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Series GSE46691 Query DataSets for GSE46691
Status Public on Jul 01, 2013
Title Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.

Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.

Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.

Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
 
Overall design 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
 
Contributor(s) Erho N, Crisan A, Vergara IA, Mitra AP, Ghadessi M, Buerki C, Bergstralh EJ, Kollmeyer T, Fink S, Haddad Z, Zimmermann B, Sierocinski T, Ballman KV, Triche TJ, Black PC, Karnes RJ, Klee G, Davicioni E, Jenkins RB
Citation(s) 23826159, 26631616, 29757368, 25986914
Submission date May 07, 2013
Last update date Jul 29, 2019
Contact name Elai Davicioni
E-mail(s) elai.davicioni@veracyte.com
Organization name Veracyte, Inc
Street address 9725 Lusk Blvd
City San Diego
State/province California
ZIP/Postal code 92121
Country USA
 
Platforms (1)
GPL5188 [HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [probe set (exon) version]
Samples (545)
GSM1134064 prostate_cancer_primary_1
GSM1134065 prostate_cancer_primary_2
GSM1134066 prostate_cancer_primary_3
Relations
BioProject PRJNA202054

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
GSE46691_RAW.tar 11.6 Gb (http)(custom) TAR (of CEL)
GSE46691_quantile_normalized.txt.gz 5.7 Gb (ftp)(http) TXT
Processed data are available on Series record

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