Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data from human ependymoma

ABSTRACT: We compared molecular characteristics of primary and recurrent pediatric ependymoma to identify sub-group specific differences. Gene expression profiles were used to identify unique immunobiologic sub-types of posterior fossa pediatric ependymoma. Gene expression profiles were generated from surgical tumor (ependymoma) (n=65) using Affymetrix HG-U133plus2 chips (Platform GPL570). Normalization was performed on our entire cohort of ependymoma. Of the 65 samples, a sub-set of 58 were used in the corresponding manuscript. Excluded samples are noted. Gene expression profiles were filtered to obtain gene expression of key immune cell markers. Comparative analyses between tumor samples were used to identifiy unique immunobiology between posterior fossa sub-groups.

ORGANISM(S): Homo sapiens

SUBMITTER: Lindsey Hoffman

PROVIDER: E-GEOD-50385 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Molecular sub-group-specific immunophenotypic changes are associated with outcome in recurrent posterior fossa ependymoma.

Hoffman Lindsey M LM Donson Andrew M AM Nakachi Ichiro I Griesinger Andrea M AM Birks Diane K DK Amani Vladimir V Hemenway Molly S MS Liu Arthur K AK Wang Michael M Hankinson Todd C TC Handler Michael H MH Foreman Nicholas K NK

Acta neuropathologica 20131117 5

Better understanding of ependymoma (EPN) biology at relapse is needed to improve therapy at this critical event. Convincing data exist defining transcriptionally distinct posterior fossa (PF) sub-groups A and B at diagnosis. The clinical and biological consequence of these sub-groups at recurrence has not yet been defined. Genome and transcriptome microarray profiles and clinical variables of matched primary and first recurrent PF EPN pairs were used to identify biologically distinct patterns of ...[more]

PMID: 24240813

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Project description:Introduction: Pediatric adamantinomatous craniopharyngioma (ACP) is a histologically benign but clinically aggressive brain tumor that arises from the sellar/suprasellar region. Despite a high survival rate with current surgical and radiation therapy (75-95% at 10 years), ACP is associated with debilitating visual, endocrine, neurocognitive and psychological morbidity, resulting in exceptionally poor quality of life for survivors. Identification of an effective pharmacological therapy would drastically decrease morbidity and improve long term outcomes for children with ACP. Results: Using microarray analysis of 15 ACP patient samples, we have found several pharmaceutical targets that are significantly and consistently overexpressed in our panel of ACP relative to other pediatric brain tumors, pituitary tumors, normal pituitary and normal brain tissue. Among the most highly expressed are several targets of the kinase inhibitor dasatinib -- LCK, EPHA2 and SRC; EGFR pathway targets -- AREG, EGFR and ERBB3; and other potentially actionable cancer targets -- SHH, MMP9 and MMP12. We confirm by Western blot that a subset of these targets is highly expressed in ACP primary tumor samples. Discussion: We report here the first microarray gene expression analysis for ACP and the identification of targets for rational therapy. Experimental drugs targeting each of these gene products are currently being tested clinically and pre-clinically for the treatment of other tumor types. This study provides a rationale for further pre-clinical and clinical studies of novel pharmacological treatments for ACP. Development of pre-clinical mouse and cell culture models for ACP will further enable the translation of these targets from the lab to the clinic. Gene expression profiles were generated from surgical tumor and normal brain samples (n=210) using Affymetrix HG-U133 Plus 2.0 chips. Gene expression profiles of adamantinomatous craniopharyngioma (ACP) were compared to a cohort of other tumor samples and normal brain tissues, and analyzed via gene set enrichment (GSEA analysis) and hierarchical clustering analysis to identify high expression of potential drug targets. The sample metadata and processed data for the complete dataset, which includes reanalysis of 23 Samples from GSE26966, 33 Samples from GSE35493, and 42 Samples from GSE50385, are linked below as supplementary files.

Dataset Information

Expression data from human ependymoma

Publications

Molecular sub-group-specific immunophenotypic changes are associated with outcome in recurrent posterior fossa ependymoma.

Similar Datasets

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