Development and validation of a digital Gleason score biomarker signature for risk stratification of patients with prostate cancer.

Abstract

40 Background: Gleason score (GS) is the most widely used grading system of cell differentiation in prostate cancer and one of the best pathological predictors of disease progression. Patients with high GS (> 7) are the most likely to experience metastasis, whereas patients with low GS (< 7) are expected to have favorable long-term outcomes. In addition to the subjective nature of GS assessment, patients with GS 7 represent a heterogeneous group in terms of patient outcomes. In this study a biomarker signature is developed and validated which could improve the prediction of high risk disease among GS 7 radical prostatectomy (RP) patients. Methods: Patient specimens from the Mayo Clinic RP Registry (n = 764) were used for feature selection and training of a 392-feature K-nearest neighbor (KNN, k = 11) classifier. These 392 genomic features were identified by assessing differential expression between patients with GS < 7 and those with GS > 7, using a Bonferroni adjusted T-Test with a p-value threshold of 0.05. The classifier was subsequently validated in two independent patient cohorts (Memorial Sloan Kettering [MSKCC] and German Cancer Research Center [DKFZ]) and compared to a state of the art biomarker signature (Penney et al. 2011). Results: In the MSKCC dataset (GSE21034) our model segregated GS < 7 from GS > 7 patients (n = 56) with an area under the receiver operating characteristic curve (AUC) of 0.97, comparable to the AUC of 0.94 obtained by Penney et al. in their independent validation set (n = 45). Strong performance was observed by our model when discriminating between primary Gleason grade (pGG) 3 and pGG 4 & 5 patients in the MSKCC (n = 130) and DKFZ prostate cancer (GSE29079, n = 47) datasets, achieving AUCs of 0.75 and 0.87, respectively. In the challenging GS 7 subset, our model segregated GS 3 + 4 and 4 + 3 patients in the DKFZ dataset (n = 64) with an AUC of 0.81 outperforming the Penney et al. signature (AUC = 0.60). Conclusions: A biomarker signature was developed which discriminates between low and high GS patients, outperforming a previously reported signature. Further validation of this biomarker signature in additional post RP patients, as well as, pretreatment biopsy specimens is warranted.