Simultaneous analysis of distinct Omics data sets with integration of biological knowledge: Multiple Factor Analysis approach

<p>Abstract</p> <p>Background</p> <p>Genomic analysis will greatly benefit from considering in a global way various sources of molecular data with the related biological knowledge. It is thus of great importance to provide useful integrative approaches dedicated to ease the interpretation of microarray data.</p> <p>Results</p> <p>Here, we introduce a data-mining approach, Multiple Factor Analysis (MFA), to combine multiple data sets and to add formalized knowledge. MFA is used to jointly analyse the structure emerging from genomic and transcriptomic data sets. The common structures are underlined and graphical outputs are provided such that biological meaning becomes easily retrievable. Gene Ontology terms are used to build gene modules that are superimposed on the experimentally interpreted plots. Functional interpretations are then supported by a step-by-step sequence of graphical representations.</p> <p>Conclusion</p> <p>When applied to genomic and transcriptomic data and associated Gene Ontology annotations, our method prioritize the biological processes linked to the experimental settings. Furthermore, it reduces the time and effort to analyze large amounts of 'Omics' data.</p

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

BACKGROUND: Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). RESULTS: We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). CONCLUSION: The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions

Analyse protéomique des glioblastones: Quel est le meilleur contrôle?

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Permanent Polymer Coating for in vivo MRI Visualization of Tissue Reinforcement Prostheses

The clinical advantage of MRI visualization of prostheses in soft tissue prolapses is very appealing as over 1?000?000 MRI-transparent synthetic meshes are implanted annually, and postoperative complications such as mesh shrinkage and migration are frequent. Here, the synthesis of a new material composed of a DTPA-Gd complex grafted onto a backbone of PMA via a covalent bond is described (DTPA-Gd-PMA). This new polymer is sprayed onto meshes and gives an MR signal for a long period without any significant release of Gd. In vitro cytocompatibility tests on fibroblasts show limited cytotoxicity. Microscopic investigations indicate that vital cells rapidly colonize the material. Finally, coated meshes implanted in rats are easily recognizable using an MR imaging system

Mouse genetic background impacts both on iron and non-iron metals parameters and on their relationships

International audienceIron is reported to interact with other metals. In addition, it has been shown that genetic background may impact iron metabolism. Our objective was to characterize, in mice of three genetic backgrounds, the links between iron and several non-iron metals. Thirty normal mice (C57BL/6, Balb/c and DBA/2; n = 10 for each group), fed with the same diet, were studied. Quantification of iron, zinc, cobalt, copper, manganese, magnesium and rubidium was performed by ICP/MS in plasma, erythrocytes, liver and spleen. Transferrin saturation was determined. Hepatic hepcidin1 mRNA level was evaluated by quantitative RT-PCR. As previously reported, iron parameters were modulated by genetic background with significantly higher values for plasma iron parameters and liver iron concentration in DBA/2 and Balb/c strains. Hepatic hepcidin1 mRNA level was lower in DBA/2 mice. No iron parameter was correlated with hepcidin1 mRNA levels. Principal component analysis of the data obtained for non-iron metals indicated that metals parameters stratified the mice according to their genetic background. Plasma and tissue metals parameters that are dependent or independent of genetic background were identified. Moreover, relationships were found between plasma and tissue content of iron and some other metals parameters. Our data: (i) confirms the impact of the genetic background on iron parameters, (ii) shows that genetic background may also play a role in the metabolism of non-iron metals, (iii) identifies links between iron and other metals parameters which may have implications in the understanding and, potentially, the modulation of iron metabolis

DGKI Methylation Status Modulates the Prognostic Value of MGMT in Glioblastoma Patients Treated with Combined Radio-Chemotherapy with Temozolomide

International audienceBackgroundConsistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status.Methods399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1) and MGMT-methylated patients (population 2). Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2.ResultsThe nomogram-based stratification of the cohort identified two risk groups (high/low) with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram.ConclusionsOur results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future

Five distinct biological processes and 14 differentially expressed genes characterize TEL/AML1-positive leukemia

<p>Abstract</p> <p>Background</p> <p>The t(12;21)(p13;q22) translocation is found in 20 to 25% of cases of childhood B-lineage acute lymphoblastic leukemia (B-ALL). This rearrangement results in the fusion of <it>ETV6 </it>(<it>TEL</it>) and <it>RUNX1 </it>(<it>AML1</it>) genes and defines a relatively uniform category, although only some patients suffer very late relapse. <it>TEL/AML1</it>-positive patients are thus an interesting subgroup to study, and such studies should elucidate the biological processes underlying TEL/AML1 pathogenesis. We report an analysis of gene expression in 60 children with B-lineage ALL using Agilent whole genome oligo-chips (44K-G4112A) and/or real time RT-PCR.</p> <p>Results</p> <p>We compared the leukemia cell gene expression profiles of 16 <it>TEL/AML1</it>-positive ALL patients to those of 44 <it>TEL/AML1</it>-negative patients, whose blast cells did not contain any additional recurrent translocation. Microarray analyses of 26 samples allowed the identification of genes differentially expressed between the TEL/AML1-positive and negative ALL groups. Gene enrichment analysis defined five enriched GO categories: cell differentiation, cell proliferation, apoptosis, cell motility and response to wounding, associated with 14 genes -<it>RUNX1, TCFL5, TNFRSF7, CBFA2T3</it>, <it>CD9</it>, <it>SCARB1, TP53INP1, ACVR1C, PIK3C3, EGFL7</it>, <it>SEMA6A, CTGF, LSP1, TFPI </it>– highlighting the biology of the <it>TEL/AML1 </it>sub-group. These results were first confirmed by the analysis of an additional microarray data-set (7 patient samples) and second by real-time RT-PCR quantification and clustering using an independent set (27 patient samples). Over-expression of <it>RUNX1 (AML1) </it>was further investigated and in one third of the patients correlated with cytogenetic findings.</p> <p>Conclusion</p> <p>Gene expression analyses of leukemia cells from 60 children with <it>TEL/AML1</it>-positive and -negative B-lineage ALL led to the identification of five biological processes, associated with 14 validated genes characterizing and highlighting the biology of the <it>TEL/AML1</it>-positive ALL sub-group.</p

Conception de prothèse visible en IRM pour la prise en charge chirurgicale des prolapsus génitaux et des hernies abdominales

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