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Series GSE33916 Query DataSets for GSE33916
Status Public on Nov 22, 2013
Title Identifying functional CpG island methylation markers in clear cell renal cell cancer cell lines
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Clear cell renal cell carcinoma (ccRCC) is the most common adult renal cancer. Although the molecular characteristics of ccRCC are currently being studied, the biologically and clinically relevant ccRCC methylome remains to be elucidated. To explore the RCC hypermethylome we employed massive sequencing of methyl-binding protein enriched DNA and validated the biological relevance of the identified hypermethylated sites by pharmacological inhibition of DNA methylation. We identified four candidate tumor suppressor genes (GREM1, LAD1, NEFH, and NEURL) of which promoter CpG island hypermethylation was strongly predictive for ccRCC survival in two independent series (n=150 and n=185) of ccRCC primary samples. The four markers combined are strongly associated with risk for cancer-related death in the test series (HR 3.64, 95% CI 1.02-13.01) as well as, independently of other clinicopathological characteristics, in the validation series (HR 7.54, 95% CI 2.68-21.19) using Cox proportional hazard models. According to Harrell’s C statistics and the Akaike Information Criterion (AIC) the four marker panel provides the best predictive capacity with the best fit of the model as assessed for the tested markers. These results provide novel insights into the ccRCC hypermethylome and identify a strong methylation marker panel to potentially guide personalized ccRCC patient management. Preliminary to implementation of this marker panel into clinical practice, enrollment of these patients in a Phase-III trial to study adjuvant treatment efficacy is essential.
 
Overall design 4 independant clear cell renal cancer cell lines were used before and after treatment with the DNA methylation inhibitor AZA or the HAZA inhibitor TSA.
 
Contributor(s) Van Neste L, Vlodrop I, De Meyer T, van Engeland M, Baylin SB, Van Criekinge W
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Submission date Nov 23, 2011
Last update date Jan 23, 2019
Contact name Leander Van Neste
Organization name Ghent University
Department Molecular Biotechnology
Lab Bioinformatics and Computational Genomics
Street address Coupure Links 653
City Ghent
ZIP/Postal code 9000
Country Belgium
 
Platforms (1)
GPL6480 Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Probe Name version)
Samples (8)
GSM838695 Effect of AZA treatment on gene expression in SKRC59
GSM838696 Effect of TSA treatment on gene expression in SKRC59
GSM838697 Effect of AZA treatment on gene expression in SKRC52
Relations
BioProject PRJNA148235

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
GSE33916_RAW.tar 104.6 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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