The α1-adrenergic receptors: diversity of signaling networks and regulation

The α1-adrenergic receptor (AR) subtypes (α1a, α1b, and α1d) mediate several physiological effects of epinephrineand norepinephrine. Despite several studies in recombinant systems and insightfrom genetically modified mice, our understanding of the physiological relevance and specificity of the α1-AR subtypes is still limited. Constitutive activity and receptor oligomerization have emerged as potential features regulating receptor function. Another recent paradigm is that βarrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effects. The aim of this review is to summarize our current knowledge on some recently identified functional paradigms and signaling networks that might help to elucidate the functional diversity of the α1-AR subtypes in various organs

Expression and function of G-protein-coupled receptorsin the male reproductive tract

This review focuses on the expression and function of muscarinic acetylcholine receptors (mAChRs), α1-adrenoceptors and relaxin receptors in the male reproductive tract. The localization and differential expression of mAChR and α1-adrenoceptor subtypes in specific compartments of the efferent ductules, epididymis, vas deferens, seminal vesicle and prostate of various species indicate a role for these receptors in the modulation of luminal fluid composition and smooth muscle contraction, including effects on male fertility. Furthermore, the activation of mAChRs induces transactivation of the epidermal growth factor receptor (EGFR) and the Sertoli cell proliferation. The relaxin receptors are present in the testis, RXFP1 in elongated spermatids and Sertoli cells from rat, and RXFP2 in Leydig and germ cells from rat and human, suggesting a role for these receptors in the spermatogenic process. The localization of both receptors in the apical portion of epithelial cells and smooth muscle layers of the vas deferens suggests an involvement of these receptors in the contraction and regulation of secretion.Esta revisão enfatiza a expressão e a função dos receptores muscarínicos, adrenoceptores α1 e receptores para relaxina no sistema reprodutor masculino. A expressão dos receptores muscarínicos e adrenoceptores α1 em compartimentos específicos de dúctulos eferentes, epidídimo, ductos deferentes, vesícula seminal e próstata de várias espécies indica o envolvimento destes receptores na modulação da composição do fluido luminal e na contração do músculo liso, incluindo efeitos na fertilidade masculina. Além disso, a ativação dos receptores muscarínicos leva à transativação do receptor para o fator crescimento epidermal e proliferação das células de Sertoli. Os receptores para relaxina estão presentes no testículo, RXFP1 nas espermátides alongadas e células de Sertoli de rato e RXFP2 nas células de Leydig e germinativas de ratos e humano, sugerindo o envolvimento destes receptores no processo espermatogênico. A localização de ambos os receptores na porção apical das células epiteliais e no músculo liso dos ductos deferentes de rato sugere um papel na contração e na regulação da secreção.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de FarmacologiaUNIFESP, EPM, Depto. de FarmacologiaSciEL

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry

Background: Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients\u2019 clinical phenotypes and analyse the differential clinical course. Methods: We performed a hierarchical cluster analysis based on Ward\u2019s Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results: A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients\u2019 prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P <.001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27\u20133.62; HR 3.42, 95%CI 2.72\u20134.31; HR 2.79, 95%CI 2.32\u20133.35), and Cluster 1 (HR 1.88, 95%CI 1.48\u20132.38; HR 2.50, 95%CI 1.98\u20133.15; HR 2.09, 95%CI 1.74\u20132.51) reported a higher risk for the three outcomes respectively. Conclusions: In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes