MAGIC_subgroup - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001000158 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:We undertook a comprehensive clinical and biological investigation of serial medulloblastoma biopsies obtained at diagnosis and relapse. Combined MYC gene family amplifications and P53 pathway defects commonly emerged at relapse, and all patients in this molecular group died of rapidly progressive disease post-relapse. To study this genetic interaction, we investigated a transgenic model of MYCN-driven medulloblastoma and found spontaneous development of Trp53 inactivating mutations. Abrogation of Trp53 function in this model produced aggressive tumors that mimicked the characteristics of relapsed human tumors with combined P53-MYC dysfunction. Restoration of p53 activity, genetic and therapeutic suppression of MYCN all reduced tumor growth and prolonged survival. Our findings identify P53–MYC interactions which emerge at medulloblastoma relapse as biomarkers of clinically aggressive disease that may be targeted therapeutically. Using this dataset, assignation of medulloblastoma molecular subgroup by Illumina 450k microarray was performed for diagnostic and relapsed medulloblastoma samples to compare subgroup membership at diagnosis and relapse.
2015-04-23 | GSE62618 | GEO
Project description:We undertook a comprehensive clinical and biological investigation of serial medulloblastoma biopsies obtained at diagnosis and relapse. Combined MYC gene family amplifications and P53 pathway defects commonly emerged at relapse, and all patients in this molecular group died of rapidly progressive disease post-relapse. To study this genetic interaction, we investigated a transgenic model of MYCN-driven medulloblastoma and found spontaneous development of Trp53 inactivating mutations. Abrogation of Trp53 function in this model produced aggressive tumors that mimicked the characteristics of relapsed human tumors with combined P53-MYC dysfunction. Restoration of p53 activity, genetic and therapeutic suppression of MYCN all reduced tumor growth and prolonged survival. Our findings identify P53–MYC interactions which emerge at medulloblastoma relapse as biomarkers of clinically aggressive disease that may be targeted therapeutically. Using this dataset, assignation of medulloblastoma molecular subgroup by Illumina 450k microarray was performed for diagnostic and relapsed medulloblastoma samples to compare subgroup membership at diagnosis and relapse. We investigated the DNA methylation profiles of 18 diagnostic and 22 relapsing samples (including 15 diagnostic / relapse pairs) using the Illumina 450k methylation microarray
2015-04-23 | E-GEOD-62618 | biostudies-arrayexpress
Project description:We explore cellular heterogeneity in 28 childhood medulloblastoma (MB) (1 WNT, 9 SHH, 7 GP3 and 11 GP4) using single-cell RNA sequencing (scRNA-seq), immunohistochemistry and deconvolution of bulk transcriptomic data. Neoplastic cells are broadly clustered according to subgroup, and within subgroups discrete sample clustering is associated with chromosomal copy number variance. Each subgroup contains subpopulations exhibiting mitotic , undifferentiated and neuronal differentiated transcript profiles , corroborating other recent medulloblastoma scRNA-seq studies and identifying new subpopulations. We identify a photoreceptor-differentiated subpopulation that is predominantly found in GP3 medulloblastoma, and in SHH, a subpopulation that constitutes differentiating nodules . Deconvolution of a large transcriptomic dataset shows that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. This scRNA-seq dataset also demonstrates medulloblastoma subgroup-specific differences in the tumor microenvironment and immune landscape, and reveals an SHH nodule -associated myeloid subpopulation. Additionally, we perform scRNA-seq on genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models specifically matched the corresponding human subgroup-specific neoplastic subpopulations. We provide an interactive online resource that facilitates exploration of these MB single cell datasets. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.
2021-06-04 | GSE155446 | GEO
Project description:Medulloblastoma is a malignant childhood brain tumour comprising four discrete subgroups. To identify mutations that drive medulloblastoma we sequenced the entire genomes of 37 tumours and matched normal blood. One hundred and thirty-six genes harbouring somatic mutations in this discovery set were sequenced in an additional 56 medulloblastomas. Recurrent mutations were detected in 41 genes not yet implicated in medulloblastoma: several target distinct components of the epigenetic machinery in different disease subgroups, e.g., regulators of H3K27 and H3K4 trimethylation in subgroup-3 and 4 (e.g., KDM6A and ZMYM3), and CTNNB1-associated chromatin remodellers in WNT-subgroup tumours (e.g., SMARCA4 and CREBBP). Modelling of mutations in mouse lower rhombic lip progenitors that generate WNT-subgroup tumours, identified genes that maintain this cell lineage (DDX3X) as well as mutated genes that initiate (CDH1) or cooperate (PIK3CA) in tumourigenesis. These data provide important new insights into the pathogenesis of medulloblastoma subgroups and highlight targets for therapeutic development. A total of 76 pediatric medulloblastoma samples were analyzed, representing 4 expression classes
2012-07-05 | E-GEOD-37418 | biostudies-arrayexpress
Project description:While international consensus and the 2021 WHO classification recognize multiple molecular medulloblastoma subgroups, these are difficult to identify in current clinical practice. As a result, biology driven risk stratification and therapy assignment for medulloblastoma constitutes a major challenge. Here, we report mass spectrometry analysis of clinical samples as a method for medulloblastoma subgroup discovery and identify MYC immunohistochemistry (IHC) as a clinically tractable method for improved risk stratification.
2025-03-06 | PXD051319 | Pride
Project description:Recent genomic approaches have suggested the existence of multiple distinct subtypes of medulloblastoma. We studied a large cohort of medulloblastomas to determine how many subgroups of the disease exist, how they differ, and the extent of overlap between subgroups. We determined gene expression profiles and DNA copy number aberrations for 103 primary medulloblastomas. Bioinformatic tools were used for class discovery of medulloblastoma subgroups based on the most informative genes in the dataset. Immunohistochemistry for subgroup-specific ‘signature’ genes was used to determine subgroup affiliation for 294 non-overlapping medulloblastomas on two independent tissue microarrays (TMAs). Multiple unsupervised analyses of transcriptional profiles identified four distinct, non-overlapping molecular variants: WNT, SHH, Group C, and Group D. Supervised analysis of these four subgroups revealed significant subgroup-specific demographics, histology, metastatic status, and DNA copy number aberrations. Immunohistochemistry for DKK1 (WNT), SFRP1 (SHH), NPR3 (Group C), and KCNA1 (Group D) could reliably and uniquely classify formalin fixed medulloblastomas in ~98% of cases. Group C patients (NPR3 +ve tumors) exhibited a significantly diminished progression free and overall survival irrespective of their metastatic status. Our integrative genomics approach to a large cohort of medulloblastomas has identified four disparate subgroups with distinct demographics, clinical presentation, transcriptional profiles, genetic abnormalities, and clinical outcome. Medulloblastomas can be reliably assigned to subgroups through immunohistochemistry, thereby making medulloblastoma sub-classification widely available. Future research on medulloblastoma and the development of clinical trials should take into consideration these four distinct types of medulloblastoma. A total of 103 primary medulloblastoma specimens were profiled by Affymetrix exon array and gene-level analysis was performed.
2010-09-13 | E-GEOD-21140 | biostudies-arrayexpress
Project description:Purpose Integrated genomics approaches have identified at least four distinct biological variants in medulloblastoma: WNT, SHH, group C, and group D. Non-WNT/Non-SHH tumors are associated with metastatic dissemination and an unfavorable prognosis. Additional markers may enhance outcome prediction in Non-WNT/Non-SHH medulloblastomas. Experimental Design We combined transcriptomic and DNA copy-number analyses for 64 primary medulloblastomas. Bioinformatic tools were applied to discover marker genes of molecular variants. Differentially expressed transcripts were evaluated for prognostic value in the screening cohort. Immunopositivity for FSTL5 was correlated with molecular and prognostic subgroups for 235 non-overlapping medulloblastoma samples on two independent tissue microarrays (TMA). Results Unsupervised clustering analyses of transcriptome profiles confirmed four distinct molecular variants. Stable subgroup separation was achieved using only the 300 most varying transcripts. Specific distributions of clinical and molecular characteristics were noted for each cluster. Distinct expression patterns of FSTL5 in each molecular subgroup were confirmed by quantitative real-time PCR. Immunopositivity of FSTL5 identified a large cohort of patients (84 of 235 patients; 36%) at high risk for relapse and death. Importantly, over 50% of Non-WNT/Non-SHH tumors displayed FSTL5 negativity, delineating a large patient cohort with an excellent prognosis who would be considered intermediate/high-risk based on current molecular subtyping. Conclusions Comprehensive analyses of transcriptomic and genetic alterations delineate four distinct variants of medulloblastoma. The addition of FSTL5 immunohistochemistry to existing molecular stratification schemes can effectively identify those Non-WNT/Non-SHH tumors with a poor outcome. Immunohistochemical staining for FSTL5 could be a high-quality and practical tool for stratification and prognostication in future clinical trials of medulloblastoma.
2011-07-01 | GSE28245 | GEO
Project description:Medulloblastoma is a malignant childhood brain tumour comprising four discrete subgroups. To identify mutations that drive medulloblastoma we sequenced the entire genomes of 37 tumours and matched normal blood. One hundred and thirty-six genes harbouring somatic mutations in this discovery set were sequenced in an additional 56 medulloblastomas. Recurrent mutations were detected in 41 genes not yet implicated in medulloblastoma: several target distinct components of the epigenetic machinery in different disease subgroups, e.g., regulators of H3K27 and H3K4 trimethylation in subgroup-3 and 4 (e.g., KDM6A and ZMYM3), and CTNNB1-associated chromatin remodellers in WNT-subgroup tumours (e.g., SMARCA4 and CREBBP). Modelling of mutations in mouse lower rhombic lip progenitors that generate WNT-subgroup tumours, identified genes that maintain this cell lineage (DDX3X) as well as mutated genes that initiate (CDH1) or cooperate (PIK3CA) in tumourigenesis. These data provide important new insights into the pathogenesis of medulloblastoma subgroups and highlight targets for therapeutic development.
2012-07-06 | GSE37418 | GEO
Project description:Recent genomic approaches have suggested the existence of multiple distinct subtypes of medulloblastoma. We studied a large cohort of medulloblastomas to determine how many subgroups of the disease exist, how they differ, and the extent of overlap between subgroups. We determined gene expression profiles and DNA copy number aberrations for 103 primary medulloblastomas. Bioinformatic tools were used for class discovery of medulloblastoma subgroups based on the most informative genes in the dataset. Immunohistochemistry for subgroup-specific ‘signature’ genes was used to determine subgroup affiliation for 294 non-overlapping medulloblastomas on two independent tissue microarrays (TMAs). Multiple unsupervised analyses of transcriptional profiles identified four distinct, non-overlapping molecular variants: WNT, SHH, Group C, and Group D. Supervised analysis of these four subgroups revealed significant subgroup-specific demographics, histology, metastatic status, and DNA copy number aberrations. Immunohistochemistry for DKK1 (WNT), SFRP1 (SHH), NPR3 (Group C), and KCNA1 (Group D) could reliably and uniquely classify formalin fixed medulloblastomas in ~98% of cases. Group C patients (NPR3 +ve tumors) exhibited a significantly diminished progression free and overall survival irrespective of their metastatic status. Our integrative genomics approach to a large cohort of medulloblastomas has identified four disparate subgroups with distinct demographics, clinical presentation, transcriptional profiles, genetic abnormalities, and clinical outcome. Medulloblastomas can be reliably assigned to subgroups through immunohistochemistry, thereby making medulloblastoma sub-classification widely available. Future research on medulloblastoma and the development of clinical trials should take into consideration these four distinct types of medulloblastoma.
2010-09-14 | GSE21140 | GEO
Project description:Comprehensive view of structural variation across dog genomes including mobile elements and nuclear mitochondrial insertions
2020-07-02 | GSE153608 | GEO