Medulloblastoma in adults: Cytogenetic phenotypes identify prognostic subgroups
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA704366 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Medulloblastoma (MB) is a rare disease in adults. In this study we elucidated the genetic landscape and prognostic impact of genetic aberrations in a cohort of 117 adult medulloblastomas. Histological features and pathway activation were evaluated on the protein level; 14.5% showed WNT activation, 63.3% SHH activation and 22.2% were annotated to non-WNT/non-SHH-MB. Genome-wide copy number analysis was performed by molecular inversion probe array technology. MB-related genes were sequenced in WNT- and SHH-activated MBs. 79.7% of SHH-MBs showed desmoplastic/nodular, all other MBs classic histology. WNT-MBs carried oncogenic CTNNB1 mutations in 88.2% and had monosomy 6 in 52.9%. In SHH-MBs, TERT promoter mutations occurred in 97%, mutations in PTCH1 in 38.2%, SMO in 15.5%, SUFU in 7.4%, and TP53-mutations in 4.1%. 84.6% of non-WNT/non-SHH-MBs had an isochromosome 17q. A whole chromosomal aberration (WCA) signature was present in 45.1% of SHH-TP53wt-MBs and 65.4% of non-WNT/non-SHH-MBs. In 98 cases with survival data, WNT-MBs had a 5-year overall survival (OS) of 68.6%. SHH-MBs TP53-wild-type and non-WNT/non-SHH-MBs showed 5-year OS of 80.4% and 70.8%, respectively. TP53-mutant SHH-MBs represented a prognostically unfavorable entity; all patients died within 5 years. Patients with a WCA signature showed significantly increased OS (p-=-0.011 for SHH-TP53wt-MBs, p-=-0.048 for non-WNT/non-SHH-MBs).
2021-02-24 | GSE167347 | GEO
Project description:Advances in transcriptomics have impacted the way of looking atimproved our understanding of leukemic development and helped enhancing the stratification of patients. Analyses of individual cohortsTranscriptomics studies often combined AML samples regardless of cytogenetic abnormalities. , which would lead to bias in Hence, deregulated genesdifferential gene expression analysis that may result from the differential representation of in less frequent AML subgroups have low weight, contrarily to those in abundant subgroups. We, thusHence, we performed a horizontal meta-analysis that integrated transcriptomic data of AML from multicentric multiple studies to enrich the less frequent cytogenetic subgroups and to uncover common genes involved in AML development and response to therapy. A total of 28 Affymetrix microarray datasets harboring 3940 AML samples were downloaded from the GEO database. After stringent quality control, transcriptomics data of 1523 samples from 11 datasets, covering 10 AML cytogenetic subgroups, were retained and merged with the transcriptomic data of 198 healthy bone marrow samples. Differentially expressed genes between each cytogenetic subgroup and normal samples were extracted, allowing the unbiased identification of 330 commonly deregulated genes (CODEGs)., which CODEGs showed enriched expression profiles in myeloid differentiation, leukemic stem cell status and relapse. Most of these genes were downregulated, in accordance with DNA hypermethylation. CODEGS were then used to create a prognostic score based on the weighted sum of expression of 22 core genes (CODEG22). The score was validated in on microarray data of five independent cohorts, and by qRT-PCR in a cohort of 142 samples, by qRT-PCR. CODEG22 stratified patients globally, as well as in subpopulations of cytologically normal and elderly patients. , and hence, couldSo, it may complement the European LeukemiaNet classification for a more accurate prediction of AML outcomes.
2020-10-29 | GSE147515 | GEO
Project description:Proteogenomic landscape of medulloblastoma subgroups
| PRJNA420382 | ENA
Project description:Extensive high-throughput sequencing led to the characterization of four main medulloblastoma subgroups. However, to date these analyses have not attained a global comprehension of their dynamic network complexity. Wishing to get a comprehensive view of all medulloblastoma subgroups, we employed a proteomic analysis to integrate accurate protein activity. In this study we present the first analysis regrouping genomic and methylation status, whole-transcriptome sequencing and quantitative proteomics. First, our proteomic analysis clarified medulloblastoma subgroup identity. Second, analysis of proteome and phosphoproteome highlighted disregulated signalling pathways that have not been predicted by transcriptomic analysis. Altogether, combined multi-scale analyses of medulloblastoma have allowed us to identify and prioritize novel molecular drivers involved in human medulloblastoma.
2018-09-09 | GSE107508 | GEO
Project description:Extensive high-throughput sequencing led to the characterization of four main medulloblastoma subgroups. However, to date these analyses have not attained a global comprehension of their dynamic network complexity. Wishing to get a comprehensive view of all medulloblastoma subgroups, we employed a proteomic analysis to integrate accurate protein activity. In this study we present the first analysis regrouping genomic and methylation status, whole-transcriptome sequencing and quantitative proteomics. First, our proteomic analysis clarified medulloblastoma subgroup identity. Second, analysis of proteome and phosphoproteome highlighted disregulated signalling pathways that have not been predicted by transcriptomic analysis. Altogether, combined multi-scale analyses of medulloblastoma have allowed us to identify and prioritize novel molecular drivers involved in human medulloblastoma.
2018-09-09 | GSE104728 | 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:Proteogenomic landscape of medulloblastoma subgroups [SNP]
| PRJNA420381 | ENA
Project description:Proteogenomic landscape of medulloblastoma subgroups [methylation]
| PRJNA413673 | ENA
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:Medulloblastoma is the most common pediatric brain tumor exhibiting high malignancy and fatality rates. Recent large-scale patient studies utilizing genome wide technologies have put forth transcriptomic and epigenetic heterogenties among the medulloblastomas, classifying them into four major subgroups: WNT, SHH, group 3 and group 4. However, the contribution of long non-coding RNAs in medulloblastoma remains unknown. Long non-coding RNAs represent a crucial part of the regulatory transcriptome that has shown to control gene expression levels and protein interactions. The relative lack of understanding of long non-coding RNA in medulloblastoma is partly due to dearth of putative functional candidate long non-coding RNAs. From RNA-seq data beloning to 175 medulloblastoma patientswe identified a diagnostic and prognostic signature. We validated the diagnostic model in the PDX dervied from t samples beloning to SHH, group 3 and group 4 patients.
2019-12-31 | GSE134248 | GEO