Phylogenetic analysis of the human thyroglobulin regions.

International audienceABSTRACT: Thyroglobulin is a large protein present in all vertebrates. It is synthesized in the thyrocytes and exported to lumen of the thyroid follicle, where its tyrosine residues are iodinated . The iodinated thyroglobulin is reintegrated into the cell and processed (cleaved to free its two extremities) for thyroid hormone synthesis. Thyroglobulin sequence analysis has identified four regions of the molecule: Tg1, Tg2, Tg3 and ChEL. Structural abnormalities and mutations result in different pathological consequences, depending on the thyroglobulin region affected. We carried out a bioinformatic analysis of thyroglobulin, determining the origin and the function of each region. Our results suggest that the Tg1 region acts as a binding protein on the apical membrane, the Tg2 region is involved in protein adhesion and the Tg3 region is involved in determining the three-dimensional structure of the protein. The ChEL domain is involved in thyroglobulin transport, dimerization and adhesion. The presence of repetitive domains in the Tg1, Tg2 and Tg3 regions suggests that these domains may have arisen through duplication

MADGene: retrieval and processing of gene identifier lists for the analysis of heterogeneous microarray datasets

Summary: MADGene is a software environment comprising a web-based database and a java application. This platform aims at unifying gene identifiers (ids) and performing gene set analysis. MADGene allows the user to perform inter-conversion of clone and gene ids over a large range of nomenclatures relative to 17 species. We propose a set of 23 functions to facilitate the analysis of gene sets and we give two microarray applications to show how MADGene can be used to conduct meta-analyses

PGC-1-Related Coactivator Modulates Mitochondrial-Nuclear Crosstalk through Endogenous Nitric Oxide in a Cellular Model of Oncocytic Thyroid Tumours

BACKGROUND:The PGC-1 related coactivator (PRC), which shares structural and functional features with PGC-1alpha, is believed to regulate several metabolic pathways as well as mitochondrial biogenesis. Its involvement in the early programming of cell proliferation suggests the existence of finely regulated crosstalk between mitochondrial functions and the cell cycle status. METHODOLOGY/PRINCIPAL FINDINGS:PRC-regulated pathways were explored in a cell-line model derived from mitochondrial-rich tumours with an essentially oxidative metabolism and specifically high PRC expression. The functional status of mitochondria was compared to the results of microarray analysis under conditions of temporal PRC inhibition. To specify the fine PRC regulation, the expression levels of the genes and proteins involved in the oxidative phosphorylation process were studied by real time quantitative PCR and western blotting. As in earlier studies on PGC-1alpha, we investigated the role of nitric oxide in PRC-regulated mitochondrial biogenesis and determined its action in the control of the phosphorylation status of the mitogen-activated protein kinase pathway. CONCLUSION/SIGNIFICANCE:We found that nitric oxide rapidly influences PRC expression at the transcriptional level. Focusing on mitochondrial energetic metabolism, we observed that PRC differentially controls respiratory chain complexes and coupling efficiency in a time-dependent manner to maintain mitochondrial homeostasis. Our results highlight the key role of PRC in the rapid modulation of metabolic functions in response to the status of the cell cycle

Targeted Next-Generation Sequencing of Congenital Hypothyroidism-causative Genes Reveals Unexpected Thyroglobulin Gene Variants in Patients with Iodide Transport Defect

Congenital iodide transport defect is an uncommon autosomal recessive disorder caused by loss-of-function variants in the sodium iodide symporter (NIS)-coding SLC5A5 gene and leading to dyshormonogenic congenital hypothyroidism. Here, we conducted a targeted next-generation sequencing assessment of congenital hypothyroidism-causative genes in a cohort of nine unrelated pediatric patients suspected of having a congenital iodide transport defect based on the absence of 99mTc-pertechnetate accumulation in a eutopic thyroid gland. Although, unexpectedly, we could not detect pathogenic SLC5A5 gene variants, we identified two novel compound heterozygous TG gene variants (p.Q29* and c.177-2A\u3eC), three novel heterozygous TG gene variants (p.F1542Vfs*20, p.Y2563C, and p.S523P), and a novel heterozygous DUOX2 gene variant (p.E1496Dfs*51). Splicing minigene reporter-based in vitro assays revealed that the variant c.177-2A\u3eC affected normal TG pre-mRNA splicing, leading to the frameshift variant p.T59Sfs*17. The frameshift TG variants p.T59Sfs*17 and p.F1542Vfs*20, but not the DUOX2 variant p.E1496Dfs*51, were predicted to undergo nonsense-mediated decay. Moreover, functional in vitro expression assays revealed that the variant p.Y2563C reduced the secretion of the TG protein. Our investigation revealed unexpected findings regarding the genetics of congenital iodide transport defects, supporting the existence of yet to be discovered mechanisms involved in thyroid hormonogenesis

Increasing the Number of Thyroid Lesions Classes in Microarray Analysis Improves the Relevance of Diagnostic Markers

BackgroundGenetic markers for thyroid cancers identified by microarray analysis have offered limited predictive accuracy so far because of the few classes of thyroid lesions usually taken into account. To improve diagnostic relevance, we have simultaneously analyzed microarray data from six public datasets covering a total of 347 thyroid tissue samples representing 12 histological classes of follicular lesions and normal thyroid tissue. Our own dataset, containing about half the thyroid tissue samples, included all categories of thyroid lesions. Methodology/Principal Findings Classifier predictions were strongly affected by similarities between classes and by the number of classes in the training sets. In each dataset, sample prediction was improved by separating the samples into three groups according to class similarities. The cross-validation of differential genes revealed four clusters with functional enrichments. The analysis of six of these genes (APOD, APOE, CLGN, CRABP1, SDHA and TIMP1) in 49 new samples showed consistent gene and protein profiles with the class similarities observed. Focusing on four subclasses of follicular tumor, we explored the diagnostic potential of 12 selected markers (CASP10, CDH16, CLGN, CRABP1, HMGB2, ALPL2, ADAMTS2, CABIN1, ALDH1A3, USP13, NR2F2, KRTHB5) by real-time quantitative RT-PCR on 32 other new samples. The gene expression profiles of follicular tumors were examined with reference to the mutational status of the Pax8-PPARγ, TSHR, GNAS and NRAS genes. Conclusion/Significance We show that diagnostic tools defined on the basis of microarray data are more relevant when a large number of samples and tissue classes are used. Taking into account the relationships between the thyroid tumor pathologies, together with the main biological functions and pathways involved, improved the diagnostic accuracy of the samples. Our approach was particularly relevant for the classification of microfollicular adenomas

Immune Response and Mitochondrial Metabolism Are Commonly Deregulated in DMD and Aging Skeletal Muscle

Duchenne Muscular Dystrophy (DMD) is a complex process involving multiple pathways downstream of the primary genetic insult leading to fatal muscle degeneration. Aging muscle is a multifactorial neuromuscular process characterized by impaired muscle regeneration leading to progressive atrophy. We hypothesized that these chronic atrophying situations may share specific myogenic adaptative responses at transcriptional level according to tissue remodeling. Muscle biopsies from four young DMD and four AGED subjects were referred to a group of seven muscle biopsies from young subjects without any neuromuscular disorder and explored through a dedicated expression microarray. We identified 528 differentially expressed genes (out of 2,745 analyzed), of which 328 could be validated by an exhaustive meta-analysis of public microarray datasets referring to DMD and Aging in skeletal muscle. Among the 328 validated co-expressed genes, 50% had the same expression profile in both groups and corresponded to immune/fibrosis responses and mitochondrial metabolism. Generalizing these observed meta-signatures with large compendia of public datasets reinforced our results as they could be also identified in other pathological processes and in diverse physiological conditions. Focusing on the common gene signatures in these two atrophying conditions, we observed enrichment in motifs for candidate transcription factors that may coordinate either the immune/fibrosis responses (ETS1, IRF1, NF1) or the mitochondrial metabolism (ESRRA). Deregulation in their expression could be responsible, at least in part, for the same transcriptome changes initiating the chronic muscle atrophy. This study suggests that distinct pathophysiological processes may share common gene responses and pathways related to specific transcription factors

Meta-analysis of muscle transcriptome data using the MADMuscle database reveals biologically relevant gene patterns

<p>Abstract</p> <p>Background</p> <p>DNA microarray technology has had a great impact on muscle research and microarray gene expression data has been widely used to identify gene signatures characteristic of the studied conditions. With the rapid accumulation of muscle microarray data, it is of great interest to understand how to compare and combine data across multiple studies. Meta-analysis of transcriptome data is a valuable method to achieve it. It enables to highlight conserved gene signatures between multiple independent studies. However, using it is made difficult by the diversity of the available data: different microarray platforms, different gene nomenclature, different species studied, etc.</p> <p>Description</p> <p>We have developed a system tool dedicated to muscle transcriptome data. This system comprises a collection of microarray data as well as a query tool. This latter allows the user to extract similar clusters of co-expressed genes from the database, using an input gene list. Common and relevant gene signatures can thus be searched more easily. The dedicated database consists in a large compendium of public data (more than 500 data sets) related to muscle (skeletal and heart). These studies included seven different animal species from invertebrates (<it>Drosophila melanogaster, Caenorhabditis elegans</it>) and vertebrates (<it>Homo sapiens, Mus musculus, Rattus norvegicus, Canis familiaris, Gallus gallus</it>). After a renormalization step, clusters of co-expressed genes were identified in each dataset. The lists of co-expressed genes were annotated using a unified re-annotation procedure. These gene lists were compared to find significant overlaps between studies.</p> <p>Conclusions</p> <p>Applied to this large compendium of data sets, meta-analyses demonstrated that conserved patterns between species could be identified. Focusing on a specific pathology (Duchenne Muscular Dystrophy) we validated results across independent studies and revealed robust biomarkers and new pathways of interest. The meta-analyses performed with MADMuscle show the usefulness of this approach. Our method can be applied to all public transcriptome data.</p

Classification moléculaire des tumeurs thyroïdiennes: intérêts et limites de l'approche transcriptormique

International audienceLe transcriptome permet d'avoir une vision globale des fonctions dérégulées dans une classe tumorale. » L'analyse du transcriptome permet d'identifier les processus tumoraux initiaux, mais aussi les réactions du tissu environnant (infiltrats lymphocytaires). » Il existe une meilleure corrélation entre le statut mutationnel et le transcriptome d'une tumeur qu'entre le statut mutationnel et l'histologie de cette tumeur. » L'identification de biomarqueurs spécifiques de classe n'est pertinente que si le transcriptome de l'ensemble des classes pathologiques de l'organe est exploré. » Le profil d'expression de biomarqueurs ciblés présente un réel potentiel diagnostique pour les classes intermédiaires de pathologies.</p

Classification moléculaire des tumeurs thyroïdiennes: intérêts et limites de l'approche transcriptormique

International audienceLe transcriptome permet d'avoir une vision globale des fonctions dérégulées dans une classe tumorale. » L'analyse du transcriptome permet d'identifier les processus tumoraux initiaux, mais aussi les réactions du tissu environnant (infiltrats lymphocytaires). » Il existe une meilleure corrélation entre le statut mutationnel et le transcriptome d'une tumeur qu'entre le statut mutationnel et l'histologie de cette tumeur. » L'identification de biomarqueurs spécifiques de classe n'est pertinente que si le transcriptome de l'ensemble des classes pathologiques de l'organe est exploré. » Le profil d'expression de biomarqueurs ciblés présente un réel potentiel diagnostique pour les classes intermédiaires de pathologies.</p

Recherche des mutations du récepteur de l EGF sur coupes de tissu tumoral pulmonaire inclus en paraffine et sensibilité aux thérapeutiques

ANGERS-BU Médecine-Pharmacie (490072105) / SudocSudocFranceF