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Updated: Mar 15, 2026

miRNA Expression Analyses in Prostate Cancer Clinical Tissues
Published on: September 8, 2015
Molecular Analysis of Low Grade Prostate Cancer Using a Genomic Classifier of Metastatic Potential
Eric A Klein1, María Santiago-Jiménez2, Kasra Yousefi2
1Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
Purpose:
We determined how frequently histological Gleason 3 + 3 = 6 tumors have the molecular characteristics of disease with metastatic potential.
Materials And Methods:
We analyzed prostatectomy tissue from 337 patients with Gleason 3 + 3 disease. All tissue was re-reviewed in blinded fashion by genitourinary pathologists using 2005 ISUP (International Society of Urological Pathology) Gleason grading criteria. A previously validated Decipher® metastasis signature was calculated in each case based on a locked model. To compare patient characteristics across pathological Gleason score categories we used the Fisher exact test or the ANOVA F test. The distribution of Decipher scores among different clinicopathological groups was compared with the Wilcoxon rank sum test. The association of Decipher score with adverse pathology features was examined using logistic regression models. The significance level of all statistical tests was 0.05.
Results:
Of men with Gleason 3 + 3 = 6 disease only 269 (80%) had a low Decipher score with intermediate and high scores in 43 (13%) and 25 (7%), respectively. Decipher scores were significantly higher among pathological Gleason 3 + 3 = 6 specimens from cases with adverse pathological features such as extraprostatic extension, seminal vesicle involvement or positive margins (p <0.001). The median Decipher score in patients with margin negative pT2 disease was 0.23 (IQR 0.09-0.42) compared to 0.30 (IQR 0.17-0.42) in patients with pT3 disease or positive margins (p = 0.005).
Conclusions:
Using a robust and validated prognostic signature we found that a small but not insignificant proportion of histological Gleason 6 tumors harbored molecular characteristics of aggressive cancer. Molecular profiling of such tumors at diagnosis may better select patients for active surveillance at diagnosis and trigger appropriate intervention during followup.
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