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.

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.

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.

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In silico analysis of long noncoding RNAs in medulloblastoma and its subgroups

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