BackgroundExpanding interest in and use of active surveillance for early state prostate cancer (PC) has increased need for prognostic biomarkers. Using a multi-institutional tissue microarray resource including over 1000 radical prostatectomy samples, we sought to correlate Ki67 expression captured by an automated image analysis system with clinicopathological features and validate its utility as a clinical grade test in predicting cancer-specific outcomes.
MethodsAfter immunostaining, the Ki67 proliferation index (PI) of tumor areas of each core (three cancer cores/case) was analyzed using a nuclear quantification algorithm (Aperio). We assessed whether Ki67 PI was associated with clinicopathological factors and recurrence-free survival (RFS) including biochemical recurrence, metastasis or PC death (7-year median follow-up).
ResultsIn 1004 PCs (∼4000 tissue cores) Ki67 PI showed significantly higher inter-tumor (0.68) than intra-tumor variation (0.39). Ki67 PI was associated with stage (P<0.0001), seminal vesicle invasion (SVI, P=0.02), extracapsular extension (ECE, P<0.0001) and Gleason score (GS, P<0.0001). Ki67 PI as a continuous variable significantly correlated with recurrence-free, overall and disease-specific survival by multivariable Cox proportional hazard model (hazards ratio (HR)=1.04-1.1, P=0.02-0.0008). High Ki67 score (defined as ⩾5%) was significantly associated with worse RFS (HR=1.47, P=0.0007) and worse overall survival (HR=2.03, P=0.03).
ConclusionsIn localized PC treated by radical prostatectomy, higher Ki67 PI assessed using a clinical grade automated algorithm is strongly associated with a higher GS, stage, SVI and ECE and greater probability of recurrence.