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Series GSE62021 Query DataSets for GSE62021
Status Public on Oct 04, 2014
Title Prediction of prognosis for small cell lung cancer based on genome-wide methylation analyses with surgical materials and robust clustering methods
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Methylation is closely involved in the development of various carcinomas. However, little datasets are available for small cell lung carcinoma (SCLC) due to the scarcity of fresh tumor samples. The aim of this study is to investigate the comprehensive genome-wide methylation profile of SCLC to predict the prognosis after surgical treatment.
We investigated the high DNA methylated and low gene expression sites using 25 SCLC tumor tissues. First, we selected most differentially methylated CpG sites across the tumor tissues. Following hierarchical clustering (HC) and non-negative matrix factorization (NMF), gene ontology analysis was performed using DAVID software. Clustering of SCLC tumors led to the important identification of a CpG island methylator phenotype (CIMP) of SCLC, and showed that CIMP-high tumors had a significantly poorer prognosis (p = 0.001). Multivariate analysis revealed that postoperative chemotherapy, low neuroendocrine expression and the CIMP-low state were significantly good prognostic factors. Association analyses of methylation and gene expression provided 46 genes with significant correlation. Ontology studies to these genes showed that genes involved in extrinsic apoptosis pathway were suppressed, including TNFRSF1A, TNFRSF10A and TRADD, in CIMP-high tumors, prognosis of which was poorer. By comprehensive DNA methylation profiling, two distinct subgroups were identified to evoke a CIMP of SCLC as a useful marker for determination of treatment. Delineation of this phenotype may also be useful for the development of novel apoptosis-related chemotherapeutic agents for the treatment of an aggressive subtype of SCLC.
Overall design Comprehensive genome-wide methylation analyses
Contributor(s) Saito Y, Ishikawa Y
Citation(s) 26748784
Submission date Oct 03, 2014
Last update date Nov 27, 2018
Contact name YUICHI SAITO
Phone 81335200111
Organization name The Cancer Institute of Japanese Foundation Cancer Research
Department Pathology
Street address 3-8-31 Ariake
City Koto
State/province Tokyo
ZIP/Postal code 1358550
Country Japan
Platforms (1)
GPL13607 Agilent-028004 SurePrint G3 Human GE 8x60K Microarray (Feature Number version)
Samples (25)
GSM1518562 SCLC_tissue_cluster 2 [GTB.409]
GSM1518563 SCLC_tissue_cluster 1 [GTB.545]
GSM1518564 SCLC_tissue_cluster 1 [GTB.2213]
BioProject PRJNA262968

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
GSE62021_RAW.tar 83.4 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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