Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

RNA expression data from primary neuroblastoma tumors

ABSTRACT: RNA expression profiles of 105 primary neuroblastomas derived from customized 4 x 44k oligonucleotide microarrays (Agilent Technologies). These profiles are part of an integrative study combining genomewide epigenetic profiles with transcriptome data of the same neuroblastoma cohort. Tumors were derived from 40 low-risk, 9 intermediate-risk and 56 high-risk patients. Transcription profiles of 105 primary neuroblastomas derived from customized 4 x 44k oligonucleotide microarrays (Agilent Technologies)

ORGANISM(S): Homo sapiens

SUBMITTER: Maral Saadati

PROVIDER: E-GEOD-73517 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Integrative Genome-Scale Analysis Identifies Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas.

Henrich Kai-Oliver KO Bender Sebastian S Saadati Maral M Dreidax Daniel D Gartlgruber Moritz M Shao Chunxuan C Herrmann Carl C Wiesenfarth Manuel M Parzonka Martha M Wehrmann Lea L Fischer Matthias M Duffy David J DJ Bell Emma E Torkov Alica A Schmezer Peter P Plass Christoph C Höfer Thomas T Benner Axel A Pfister Stefan M SM Westermann Frank F

Cancer research 20160907 18

The broad clinical spectrum of neuroblastoma ranges from spontaneous regression to rapid progression despite intensive multimodal therapy. This diversity is not fully explained by known genetic aberrations, suggesting the possibility of epigenetic involvement in pathogenesis. In pursuit of this hypothesis, we took an integrative approach to analyze the methylomes, transcriptomes, and copy number variations in 105 cases of neuroblastoma, complemented by primary tumor- and cell line-derived global ...[more]

PMID: 27635046

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Project description:We generated gene expression profiles from 498 primary neuroblastomas using RNA-Seq and microarrays. We sought to systematically evaluate the capability of RNA deep-sequencing (RNA-Seq)-based classification for clinical endpoint prediction in comparison to microarray-based ones. The neuroblastoma cohort was randomly divided into training and validation sets, and 360 predictive models on six clinical endpoints were generated and evaluated. While prediction performances did not differ considerably between the two technical platforms, the RNA-Seq data processing pipelines, or feature levels (i.e., gene, transcript, and exon junction levels), RNA-Seq models based on the AceView database performed best on most endpoints. Collectively, our study reveals an unprecedented complexity of the neuroblastoma transcriptome, and provides guidelines for the development of gene expression-based predictive classifiers using high-throughput technologies. Sample clinical characteristics definitions: dataset: Expression data set used for classification training (1) or validation (2) Sex: M = male; F= female age at diagnosis: the age in days at diagnosis mycn status: Amplification status of the MYCN proto-oncogene (amplified = 1, no amplification = 0; no information = N/A) high risk: Clinically considered as high-risk neuroblastoma (yes=1, no= 0) INSS stage: disease stage according to International Neuroblastoma Staging System (INSS) (1, 2, 3, 4 and 4S) class label: Maximally divergent disease courses - unfavorable (= 1): patient died despite intensive chemotherapy, favorable (=0): patient survived without chemotharapy for at least 1000 days post diagnosis; not applicable (N/A) progression: Occurrence of a tumor progression event (yes=1; no=0) death from disease: Occurrence of death from the disease (yes=1; no=0) Gene expression of 498 neuroblastoma samples was quantified by RNA sequencing as well as by microarray analyses in order to understand the neuroblastoma transcriptome and predict clinical endpoints.

Dataset Information

RNA expression data from primary neuroblastoma tumors

Publications

Integrative Genome-Scale Analysis Identifies Epigenetic Mechanisms of Transcriptional Deregulation in Unfavorable Neuroblastomas.

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