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.

Heterogeneous MYCN amplification in neuroblastoma: a SIOP Europe Neuroblastoma Study.

BACKGROUND: In neuroblastoma (NB), the most powerful prognostic marker, the MYCN amplification (MNA), occasionally shows intratumoural heterogeneity (ITH), i.e. coexistence of MYCN-amplified and non-MYCN-amplified tumour cell clones, called heterogeneous MNA (hetMNA). Prognostication and therapy allocation are still unsolved issues. METHODS: The SIOPEN Biology group analysed 99 hetMNA NBs focussing on the prognostic significance of MYCN ITH. RESULTS: Patients <18 months (18 m) showed a better outcome in all stages as compared to older patients (5-year OS in localised stages: <18 m: 0.95 ± 0.04, >18 m: 0.67 ± 0.14, p = 0.011; metastatic: <18 m: 0.76 ± 0.15, >18 m: 0.28 ± 0.09, p = 0.084). The genomic 'background', but not MNA clone sizes, correlated significantly with relapse frequency and OS. No relapses occurred in cases of only numerical chromosomal aberrations. Infiltrated bone marrows and relapse tumour cells mostly displayed no MNA. However, one stage 4s tumour with segmental chromosomal aberrations showed a homogeneous MNA in the relapse. CONCLUSIONS: This study provides a rationale for the necessary distinction between heterogeneous and homogeneous MNA. HetMNA tumours have to be evaluated individually, taking age, stage and, most importantly, genomic background into account to avoid unnecessary upgrading of risk/overtreatment, especially in infants, as well as in order to identify tumours prone to developing homogeneous MNA.

Event-free survival of infants and toddlers enrolled in the HR-NBL-1/SIOPEN trial is associated with the level of neuroblastoma mRNAs at diagnosis.

BACKGROUND: The purpose of this study was to evaluate whether levels of neuroblastoma mRNAs in bone marrow and peripheral blood from stage M infants (≤12 months of age at diagnosis, MYCN amplified) and toddlers (between 12 and 18 months, any MYCN status) predict event-free survival (EFS). METHODS: Bone marrow aspirates and peripheral blood samples from 97 infants/toddlers enrolled in the European High-Risk Neuroblastoma trial were collected at diagnosis in PAXgene™ blood RNA tubes. Samples were analyzed by reverse transcription quantitative polymerase chain reaction according to standardized procedures. RESULTS: Bone marrow tyrosine hydroxylase (TH) or paired-like homeobox 2b (PHOX2B) levels in the highest tertile were associated with worse EFS; hazard ratios, adjusted for age and MYCN status, were 1.5 and 1.8 respectively. Expression of both TH and PHOX2B in the highest tertile predicted worse outcome (p = 0.015), and identified 20 (23%) infants/toddlers with 5-year EFS of 20% (95%CI: 4%-44%). Prognostic significance was maintained after adjusting for over-fitting bias (p = 0.038), age and MYCN status. In peripheral blood, PHOX2B levels in the highest tertile predicted a two-fold increased risk of an event (p = 0.032), and identified 23 (34%) infants/toddlers with 5-year EFS of 29% (95%CI: 12%-48%). Time-dependent receiver operating characteristic analysis confirmed the prognostic value of combined TH and PHOX2B in bone marrow and of PHOX2B in peripheral blood during the first year of follow-up. CONCLUSIONS: High levels of bone marrow TH and PHOX2B and of peripheral blood PHOX2B at diagnosis allow early identification of a group of high-risk infant and toddlers with neuroblastoma who may be candidates for alternative treatments. Integration with additional biomarkers, as well as validation in additional international trials is warranted.

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.

Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

BACKGROUND: Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. RESULTS: We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. CONCLUSIONS: Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.

A digital repository with an extensible data model for biobanking and genomic analysis management.

MOTIVATION: Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management. RESULTS: We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing. CONCLUSIONS: Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.

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.

Hypoxia downregulates the expression of activating receptors involved in NK-cell-mediated target cell killing without affecting ADCC.

In certain infection sites or tumor tissues, the disruption of homeostasis can give rise to a hypoxic microenvironment, which, in turn, can alter the function of different immune cell types and favor the progression of the disease. Natural killer (NK) cells are directly involved in the elimination of virus-infected or transformed cells, however it is unknown whether their function is affected by hypoxia or not. In this study, we show that NK cells adapt to a hypoxic environment by upregulating the hypoxia-inducible factor 1α. However, NK cells lose their ability to upregulate the surface expression of the major activating NK-cell receptors (NKp46, NKp30, NKp44, and NKG2D) in response to IL-2 (or other activating cytokines, including IL-15, IL-12, and IL-21). These altered phenotypic features correlate with reduced responses to triggering signals resulting in impaired capability of killing infected or tumor target cells. Remarkably, hypoxia does not significantly alter the surface density and the triggering function of the Fc-γ receptor CD16, thus allowing NK cells to maintain their capability of killing target cells via antibody-dependent cellular cytotoxicity. This finding offers an important clue for exploitation of NK cell in antibody-based immunotherapy of cancer.

Spermine metabolism and radiation-derived reactive oxygen species for future therapeutic implications in cancer: an additive or adaptive response.

Destruction of cells by irradiation-induced radical formation is one of the most frequent interventions in cancer therapy. An alternative to irradiation-induced radical formation is in principle drug-induced formation of radicals, and the formation of toxic metabolites by enzyme catalyzed reactions. Thus, combination therapy targeting polyamine metabolism could represent a promising strategy to fight hyper-proliferative disease. The aim of this work is to discuss and evaluate whether the presence of a DNA damage provoked by enzymatic ROS overproduction may act as an additive or adaptive response upon radiation and combination of hyperthermia with lysosomotropic compounds may improve the cytocidal effect of polyamines oxidation metabolites. Low level of X-irradiations delivers challenging dose of damage and an additive or adaptive response with the chronic damage induced by spermine oxidase overexpression depending on the deficiency of the DNA repair mechanisms. Since reactive oxygen species lead to membrane destabilization and cell death, we discuss the effects of BSAO and spermine association in multidrug resistant cells that resulted more sensitive to spermine metabolites than their wild-type counterparts, due to an increased mitochondrial activity. Since mammal spermine oxidase is differentially activated in a tissue specific manner, and cancer cells can differ in term of DNA repair capability, it could be of interest to open a scientific debate to use combinatory treatments to alter spermine metabolism and deliver differential response.

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.

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.

Cytokines induce tight junction disassembly in airway cells via an EGFR-dependent MAPK/ERK1/2-pathway.

Epithelial barrier permeability is altered in inflammatory respiratory disorders by a variety of noxious agents through modifications of the epithelial cell structure that possibly involve tight junction (TJ) organization. To evaluate in vitro whether pro-inflammatory cytokines involved in the pathogenesis of respiratory disorders could alter TJ organization and epithelial barrier integrity, and to characterize the signal transduction pathway involved Calu-3 airway epithelial cells were exposed to TNF-a, IL-4 and IFN-g to assess changes in: (a) TJ assembly, that is, occludin and zonula occludens (ZO)-1 expression and localization, evaluated by confocal microscopy; (b) apoptotic activity, quantified using terminal transferase deoxyuridine triphosphate nick-end labeling staining; (c) epithelial barrier integrity, detected as transmembrane electrical resistance and expressed as G(T) values; (d) epidermal growth factor receptor (EGFR)-dependent mitogenactivated protein (MAP) kinase (MAPK)/extracellular signal-regulated kinases (ERK)1/2 phosphorylation, assessed by western blotting. Exposure to cytokines for 48 h induced a noticeable downregulation of the TJ transmembrane proteins. The degree ZO-1 and occludin colocalization was 62±2% in control cultures and significantly decreased in the presence of TNF-a (47±3%), IL-4 (43±1%) and INF-g (35±3%). Although no apoptosis induction was detected following exposure to cytokines, changes in the epithelial barrier integrity were observed, with a significant enhancement in paracellular conductance. G(T) values were, respectively, 1.030±0.0, 1.300±0.04, 1.260±0.020 and 2.220±0.015 (mS/cm²)1000 in control cultures and in those exposed to TNF-a, IFN-g and IL-4. The involvement of EGFR-dependent MAPK/ERK1/2 signaling pathway in cytokine-induced damage was demonstrated by a significant increase in threonine/tyrosine phosphorylation of ERK1/2, already detectable after 5 min incubation. All these cytokine-induced changes were markedly prevented when Calu-3 cells were cultured in the presence of an EGFR inhibitor (AG1478, 1 µM) or a MAP kinase inhibitor (U0126, 25 µM). In conclusion, cytokine-induced epithelial injury includes TJ disassembly and epithelial barrier permeability alteration and involves the EGFR-dependent MAPK/ERK1/2 signaling pathway.

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.

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

BACKGROUND: Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome. RESULTS: We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo) taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification. CONCLUSIONS: Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

Identification of multiple hypoxia signatures in neuroblastoma cell lines by l1-l2 regularization and data reduction.

Hypoxia is a condition of low oxygen tension occurring in the tumor and negatively correlated with the progression of the disease. We studied the gene expression profiles of nine neuroblastoma cell lines grown under hypoxic conditions to define gene signatures that characterize hypoxic neuroblastoma. The l(1)-l(2) regularization applied to the entire transcriptome identified a single signature of 11 probesets discriminating the hypoxic state. We demonstrate that new hypoxia signatures, with similar discriminatory power, can be generated by a prior knowledge-based filtering in which a much smaller number of probesets, characterizing hypoxia-related biochemical pathways, are analyzed. l(1)-l(2) regularization identified novel and robust hypoxia signatures within apoptosis, glycolysis, and oxidative phosphorylation Gene Ontology classes. We conclude that the filtering approach overcomes the noisy nature of the microarray data and allows generating robust signatures suitable for biomarker discovery and patients risk assessment in a fraction of computer time.

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

The biological and clinical heterogeneity of neuroblastoma (NB) demands novel biomarkers and therapeutic targets in order to drive the most appropriate treatment for each patient. Hypoxia is a condition of low-oxygen tension occurring in poorly vascularized tumor tissues. In this study, we aimed to assess the role of hypoxia in the pathogenesis of NB and at developing a new clinically relevant hypoxia-based predictor of outcome. We analyzed the gene expression profiles of 1882 untreated NB primary tumors collected at diagnosis and belonging to four existing data sets. Analyses took advantage of machine learning methods. We identified NB-hop, a seven-gene hypoxia biomarker, as a predictor of NB patient prognosis, which is able to discriminate between two populations of patients with unfavorable or favorable outcome on a molecular basis. NB-hop retained its prognostic value in a multivariate model adjusted for established risk factors and was able to additionally stratify clinically relevant groups of patients. Tumors with an unfavorable NB-hop expression showed a significant association with telomerase activation and a hypoxic, immunosuppressive, poorly differentiated, and apoptosis-resistant tumor microenvironment. NB-hop defines a new population of NB patients with hypoxic tumors and unfavorable prognosis and it represents a critical factor for the stratification and treatment of NB patients.

The SRCIN1/p140Cap adaptor protein negatively regulates the aggressiveness of neuroblastoma.

Neuroblastoma is the most common extra-cranial pediatric solid tumor, responsible for 13-15% of pediatric cancer death. Its intrinsic heterogeneity makes it difficult to target for successful therapy. The adaptor protein p140Cap/SRCIN1 negatively regulates tumor cell features and limits breast cancer progression. This study wish to assess if p140Cap is a key biological determinant of neuroblastoma outcome. RNAseq profiles of a large cohort of neuroblastoma patients show that SRCIN1 mRNA levels are an independent risk factor inversely correlated to disease aggressiveness. In high-risk patients, CGH+SNP microarray analysis of primary neuroblastoma identifies SRCIN1 as frequently altered by hemizygous deletion, copy-neutral loss of heterozygosity, or disruption. Functional experiments show that p140Cap negatively regulates Src and STAT3 signaling, affects anchorage-independent growth and migration, in vivo tumor growth and spontaneous lung metastasis formation. p140Cap also increases sensitivity of neuroblastoma cells to doxorubicin and etoposide treatment, as well as to a combined treatment with chemotherapy drugs and Src inhibitors. Our functional findings point to a causal role of p140Cap in curbing the aggressiveness of neuroblastoma, due to its ability to impinge on specific molecular pathways, and to sensitize cells to therapeutic treatment. This study provides the first evidence that the SRCIN1/p140Cap adaptor protein is a key player in neuroblastoma as a new independent prognostic marker for patient outcome and treatment. Altogether, these data highlight the potential clinical impact of SRCIN1/p140Cap expression in neuroblastoma tumors, in terms of reducing cytotoxic effects of chemotherapy, one of the main issues for pediatric tumor treatment.