Gene expression in normal-appearing tissue adjacent to prostate cancers are predictive of clinical outcome: evidence for a biologically meaningful field effect

被引:16
作者
Magi-Galluzzi, Cristina [1 ,2 ]
Maddala, Tara [3 ]
Falzarano, Sara Moscovita [1 ]
Cherbavaz, Diana B. [3 ]
Zhang, Nan [3 ]
Knezevic, Dejan [3 ]
Febbo, Phillip G. [3 ]
Lee, Mark [3 ]
Lawrence, H. Jeffrey [3 ]
Klein, Eric A. [2 ]
机构
[1] Cleveland Clin, Pathol & Lab Med Inst, Cleveland, OH 44106 USA
[2] Cleveland Clin, Glickman Urol & Kidney Inst, Cleveland, OH 44106 USA
[3] Genom Hlth Inc, Redwood City, CA USA
关键词
prostate cancer; gene expression profiling; molecular diagnostics; prognosis; risk assessment; BENIGN PROSTATE; BIOMARKERS; EPITHELIUM; CONTEXT; ASSAY;
D O I
10.18632/oncotarget.8944
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: We evaluated gene expression in histologically normal-appearing tissue (NT) adjacent to prostate tumor in radical prostatectomy specimens, assessing for biological significance based on prediction of clinical recurrence (cR - metastatic disease or local recurrence). Results: A total of 410 evaluable patients had paired tumor and NT. Forty-six genes, representing diverse biological pathways (androgen signaling, stromal response, stress response, cellular organization, proliferation, cell adhesion, and chromatin remodeling) were associated with cR in NT (FDR < 20%), of which 39 concordantly predicted cR in tumor (FDR < 20%). Overall GPS and its stromal response and androgen-signaling gene group components also significantly predicted time to cR in NT (RM-corrected HR/20 units = 1.25; 95% CI: 1.01-1.56; P = 0.024). Experimental Design: Expression of 732 genes was measured by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) separately in tumor and adjacent NT specimens from 127 patients with and 374 without cR following radical prostatectomy for T1/T2 prostate cancer. A 17-gene expression signature (Genomic Prostate Score [GPS]), previously validated to predict aggressive prostate cancer when measured in tumor tissue, was also assessed using pre-specified genes and algorithms. Analysis used Cox proportional hazards models, Storey's false discovery rate (FDR) control, and regression to the mean (RM) correction. Conclusions: Gene expression profiles, including GPS, from NT adjacent to tumor can predict prostate cancer outcome. These findings suggest that there is a biologically significant field effect in primary prostate cancer that is a marker for aggressive disease.
引用
收藏
页码:33855 / 33865
页数:11
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