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Series GSE25136 Query DataSets for GSE25136
Status Public on Nov 05, 2010
Title Optimizing molecular signatures for prostate cancer recurrence
Organism Homo sapiens
Experiment type Expression profiling by array
Summary The derivation of molecular signatures indicative of disease status and predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate cancer patients. In this study, we conducted a computational analysis of gene expression profile data obtained from 79 cases, 39 of which were classified as having disease recurrence, to investigate whether advanced computational algorithms can derive more accurate prognostic signatures for prostate cancer. At the 90% sensitivity level, a newly derived prognostic genetic signature achieved 85% specificity. This is the first reported genetic signature to outperform a clinically used postoperative nomogram. Furthermore, a hybrid prognostic signature derived by combination of the nomogram and gene expression data significantly outperformed both genetic and clinical signatures, and achieved a specificity of 95%. Our study demonstrates the feasibility of utilizing gene expression information for highly accurate prostate cancer prognosis beyond the current clinical systems, and shows that more advanced computational modeling of tissue-derived microarray data is warranted before clinical application of molecular signatures is considered.
 
Overall design mRNA profiling was performed using 79 cases of prostate cancer of known disease recurrence status
 
Contributor(s) Goodison S, Sun Y
Citation(s) 19343730
Submission date Nov 04, 2010
Last update date Aug 10, 2018
Contact name Steve Goodison
Organization name M. D. Anderson Cancer Center Orlando
Department Cancer Research Institute
Street address 6900 Lake Nona Blvd
City Orlando
ZIP/Postal code 32827
Country USA
 
Platforms (1)
GPL96 [HG-U133A] Affymetrix Human Genome U133A Array
Samples (79)
GSM617581 Prostate cancer primary tumor PG8
GSM617582 Prostate cancer primary tumor PG12
GSM617583 Prostate cancer primary tumor PG13
Relations
BioProject PRJNA134591

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
GSE25136_RAW.tar 269.5 Mb (http)(custom) TAR (of CEL)
Processed data included within Sample table

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