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Series GSE19949 Query DataSets for GSE19949
Status Public on Jul 24, 2012
Title Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome
Organism Homo sapiens
Experiment type Expression profiling by array
Genome variation profiling by SNP array
Summary Background: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach.
Methods: We integrated gene expression data from 97 primary RCCs of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. Results: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance.
 
Overall design Expression profiling by array, combined data analysis with genomic profiling data. Genomic DNA from renal cell was hybridized to renal cell carcinoma samples and matched normal kidney tissue biopsies, using the Affymetrix GenomewideSNP_6 platform. CEL files were processed using R, Bioconductor and software from the aroma.affymetrix project. Visualized Copy number profiles are accessible through the Progenetix site (www.progenetix.net). CN,raw.csv and segments.csv: Probes are mapped by their position in genome build 36 / HG18. Probes are ordered according to their linear position on the Golden Path.
 
Contributor(s) Baudis M, Beleut M, Moch H, Schraml P, Philip Z
Citation(s) 22824167
Submission date Jan 19, 2010
Last update date Nov 27, 2018
Contact name Michael Baudis
E-mail(s) mbaudis@gmail.com
Organization name University of Zurich
Department Institute of Molecular Life Sciences
Street address Winterthurerstrasse 190
City Zurich
ZIP/Postal code 8057
Country Switzerland
 
Platforms (2)
GPL3921 [HT_HG-U133A] Affymetrix HT Human Genome U133A Array
GPL6801 [GenomeWideSNP_6] Affymetrix Genome-Wide Human SNP 6.0 Array
Samples (261)
GSM498450 UZHRCC006_RCC_clear_cell_BI_mRNA_rep1
GSM498451 UZHRCC007_RCC_clear_cell_BI_mRNA_rep2
GSM498452 UZHRCC008_RCC_clear_cell_BI_mRNA_rep3
Relations
BioProject PRJNA120185

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE19949_RAW.tar 7.0 Gb (http)(custom) TAR (of CEL, CSV)
Processed data provided as supplementary file
Processed data included within Sample table
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