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Series GSE30929 Query DataSets for GSE30929
Status Public on Sep 02, 2011
Title Whole-transcript expression data for liposarcoma
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Liposarcoma is the most common soft tissue sarcoma, accounting for about 20% of cases. Liposarcoma is classified into 5 histologic subtypes that fall into 3 biological groups characterized by specific genetic alterations. To identify genes that contribute to liposarcomagenesis and to better predict outcome for patients with the disease, we undertook expression profiling of liposarcoma. U133A expression profiling was performed on 140 primary liposarcoma samples, which were randomly split into training set (n=95) and test set (n=45). A multi-gene predictor for distant recurrence-free survival (DRFS) was developed using the supervised principal component method. Expression levels of the 588 genes in the predictor were used to calculate a risk score for each patient. In validation of the predictor in the test set, patients with low risk score had a 3-year DRFS of 83% vs. 45% for high risk score patients (P=0.001). The hazard ratio for high vs. low score, adjusted for histologic subtype, was 4.42 (95% confidence interval 1.26-15.55; P=0.021). The concordance probability for risk score was 0.732. Genes related to adipogenesis, DNA replication, mitosis, and spindle assembly checkpoint control were all highly represented in the multi-gene predictor. Three genes from the predictor, TOP2A, PTK7, and CHEK1, were found to be overexpressed in liposarcoma samples of all five subtypes and in liposarcoma cell lines. Knockdown of these genes in liposarcoma cell lines reduced proliferation and invasiveness and increased apoptosis. Thus, genes identified from this predictor appear to have roles in liposarcomagenesis and have promise as therapeutic targets. In addition, the multi-gene predictor will improve risk stratification for individual patients with liposarcoma.
 
Overall design 140 human liposarcoma specimens were profiled on Affymetrix U133A arrays per manufacturer's instructions.
 
Contributor(s) Gobble RM, Qin LX, Brill ER, Angeles CV, Ugras S, O'Connor RB, Moraco NH, Decarolis PL, Antonescu C, Singer S
Citation(s) 21335544
Submission date Jul 25, 2011
Last update date Aug 10, 2018
Contact name Brian Denton
E-mail(s) dentonb@mskcc.org
Organization name Memorial Sloan-Kettering Cancer Center
Department Epidemiology and Biostatistics
Street address 307 E. 63rd Street
City New York
State/province NY
ZIP/Postal code 10065
Country USA
 
Platforms (1)
GPL96 [HG-U133A] Affymetrix Human Genome U133A Array
Samples (140)
GSM766533 Sarcoma tumor DD0728
GSM766534 Sarcoma tumor DD103
GSM766535 Sarcoma tumor DD112
Relations
BioProject PRJNA146279

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
GSE30929_RAW.tar 477.0 Mb (http)(custom) TAR (of CEL)
Processed data included within Sample table

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