Expression data from primary human skin fibroblasts treated with vehicle (DMSO) and the antioxidant Trolox (0.5 mM, 96 hrs)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Werner Koopman
PROVIDER: E-GEOD-32502 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:While blood transcriptional profiling has improved diagnosis and understanding of disease pathogenesis of adult tuberculosis (TB), no studies applying gene expression profiling of children with TB have been described so far. In this study, we have compared whole blood gene expression in childhood TB patients, as well as in healthy latently infected (LTBI) and uninfected (HC) children in a cohort of Warao Amerindians in the Delta Amacuro in Venezuela. We identified a 116-gene signature set by means of random forest analysis that showed an average prediction error of 11% for TB vs. LTBI and for TB vs. LTBI vs. HC in our dataset. Furthermore, a minimal set of only 9 genes showed a significant predictive value for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. Additionally, a minimal gene set of 42 genes with a comparable predictive value to the 116-gene set in both our dataset and the previously published literature cohorts for the comparsion of TB vs. LTBI vs. HC was identified. In order to identify a robust representative gene set that would hold stand among different ethnic populations, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these ten genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to diagnose 78% of the TB cases correctly with 100% specificity. We conclude that our data justify the further exploration of our signature set as biomarkers to diagnose childhood TB. Furthermore, as the identification of different biomarkers in ethnically distinct cohorts is apparent, it is important to cross-validate newly identified markers in all available cohorts. In this study, 27 children 1 to 15 years of age with TB (n=9), LTBI (n=9) and HC (n=9) were recruited between May 2010 and December 2010. Tuberculin skin test (TST) and QuantiFERON-TB Gold In-Tube assay (QFT-GIT) were performed on all children. A sputum sample was collected from all children with expectoration and a gastric aspirate was taken from all children under 6 years of age. Children with active TB were diagnosed based on culture of M. tuberculosis (n=2) or on the basis of clinical, epidemiological and radiological features (n=7). The latter group were children with a TST = 10 mm or a positive QFT-GIT result who presented all of: persistent fever >38M-BM-0C objectively recorded daily for at least two weeks, persistent cough for more than three weeks, weight loss (>5% reduction in weight compared with the highest weight recorded in last three months) or failure to thrive (documented crossing of percentile lines in the preceding three months), persistent lethargy or decrease in playfulness/activity reported by the parent and absence of clinical response on broad-spectrum antibiotics. Standard antero-posterior and lateral chest radiographs (CXRs) were taken from all children. Two independent experts, blinded to all clinical information, evaluated the CXRs and documented their findings on a standard report form. Where the two objective experts disagreed, a third expert was consulted and final consensus was achieved. A diagnosis of TB was only made when the CXR was consistent with TB9 and the child showed a positive clinical response to anti-TB treatment. Children were followed up clinically, radiologically and, in case of a negative TST at inclusion, by means of TST at six and 12 months after inclusion. LTBI was defined as a TST = 10mm and a positive QFT-GIT with a negative culture result on inclusion in the absence of radiological and clinical evidence of TB disease on inclusion as well as on t=6 and t=12 months. HC were children with a TST = 0 mm at inclusion and at t=6 and t=12 months. The HC had a negative QFT-GIT and a negative culture result at inclusion without radiological or clinical evidence of TB disease on inclusion nor on t=6 and t=12 months. TB patients were sampled before initiation of anti-TB treatment. Of three of the nine TB patients, a follow-up sample was taken when the patient was in anti-TB treatment for five months. All children were HIV-negative. 27 samples in total where analyzed, active TB infection (TB, n=9), Latent TB infection (LTBI, n=9) and healthy controls (HC, n=9) . Gene expression values were log2-transformed and differentially expressed genes were identified based on log2 fold changes (M-values). P values were calculated with a Bayes-regularized one-way ANOVA. Random Forest recursive feature elimination was used to find a signature geneset capable of discrimination active TB from latent TB and from non-infected individuals.
2013-02-05 | E-GEOD-41055 | biostudies-arrayexpress
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Project description:transcriptome profiling of miR-92a inhibitor treated and control cells with the aim of measuring miR-92a influence on its mRNA targets Abstract: MicroRNAs (miRNAs) play key roles in gene regulation, but reliable bioinformatic or experimental identification of their targets remains difficult. To provide an unbiased view of human miRNA targets we developed a technique for ligation and sequencing of miRNA-target RNA duplexes associated with human Ago1. Here we report datasets of more than 18,000 high-confidence miRNA-mRNA interactions. The binding of most miRNAs includes the 5' seed region, but around 60% of seed interactions are noncanonical, containing bulged or mismatched nucleotides. Moreover, seed interactions are generally accompanied by specific, non-seed basepairing. 18% of miRNA-mRNA interactions involve the miRNA 3' end, with little evidence for 5' contacts, and some of these were functionally validated. Analyses of miRNA:mRNA basepairing showed that miRNA species systematically differ in their target RNA interactions, and strongly overrepresented motifs were found in the interaction sites of several miRNAs. We speculate that these affect the response of RISC to miRNA-target binding. In total 10 samples were analyzed, 5 repeats for each experimental condition.
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Project description:The oviducts contain high grade serous cancer precursors, which are M-NM-3-H2AXp and p53 mutation positive. Secretory cell outgrowths (SCOUTs) are associated with older age and serous cancer. We evaluated PAX2 expression in proliferating oviductal cells, normal mucosa, SCOUTs, Walthard cell nests, STINs and HGSCs. Non-ciliated cells in normal mucosa were PAX2 positive but became PAX2 negative in multilayered epithelium. PAX2 negative SCOUTs fell into two groups; Type I were secretory or secretory/ciliated with a M-bM-^@M-^\tubalM-bM-^@M-^] phenotype and were ALDH1 negative. Type II displayed a columnar to pseudostratified phenotype, with an EZH2,ALDH1, M-NM-2-catenin, Stathmin, LEF1, RCN1 and RUNX2 expression signature . This study, for the first time, links PAX2 negative with proliferating fetal and adult oviductal cells undergoing basal and ciliated differentiation and shows that this expression state is maintained in SCOUTs, STINs and HGSCs. All three entities can demonstrate a consistent perturbation of genes involved in potential tumor suppressor gene silencing (EZH2), transcriptional regulation (LEF1), regulation of differentiation (RUNX2) calcium binding (RCN1) and oncogenesis (Stathmin). This shared expression signature between benign and neoplastic entities links normal progenitor cell expansion to abnormal and neoplastic outgrowth in the oviduct and exposes a common pathway that could be a target of early prevention. 17 total samples are analyzed. 4 for TYPE 1 SCOUTs, 3 for TYPE 2 SCOUTs, 7 for paired normal epithelium, 3 for tumor
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