MRNA expression data of 62 human medulloblastoma tumors
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Kool M
PROVIDER: S-ECPF-GEOD-10327 | biostudies-other | 2008
REPOSITORIES: biostudies-other
Similar Datasets
Project description:To identify molecular subtypes of medulloblastoma we have profiled a series of 62 medulloblastoma tumors. Unsupervised hierarchical cluster analysis of these data identified 5 distinct molecular subtypes. Manuscript submitted. Title: Identification of medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features. Authors: Marcel Kool, Jan Koster, Jens Bunt, Nancy E. Hasselt, Arjan Lakeman, Peter van Sluis, Dirk Troost, Netteke Schouten – van Meeteren, Huib N. Caron, Alan Mršić, Bauke Ylstra, Wieslawa Grajkowska, Wolfgang Hartmann, Torsten Pietsch, David Ellison, Steven C. Clifford, Rogier Versteeg. Keywords: tumor classification
2008-09-02 | GSE10327 | GEO
Project description:To identify molecular subtypes of medulloblastoma we have profiled a series of 62 medulloblastoma tumors. Unsupervised hierarchical cluster analysis of these data identified 5 distinct molecular subtypes. Manuscript submitted. Title: Identification of medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features. Authors: Marcel Kool, Jan Koster, Jens Bunt, Nancy E. Hasselt, Arjan Lakeman, Peter van Sluis, Dirk Troost, Netteke Schouten â van Meeteren, Huib N. Caron, Alan MrÅ¡iÄ, Bauke Ylstra, Wieslawa Grajkowska, Wolfgang Hartmann, Torsten Pietsch, David Ellison, Steven C. Clifford, Rogier Versteeg. Keywords: tumor classification 62 human medulloblastoma samples were analzyed
2008-09-02 | E-GEOD-10327 | biostudies-arrayexpress
Project description:mRNA expression analysis of 4 different pools of medulloblastoma samples with characteristic cytogenetic aberrations Keywords: Genetic modification Comparison of tumor RNA 1 (equally represented, pooled mRNA of tumors with cytogenetic aberration 1) versus tumor RNA (equally represented, pooled mRNA of tumors without cytogenetic aberration 1). Whole-genome screening for differential gene expression.
| S-ECPF-GEOD-22823 | biostudies-other
Project description:Purpose:Medulloblastoma (MB), the most common malignant brain tumor in children, is divided into four tumor subgroups: wingless-type (WNT), sonic hedgehog (SHH), Group 3, and Group 4. Ideally, clinical practice and treatment design should be subgroup specific. While WNT and SHH subgroups have well-defined biomarkers, distinguishing Group 3 from Group 4 is not straightforward. MicroRNAs (miRNAs), which regulate posttranscriptional gene expression, are involved in MB tumorigenesis. However, the miRNA-messenger RNA (mRNA) regulatory network in MB is far from being fully understood. Our aims were to investigate miRNA expression regulation in MB subgroups, to assess miRNA target relationships, and to identify miRNAs that can distinguish Group 3 from Group 4. Patients and methods:With these aims, integrated transcriptome mRNA and miRNA expression analysis was performed on primary tumor samples collected from 18 children with MB, using miRNA sequencing (miRNA-seq), RNA sequencing (RNA-seq), and quantitative PCR. Results:Of all the expressed miRNAs, 19 appeared to be significantly differentially expressed (DE) between Group 4 and non-Group 4 subgroups (false discovery rate [FDR] <0.05), including 10 miRNAs, which, for the first time, are reported to be in conjunction with MB. RNA-seq analysis identified 165 genes that were DE between Group 4 and the other subgroups (FDR <0.05), among which seven are predicted targets of five DE miRNAs and exhibit inverse expression pattern. Conclusion:This study identified miRNA molecules that may be involved in Group 4 etiology, in general, and can distinguish between Group 3 and Group 4, in particular. In addition, understanding the involvement of miRNAs and their targets in MB may improve diagnosis and advance the development of targeted treatment for MB.
| S-EPMC5818864 | biostudies-literature
Project description:Smoothened (SMO)-inhibitors recently entered clinical trials for sonic-hedgehog driven medulloblastoma (SHH-MB). Clinical response appears highly variable. To understand the mechanism(s) of primary resistance and to identify pathways co-operating with aberrant SHH-signaling, we sequenced a large cohort of SHH-MBs across all age groups by sequencing, DNA methylation and expression profiling. Our data show that most adults but only half of the pediatric patients with SHH-MB will respond to SMO inhibition as predicted by molecular analysis of the primary tumor and tested in the SHH-xenografts, demonstrating that the next generation of SMO-inhibitor trials should be based on these predictive biomarkers. To further dissect the biological differences between the different age groups within SHH medulloblastomas, we looked at the transcriptomic profiles of SHH medulloblastoma samples. 73 medulloblastoma samples from patients of various ages were selected for RNA extraction and hybridization on Affymetrix Human Genome U133 Plus 2.0 Arrays.
| S-ECPF-GEOD-49243 | biostudies-other
Project description:MicroRNAs (miRNAs) regulate many genes critical for tumorigenesis. We profiled miRNAs from 11 normal breast tissues, 17 non-invasive, 151 invasive breast carcinomas, and 6 cell lines by in-house-developed barcoded Solexa sequencing. miRNAs were organized in genomic clusters representing promoter-controlled miRNA expression and sequence families representing seed-sequence-dependent miRNA-target regulation. Unsupervised clustering of samples by miRNA sequence families best reflected the clustering based on mRNA expression available for this sample set. Clustering and comparative analysis of miRNA read frequencies showed that normal breast samples were separated from most non-invasive ductal carcinoma in situ and invasive carcinomas by increased miR-21 (the most abundant miRNA in carcinomas) and multiple decreased miRNA families (including mir-98/let-7), with most miRNA changes apparent already in the non-invasive carcinomas. In addition, patients that went on to develop metastasis demonstrated increased expression of mir-423, and triple negative breast carcinomas were most distinct from other tumor subtypes due to up-regulation of the mir-17~92 cluster. However, absolute miRNA levels between normal breast and carcinomas did not reveal any significant differences. We also discovered two polymorphic nucleotide variations among the more abundant miRNAs miR-181a (T19G) and miR-185 (T16G), but we did not identify nucleotide variations expected for classical tumor suppressor function associated with miRNAs. The differentiation of tumor subtypes and prediction of metastasis based on miRNA levels is statistically possible, but is not driven by deregulation of abundant miRNAs, implicating far fewer miRNAs in tumorigenic processes than previously suggested. mRNA profiles for 161 normal breast and invasive breast carcinomas using NKI Operon V3 arrays; These samples have matched entries for miRNA profiles also included in this GEO submission.
| S-ECPF-GEOD-29174 | biostudies-other
Project description:The characteristics of immune cells infiltrating pediatric brain tumors is largely unexplored. A better understanding of these characteristics will provide a foundation for development of immunotherapy for pediatric brain tumors. Gene expression profiles were used to identify immune marker gene that are differentially expressed between various brain tumor types. Gene expression profiles were generated from surgical tumor and normal brain samples (n=130) using Affymetrix HG-U133plus2 chips (Platform GPL570). Gene expression profiles of different types of brain tumors and normal brain were filtered to obtain gene expression of key immune cell markers. Comparative analyses between different brain tumors and normal brain was used to identifiy differential immune characteristics of these tumors.
| S-ECPF-GEOD-50161 | biostudies-other
Project description:Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several "multiple-omics" studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.
| S-EPMC8469239 | biostudies-literature
Project description:Medulloblastoma (MB) is one of the most common malignant pediatric brain tumor. The aim of our study was to understand which mechanisms are involved in aberrant activation of Wnt pathway and its association with MB tumor development. We studied the expression profiles of 19 MBs tumors using a genome-wide approach, furthermore we have included the data obtained from four independent public Datasets of gene expression (see README file below) to increase the statistical power of the study. The expression profiles identified the Wnt inhibitor gene, DKK3, significant down-regulated. DKK3 down-regulation was confirmed by qPCR in 80% of samples (27/33 MB tumors and in 3/5 MB human cell lines). Since DKK3 was found methylated in several cancers we also investigated the status of methylated CpG sites within the three promoters by a combination of two approaches: the MSP and pyrosequencing. MSP showed no methylation in all promoters while the pyrosequencing, a quantitative technique, indicated a very low level of methylation. To verify the epigenetic involvement on DKK3 silencing, we also studied the effect of Trichostatin A (TSA) in 4 MB cell lines (DAOY; D283; D425; D458). After TSA treatment we observed a significant DKK3 mRNA expression increase in 3/4 cell lines compared to the no treated cells. DAOY cells, that have a normal DKK3 expression value, did not change significantly the DKK3 expression after TSA treatment. To further validate the role of histone tail modifications as an epigenetic silencing mechanism for DKK3 in MB, we performed Chromatin Immunoprecipitation (ChIP) experiment using antibodies against acetylated histones. According to our earlier results, TSA treatment increased the signal of the histone modification meH3K4 which is related to a transcriptionally active gene respect to the untreated controls. Finally, we evaluated the DKK3 protein in three MB cell lines (DAOY; D283; D425) after 24h of TSA treatment, by immunofluorescence. We analysed 19 Medulloblastoma tumor from pediatric patients, a commercial pool (Clontech) of 24 normal cerebellum from female and male Caucasians (ages: 16-70 years; cause of death: sudden death) and a pool of 10 normal cerebellum from children (6 Caucasians and 4 African Americans; ages: 0-16 years; cause of death: sudden death) using 44K whole genome oligonucleotids microarray
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Project description:We stratified colorectal tumor samples using a new unsupervised, iterative method based on non-negative matrix factorization (NMF). The resulting five subtypes exhibited activation of specific signaling pathways, and significant differences in microsatellite status and tumor location. We could also align three CRC cell lines panels to these subtypes.
2013-01-14 | GSE35896 | GEO