Molecular mechanism underlying impaired hepatic autophagy in glycogen storage disease type Ib.

Type Ib glycogen storage disease (GSD-Ib) is caused by a deficiency in the glucose-6-phosphate (G6P) transporter (G6PT) that translocates G6P from the cytoplasm into the endoplasmic reticulum lumen, where the intraluminal G6P is hydrolyzed to glucose by glucose-6-phosphatase-α (G6Pase-α). Clinically, GSD-Ib patients manifest a metabolic phenotype of impaired blood glucose homeostasis and a long-term risk of hepatocellular adenoma/carcinoma (HCA/HCC). Studies have shown that autophagy deficiency contributes to hepatocarcinogenesis. In this study, we show that G6PT deficiency leads to impaired hepatic autophagy evident from attenuated expression of many components of the autophagy network, decreased autophagosome formation and reduced autophagy flux. The G6PT-deficient liver displayed impaired sirtuin 1 (SIRT1) and AMP-activated protein kinase (AMPK) signaling, along with reduced expression of SIRT1, forkhead boxO3a (FoxO3a), liver kinase B-1 (LKB1) and the active p-AMPK. Importantly, we show that overexpression of either SIRT1 or LKB1 in G6PT-deficient liver restored autophagy and SIRT1/FoxO3a and LKB1/AMPK signaling. The hepatosteatosis in G6PT-deficient liver decreased SIRT1 expression. LKB1 overexpression reduced hepatic triglyceride levels, providing a potential link between LKB1/AMPK signaling upregulation and the increase in SIRT1 expression. In conclusion, downregulation of SIRT1/FoxO3a and LKB1/AMPK signaling underlies impaired hepatic autophagy which may contribute to HCA/HCC development in GSD-Ib. Understanding this mechanism may guide future therapies.

Dapagliflozin Prevents Kidney Glycogen Accumulation and Improves Renal Proximal Tubule Cell Functions in a Mouse Model of Glycogen Storage Disease Type 1b.

BACKGROUND: Mutations in SLC37A4, which encodes the intracellular glucose transporter G6PT, cause the rare glycogen storage disease type 1b (GSD1b). A long-term consequence of GSD1b is kidney failure, which requires KRT. The main protein markers of proximal tubule function, including NaPi2A, NHE3, SGLT2, GLUT2, and AQP1, are downregulated as part of the disease phenotype. METHODS: We utilized an inducible mouse model of GSD1b, TM-G6PT-/-, to show that glycogen accumulation plays a crucial role in altering proximal tubule morphology and function. To limit glucose entry into proximal tubule cells and thus to prevent glycogen accumulation, we administered an SGLT2-inhibitor, dapagliflozin, to TM-G6PT-/- mice. RESULTS: In proximal tubule cells, G6PT suppression stimulates the upregulation and activity of hexokinase-I, which increases availability of the reabsorbed glucose for intracellular metabolism. Dapagliflozin prevented glycogen accumulation and improved kidney morphology by promoting a metabolic switch from glycogen synthesis toward lysis and by restoring expression levels of the main proximal tubule functional markers. CONCLUSION: We provide proof of concept for the efficacy of dapagliflozin in preserving kidney function in GSD1b mice. Our findings could represent the basis for repurposing this drug to treat patients with GSD1b.

Exosomal MicroRNAs as Potential Biomarkers of Hepatic Injury and Kidney Disease in Glycogen Storage Disease Type Ia Patients.

Glycogen storage disease type Ia (GSDIa) is an inherited metabolic disorder caused by mutations in the enzyme glucose-6-phosphatase-α (G6Pase-α). Affected individuals develop renal and liver complications, including the development of hepatocellular adenoma/carcinoma and kidney failure. The purpose of this study was to identify potential biomarkers of the evolution of the disease in GSDIa patients. To this end, we analyzed the expression of exosomal microRNAs (Exo-miRs) in the plasma exosomes of 45 patients aged 6 to 63 years. Plasma from age-matched normal individuals were used as controls. We found that the altered expression of several Exo-miRs correlates with the pathologic state of the patients and might help to monitor the progression of the disease and the development of late GSDIa-associated complications.

Transcriptome analysis defines myocardium gene signatures in children with ToF and ASD and reveals disease-specific molecular reprogramming in response to surgery with cardiopulmonary bypass.

BACKGROUND: Tetralogy of Fallot (ToF) and Atrial Septal Defects (ASD) are the most common types of congenital heart diseases and a major cause of childhood morbidity and mortality. Cardiopulmonary bypass (CPB) is used during corrective cardiac surgery to support circulation and heart stabilization. However, this procedure triggers systemic inflammatory and stress response and consequent increased risk of postoperative complications. The aim of this study was to define the molecular bases of ToF and ASD pathogenesis and response to CPB and identify new potential biomarkers. METHODS: Comparative transcriptome analysis of right atrium specimens collected from 10 ToF and 10 ASD patients was conducted before (Pre-CPB) and after (Post-CPB) corrective surgery. Total RNA isolated from each sample was individually hybridized on Affymetrix HG-U133 Plus Array Strips containing 38,500 unique human genes. Differences in the gene expression profiles and functional enrichment/network analyses were assessed using bioinformatic tools. qRT-PCR analysis was used to validate gene modulation. RESULTS: Pre-CPB samples showed significant differential expression of a total of 72 genes, 28 of which were overexpressed in ToF and 44 in ASD. According to Gene Ontology annotation, the mostly enriched biological processes were represented by matrix organization and cell adhesion in ToF and by muscle development and contractility in ASD specimens. GSEA highlighted the specific enrichment of hypoxia gene sets in ToF samples, pointing to a role for hypoxia in disease pathogenesis. The post-CPB myocardium exhibited significant alterations in the expression profile of genes related to transcription regulation, growth/apoptosis, inflammation, adhesion/matrix organization, and oxidative stress. Among them, only 70 were common to the two disease groups, whereas 110 and 24 were unique in ToF and ASD, respectively. Multiple functional interactions among differentially expressed gene products were predicted by network analysis. Interestingly, gene expression changes in ASD samples followed a consensus hypoxia profile. CONCLUSION: Our results provide a comprehensive view of gene reprogramming in right atrium tissues of ToF and ASD patients before and after CPB, defining specific molecular pathways underlying disease pathophysiology and myocardium response to CPB. These findings have potential translational value because they identify new candidate prognostic markers and targets for tailored cardioprotective post-surgical therapies.

A Proteomic Analysis of GSD-1a in Mouse Livers: Evidence for Metabolic Reprogramming, Inflammation, and Macrophage Polarization.

Glycogen storage disease type 1a (GSD-1a) is a rare genetic disease caused by mutations in the catalytic subunit of the enzyme glucose-6-phosphatase-alpha (G6Pase-α). The majority of patients develop long-term complications including renal failure and hepatocellular adenoma/carcinoma. The purpose of this study was to ascertain the proteomic changes in the liver of LS- G6pc-/- mice, a murine model of GSD-1a, in comparison with wild type mice to identify potential biomarkers of the pathophysiology of the affected liver. We used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze liver lysates from a total of 20 LS- G6pc-/- and 18 wild type (WT) mice. We compared the proteomic expression profile of LS- G6pc-/- and WT mice. We identified 4138 significantly expressed proteins, 1243 of which were differentially represented. Network and pathway analyses indicate that LS- G6pc-/- livers display an age-dependent modulation of the expression of proteins involved in specific biological processes associated with increased progression of liver disease. Moreover, we found upregulation of proteins involved in the process of tissue inflammation and macrophage polarization toward the M2 phenotype in LS- G6pc-/- mice with adenomas. Our results identify a metabolic reprogramming of glucose-6-P and a pathologic environment in the liver compatible with tumor development and progression.

Development and characterization of an inducible mouse model for glycogen storage disease type Ib.

BACKGROUND AND AIMS: Glycogen storage disease type Ib (GSD1b) is a rare metabolic and immune disorder caused by a deficiency in the glucose-6-phosphate transporter (G6PT) and characterized by impaired glucose homeostasis, myeloid dysfunction, and long-term risk of hepatocellular adenomas. Despite maximal therapy, based on a strict diet and on granulocyte colony-stimulating factor treatment, long-term severe complications still develop. Understanding the pathophysiology of GSD1b is a prerequisite to develop new therapeutic strategies and depends on the availability of animal models. The G6PT-KO mouse mimics the human disease but is very fragile and rarely survives weaning. We generated a conditional G6PT-deficient mouse as an alternative model for studying the long-term pathophysiology of the disease. We utilized this conditional mouse to develop an inducible G6PT-KO model to allow temporally regulated G6PT deletion by the administration of tamoxifen (TM). METHODS: We generated a conditional G6PT-deficient mouse utilizing the CRElox strategy. Histology, histochemistry, and phenotype analyses were performed at different times after TM-induced G6PT inactivation. Neutrophils and monocytes were isolated and analyzed for functional activity with standard techniques. RESULTS: The G6PT-inducible KO mice display the expected disturbances of G6P metabolism and myeloid dysfunctions of the human disorder, even though with a milder intensity. CONCLUSIONS: TM-induced inactivation of G6PT in these mice leads to a phenotype which mimics that of human GSD1b patients. The conditional mice we have generated represent an excellent tool to study the tissue-specific role of the G6PT gene and the mechanism of long-term complications in GSD1b.

Artificial neural network classifier predicts neuroblastoma patients' outcome.

BACKGROUND: More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. METHODS: Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. RESULTS: We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. CONCLUSIONS: We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Chronic hypoxia reprograms human immature dendritic cells by inducing a proinflammatory phenotype and TREM-1 expression.

DCs are powerful antigen-presenting cells central in the orchestration of innate and acquired immunity. DC development, migration, and activities are intrinsically linked to the microenvironment. DCs migrate through pathologic tissues before reaching their final destination in the lymph nodes. Hypoxia, a condition of low partial oxygen pressure, is a common feature of many pathologic situations, capable of modifying DC phenotype and functional behavior. We studied human monocyte-derived immature DCs generated under chronic hypoxic conditions (H-iDCs). We demonstrate by gene expression profiling the upregulation of a cluster of genes coding for antigen-presentation, immunoregulatory, and pattern recognition receptors, suggesting a stimulatory role for hypoxia on iDC immunoregulatory functions. In particular, we show that H-iDCs express triggering receptor expressed on myeloid cells(TREM-1), a member of the Ig superfamily of immunoreceptors and an amplifier of inflammation. This effect is reversible because H-iDC reoxygenation results in TREM-1 down-modulation. TREM-1 engagement promotes upregulation of T-cell costimulatory molecules and homing chemokine receptors, typical of mature DCs, and increases the production of proinflammatory, Th1/Th17-priming cytokines/chemokines, resulting in increased T-cell responses. These results suggest that TREM-1 induction by the hypoxic microenvironment represents a mechanism of regulation of Th1-cell trafficking and activation by iDCs differentiated at pathologic sites.

Exploring the role of HLA variants in neuroblastoma susceptibility through whole exome sequencing.

Although a number of susceptibility loci for neuroblastoma (NB) have been identified by genome-wide association studies, it is still unclear whether variants in the HLA region contribute to NB susceptibility. In this study, we conducted a comprehensive genetic analysis of variants in the HLA region among 724 NB patients and 2863 matched controls from different cohorts. We exploited whole-exome sequencing data to accurately type HLA alleles with an ensemble approach on the results from three different typing tools, and carried out rigorous sample quality control to ensure a fine-scale ancestry matching. The frequencies of common HLA alleles were compared between cases and controls by logistic regression under additive and non-additive models. Population stratification was taken into account adjusting for ancestry-informative principal components. We detected significant HLA associations with NB. In particular, HLA-DQB1*05:02 (OR = 1.61; padj = 5.4 × 10-3) and HLA-DRB1*16:01 (OR = 1.60; padj = 2.3 × 10-2) alleles were associated to higher risk of developing NB. Conditional analysis highlighted the HLA-DQB1*05:02 allele and its residue Ser57 as key to this association. DQB1*05:02 allele was not associated to clinical features worse outcomes in the NB cohort. Nevertheless, a risk score derived from the allelic combinations of five HLA variants showed a substantial predictive value for patient survival (HR = 1.53; p = 0.032) that was independent from established NB prognostic factors. Our study leveraged powerful computational methods to explore WES data and HLA variants and to reveal complex genetic associations. Further studies are needed to validate the mechanisms of these interactions that contribute to the multifaceted pattern of factors underlying the disease initiation and progression.

Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients.

BACKGROUND: Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. RESULTS: Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. CONCLUSIONS: The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four stable rules identifying a new class of poor outcome patients that could benefit from new therapies potentially targeting tumor hypoxia or its consequences.

Hypoxia modulates the gene expression profile of immunoregulatory receptors in human mature dendritic cells: identification of TREM-1 as a novel hypoxic marker in vitro and in vivo.

Dendritic cells (DCs) are a heterogeneous group of professional antigen-presenting cells functioning as sentinels of the immune system and playing a key role in the initiation and amplification of innate and adaptive immune responses. DC development and functions are acquired during a complex differentiation and maturation process influenced by several factors present in the local milieu. A common feature at pathologic sites is represented by hypoxia, a condition of low pO(2), which creates a unique microenvironment affecting cell phenotype and behavior. Little is known about the impact of hypoxia on the generation of mature DCs (mDCs). In this study, we identified by gene expression profiling a significant cluster of genes coding for immune-related cell surface receptors strongly up-regulated by hypoxia in monocyte-derived mDCs and characterized one of such receptors, TREM-1, as a new hypoxia-inducible gene in mDCs. TREM-1 associated with DAP12 in hypoxic mDCs, and its engagement elicited DAP12-linked signaling, resulting in ERK-1, Akt, and IκBα phosphorylation and proinflammatory cytokine and chemokine secretion. Finally, we provided the first evidence that TREM-1 is expressed on mDCs infiltrating the inflamed hypoxic joints of children affected by juvenile idiopathic arthritis, representing a new in vivo marker of hypoxic mDCs endowed with proinflammatory properties.

Plasma-Derived Exosome Proteins as Novel Diagnostic and Prognostic Biomarkers in Neuroblastoma Patients.

Neuroblastoma (NB) is the most common extracranial solid tumor during infancy, causing up to 10% of mortality in children; thus, identifying novel early and accurate diagnostic and prognostic biomarkers is mandatory. NB-derived exosomes carry proteins (Exo-prots) reflecting the status of the tumor cell of origin. The purpose of this study was to characterize, for the first time, the Exo-prots specifically expressed in NB patients associated with tumor phenotype and disease stage. We isolated exosomes from plasma specimens of 24 HR-NB patients and 24 low-risk (LR-NB) patients at diagnosis and of 24 age-matched healthy controls (CTRL). Exo-prot expression was measured by liquid chromatography-mass spectrometry. The data are available via ProteomeXchange (PXD042422). The NB patients had a different Exo-prot expression profile compared to the CTRL. The deregulated Exo-prots in the NB specimens acted mainly in the tumor-associated pathways. The HR-NB patients showed a different Exo-prot expression profile compared to the LR-NB patients, with the modulation of proteins involved in cell migration, proliferation and metastasis. NCAM, NCL, LUM and VASP demonstrated a diagnostic value in discriminating the NB patients from the CTRL; meanwhile, MYH9, FN1, CALR, AKAP12 and LTBP1 were able to differentiate between the HR-NB and LR-NB patients with high accuracy. Therefore, Exo-prots contribute to NB tumor development and to the aggressive metastatic NB phenotype.

Inherited rare variants in homologous recombination and neurodevelopmental genes are associated with increased risk of neuroblastoma.

BACKGROUND: Neuroblastoma (NB) is the most common solid extracranial paediatric tumour. Genome-wide association studies have driven the discovery of common risk variants, but no large study has investigated the contribution of rare variants to NB susceptibility. Here, we conducted a whole-exome sequencing (WES) of 664 NB cases and 822 controls and used independent validation datasets to identify genes with rare risk variants and involved pathways. METHODS: WES was performed at 50× depth and variants were jointly called in cases and controls. We developed two models to identify mutations with high clinical impact (P/LP model) and to discover less penetrant risk mutations affecting non-canonical cancer pathways (RPV model). We performed a gene-level collapsing test using Firth's logistic regression in 242 selected cancer predisposition genes (CPGs) and a gene-sets burden analysis of biologically-informed pathways. FINDINGS: Twelve percent of patients carried P/LP variants in CPGs and showed a significant enrichment (P = 2.3 × 10-4) compared to controls (6%). We identified P/LP variants in 45 CPGs enriched in homologous recombination (HR) pathway. The most P/LP enriched genes in NB were BRCA1, ALK and RAD51C. Additionally, we found higher RPV burden in gene-sets of neuron differentiation, neural tube development and synapse assembly, and in gene-sets associated with neurodevelopmental disorders (NDD). INTERPRETATION: The high fraction of NB patients with P/LP variants indicates the need of genetic counselling. Furthermore, inherited rare variants predispose to NB development by affecting mechanisms related to HR and neurodevelopmental processes, and demonstrate that NDD genes are altered in NB at the germline level. FUNDING: Associazione Italiana per la Ricerca sul Cancro, Fondazione Italiana per la Lotta al Neuroblastoma, Associazione Oncologia Pediatrica e Neuroblastoma, Regione Campania, Associazione Giulio Adelfio onlus, and Italian Health Ministry.

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.

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

BACKGROUND: Neuroblastoma is the most common pediatric solid tumor of the sympathetic nervous system. Development of improved predictive tools for patients stratification is a crucial requirement for neuroblastoma therapy. Several studies utilized gene expression-based signatures to stratify neuroblastoma patients and demonstrated a clear advantage of adding genomic analysis to risk assessment. There is little overlapping among signatures and merging their prognostic potential would be advantageous. Here, we describe a new strategy to merge published neuroblastoma related gene signatures into a single, highly accurate, Multi-Signature Ensemble (MuSE)-classifier of neuroblastoma (NB) patients outcome. METHODS: Gene expression profiles of 182 neuroblastoma tumors, subdivided into three independent datasets, were used in the various phases of development and validation of neuroblastoma NB-MuSE-classifier. Thirty three signatures were evaluated for patients' outcome prediction using 22 classification algorithms each and generating 726 classifiers and prediction results. The best-performing algorithm for each signature was selected, validated on an independent dataset and the 20 signatures performing with an accuracy > = 80% were retained. RESULTS: We combined the 20 predictions associated to the corresponding signatures through the selection of the best performing algorithm into a single outcome predictor. The best performance was obtained by the Decision Table algorithm that produced the NB-MuSE-classifier characterized by an external validation accuracy of 94%. Kaplan-Meier curves and log-rank test demonstrated that patients with good and poor outcome prediction by the NB-MuSE-classifier have a significantly different survival (p < 0.0001). Survival curves constructed on subgroups of patients divided on the bases of known prognostic marker suggested an excellent stratification of localized and stage 4s tumors but more data are needed to prove this point. CONCLUSIONS: The NB-MuSE-classifier is based on an ensemble approach that merges twenty heterogeneous, neuroblastoma-related gene signatures to blend their discriminating power, rather than numeric values, into a single, highly accurate patients' outcome predictor. The novelty of our approach derives from the way to integrate the gene expression signatures, by optimally associating them with a single paradigm ultimately integrated into a single classifier. This model can be exported to other types of cancer and to diseases for which dedicated databases exist.

The tumor suppressor hamartin enhances Dbl protein transforming activity through interaction with ezrin.

The Rho guanine nucleotide exchange factor (GEF) Dbl binds to the N-terminal region of ezrin, a member of the ERM (ezrin, radixin, moesin) proteins known to function as linkers between the plasma membrane and the actin cytoskeleton. Here we have characterized the interaction between ezrin and Dbl. We show that binding of Dbl with ezrin involves positively charged amino acids within the region of the pleckstrin homology (PH) domain comprised between ß1 and ß2 sheets. In addition, we show that Dbl forms a complex with the tuberous sclerosis-1 (TSC-1) gene product hamartin and with ezrin. We demonstrate that hamartin and ezrin are both required for activation of Dbl. In fact, the knock-down of ezrin and hamartin, as well as the expression of a mutant hamartin, unable to bind ezrin, inhibit Dbl transforming and exchange activity. These results suggest that Dbl is regulated by hamartin through association with ezrin.

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.

Targeting of Ubiquitin E3 Ligase RNF5 as a Novel Therapeutic Strategy in Neuroectodermal Tumors.

RNF5, an endoplasmic reticulum (ER) E3 ubiquitin ligase, participates to the ER-associated protein degradation guaranteeing the protein homeostasis. Depending on tumor model tested, RNF5 exerts pro- or anti-tumor activity. The aim of this study was to elucidate the controversial role of RNF5 in neuroblastoma and melanoma, two neuroectodermal tumors of infancy and adulthood, respectively. RNF5 gene levels are evaluated in publicly available datasets reporting the gene expression profile of melanoma and neuroblastoma primary tumors at diagnosis. The therapeutic effect of Analog-1, an RNF5 pharmacological activator, was investigated on in vitro and in vivo neuroblastoma and melanoma models. In both neuroblastoma and melanoma patients the high expression of RNF5 correlated with a better prognostic outcome. Treatment of neuroblastoma and melanoma cell lines with Analog-1 reduced cell viability by impairing the glutamine availability and energy metabolism through inhibition of F1Fo ATP-synthase activity. This latter event led to a marked increase in oxidative stress, which, in turn, caused cell death. Similarly, neuroblastoma- and melanoma-bearing mice treated with Analog-1 showed a significant delay of tumor growth in comparison to those treated with vehicle only. These findings validate RNF5 as an innovative drug target and support the development of Analog-1 in early phase clinical trials for neuroblastoma and melanoma patients.

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.

Treatment of newborn G6pc(-/-) mice with bone marrow-derived myelomonocytes induces liver repair.

BACKGROUND & AIMS: Several studies have shown that bone marrow-derived committed myelomonocytic cells can repopulate diseased livers by fusing with host hepatocytes and can restore normal liver function. These data suggest that myelomonocyte transplantation could be a promising approach for targeted and well-tolerated cell therapy aimed at liver regeneration. We sought to determine whether bone marrow-derived myelomonocytic cells could be effective for liver reconstitution in newborn mice knock-out for glucose-6-phosphatase-α. METHODS: Bone marrow-derived myelomonocytic cells obtained from adult wild type mice were transplanted in newborn knock-out mice. Tissues of control and treated mice were frozen for histochemical analysis, or paraffin-embedded and stained with hematoxylin and eosin for histological examination or analyzed by immunohistochemistry or fluorescent in situ hybridization. RESULTS: Histological sections of livers of treated knock-out mice revealed areas of regenerating tissue consisting of hepatocytes of normal appearance and partial recovery of normal architecture as early as 1 week after myelomonocytic cells transplant. FISH analysis with X and Y chromosome paints indicated fusion between infused cells and host hepatocytes. Glucose-6-phosphatase activity was detected in treated mice with improved profiles of liver functional parameters. CONCLUSIONS: Our data indicate that bone marrow-derived myelomonocytic cell transplant may represent an effective way to achieve liver reconstitution of highly degenerated livers in newborn animals.