Gene expression signature of Gleason score is associated with prostate cancer outcomes in a radical prostatectomy cohort

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.

Oncotarget. 2017 Apr 26 [Epub ahead of print]

Min A Jhun, Milan S Geybels, Jonathan L Wright, Suzanne Kolb, Craig April, Marina Bibikova, Elaine A Ostrander, Jian-Bing Fan, Ziding Feng, Janet L Stanford

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA., Department of Oncology, Illumina, Inc., San Diego, CA, USA., Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD, USA., Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.