Project description:MALT lymphoma is characterized by t(11;18)(q21;q21)/API2-MALT1, t(1;14)(p22;q32)/BCL10-IGH and t(14;18)(q32;q21)/IGH-MALT1, which commonly activate the NF-ÎºB pathway. Gastric MALT lymphomas harboring such translocation do not respond to H. pylori eradication, while those without translocation can be cured by antibiotics. To understand the molecular mechanism of these different MALT lymphoma subgroups, we performed gene expression profiling analysis of 24 MALT lymphomas (15 translocation-positive, 9 translocation-negative). Gene set enrichment analysis (GSEA) of the NF-ÎºB target genes and 4394 additional gene sets covering various cellular pathways, biological processes and molecular functions showed that translocation-positive MALT lymphomas are characterized by an enhanced expression of NF-ÎºB target genes, particularly TLR6, CCR2, CD69 and BCL2, while translocation-negative cases were featured by active inflammatory and immune responses, such as IL8, CD86, CD28 and ICOS. Separate analyses of the genes differentially expressed between translocation-positive and negative cases and measurement of gene ontology term in these differentially expressed genes by hypergeometric test reinforced the above findings by GSEA. Finally, expression of TLR6, in the presence of TLR2, enhanced both API2-MALT1 and BCL10 mediated NF-ÎºB activation in vitro. Our findings provide novel insights into the molecular mechanism of MALT lymphomas with and without translocation, potentially explaining their different clinical behaviors. This study compares MALT with other lymphomas, namely follicular lymphomas (FL) and mantle cell lymphomas (MCL), and investigates the molecular mechanisms of the lymphomagenesis between translocation-positive versus -negative MALT lymphoma cases in order to derive the pathways leading to MALT lymphoma pathogenesis. The study uses fresh frozen tissues from 24 MALT lymphoma cases with 7 FL and 7 MCL. Samples were run on the HG-U133A, HG-U133B, and HG-U133 plus2 GeneChips.

Project description:MALT lymphoma is characterized by t(11;18)(q21;q21)/API2-MALT1, t(1;14)(p22;q32)/BCL10-IGH and t(14;18)(q32;q21)/IGH-MALT1, which commonly activate the NF-κB pathway. Gastric MALT lymphomas harboring such translocation do not respond to H. pylori eradication, while those without translocation can be cured by antibiotics. To understand the molecular mechanism of these different MALT lymphoma subgroups, we performed gene expression profiling analysis of 24 MALT lymphomas (15 translocation-positive, 9 translocation-negative). Gene set enrichment analysis (GSEA) of the NF-κB target genes and 4394 additional gene sets covering various cellular pathways, biological processes and molecular functions showed that translocation-positive MALT lymphomas are characterized by an enhanced expression of NF-κB target genes, particularly TLR6, CCR2, CD69 and BCL2, while translocation-negative cases were featured by active inflammatory and immune responses, such as IL8, CD86, CD28 and ICOS. Separate analyses of the genes differentially expressed between translocation-positive and negative cases and measurement of gene ontology term in these differentially expressed genes by hypergeometric test reinforced the above findings by GSEA. Finally, expression of TLR6, in the presence of TLR2, enhanced both API2-MALT1 and BCL10 mediated NF-κB activation in vitro. Our findings provide novel insights into the molecular mechanism of MALT lymphomas with and without translocation, potentially explaining their different clinical behaviors. This study compares MALT with other lymphomas namely follicular and mantle cell lymphomas, and investigates the molecular mechanisms of the lymphomagenesis between translocation positive versus negative MALT lymphoma cases in order to derive the pathways leading to MALT lymphoma pathogenesis using GSEA, GO, dynamic pathway analysis as well as other bioinformatics analysis. Samples were run on the Affymetrix HG-U133A and HG-U133 plus2 GeneChips.

Project description:The full complement of molecular pathways contributing to Parkinson’s disease (PD) pathogenesis remains unknown. Here, to address this issue, we began by using a high-resolution variant of functional magnetic resonance imaging (fMRI) to pinpoint brainstem regions differentially affected by, and resistant to, the disease. Then, relying on the imaging information as a guide, we profiled gene expression levels of postmortem brain samples and used a factorial statistical model to identify a disease related decrease in the expression of the polyamine enzyme spermidine/spermine N1-acetyltransferase 1 (SAT1). Next, a series of studies were performed to confirm the pathogenic relevance of this finding. First, to test for a causal link between polyamines and α-synuclein toxicity, we investigated a yeast model expressing α-synuclein. Polyamines were found to enhance the toxicity of α-synuclein, and an unbiased genome-wide screen for modifiers of α-synuclein toxicity identified Tpo4, a member of a family of proteins responsible for polyamine transport. Second, to test for a causal link between SAT1 activity and PD histopathology we investigated a mouse model expressing α-synuclein. DENSPM (N1, N11-diethylnorspermine), a polyamine analog that increases SAT1 activity, was found to reduce PD histopathology, while Berenil (diminazene aceturate), a pharmacological agent that reduces SAT1 activity, worsened the histopathology. Third, we genotyped PD patients and controls and isolated a rare but novel variant in the SAT1 gene, although the functional significance of this genetic variant was not identified. Taken together, the results suggest that the polyamine pathway contributes to PD pathogenesis. Imaging-guided microarray In principle, gene expression profiling techniques like microarray are well suited to identify molecular pathways contributing to the pathogenesis of complex diseases. In practice, however, microarray applied to diseases of the brain present a number of analytic challenges. By identifying regions within the same brain structure that are differentially targeted by and resistant to a disease, imaging-guided microarray is an approach designed to address these limitations. Specifically, guided by the spatial information generated from high resolution functional imaging, a 2x2 factorial analysis-of-variance can be designed, including both within and between group factors, and this “double subtraction” model is effective in improving signal-to-noise in a microarray experiment. Relying on imaging findings, we harvested the DMNV from 6 postmortem brains with evidence of PD and from 5 control brains. The postmortem PD cases were evaluated for pathological changes (Lewy body-containing neurons and Lewy neurites evidenced with antibodies directed against α-synuclein aggregates) that matched the pattern proposed by Braak. We relied on the imaging results to identify a neighboring medullary region relatively unaffected by the disease to be used as a within-brain control. We decided on the inferior olivary nucleus (ION), because it is histologically identifiable, and harvested the ION from each of the 6 PD cases and 5 controls. Microarray techniques were used to generate gene expression profiles for each of the 22 tissue samples. A repeated-measures 2x2 factorial ANOVA model constructed for the imaging study was applied to the expression dataset, in which expression levels from two regions of the medulla (DMNV vs. ION) were included as the first within group factor, diagnosis (PD vs. controls) was the between group factor, and age and sex were included as covariates. Based on current literature, one of the top hits (SAT1) was investigated further to determine if it played a role in PD pathogenesis.

Project description:Splenic marginal zone lymphoma (SMZL) is an indolent B-cell lymphoproliferative disorder characterised by 7q32 deletion, but the target genes of this deletion remain unknown. In order to elucidate the genetic target of this deletion, we performed an integrative analysis of the genetic, epigenetic, transcriptomic and miRNomic data. High resolution array comparative genomic hybridization of 56 cases of SMZL delineated a minimally deleted region (2.8Mb) at 7q32, but showed no evidence of any cryptic homozygous deletion or recurrent breakpoint in this region. Integrative transcriptomic analysis confirmed significant under-expression of a number of genes in this region in cases of SMZL with deletion, several of which showed hypermethylation. In addition, a cluster of 8 miRNA in this region showed under-expression in cases with the deletion, and three (miR-182/96/183) were also significantly under-expressed (P <0.05) in SMZL relative to other lymphomas. Genomic sequencing of these miRNA and IRF5, a strong candidate gene, did not show any evidence of somatic mutation in SMZL. For gene expression microarrays. A total of 48 cases of SMZL (including 15 with 7q deletion) were analysed using the Affymetrix HG-U133 Plus 2.0 platform (Affymetrix, Santa Clara, California, USA). 14 SMZL and 10 FL/MCL are included in this submission. The other Samples are part of GSE35348. Arrays were performed according to the manufacturer’s instructions. Briefly, RNA was extracted from snap frozen tissues with >70% tumour cells using the RNEasy extraction kit (Qiagen) and subjected to DNAse treatment (Turbo DNAse kit, Ambion). RNA integrity was assessed using an Agilent 2100 Bioanalyzer. cDNA synthesis was carried out with 2ug RNA using the GeneChip® One-Cycle cDNA Synthesis Kit (Affymetrix), followed by in vitro transcription with biotin-labelled nucleotides using GeneChip® IVT Labeling Kit. Biotinylated cRNA was purified and hybridized to the Affymetrix HG-U133 Plus 2.0 chips in a GeneChip® Hybridisation Oven 640 at 45oC for 14 hours. The arrays were then washed and stained using the Fluidics station 450 system (Affymetrix). The arrays were scanned using the Affymetrix GeneArray® Scanner 3000. Hybridisation and labelling controls were included according to the manufacturer’s instructions, and quality control analysis of microarrays was performed to published standards.

Project description:Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n=223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals (42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD) were processed and hybridized to Affymetrix HG-U133 2.0 Plus microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥7.0 using Agilent 2100 Bioanalyzer software; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤3.0; and (3) the multi-chip normalization scaling factor ≤10.0 Of the 223 samples, 213 (95.5%) passed the QC criteria. In a data set of 34 arrays (10 samples failing QC criteria, 24 randomly chosen samples passing QC criteria), correlation coefficients for pairwise comparisons of expression levels for 100 housekeeping genes in which at least one array failed the QC criteria were significantly lower (average Pearson r = 0.90 ± 0.04) and more broadly dispersed than correlation coefficients for pairwise comparisons between any two arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). By using the QC cutoff criteria, the inter-array variability, as assessed by the coefficient of variation in the expression levels for 100 housekeeping genes, was reduced from 35.7% to 21.7%. Based on the aberrant housekeeping gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation. Affymetrix arrays were used to assess the quality of gene expression data in trachea, large airway and small airway epithelium obtained by fiberoptic bronchoscopy of 42 healthy non-smokers, 49 healthy smokers, 11 symptomatic smokers, 22 smokers with lone emphysema with normal spirometry, and 20 smokers with COPD.

Dataset Information

Human skeletal muscle gene expression meta analysis

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure