2013-11-19-17-24-36-breez-MB-2013-10-18-Whole_exome_DNAseq_Medulloblastoma - samples
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA213744PRJNA213380PRJNA214321
PROVIDER: EGAD00001000698 | EGA |
REPOSITORIES: EGA
Publications
Genome sequencing of SHH medulloblastoma predicts genotype-related response to smoothened inhibition.
Kool Marcel M Jones David T W DT Jäger Natalie N Northcott Paul A PA Pugh Trevor J TJ Hovestadt Volker V Piro Rosario M RM Esparza L Adriana LA Markant Shirley L SL Remke Marc M Milde Till T Bourdeaut Franck F Ryzhova Marina M Sturm Dominik D Pfaff Elke E Stark Sebastian S Hutter Sonja S Seker-Cin Huriye H Johann Pascal P Bender Sebastian S Schmidt Christin C Rausch Tobias T Shih David D Reimand Jüri J Sieber Laura L Wittmann Andrea A Linke Linda L Witt Hendrik H Weber Ursula D UD Zapatka Marc M König Rainer R Beroukhim Rameen R Bergthold Guillaume G van Sluis Peter P Volckmann Richard R Koster Jan J Versteeg Rogier R Schmidt Sabine S Wolf Stephan S Lawerenz Chris C Bartholomae Cynthia C CC von Kalle Christof C Unterberg Andreas A Herold-Mende Christel C Hofer Silvia S Kulozik Andreas E AE von Deimling Andreas A Scheurlen Wolfram W Felsberg Jörg J Reifenberger Guido G Hasselblatt Martin M Crawford John R JR Grant Gerald A GA Jabado Nada N Perry Arie A Cowdrey Cynthia C Croul Sydney S Zadeh Gelareh G Korbel Jan O JO Doz Francois F Delattre Olivier O Bader Gary D GD McCabe Martin G MG Collins V Peter VP Kieran Mark W MW Cho Yoon-Jae YJ Pomeroy Scott L SL Witt Olaf O Brors Benedikt B Taylor Michael D MD Schüller Ulrich U Korshunov Andrey A Eils Roland R Wechsler-Reya Robert J RJ Lichter Peter P Pfister Stefan M SM
Cancer cell 20140301 3
Smoothened (SMO) inhibitors recently entered clinical trials for sonic-hedgehog-driven medulloblastoma (SHH-MB). Clinical response is highly variable. To understand the mechanism(s) of primary resistance and identify pathways cooperating with aberrant SHH signaling, we sequenced and profiled a large cohort of SHH-MBs (n = 133). SHH pathway mutations involved PTCH1 (across all age groups), SUFU (infants, including germline), and SMO (adults). Children >3 years old harbored an excess of downstream ...[more]
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below. The raw sequencing data is available through dbGaP (controlled access) due to patient privacy concerns. https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001961.v1.p1
2020-11-23 | GSE161383 | GEO
Project description:We performed RRBS and WGBS on primary human chronic lymphocytic leukemia and normal healthy donor B cell samples Due to patient privacy concerns, the raw data is being made available via controlled access in dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000435.v1.p1).
2015-01-01 | GSE58889 | GEO
Project description:We performed RRBS and WGBS on primary human chronic lymphocytic leukemia and normal healthy donor B cell samples Due to patient privacy concerns, the raw data is being made available via controlled access in dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000435.v1.p1). cross-sectional/longitudinal
2015-01-01 | E-GEOD-58889 | 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
2010-04-20 | GSE15745 | GEO
Project description:In order to gain a global molecular perspective on how the human genome gives rise to the brain, we explore the temporal dynamics and genetic control of transcription in human dorsolateral prefrontal cortex in an extensive series of brain tissue from fetal development through aging. We discover a wave of gene expression changes occurring during fetal development which are reversed in early postnatal life. One half century later in life, this phenomenon is mirrored in aging as well as neurodegeneration. While we identify thousands of robust associations of individual genetic polymorphisms with gene expression, we also demonstrate that there is no association between the total extent of genetic differences between subjects and the global similarity of their transcriptional profiles. Hence, the human genome produces a consistent molecular architecture in the prefrontal cortex, despite millions of genetic differences across individuals and races. To enable further discovery, this entire dataset is freely available (GEO). RNA from 269 human prefrontal cortex samples ranging from fetal development (negative ages) through aging (80 years) were analyzed on custom 2-color microarrays from the National Human Genome Research Institute (NHGRI) microarray core facility using a reference RNA comprised of a pool of all samples. SNP genotype data for these subjects can be found in dbGAP under Study ID *phs000417.v1.p1* http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000417.v1.p1 Both the gene expression and SNP data from this study can be interrogated gene-by-gene with a biologist-friendly stand-alone application available at http://www.libd.org/braincloud . The original publication of this data appeared in the Oct. 27th 2011 volume of Nature: http://www.nature.com/nature/journal/v478/n7370/full/nature10524.html .
2011-10-26 | E-GEOD-30272 | biostudies-arrayexpress
Project description:<p>The Sjögren's International Collaborative Clinical Alliance (SICCA) is a multisite observational cohort study that recruited a large cohort of geographically diverse participants. Enrollment of participants began in late 2004 at five (one domestic and four international) sites, in which all groups used the same protocol-directed methods to provide uniform evaluations; collect oral, ocular, and rheumatologic data; and collect specimens. The sites were located at the University of Buenos Aires, Argentina; Peking Union Medical College, Beijing, China; Rigshopitalet (formerly at Glostrup Hospital), Copenhagen, Denmark; Kanazawa Medical University, Ishikawa, Japan; King's College, London, UK (joined in 2007); and the University of California, San Francisco (UCSF). In 2009, Aravind Eye Hospital, Madurai, India; Johns Hopkins University, Baltimore, MD; and University of Pennsylvania, Philadelphia, PA were added as additional SICCA sites. UCSF is the coordinating center for SICCA. All specimens and data collected for SICCA are housed at UCSF.</p> <p>To facilitate the research focused on understanding the genetics of Sjögren'sSjögren's syndrome, high-density SNP genotype data and SICCA clinical information are being made available to the research community. This includes participants recruited from all SICCA research groups (RG). These participants (3,382), blood relatives (439), and unrelated healthy controls (25) had their whole blood or saliva sample (Oragene) extracted for DNA for the GWAS at the UCSF DNA Bank. Eighty eight percent of the participants are women, most are of European or Asian ancestry and the median age is 55.</p> <p>To assess potential batch effects when doing case-control comparisons using planned external controls, 30 DNA samples from each of three studies were genotyped with SICCA DNA samples:</p> <ol> <li>The Genetic Architecture of Smoking and Smoking Cessation - <a href="http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000404.v1.p1">Collaborative Genetic Study of Nicotine Dependence (COGEND)</a> - PI: Laura Bierut.</li> <li>NEI-Age-related disease study (AREDS) - <a href="http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000429.v1.p1">Genetic Variation in Refractive Error Substudy</a> - PI: Dwight Stambolian.</li> <li>Controls from the National Institute of Mental Health's <a href="http://www.nimhgenetics.org/available_data/controls/">(NIMH's)</a> Human Genetics Initiative.</li> </ol> <ul><a href="http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000021.v3.p2">Genome-Wide Association Study of Schizophrenia</a> - PI: Pablo V. Gejman.</ul> <ul><a href="http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000167.v1.p1">Molecular Genetics of Schizophrenia - nonGAIN Sample</a> (MGS_nonGAIN) - PI: Pablo V. Gejman.</ul> <p>Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data quality control, dbGaP preparation and posting, and imputation to 1000 Genomes to increase SNP density was performed by the Center for Biomedical Statistics at the University of Washington. Data analysis was performed at UCSF using software PLINK, EIGENSOFT, and SNPTEST.</p>
| phs000672 | dbGaP
Project description:Previous studies in bulk tissue suggest that there are abundant expression quantitative trait loci (eQTLs) in human brain. This sample series is of cerebellar Purkinje cells isolated using laser capture microdissection from human cases without neurological disease but of known genotypes. These data may be helpful in confirming eQTLs in bulk tissue or in mapping other gene expression traits in an enriched neuronal population. 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
2013-01-01 | GSE37205 | GEO
Project description:<p>Shankha Satpathy, Eric J. Jaehnig, et al., <a href="https://www.nature.com/articles/s41467-020-14381-2" target="_blank">Nature Communications volume 11, Article number: 532 (2020)</a></p><p>Cancer proteogenomics promises new insights into cancer biology and treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifications by mass spectrometry (MS). A critical limitation is sample input requirements that exceed many sources of clinically important material. Here we report a proteogenomics approach for core biopsies using tissue-sparing specimen processing and microscaled proteomics. As a demonstration, we analyze core needle biopsies from ERBB2 positive breast cancers before and 48-72 h after initiating neoadjuvant trastuzumab-based chemotherapy. We show greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identify potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression and an inactive immune microenvironment. The clinical utility and discovery potential of proteogenomics at biopsy-scale warrants further investigation.<br><br><em>Genomic Data</em> for samples in the Microscaled Proteogenomic Methods Publication are available from the NIH Database of Genotypes and Phenotypes (dbGaP), Study Accession: phs001907.v1.p1, <a href="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001907.v1.p1" target="_blank">here</a></p>
<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/study-summary/S051">https://cptac-data-portal.georgetown.edu/study-summary/S051</a> on 06/02/21</li></ul>
2021-06-02 | MSV000087566 | MassIVE
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.
2010-04-20 | E-GEOD-15745 | biostudies-arrayexpress
Project description:Medulloblastoma is the most common malignant pediatric brain tumor, and mechanisms underlying its development are poorly understood. We identified recurrent amplification of the miR-17/92 polycistron proto-oncogene in 6% of pediatric medulloblastomas by high-resolution single-nucleotide polymorphism genotyping arrays and subsequent interphase fluorescence in situ hybridization on a human medulloblastoma tissue microarray. Profiling the expression of 427 mature microRNAs (miRNA) in a series of 90 primary human medulloblastomas revealed that components of the miR-17/92 polycistron are the most highly up-regulated miRNAs in medulloblastoma. Expression of miR-17/92 was highest in the subgroup of medulloblastomas associated with activation of the sonic hedgehog (Shh) signaling pathway compared with other subgroups of medulloblastoma. Medulloblastomas in which miR-17/92 was up-regulated also had elevated levels of MYC/MYCN expression. Consistent with its regulation by Shh, we observed that Shh treatment of primary cerebellar granule neuron precursors (CGNP), proposed cells of origin for the Shh-associated medulloblastomas, resulted in increased miR-17/92 expression. In CGNPs, the Shh effector N-myc, but not Gli1, induced miR-17/92 expression. Ectopic miR-17/92 expression in CGNPs synergized with exogenous Shh to increase proliferation and also enabled them to proliferate in the absence of Shh. We conclude that miR-17/92 is a positive effector of Shh-mediated proliferation and that aberrant expression/amplification of this miR confers a growth advantage to medulloblastomas. A total of 90 primary medulloblastoma specimens were profiled by Affymetrix exon array and gene-level analysis was performed.
2010-04-14 | E-GEOD-21166 | biostudies-arrayexpress