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The insulin receptor isoform A (IR-A) plays an increasingly recognized role in fetal growth and tumor biology in response to circulating insulin and/or locally produced IGF2. This role seems not to be shared by the IR isoform B (IR-B). We aimed to dissect the specific impact of IR isoforms in modulating insulin signaling in triple negative breast cancer (TNBC) cells. We generated murine 4T1 TNBC cells deleted from the endogenous insulin receptor (INSR) gene and expressing comparable levels of either human IR-A or IR-B. We then measured IR isoform-specific in vitro and in vivo biological effects and transcriptome in response to insulin. Overall, the IR-A was more potent than the IR-B in mediating cell migration, invasion, and in vivo tumor growth. Transcriptome analysis showed that approximately 89% of insulin-stimulated transcripts depended solely on the expression of the specific isoform. Notably, in cells overexpressing IR-A, insulin strongly induced genes involved in tumor progression and immune evasion including chemokines and genes related to innate immunity. Conversely, in IR-B overexpressing cells, insulin predominantly induced the expression of genes primarily involved in the regulation of metabolic pathways and, to a lesser extent, tumor growth and angiogenesis. [ABSTRACT FROM AUTHOR]

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and, although its genetic background has been extensively studied, little is known about the contribution of non-coding RNAs (ncRNAs) to its pathogenesis. Indeed, its competitive endogenous RNA (ceRNA) regulatory network comprising microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs has been insufficiently explored. Thanks to UM findings from The Cancer Genome Atlas (TCGA), it is now possible to statistically elaborate these data to identify the expression relationships among RNAs and correlative interaction data. In the present work, we propose the VECTOR (uVeal mElanoma Correlation NeTwORk) database, an interactive tool that identifies and visualizes the relationships among RNA molecules, based on the ceRNA model. The VECTOR database contains: (i) the TCGA-derived expression correlation values of miRNA-mRNA, miRNA-lncRNA and lncRNA-mRNA pairs combined with predicted or validated RNA-RNA interactions; (ii) data of sense-antisense sequence overlapping; (iii) correlation values of Transcription Factor (TF)-miRNA, TF-lncRNA, and TF-mRNA pairs associated with ChiPseq data; (iv) expression data of miRNAs, lncRNAs and mRNAs both in UM and physiological tissues. The VECTOR web interface can be queried, by inputting the gene name, to retrieve all the information about RNA signaling and visualize this as a graph. Finally, VECTOR provides a very detailed picture of ceRNA networks in UM and could be a very useful tool for researchers studying RNA signaling in UM. The web version of Vector is freely available at the URL reported at the end of the Introduction. [ABSTRACT FROM AUTHOR]

Obesity represents a major risk factor for metabolic disorders, but some individuals, "metabolically healthy" (MHO), show less clinical evidence of these complications, in contrast to "metabolically unhealthy" (MUO) individuals. The aim of this cross-sectional study is to assess the prevalence of the MHO phenotype in a cohort of 246 overweight/obese Italian children and adolescents, and to evaluate their characteristics and the role of insulin resistance. Homeostasis model assessment–insulin resistance (HOMA-IR), insulin sensitivity index (ISI), insulinogenic index (IGI) and disposition index (DI) were all calculated from the Oral Glucose Tolerance Test (OGTT). MHO was defined by either: (1) HOMA-IR < 2.5 (MHO-IRes), or (2) absence of the criteria for metabolic syndrome (MHO-MetS). The MHO prevalence, according to MHO-MetS or MHO-IRes criteria, was 37.4% and 15.8%, respectively. ISI was the strongest predictor of the MHO phenotype, independently associated with both MHO-IRes and MHO-MetS. The MHO-MetS group was further subdivided into insulin sensitive or insulin resistant on the basis of HOMA-IR (either < or ≥ 2.5). Insulin sensitive MHO-MetS patients had a better metabolic profile compared to both insulin resistant MHO-MetS and MUO-MetS individuals. These data underscore the relevance of insulin sensitivity to identifying, among young individuals with overweight/obesity, the ones who have a more favorable metabolic phenotype. [ABSTRACT FROM AUTHOR]

Gilles de la Tourette syndrome (GTS) and autism spectrum disorder (ASD) are two neurodevelopmental disorders with male predominance, frequently comorbid, that share clinical and behavioral features. The incidence of ASD in patients affected by GTS was reported to be between 2.9% and 22.8%. We hypothesized that higher ASD rates among children affected by GTS previously reported may be due to difficulty in discriminating GTS sub-phenotypes from ASD, and the higher scores in the restrictive and repetitive behaviors in particular may represent at least a "false comorbidity". We studied a large population of 720 children and adolescents affected by GTS (n = 400) and ASD (n = 320), recruited from a single center. Patients were all assessed with The Yale Global Tic Severity Rating Scale (YGTSS), The Autism Diagnostic Observation Schedule (ADOS), The Autism Diagnostic Interview Revised (ADI-R), The Children's Yale–Brown Obsessive–Compulsive Scale (CY-BOCS), and The Children's Yale–Brown Obsessive–Compulsive Scale for autism spectrum disorder (CY-BOCS ASD). Our results showed statistically significant differences in ADOS scores for social aspects between GTS with comorbid attention deficit hyperactivity disorder (ADHD) and obsessive–compulsive disorder (OCD) sub-phenotypes and ASD. No differences were present when we compared GTS with comorbid ASD sub-phenotype to ASD, while repetitive and restrictive behavior scores in ASD did not present statistical differences in the comparison with GTS and comorbid OCD and ASD sub-phenotypes. We also showed that CY-BOCS ASD could be a useful instrument to correctly identify OCD from ASD symptoms. [ABSTRACT FROM AUTHOR]