Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort
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Min A. Jhun1, Milan S. Geybels1,2, Jonathan L. Wright1,3, Suzanne Kolb1, Craig April4, Marina Bibikova4, Elaine A. Ostrander5, Jian-Bing Fan4, Ziding Feng6 and Janet L. Stanford1,7
1Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
2Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands
3Department of Urology, University of Washington School of Medicine, Seattle, WA, USA
4Department of Oncology, Illumina, Inc., San Diego, CA, USA
5Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD, USA
6Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
7Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
Janet L. Stanford, email: [email protected]
Keywords: gene expression, Gleason score, prostate cancer, recurrence, metastasis
Received: February 17, 2017 Accepted: March 30, 2017 Published: April 26, 2017
Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide. Gleason score (GS) is one of the best predictors of PCa aggressiveness, but additional tumor biomarkers may improve its prognostic accuracy. We developed a gene expression signature of GS to enhance the prediction of PCa outcomes. Elastic net was used to construct a gene expression signature by contrasting GS 8-10 vs. ≤6 tumors in The Cancer Genome Atlas (TCGA) dataset. The constructed signature was then evaluated for its ability to predict recurrence and metastatic-lethal (ML) progression in a Fred Hutchinson (FH) patient cohort (N=408; NRecurrence=109; NMLprogression=27). The expression signature included transcripts representing 49 genes. In the FH cohort, a 25% increase in the signature was associated with a hazard ratio (HR) of 1.51 (P=2.7×10−5) for recurrence. The signature’s area under the curve (AUC) for predicting recurrence and ML progression was 0.68 and 0.76, respectively. Compared to a model with age at diagnosis, pathological stage and GS, the gene expression signature improved the AUC for recurrence (3%) and ML progression (6%). Higher levels of the signature were associated with increased expression of genes in cell cycle-related pathways and decreased expression of genes in androgen response, estrogen response, oxidative phosphorylation, and apoptosis. This gene expression signature based on GS may improve the prediction of recurrence as well as ML progression in PCa patients after radical prostatectomy.
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