Molecular subgroups of adult medulloblastoma: a long-term single-institution study
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE116028 | GEO | 2018/06/26
REPOSITORIES: GEO
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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: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:Background: Since 2016, a project for molecular diagnosis of childhood medulloblastoma (MB) was initiated in Taiwan. We aimed to integrate molecular classification, molecular and clinical risk factors, somatic mutations, and phenotypic traits for up to date adaptive care. Method: Fifty-two MBs in children with frozen tumor tissue were assembled. Clinical data were retrieved. RNA-Seq and DNA methylation array data were generated. Molecular subgrouping and molecular-clinical correlation were performed. Subgroup-based risk stratification included an adjusted Heidelberg risk stratification scheme were defined and evaluated. We selected 51 genes for somatic variant calling using RNA-Seq. Relevant phenotypic traits were defined for the linkage of genetic predisposition. Results: Four core molecular subgroups (WNT, SHH, Group 3, and Group 4) were identified. Genetic backgrounds of metastasis at diagnosis and extent of tumor resection were observed. The overall survivals of the adjusted Heidelberg scheme matched with the definition of each risk subgroups. Somatic mutations in DNA damage response were detected. Five patients with SHH MB presented potential genetic predisposition and three patients had related germline mutations. Conclusion: The findings of this study provide valuable information for adaptive risk stratified treatment and personalized care of childhood MBs in our cohort series and in Taiwan.
2022-05-18 | GSE143940 | GEO
Project description:Background: Since 2016, a project for molecular diagnosis of childhood medulloblastoma (MB) was initiated in Taiwan. We aimed to integrate molecular classification, molecular and clinical risk factors, somatic mutations, and phenotypic traits for up to date adaptive care. Method: 18 MBs in children with frozen tumor tissue were assembled. Clinical data were retrieved. RNA-Seq and DNA methylation array data were generated. Molecular subgrouping and molecular-clinical correlation were performed. Subgroup-based risk stratification included an adjusted Heidelberg risk stratification scheme were defined and evaluated. We selected 51 genes for somatic variant calling using RNA-Seq. Relevant phenotypic traits were defined for the linkage of genetic predisposition. Results: Four core molecular subgroups (WNT, SHH, Group 3, and Group 4) were identified. Genetic backgrounds of metastasis at diagnosis and extent of tumor resection were observed. The overall survivals of the adjusted Heidelberg scheme matched with the definition of each risk subgroups. Somatic mutations in DNA damage response were detected. Conclusion: The findings of this study provide valuable information for adaptive risk stratified treatment and personalized care of childhood MBs in our cohort series and in Taiwan.
2022-05-18 | GSE158413 | GEO
Project description:Deregulations in fundamental signaling pathways are key events in pathogenesis of cancer. One intriguing illustration that still holds blind spots is the pediatric brain tumor arising from the developing cerebellum: medulloblastoma (MB). Extensive high-throughput sequencing led to the characterization of four MB subgroups (WNT, SHH, Group 3 and Group 4) delineated with distinct molecular signatures and clinical outcomes. However, up-to-date these analyses have not attained the global comprehension of their dynamic network complexity. Wishing to uncover a comprehensive view of all MB subgroups we employed a proteomic analysis to integrate accurate protein expression and activity that should ultimately give rise to a realistic picture of how MB cancer cells are regulated. In this study we present the first analysis regrouping methylation status, whole-transcriptome sequencing and quantitative proteomics (proteome and phosphoproteome) using a super SILAC / spiked in strategy across 38 flash frozen primary human MBs (5 WNT, 10 SHH, 10 Group 3 and 13 Group 4). First, our data pinpointed that proteomic analysis could reveal MB subgroup identity. Second, analysis of proteome and phosphoproteome highlighted disregulated signaling pathways that have not been predicted by transcriptomic analysis. Altogether, combined multi-scale analyses of MB have allowed us to identify unrevealed pathways involved in human MB genesis and progression.
2020-07-23 | PXD006607 | Pride
Project description:Background: Medulloblastoma (MB) is a malignant brain tumor in childhood. It comprises four subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts. Methods: We used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis (NTA) and electron microscopy (EM), to investigate intercellular communication in the MB tumor niche. Results: Tumor cells of the SHH-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from otherwise very different MB subgroups or subtypes. Conclusions: With EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.
2020-12-11 | GSE159763 | GEO
Project description:Background: Medulloblastoma (MB) is a malignant brain tumor in childhood. It comprises four subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts. Methods: We used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis (NTA) and electron microscopy (EM), to investigate intercellular communication in the MB tumor niche. Results: Tumor cells of the SHH-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from otherwise very different MB subgroups or subtypes. Conclusions: With EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.
2020-12-11 | GSE127997 | GEO
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. Whole-genome transcriptional profiling of human medulloblastomas. Subgrouping based on mRNA expression profiles. Fresh frozen tumor material was collected during tumor resection. Dye-swap design used for expression profiling. Reference was a pool of normal cerebellum tissue from 24 donors. Gene expression profiles illustrate distinct expression pattern at diagnosis. This submission represents the gene expression component of the study.
2011-07-01 | E-GEOD-28245 | 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:Distinct molecular subgroups and subtypes have been identified for medulloblastoma (MB), one of the most malignant brain tumors of childhood, with the sonic hedgehog (SHH)-activated subgroup of patients with mutations in p53 having a very severe outcome, associated with unfavorable histological large cell/anaplastic (LC/A) features. Aim of this study was to determine whether hyperactivation of mechanistic Target Of Rapamycin Complex 1 (mTORC1) pathway, whose role in molecular subtypes of MB is currently undefined, underlies the acquisition of LC/A histology in this subtype. MBs developing in p53-deficient Ptch+/- SHH mice show LC/A features that correlate with mTORC1 hyperactivation, which, mechanistically, is mediated by a decrease in the p53-dependent expression of the negative mTORC1 regulator Tsc2. Ectopic mTORC1 activation in mouse MB cancer stem cells (CSCs) promotes the acquisition of the LC/A phenotype. Furthermore, mTORC1 inhibition in both autochthonous p53-mutant SHH MBs and CSC-derived LC/A MBs results in reduced tumor burden and enhanced survival. Most remarkably, mTORC1 hyperactivation in tumor cells is detected only in human p53-mutant SHH MB samples and treatment with rapamycin of a human preclinical model phenocopying this subgroup decreases tumor growth and malignancy. As such, mTORC1 may act as a new and specific druggable target for this subset of SHH MB, thus resulting in the implementation of a more stringent MB risk stratification and in the potentially rapid translation of this precision medicine approach into the clinical setting.
2021-10-21 | GSE183901 | GEO