CIT_VADS_BW_OMICS
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Fabien PETEL
PROVIDER: E-MTAB-1328 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:A Cartes d'Identite des Tumeurs (CIT) project from the French Ligue Nationale Contre le Cancer (<a href=\\ttp://cit.ligue-cancer.net/\\ target=\\_blank\\>http://cit.ligue-cancer.net</a>). Selecting patients with metastatic clear-cell renal cell carcinoma (m-ccRCC) who might benefit from treatment with targeted tyrosine kinase inhibitors (TKIs) is a challenge. Our aim was to identify molecular markers associated with outcome in m-ccRCC patients treated with sunitinib.\
2016-02-26 | E-MTAB-3274 | biostudies-arrayexpress
Project description:A Cartes d'Identite des Tumeurs (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net: Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable with few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome and/or transcriptome sequencing identifying previously reported frequent somatic mutations in CIC and FUBP1 genes. We also identified recurrent mutations in TCF12 (11% of IDHmut-codel) which encodes basic helix-loop-helix (bHLFH) transcription factor 12 which is an oligodendrocyte-related transcription factor in IDHmut-codel tumors. Strikingly, the somatic mutations (encoding E548R and R602M substitutions) have not been reported previously in cancer but are identical to germline mutations causing craniosynostosis. Incorporating TCGA data on 43 AO tumors also implicates functional mutation of SMARCA4, NOTCH1, NOTCH2, SETD2, RBPJ and ARID1A/1B. These data are compatible with the combined deregulation of metabolism, chromatin organization/remodeling and Notch-pathway genes in AO oncogenesis. Our analysis provides further insights into the unique and shared pathways driving AO and new targets for therapeutic intervention.
2015-06-15 | E-MTAB-2767 | biostudies-arrayexpress
Project description:In this study, a series of 102 cartilage tumors was used to uncover the molecular diversity of chondrosarcomas through the profiling of mRNA, miRNA, DNA methylation, DNA copy number aberrations and point mutations. An integrated classification using multiple molecular dimensions revealed three major molecular features unraveling the diversity in clinical outcome of chondrosarcoma: a high mitotic state, regional 14q32 loss of expression and IDH mutations leading to genome-wide hypermethylation. These three robust and simple molecular features classify chondrosarcoma in subtypes with superior clinical value as compared to the current grading system.
2019-07-19 | E-MTAB-7263 | biostudies-arrayexpress
Project description:A Cartes d'Identite des Tumeurs (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net: Oligodendroglial tumours (OT) are a heterogeneous group of gliomas. Three molecular subgroups are currently distinguished based on the IDH mutation and the 1p/19q co-deletion. Here we performed an integrated analysis of the transcriptome, genome and methylome of 156 OT. Beyond the 3 well-known molecular classes, our multi-omics classification revealed 3 subgroups within 1p/19q co-deleted tumours, associated with different expression patterns of oligodendroglial progenitor cell (OPC), astrocytic, oligodendrocytic and neuronal lineage genes. The validity of these 3 subgroups was confirmed on public datasets. The OPC-like group was associated with a more aggressive histological and genomic profile and with MYC activation that occurred through various alterations including MYC locus genomic gain, MYC exon 3 hypo-methylation and down-regulation of microRNA-34b/c. In the lower grade glioma TCGA dataset, the OPC-like group was associated with a poorer outcome independently from histological grade. Our study unravels previously unrecognized heterogeneity among 1p/19q co-deleted tumours.
2016-03-11 | E-MTAB-3903 | biostudies-arrayexpress
Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. the variable MultiOmicsClassification indicates the resulting sample's group. Whole-genome DNA methylation was analyzed using the Illumina Infinium HumanMethylation450 Beadchips. Integragen SA (Evry, France) carried out microarray experiments and hybridized to the BeadChip arrays following the manufacturer’s instructions. Illumina GenomeStudio software was used to extract the beta value DNA methylation score for each locus. We removed data from probes that contained SNPs or overlapped with a repetitive element that was not uniquely aligned to the human genome or regions of insertions and deletions in the human genome. The CpG Island Methylator Phenotype (CIMP) index was determined using methylation Illumina Infinium HumanMethylation450 BeadChips based on previous low throughput work (Toyota, 1999). In brief, all island CpG found to be unmethylated (<20% Beta-value) in all 25 normal pancreatic samples from the ICGC consortium (Nones, 2014) were selected. The CIMP index was calculated independently for each sample as the proportion of methylated (>30% Beta-value) CpGs among the selected normally unmethylated island CpG.
2017-12-12 | E-MTAB-5008 | biostudies-arrayexpress
Project description:Systemic lupus erythematosus (SLE) is a chronic-relapsing autoimmune disease of incompletely understood etiology. Recent evidence strongly supports an epigenetic contribution to the pathogenesis of lupus. To understand the extent and nature of dysregulated DNA methylation in lupus T cells, we performed a genome-wide DNA methylation study in CD4+ T cells from 12 lupus patients and 12 normal healthy controls. Cytosine methylation was quantified in 27,578 CG pairs located within the promoter regions of 14,495 genes. We identified 236 hypomethylated and 105 hypermethylated CG sites in lupus CD4+ T cells compared to normal controls, consistent with a global hypomethylation in lupus T cells. Further analysis identified hypomethylation in genes involved in connective tissue development including CD9, MMP9, and PDGFRA. Hypermethylated genes highlight “response to nutrients” ontology such as folate biosynthesis, suggesting a link between environmental factor and lupus and emphasizing the role of folate in DNA methylation. In addition, the transcription factor RUNX3 was hypermethylated in lupus CD4+ T cells. Protein-protein interaction maps identified a transcription factor, HNF4a, as a regulatory hub affecting a number of differentially methylated genes. Functional annotations such as apoptosis is also overrepresented. Further, our data indicate that the methylation status of certain genes predicts disease activity in lupus patients. This work provides a foundation to begin identifying novel pathogenic pathways in lupus T cells and developing novel epigenetic biomarkers for disease activity in lupus. We employed microarray-based technologies to perform a genome-wide DNA methylation assay and quantify CD4+ T cell DNA methylation levels at 27,578 CG sites spanning 14,495 genes of 11 lupus patients and 12 healthy controls.
2011-06-10 | E-GEOD-27895 | biostudies-arrayexpress
Project description:A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on DNA methylation and mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on methylation status or expression profile. We find an abundance of genetic cis regulation mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation. Authorized Access data: Mapping of GEO sample accessions to dbGaP subject/sample IDs is available through dbGaP Authorized Access, see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000249 Because of our interest in genomic regulation of expression and neurological disorders we embarked upon a series of experiments to provide a brain region-specific contextual framework for genetic and epigenetic regulation of gene expression. We obtained frozen brain tissue from the cerebellum and frontal cortex from 318 subjects (total 724 tissue samples).
2012-05-08 | E-GEOD-36194 | biostudies-arrayexpress
Project description:Epigenetic changes such as DNA methylation variation are known to play a role in gene regulation and common disease susceptibility. Little is known about the genome-wide frequency, localization and function of such changes and how they are regulated by genetic and environmental factors. We have utilized the MuTHER resource and generated methylation profiles across multiple tissues conducted in a large set of female individuals that allows systematic dissection of genetic and non-genetic effects on DNA methylation. DNA methylation was quantified in subcutaneous fat and skin derived from 648 TwinsUK participants using the Infinium HumanMethylation450 BeadChips. Data from transcription profiling of skin, adipose fat and lymphoblastoid cell lines (LCLs) from the same set of TwinsUK participants have been deposited in ArrayExpress under accession number E-TABM-1140 (https://www.ebi.ac.uk/arrayexpress/experiments/E-TABM-1140).
2013-10-01 | E-MTAB-1866 | biostudies-arrayexpress
Project description:A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on DNA methylation, mRNA expression and microRNA (miRNA) expression in four distinct human brain regions. We show that brain tissues may be readily distinguished based on methylation status or expression profile. We find an abundance of genetic cis regulation mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation. Authorized Access data: Mapping of GEO sample accessions to dbGaP subject/sample IDs is available through dbGaP Authorized Access, see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000249.v1.p1 Because of our interest in genomic regulation of expression and neurological disorders we embarked upon a series of experiments to provide a brain region-specific contextual framework for genetic and epigenetic regulation of gene expression. We obtained frozen brain tissue from the cerebellum, frontal cortex, pons and temporal cortex from 150 subjects (total 600 tissue samples). We undertook four separate assays across this series; first, genome-wide SNP genotyping; second, assay of >27,000 CpG methylation sites in each of the four brain regions; third, mRNA expression profiling of >22,000 transcripts in all four brain regions; and, fourth, miRNA expression profiling of 735 miRNA transcripts. Here we discuss the results of these experiments, particularly in the context of integrated datasets to define expression and CpG methylation quantitative trait loci (eQTL and methQTL) and detailing differences and similarities across brain regions.
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