Name: Methylation profiling by array of 108 clear cell renal cell carcinoma
Keywords: methylation profiling by array

Dataset Information

Methylation profiling by array of 108 clear cell renal cell carcinoma

ABSTRACT: A Cartes d'Identite des Tumeurs (CIT) project from the French Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net). Selecting patients with metastatic clear-cell renal cell carcinoma (m-ccRCC) who might benefit from treatment with targeted tyrosine kinase inhibitors (TKIs) is a challenge. Our aim was to identify molecular markers associated with outcome in m-ccRCC patients treated with sunitinib."

INSTRUMENT(S): Illumina iScan

ORGANISM(S): Homo sapiens

DISEASE(S): Tumor,Normal

SUBMITTER: Elarouci Nabila

PROVIDER: E-MTAB-3274 | ArrayExpress | 2016-02-26

REPOSITORIES: ArrayExpress

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Publications

Molecular subtypes of clear cell renal cell carcinoma are associated with sunitinib response in the metastatic setting.

Beuselinck Benoit B Job Sylvie S Becht Etienne E Karadimou Alexandra A Verkarre Virginie V Couchy Gabrielle G Giraldo Nicolas N Rioux-Leclercq Nathalie N Molinié Vincent V Sibony Mathilde M Elaidi Reza R Teghom Corinne C Patard Jean-Jacques JJ Méjean Arnaud A Fridman Wolf Herman WH Sautès-Fridman Catherine C de Reyniès Aurélien A Oudard Stéphane S Zucman-Rossi Jessica J

Clinical cancer research : an official journal of the American Association for Cancer Research 20150112 6

<h4>Purpose</h4>Selecting patients with metastatic clear-cell renal cell carcinoma (m-ccRCC) who might benefit from treatment with targeted tyrosine kinase inhibitors (TKI) is a challenge. Our aim was to identify molecular markers associated with outcome in patients with m-ccRCC treated with sunitinib.<h4>Experimental design</h4>We performed global transcriptome analyses on 53 primary resected ccRCC tumors from patients who developed metastatic disease and were treated with first-line sunitinib. ...[more]

PMID: 25583177

Similar Datasets

Project description:A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on DNA methylation, mRNA expression and microRNA (miRNA) expression in four distinct human brain regions. We show that brain tissues may be readily distinguished based on methylation status or expression profile. We find an abundance of genetic cis regulation mRNA expression and show for the first time abundant quantitative trait loci for DNA CpG methylation. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation. Authorized Access data: Mapping of GEO sample accessions to dbGaP subject/sample IDs is available through dbGaP Authorized Access, see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000249.v1.p1 Because of our interest in genomic regulation of expression and neurological disorders we embarked upon a series of experiments to provide a brain region-specific contextual framework for genetic and epigenetic regulation of gene expression. We obtained frozen brain tissue from the cerebellum, frontal cortex, pons and temporal cortex from 150 subjects (total 600 tissue samples). We undertook four separate assays across this series; first, genome-wide SNP genotyping; second, assay of >27,000 CpG methylation sites in each of the four brain regions; third, mRNA expression profiling of >22,000 transcripts in all four brain regions; and, fourth, miRNA expression profiling of 735 miRNA transcripts. Here we discuss the results of these experiments, particularly in the context of integrated datasets to define expression and CpG methylation quantitative trait loci (eQTL and methQTL) and detailing differences and similarities across brain regions.

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	E-MTAB-3274.idf.txt_original	Idf
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	E-MTAB-3274.sdrf.txt	Txt