A, and CXCR4 were associated with shorter disease-free intervals (DFI) compared with tumors that were negative for these markers (P = .03), suggesting hypoxia can influence immunotherapy response. Western blotting showed that, under chemically induced hypoxia, COMM cells accumulate HIF-1α and smaller amounts of CAIX. HIF-1α induction and stabilization triggered by hypoxia was corroborated by immunofluorescence, showing its nuclear translocation. These findings reinforce the role of an hypoxic microenvironment in tumor progression and patient outcome in COMM, as previously established in several human and canine cancers. In addition, hypoxic markers may represent promising prognostic markers, highlighting opportunities for their use in therapeutic strategies for COMMs.

Silencing of the PHLDA1 leads to global proteome changes and differentiation pathways of human neuroblastoma cells

Neuroblastoma (NB) is the most common extracranial pediatric solid tumor originating from the abnormal development of cells of the sympathoadrenal lineage of the neural crest. Targeting GD2 ganglioside (GD2), a glycolipid expressed on neuroblastoma cells, with GD2 ganglioside-recognizing antibodies affects several pivotal signaling routes that drive or influence the malignant phenotype of the cells. Previously performed gene expression profiling helped us to identify the PHLDA1 (pleckstrin homology-like domain family A member 1) gene as the most upregulated gene in the IMR-32 human neuroblastoma cells treated with the mouse 14G2a monoclonal antibody. Mass spectrometry-based proteomic analyses were applied to better characterize a role of PHLDA1 protein in the response of neuroblastoma cells to chimeric ch14.18/CHO antibody. Additionally, global protein expression profile analysis in the IMR-32 cell line with PHLDA1 silencing revealed the increase in biological functions of mitochondria, accompanied by differentiation-like phenotype of the cells. Moreover, mass spectrometry analysis of the proteins co-immunoprecipitated using anti-PHLDA1-specific antibody, selected a group of possible PHLDA1 binding partners. Also, a more detailed analysis suggested that PHLDA1 interacts with the DCAF7/AUTS2 complex, a key component of neuronal differentiation in vitro. Importantly, our results indicate that PHLDA1 silencing enhances the EGF receptor signaling pathway and combinatory treatment of gefitinib and ch14.18/CHO antibodies might be beneficial for neuroblastoma patients. Data are available via ProteomeXchange with the identifier PXD044319.

The regulations of telomerase reverse transcriptase (TERT) in cancer

Abnormal activation of telomerase occurs in most cancer types, which facilitates escaping from cell senescence. As the key component of telomerase, telomerase reverse transcriptase (TERT) is regulated by various regulation pathways. TERT gene changing in its promoter and phosphorylation respectively leads to TERT ectopic expression at the transcription and protein levels. The co-interacting factors play an important role in the regulation of TERT in different cancer types. In this review, we focus on the regulators of TERT and these downstream functions in cancer regulation. Determining the specific regulatory mechanism will help to facilitate the development of a cancer treatment strategy that targets telomerase and cancer cell senescence. As the most important catalytic subunit component of telomerase, TERT is rapidly regulated by transcriptional factors and PTM-related activation. These changes directly influence TERT-related telomere maintenance by regulating telomerase activity in telomerase-positive cancer cells, telomerase assembly with telomere-binding proteins, and recruiting telomerase to the telomere. Besides, there are also non-canonical functions that are influenced by TERT, including the basic biological functions of cancer cells, such as proliferation, apoptosis, cell cycle regulation, initiating cell formation, EMT, and cell invasion. Other downstream effects are the results of the influence of transcriptional factors by TERT. Currently, some small molecular inhibitors of TERT and TERT vaccine are under research as a clinical therapeutic target. Purposeful work is in progress.

Predicting MYCN amplification in paediatric neuroblastoma: development and validation of a 18F-FDG PET/CT-based radiomics signature

OBJECTIVES

To develop and validate an 18F-FDG PET/CT-based clinical-radiological-radiomics nomogram and evaluate its value in the diagnosis of MYCN amplification (MNA) in paediatric neuroblastoma (NB) patients.

METHODS

A total of 104 patients with NB were retrospectively included. We constructed a nomogram to predict MNA based on radiomics signatures, clinical and radiological features. The multivariable logistic regression and the least absolute shrinkage and selection operator (LASSO) were used for feature selection. Radiomics models are constructed using decision trees (DT), logistic regression (LR) and support vector machine (SVM) classifiers. A clinical-radiological (C-R) model was developed using clinical and radiological features. A clinical-radiological-radiomics (C-R-R) model was developed using the C-R model of the best radiomics model. The prediction performance was verified by receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

The present study showed that four radiomics signatures were significantly correlated with MNA. The SVM classifier was the best model of radiomics signature. The C-R-R model has the best discriminant ability to predict MNA, with AUCs of 0.860 (95% CI, 0.757-0.963) and 0.824 (95% CI, 0.657-0.992) in the training and validation cohorts, respectively. The calibration curve indicated that the C-R-R model has the goodness of fit and DCA confirms its clinical utility.

CONCLUSION

Our research provides a non-invasive C-R-R model, which combines the radiomics signatures and clinical and radiological features based on 18F-FDGPET/CT images, shows excellent diagnostic performance in predicting MNA, and can provide useful biological information with stratified therapy.

CRITICAL RELEVANCE STATEMENT

Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma.

KEY POINTS

• Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma. • SF, LDH, necrosis and TLG are the independent risk factors of MYCN amplification. • Clinical-radiological-radiomics model improved the predictive performance of MYCN amplification.

Anti-CCL2 antibody combined with etoposide prolongs survival in a minimal residual disease mouse model of neuroblastoma

C-C motif chemokine ligand 2 (CCL2) is a monocyte chemoattractant that promotes metastatic disease and portends a poor prognosis in many cancers. To determine the potential of anti-CCL2 inhibition as a therapy for recurrent metastatic disease in neuroblastoma, a mouse model of minimal residual disease was utilized in which residual disease was treated with anti-CCL2 monoclonal antibody with etoposide. The effect of anti-CCL2 antibody on neuroblastoma cells was determined in vitro with cell proliferation, transwell migration, and 2-dimensional chemotaxis migration assays. The in vivo efficacy of anti-CCL2 antibody and etoposide against neuroblastoma was assessed following resection of primary tumors formed by two cell lines or a patient-derived xenograft (PDX) in immunodeficient NOD-scid gamma mice. In vitro, anti-CCL2 antibody did not affect cell proliferation but significantly inhibited neuroblastoma cell and monocyte migration towards an increasing CCL2 concentration gradient. Treatment of mice with anti-CCL2 antibody combined with etoposide significantly increased survival of mice after resection of primary tumors, compared to untreated mice.

Computational intelligence analysis of high-risk neuroblastoma patient health records reveals time to maximum response as one of the most relevant factors for outcome prediction

OBJECTIVE

Seek new candidate prognostic markers for neuroblastoma outcome, relapse or progression.

MATERIALS AND METHODS

In this multicentre and retrospective study, Random Forests coupled with recursive feature elimination techniques were applied to electronic records (55 clinical features) of 3034 neuroblastoma patients. To assess model performance and feature importance, dataset was split into a training set (80%) and a test set (20%).

RESULTS

In the test set, the mean Matthews correlation coefficient for the Random Forests models was greater than 0.46. Feature importance analysis revealed that, together with maximum response to first-line treatment (D_MAX_RESP), time to maximum response to first-line treatment (TIME_MAX_RESP.days) is a relevant predictor of both patients' outcome and relapse\progression. We showed the prognostic value of the max response to first-line treatment in clinically relevant subsets of high-, intermediate-, and low-risk patients for both overall and relapse-free survival (Log-rank p-value<0.0001). In high-risk patients older than 18 months and stage 4 tumour achieving a complete response or very good partial response, patients who exhibited a D_MAX_RESP greater than 9 months showed a better prognosis with respect to patients achieving D_MAX_RESP earlier than 9 months (overall survival): hazard ratio 3.3 95% confidence interval 1.8-5.9, Log-rank p-value p < 0.0001; relapse-free survival: 3.2 95%CI 1.8-5.6, Log-rank p-value p < 0.0001).

CONCLUSION

Our findings evidence the emerging role of the TIME_MAX_RESP.days in addition to the D_MAX_RESP as relevant predictors of outcome and relapse\progression in neuroblastoma with potential clinical impact on the management and treatment of patients.

Identification and targeting of protein tyrosine kinase 7 (PTK7) as an immunotherapy candidate for neuroblastoma

GD2-targeting immunotherapies have improved survival in children with neuroblastoma, yet on-target, off-tumor toxicities can occur and a subset of patients cease to respond. The majority of neuroblastoma patients who receive immunotherapy have been previously treated with cytotoxic chemotherapy, making it paramount to identify neuroblastoma-specific antigens that remain stable throughout standard treatment. Cell surface glycoproteomics performed on human-derived neuroblastoma tumors in mice following chemotherapy treatment identified protein tyrosine kinase 7 (PTK7) to be abundantly expressed. Furthermore, PTK7 shows minimal expression on pediatric-specific normal tissues. We developed an anti-PTK7 chimeric antigen receptor (CAR) and find PTK7 CAR T cells specifically target and kill PTK7-expressing neuroblastoma in vitro. In vivo, human/murine binding PTK7 CAR T cells regress aggressive neuroblastoma metastatic mouse models and prolong survival with no toxicity. Together, these data demonstrate preclinical efficacy and tolerability for targeting PTK7 and support ongoing investigations to optimize PTK7-targeting CAR T cells for neuroblastoma.

Multiple Genes with Potential Tumor Suppressive Activity Are Present on Chromosome 10q Loss in Neuroblastoma and Are Associated with Poor Prognosis

Neuroblastoma (NB) is a tumor affecting the peripheral sympathetic nervous system that substantially contributes to childhood cancer mortality. Despite recent advances in understanding the complexity of NB, the mechanisms determining its progression are still largely unknown. Some recurrent segmental chromosome aberrations (SCA) have been associated with poor survival. However, the prognostic role of most SCA has not yet been investigated. We examined a cohort of 260 NB primary tumors at disease onset for the loss of chromosome 10q, by array-comparative genomic hybridization (a-CGH) and Single Nucleotide Polymorphism (SNP) array and we found that 26 showed 10q loss, while the others 234 displayed different SCA. We observed a lower event-free survival for NB patients displaying 10q loss compared to patients with tumors carrying other SCA. Furthermore, analyzing the region of 10q loss, we identified a cluster of 75 deleted genes associated with poorer outcome. Low expression of six of these genes, above all CCSER2, was significantly correlated to worse survival using in silico data from 786 NB patients. These potential tumor suppressor genes can be partly responsible for the poor prognosis of NB patients with 10q loss.

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.

Stimulation of natural killer cells with small molecule inhibitors of CD38 for the treatment of neuroblastoma

High-risk neuroblastoma (NB) accounts for 15% of all pediatric cancer deaths. Refractory disease for high-risk NB patients is attributed to chemotherapy resistance and immunotherapy failure. The poor prognosis for high-risk NB patients demonstrates an unmet medical need for the development of new, more efficacious therapeutics. CD38 is an immunomodulating protein that is expressed constitutively on natural killer (NK) cells and other immune cells in the tumor microenvironment (TME). Furthermore, CD38 over expression is implicated in propagating an immunosuppressive milieu within the TME. Through virtual and physical screening, we have identified drug-like small molecule inhibitors of CD38 with low micromolar IC50 values. We have begun to explore structure activity relationships for CD38 inhibition through derivatization of our most effective hit molecule to develop a new compound with lead-like physicochemical properties and improved potency. We have demonstrated that our derivatized inhibitor, compound 2, elicits immunomodulatory effects in NK cells by increasing cell viability by 190 ± 36% in multiple donors and by significantly increasing interferon gamma. Additionally, we have illustrated that NK cells exhibited enhanced cytotoxicity toward NB cells (14% reduction of NB cells over 90 minutes) when given a combination treatment of our inhibitor and the immunocytokine ch14.18-IL2. Herein we describe the synthesis and biological evaluation of small molecule CD38 inhibitors and demonstrate their potential utility as a novel approach to NB immunotherapy. These compounds represent the first examples of small molecules that stimulate immune function for the treatment of cancer.

A Simple, Test-Based Method to Control the Overestimation Bias in the Analysis of Potential Prognostic Tumour Markers

The early evaluation of prognostic tumour markers is commonly performed by comparing the survival of two groups of patients identified on the basis of a cut-off value. The corresponding hazard ratio (HR) is usually estimated, representing a measure of the relative risk between patients with marker values above and below the cut-off. A posteriori methods identifying an optimal cut-off are appropriate when the functional form of the relation between the marker distribution and patient survival is unknown, but they are prone to an overestimation bias. In the presence of a small sample size, which is typical of rare diseases, the external validation sets are hardly available and internal cross-validation could be unfeasible. We describe a new method to obtain an unbiased estimate of the HR at an optimal cut-off, exploiting the simple relation between the HR and the associated p-value estimated by a random permutation analysis. We validate the method on both simulated data and set of gene expression profiles from two large, publicly available data sets. Furthermore, a reanalysis of a previously published study, which included 134 Stage 4S neuroblastoma patients, allowed for the identification of E2F1 as a new gene with potential oncogenic activity. This finding was confirmed by an immunofluorescence analysis on an independent cohort.

Proteomic profiling of extracellular vesicles in synovial fluid and plasma from Oligoarticular Juvenile Idiopathic Arthritis patients reveals novel immunopathogenic biomarkers

Introduction

New early low-invasive biomarkers are demanded for the management of Oligoarticular Juvenile Idiopathic Arthritis (OJIA), the most common chronic pediatric rheumatic disease in Western countries and a leading cause of disability. A deeper understanding of the molecular basis of OJIA pathophysiology is essential for identifying new biomarkers for earlier disease diagnosis and patient stratification and to guide targeted therapeutic intervention. Proteomic profiling of extracellular vesicles (EVs) released in biological fluids has recently emerged as a minimally invasive approach to elucidate adult arthritis pathogenic mechanisms and identify new biomarkers. However, EV-prot expression and potential as biomarkers in OJIA have not been explored. This study represents the first detailed longitudinal characterization of the EV-proteome in OJIA patients.

Methods

Fourty-five OJIA patients were recruited at disease onset and followed up for 24 months, and protein expression profiling was carried out by liquid chromatography-tandem mass spectrometry in EVs isolated from plasma (PL) and synovial fluid (SF) samples.

Results

We first compared the EV-proteome of SF vs paired PL and identified a panel of EV-prots whose expression was significantly deregulated in SF. Interaction network and GO enrichment analyses performed on deregulated EV-prots through STRING database and ShinyGO webserver revealed enrichment in processes related to cartilage/bone metabolism and inflammation, suggesting their role in OJIA pathogenesis and potential value as early molecular indicators of OJIA development. Comparative analysis of the EV-proteome in PL and SF from OJIA patients vs PL from age/gender-matched control children was then carried out. We detected altered expression of a panel of EV-prots able to differentiate new-onset OJIA patients from control children, potentially representing a disease-associated signature measurable at both the systemic and local levels with diagnostic potential. Deregulated EV-prots were significantly associated with biological processes related to innate immunity, antigen processing and presentation, and cytoskeleton organization. Finally, we ran WGCNA on the SF- and PL-derived EV-prot datasets and identified a few EV-prot modules associated with different clinical parameters stratifying OJIA patients in distinct subgroups.

Discussion

These data provide novel mechanistic insights into OJIA pathophysiology and an important contribution in the search of new candidate molecular biomarkers for the disease.

The human ion channel TRPM2 modulates migration and invasion in neuroblastoma through regulation of integrin expression

Transient receptor potential channel TRPM2 is highly expressed in many cancers and involved in regulation of key physiological processes including mitochondrial function, bioenergetics, and oxidative stress. In Stage 4 non-MYCN amplified neuroblastoma patients, high TRPM2 expression is associated with worse outcome. Here, neuroblastoma cells with high TRPM2 expression demonstrated increased migration and invasion capability. RNA sequencing, RT-qPCR, and Western blotting demonstrated that the mechanism involved significantly greater expression of integrins α1, αv, β1, and β5 in cells with high TRPM2 expression. Transcription factors HIF-1α, E2F1, and FOXM1, which bind promoter/enhancer regions of these integrins, were increased in cells with high TRPM2 expression. Subcellular fractionation confirmed high levels of α1, αv, and β1 membrane localization and co-immunoprecipitation confirmed the presence of α1β1, αvβ1, and αvβ5 complexes. Inhibitors of α1β1, αvβ1, and αvβ5 complexes significantly reduced migration and invasion in cells highly expressing TRPM2, confirming their functional role. Increased pAkt^Ser473 and pERK^{Thr202/Tyr204}, which promote migration through mechanisms including integrin activation, were found in cells highly expressing TRPM2. TRPM2 promotes migration and invasion in neuroblastoma cells with high TRPM2 expression through modulation of integrins together with enhancing cell survival, negatively affecting patient outcome and providing rationale for TRPM2 inhibition in anti-neoplastic therapy.

Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning

Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand which genes might be involved in patients’ survival, researchers have invented prognostic genetic signatures: lists of genes that can be used in scientific analyses to predict if a patient will survive or not. In this study, we joined together five different prognostic signatures, each of them related to a specific cancer type, to generate a unique pan-cancer prognostic signature, that contains 207 unique probesets related to 187 unique gene symbols, with one particular probeset present in two cancer type-specific signatures (203072_at related to the MYO1E gene). We applied our proposed pan-cancer signature with the Random Forests machine learning method to 57 microarray gene expression datasets of 12 different cancer types, and analyzed the results. We also compared the performance of our pan-cancer signature with the performances of two alternative prognostic signatures, and with the performances of each cancer type-specific signature on their corresponding cancer type-specific datasets. Our results confirmed the effectiveness of our prognostic pan-cancer signature. Moreover, we performed a pathway enrichment analysis, which indicated an association between the signature genes and a protein-protein interaction analysis, that highlighted PIK3R2 and FN1 as key genes having a fundamental relevance in our signature, suggesting an important role in pan-cancer prognosis for both of them.

Prognostic value of texture analysis of the primary tumour in high-risk neuroblastoma: An 18 F-DOPA PET study

PURPOSE

To evaluate the prognostic value of texture analysis of the primary tumour with ¹⁸ fluorine-dihydroxyphenylalanine positron emission tomography/X-ray computed tomography (¹⁸ F-DOPA PET/CT) in patients affected by high-risk neuroblastoma (HR-NBL).

METHODS

We retrospectively analysed 18 patients with HR-NBL, which had been prospectively enrolled in the course of a previous trial investigating the diagnostic role of ¹⁸ F-DOPA PET/CT at the time of the first onset. Texture analysis of the primary tumour was carried out on the PET images using LifeX. Conventional indices, histogram parameters, grey level co-occurrence (GLCM), run-length (GLRLM), neighbouring difference (NGLDM) and zone-length (GLZLM) matrices parameter were extracted; their values were compared with the overall metastatic load, expressed by means of whole-body metabolic burden (WBMB) score and the progression-free/overall survival (PFS and OS).

RESULTS

There was a direct correlation between WBMB and radiomics parameter describing uptake intensity (SUV_mean : p = .004) and voxel heterogeneity (entropy: p = .026; GLCM_Contrast: p = .001). Conversely, texture indices of homogeneity showed an inverse correlation with WBMB (energy: p = .026; GLCM_Homogeneity: p = .006). On the multivariate model, WBMB (p < .01) and the first standardised uptake value (SUV) quartile (p < .001) predicted PFS; OS was predicted by WBMB and the N-myc proto-oncogene protein (MYCN) amplification (p < .05) for both.

CONCLUSIONS

Textural parameters describing heterogeneity and metabolic intensity of the primary HR-NBL are closely associated with its overall metastatic burden. In turn, the whole-body tumour load appears to be one of the most relevant predictors of progression-free and overall survival.

Nucleolin expression has prognostic value in neuroblastoma patients

BACKGROUND

Neuroblastoma (NB) represents the most frequent form of extra-cranial solid tumour of infants, responsible for 15% of childhood cancer deaths. Nucleolin (NCL) prognostic value in NB was investigated.

METHODS

NCL protein expression was retrospectively evaluated in tumour samples of NB patients at diagnosis and after chemotherapy. NCL prognostic value at mRNA level was assessed in a cohort of 20 patients with stage 4 NB (qPCR20, n=20, discovery dataset) and in the MultiPlatform786 including 786 patients of all stages (validation dataset). Overall and event-free survival curves were plotted by Kaplan-Meier method and compared by log-rank test.

FINDINGS

NCL protein, down-modulated after chemotherapy in association with features of neuroblastic differentiation,resulted statistically significantly overexpressed in NB tumours and higher in stage 4 compared to stage 1,2,3 patients. In the stage 4 patients cohort qPCR20, patients with high NCLmRNA expression revealed a statisticallysignificant lower survival probability than those with low NCL expression (OS: HR 4.1 95%CI 1.2-13.8;p=0.0215[Log-rank test], EFS: HR 4.1 95%CI 1.2-14.0, p=0.0197[Log-rank test]). In the MultiPlatform786 (n=786), multivariate analysis suggested thatNCL expression has a statistically significant prognostic value even in the model adjusted for established prognostic markers. NCL expression significantly stratified also patients with >18 months and stage 4 tumour (OS: HR 1.8 95%CI 1.2-2.7, p=0.0009[Log-rank test]; EFS: HR 1.7 95%CI 1.1-2.5, p=0.002[Log-rank test]), patients with>18 months stage 4 with MYCN non amplified tumour[EFS: HR 2.3 95%CI 1.2-4.7, p=0.01[Log-rank test]), and patients with MYCN non amplified and MYC high [OS: HR 11.9 95%CI 2.3-62.4, p=0.003[Log-rank test]; EFS: HR 7.2 95%CI 1.6-33.4, p=0.01[Log-rank test]). A statistically significant correlation between NCL and MYCN, MYC, and TERT was found in independent datasets (MultiPlatform786 (n=786) and Agilent394 (n=394). Gene set enrichment analysis revealed a statisticallysignificant positive enrichment of MYC target genes and genes involved in telomerase maintenance.

INTERPRETATION

NCL is a novel and independent (adjusting for age, INSS stage, and MYCN status) prognostic marker for NB.

FUNDING

IMH-EuroNanoMed II-2015 and AIRC-IG.

E2F3 gene expression is a potential negative prognostic marker for localised and MYCN not-amplified neuroblastoma: Results of in silico analysis of 786 samples

BACKGROUND

Neuroblastoma (NB) is an enigmatic childhood malignancy characterised by a wide range of clinical behaviour. Many potential oncogenes for NB have recently been identified. Among them, E2 transcription factor 3 (E2F3) expression was associated with a poor survival in 134 stage 4S patients, but evidence for other stage groups remains poorly investigated.

METHODS

We have analysed the expression of E2F3 gene from a database of 786 NB samples. Overall and event-free survivals (EFS) were assessed by the Kaplan-Meier method, splitting the data on the median and tertile expression values. The Cox model was applied to control for the confounding by stage, age and MYCN amplification. Validation was performed by an in silico analysis of an independent cohort of 283 NB patients. Furthermore, an immunofluorescence analysis on 48 formalin-fixed, paraffin-embedded NB specimens was also performed.

RESULTS

E2F3 overexpression was associated with a poor survival (EFS = 84%, 95% CI: 79%-95%, for low expression levels; EFS = 62%, 95% CI: 56%-68% for middle levels; EFS = 30%, 95% CI: 24%-36%, for high levels, p < .001). This association was confirmed in multivariable analysis and was more evident in patients with MYCN not-amplified and localised stages. Immunofluorescence results and the validation on an independent cohort of NB primary samples confirmed these findings.

CONCLUSIONS

E2F3 is a new potential prognostic marker in NB with favourable characteristics at diagnosis. Further studies are needed to elucidate the potential role of E2F3 in NB oncogenesis and progression, in order to identify new targets for therapeutic interventions.

Tumoral heterogeneity in neuroblastoma

Neuroblastoma is a solid, neuroendocrine tumor with divergent clinical behavior ranging from asymptomatic to fatal. The diverse clinical presentations of neuroblastoma are directly linked to the high intra- and inter-tumoral heterogeneity it presents. This heterogeneity is strongly associated with therapeutic resistance and continuous relapses, often leading to fatal outcomes. The development of successful risk assessment and tailored treatment strategies lies in evaluating the extent of heterogeneity via the accurate genetic and epigenetic profiling of distinct cell subpopulations present in the tumor. Recent studies have focused on understanding the molecular mechanisms that drive tumoral heterogeneity in pursuing better therapeutic and diagnostic approaches. This review describes the cellular, genetic, and epigenetic aspects of neuroblastoma heterogeneity. In addition, we summarize the recent findings on three crucial factors that can lead to heterogeneity in solid tumors: the inherent diversity of the progenitor cells, the presence of cancer stem cells, and the influence of the tumor microenvironment.

Nine quick tips for pathway enrichment analysis

Pathway enrichment analysis (PEA) is a computational biology method that identifies biological functions that are overrepresented in a group of genes more than would be expected by chance and ranks these functions by relevance. The relative abundance of genes pertinent to specific pathways is measured through statistical methods, and associated functional pathways are retrieved from online bioinformatics databases. In the last decade, along with the spread of the internet, higher availability of computational resources made PEA software tools easy to access and to use for bioinformatics practitioners worldwide. Although it became easier to use these tools, it also became easier to make mistakes that could generate inflated or misleading results, especially for beginners and inexperienced computational biologists. With this article, we propose nine quick tips to avoid common mistakes and to out a complete, sound, thorough PEA, which can produce relevant and robust results. We describe our nine guidelines in a simple way, so that they can be understood and used by anyone, including students and beginners. Some tips explain what to do before starting a PEA, others are suggestions of how to correctly generate meaningful results, and some final guidelines indicate some useful steps to properly interpret PEA results. Our nine tips can help users perform better pathway enrichment analyses and eventually contribute to a better understanding of current biology.

Untargeted LC-HRMS Based-Plasma Metabolomics Reveals 3-O-Methyldopa as a New Biomarker of Poor Prognosis in High-Risk Neuroblastoma

Neuroblastoma (NB) is the most common extracranial malignant tumor in children. Although the survival rate of NB has improved over the years, the outcome of NB still remains poor for over 30% of cases. A more accurate risk stratification remains a key point in the study of NB and the availability of novel prognostic biomarkers of “high-risk” at diagnosis could help improving patient stratification and predicting outcome.

In this paper we show a biomarker discovery approach applied to the plasma of 172 NB patients. Plasma samples from a first cohort of NB patients and age-matched healthy controls were used for untargeted metabolomics analysis based on high-resolution mass spectrometry (HRMS). Differential expression analysis highlighted a number of metabolites annotated with a high degree of identification. Among them, 3-O-methyldopa (3-O-MD) was validated in a second cohort of NB patients using a targeted metabolite profiling approach and its prognostic potential was also analyzed by survival analysis on patients with 3 years follow-up. High expression of 3-O-MD was associated with worse prognosis in the subset of patients with stage M tumor (log-rank p < 0.05) and, among them, it was confirmed as a prognostic factor able to stratify high-risk patients older than 18 months. 3-O-MD might be thus considered as a novel prognostic biomarker of NB eligible to be included at diagnosis among catecholamine metabolite panels in prospective clinical studies. Further studies are warranted to exploit other potential biomarkers highlighted using our approach.

Construction of a Six-Gene Prognostic Risk Model Related to Hypoxia and Angiogenesis for Cervical Cancer

Background: The prognosis of cervical cancer (CC) is poor and not accurately reflected by the primary tumor node metastasis staging system. Our study aimed to develop a novel survival-prediction model.

Methods: Hallmarks of CC were quantified using single-sample gene set enrichment analysis and univariate Cox proportional hazards analysis. We linked gene expression, hypoxia, and angiogenesis using weighted gene co-expression network analysis (WGCNA). Univariate and multivariate Cox regression was combined with the random forest algorithm to construct a prognostic model. We further evaluated the survival predictive power of the gene signature using Kaplan-Meier analysis and receiver operating characteristic (ROC) curves.

Results: Hypoxia and angiogenesis were the leading risk factors contributing to poor overall survival (OS) of patients with CC. We identified 109 candidate genes using WGCNA and univariate Cox regression. Our established prognostic model contained six genes (MOCSI, PPP1R14A, ESM1, DES, ITGA5, and SERPINF1). Kaplan-Meier analysis indicated that high-risk patients had worse OS (hazard ratio = 4.63, p < 0.001). Our model had high predictive power according to the ROC curve. The C-index indicated that the risk score was a better predictor of survival than other clinicopathological variables. Additionally, univariate and multivariate Cox regressions indicated that the risk score was the only independent risk factor for poor OS. The risk score was also an independent predictor in the validation set (GSE52903). Bivariate survival prediction suggested that patients exhibited poor prognosis if they had high z-scores for hypoxia or angiogenesis and high risk scores.

Conclusions: We established a six-gene survival prediction model associated with hypoxia and angiogenesis. This novel model accurately predicts survival and also provides potential therapeutic targets.

Genomic Analysis Made It Possible to Identify Gene-Driver Alterations Covering the Time Window between Diagnosis of Neuroblastoma 4S and the Progression to Stage 4

Neuroblastoma (NB) is a tumor of the developing sympathetic nervous system. Despite recent advances in understanding the complexity of NB, the mechanisms that determine its regression or progression are still largely unknown. Stage 4S NB is characterized by a favorable course of disease and often by spontaneous regression, while progression to true stage 4 is a very rare event. Here, we focused on genomic analysis of an NB case that progressed from stage 4S to stage 4 with a very poor outcome. Array-comparative genomic hybridization (a-CGH) on tumor-tissue DNA, and whole-exome sequencing (WES) on exosomes DNA derived from plasma collected at the onset and at the tumor progression, pointed out relevant genetic changes that can explain this clinical worsening. The combination of a-CGH and WES data allowed for the identification iof somatic copy number aberrations and single-nucleotide variants in genes known to be responsible for aggressive NB. KLRB1, MAPK3 and FANCA genes, which were lost at the time of progression, were studied for their possible role in this event by analyzing in silico the impact of their expression on the outcome of 786 NB patients.

geneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO)

Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in online databases and repositories, such as Gene Expression Omnibus (GEO). To read and analyze gene expression data, the computational biology community has developed several tools and platforms, including Bioconductor, an R open-source platform of software packages that can be used to analyze these data. Despite the usefulness of Bioconductor and of its packages, it is still difficult to read gene expression data from GEO, and to assign gene symbols to the probesets of datasets. To alleviate this problem, we introduce here a new R software package, geneExpressionFromGEO, which provides to the users the possibility to easily download gene expression data from GEO and to easily associate gene symbols to probesets. In this short chapter, we describe the assets of our software package, and we report an example of its usage. We believe that geneExpressionFromGEO can be very useful for the R community of bioinformaticians working on gene expression data.

High Grade of Amplification of Six Regions on Chromosome 2p in a Neuroblastoma Patient with Very Poor Outcome: The Putative New Oncogene TSSC1

Simple Summary

Here, a case of neuroblastoma (NB) carrying a high-grade amplification of six loci besides MYCN is described. Since the patient had a very poor outcome, we postulated that these DNA co-amplifications might have a synergistic effect in increasing NB cell proliferation. In order to verify this hypothesis, we analyzed in silico the impact of high expression of the genes located within the amplifications on the NB patients’ outcome using a large dataset integrating three different platforms. These analyses disclosed that high expression of the TSSC1 gene was the most significantly associated with reduced overall survival of NB patients, suggesting that it may have a potential prognostic role in NB in both MYCN amplified and MYCN not amplified tumors. Further studies on TSSC1 interactions and functioning could lead to possible focused therapies for high-risk NB patients.

Abstract

We observed a case of high-risk neuroblastoma (NB) carried by a 28-month-old girl, displaying metastatic disease and a rapid decline of clinical conditions. By array-CGH analysis of the tumor tissue and of the metastatic bone marrow aspirate cells, we found a high-grade amplification of six regions besides MYCN on bands 2p25.3–p24.3. The genes involved in these amplifications were MYT1L, TSSC1, CMPK2, RSAD2, RNF144A, GREB1, NTSR2, LPIN1, NBAS, and the two intergenic non-protein coding RNAs LOC730811 and LOC339788. We investigated if these DNA co-amplifications may have an effect on enhancing tumor aggressiveness. We evaluated the association between the high expression of the amplified genes and NB patient’s outcome using the integration of gene expression data of 786 NB samples profiled with different public platforms from patients with at least five-year follow-up. NB patients with high expression of the TSSC1 gene were associated with a reduced survival rate. Immunofluorescence staining on primary tumor tissues confirmed that the TSSC1 protein expression was high in the relapsed or dead stage 4 cases, but it was generally low in NB patients in complete remission. TSSC1 appears as a putative new oncogene in NB.

Growth factor signaling predicts therapy resistance mechanisms and defines neuroblastoma subtypes

Neuroblastoma (NB) has a low frequency of recurrent mutations compared to other cancers, which hinders the development of targeted therapies and novel risk stratification strategies. Multikinase inhibitors have shown potential in treating high-risk NB, but their efficacy is likely impaired by the cancer cells' ability to adapt to these drugs through the employment of alternative signaling pathways. Based on the expression of 48 growth factor-related genes in 1189 NB tumors, we have developed a model for NB patient survival prediction. This model discriminates between stage 4 NB tumors with favorable outcomes (>80% overall survival) and very poor outcomes (<10%) independently from MYCN-amplification status. Using signaling pathway analysis and gene set enrichment methods in 60 NB patients with known therapy response, we identified signaling pathways, including EPO, NGF, and HGF, upregulated in patients with no or partial response. In a therapeutic setting, we showed that among six selected growth factors, EPO, and NGF showed the most pronounced protective effects in vitro against several promising anti-NB multikinase inhibitors: imatinib, dasatinib, crizotinib, cabozantinib, and axitinib. Mechanistically kinase inhibitors potentiated NB cells to stronger ERK activation by EPO and NGF. The protective action of these growth factors strongly correlated with ERK activation and was ERK-dependent. ERK inhibitors combined with anticancer drugs, especially with dasatinib, showed a synergistic effect on NB cell death. Consideration of growth factor signaling activity benefits NB outcome prediction and tailoring therapy regimens to treat NB.

A New Player in Neuroblastoma: YAP and Its Role in the Neuroblastoma Microenvironment

Neuroblastoma is the most common extra-cranial pediatric solid tumor that accounts for more than 15% of childhood cancer-related deaths. High risk neuroblastomas that recur during or after intense multimodal therapy have a <5% chance at a second sustained remission or cure. The solid tumor microenvironment (TME) has been increasingly recognized to play a critical role in cancer progression and resistance to therapy, including in neuroblastoma. The Yes-Associated Protein (YAP) in the Hippo pathway can regulate cancer proliferation, tumor initiation, and therapy response in many cancer types and as such, its role in the TME has gained interest. In this review, we focus on YAP and its role in neuroblastoma and further describe its demonstrated and potential effects on the neuroblastoma TME. We also discuss the therapeutic strategies for inhibiting YAP in neuroblastoma.

Oxygen-dependent changes in binding partners and post-translational modifications regulate the abundance and activity of HIF-1α/2α

Cellular adaptation to low-oxygen environments is mediated in part by the hypoxia-inducible factors (HIFs). Like other transcription factors, the stability and transcriptional activity of HIFs-and consequently, the hypoxic response-are regulated by post-translational modifications (PTMs) and changes in protein-protein interactions. Our current understanding of PTM-mediated regulation of HIFs is primarily based on in vitro protein fragment-based studies typically validated in fragment-expressing cells treated with hypoxia-mimicking compounds. Here, we used immunoprecipitation-based mass spectrometry to characterize the PTMs and binding partners for full-length HIF-1α and HIF-2α under normoxic (21% oxygen) and hypoxic (1% oxygen) conditions. Hypoxia substantially altered the complexity and composition of the HIFα protein interaction networks, particularly for HIF-2α, with the hypoxic networks of both isoforms being enriched for mitochondrial proteins. Moreover, both HIFα isoforms were heavily covalently modified. We identified ~40 PTM sites composed of 13 different types of modification on both HIFα isoforms, including multiple cysteine modifications and an unusual phosphocysteine. More than 80% of the PTMs identified were not previously known and about half exhibited oxygen dependency. We further characterized an evolutionarily conserved phosphorylation of Ser31 in HIF-1α as a regulator of its transcriptional function, and we propose functional roles for Thr406, Thr528, and Ser581 in HIF-2α. These data will help to delineate the different physiological roles of these closely related isoforms in fine-tuning the hypoxic response.

Connectivity Map Analysis Indicates PI3K/Akt/mTOR Inhibitors as Potential Anti-Hypoxia Drugs in Neuroblastoma

Neuroblastoma (NB) is one of the deadliest pediatric cancers, accounting for 15% of deaths in childhood. Hypoxia is a condition of low oxygen tension occurring in solid tumors and has an unfavorable prognostic factor for NB. In the present study, we aimed to identify novel promising drugs for NB treatment. Connectivity Map (CMap), an online resource for drug repurposing, was used to identify connections between hypoxia-modulated genes in NB tumors and compounds. Two sets of 34 and 21 genes up- and down-regulated between hypoxic and normoxic primary NB tumors, respectively, were analyzed with CMap. The analysis reported a significant negative connectivity score across nine cell lines for 19 compounds mainly belonging to the class of PI3K/Akt/mTOR inhibitors. The gene expression profiles of NB cells cultured under hypoxic conditions and treated with the mTORC complex inhibitor PP242, referred to as the Mohlin dataset, was used to validate the CMap findings. A heat map representation of hypoxia-modulated genes in the Mohlin dataset and the gene set enrichment analysis (GSEA) showed an opposite regulation of these genes in the set of NB cells treated with the mTORC inhibitor PP242. In conclusion, our analysis identified inhibitors of the PI3K/Akt/mTOR signaling pathway as novel candidate compounds to treat NB patients with hypoxic tumors and a poor prognosis.

Melatonin and neuroblastoma: a novel therapeutic approach

Neuroblastoma is a deadly and serious malignancy among children. Although many developments have been occurred for the treatment of this disease, the rate of mortality is still high. Therefore, it is necessary to search for novel complementary and alternative therapies. Melatonin, a hormone secreted from pineal gland, is a multifunctional agent having anticancer potentials. Recently, several investigations have been conducted indicating melatonin effects against neuroblastoma. In this paper, we summarize current evidence on anti-neuroblastoma effects of melatonin based on cellular pathways.

Molecular Genetics in Neuroblastoma Prognosis

In recent years, much research has been carried out to identify the biological and genetic characteristics of the neuroblastoma (NB) tumor in order to precisely define the prognostic subgroups for improving treatment stratification. This review will describe the major genetic features and the recent scientific advances, focusing on their impact on diagnosis, prognosis, and therapeutic solutions in NB clinical management.