Hatem Abou-Ouf1,2, Mohammed Alshalalfa3, Mandeep Takhar3, Nicholas Erho3, Bryan Donnelly4, Elai Davicioni3, R Jeffrey Karnes5, Tarek A Bismar6,7,8,9,10. 1. Department of Pathology and Laboratory Medicine, University of Calgary, Cumming School of Medicine, Calgary, AB, Canada. 2. Calgary Laboratory Services, Calgary, AB, Canada. 3. Genome DX Biosciences, San Diego, CA, USA. 4. Department of Urology, University of Calgary, Calgary, AB, Canada. 5. Department of Urology, Mayo Clinic, Rochester, MN, USA. 6. Department of Pathology and Laboratory Medicine, University of Calgary, Cumming School of Medicine, Calgary, AB, Canada. tabismar@ucalgary.ca. 7. Calgary Laboratory Services, Calgary, AB, Canada. tabismar@ucalgary.ca. 8. Department of Oncology, University of Calgary, Calgary, AB, Canada. tabismar@ucalgary.ca. 9. Arnie Charbonneau Cancer Institute and Tom Baker Cancer Center, Calgary, AB, Canada. tabismar@ucalgary.ca. 10. Rockyview General Hospital, Department of Pathology, Calgary Laboratory Services, 7007 - 14th Street SW, Calgary, AB, T2V 1P9, Canada. tabismar@ucalgary.ca.
Abstract
PURPOSE: To validate a previously characterized 10-gene signature in prostate cancer with implication to distinguish aggressive and indolent disease within low and intermediate patients' risk groups. METHODS: A case-control study design used to select 545 patients from the Mayo clinic tumor registry who underwent radical prostatectomy. A training set from this cohort (n = 359) was used to build a 10-gene model, based on high-dimensional discriminant analysis (HDDA10) to predict several endpoints of clinical patients' outcome. An independent set (n = 219) from the same institution was used as validation set. RESULTS: HDDA10 showed significant performance for predicting metastasis (Mets) (AUC 0.68, p = 6.4E - 6) and biochemical recurrence (BCR) (AUC = 0.65, p = 0.003) in the validation set outperforming Gleason grade grouping (GG) for BCR (AUC 0.57, p = 0.03) and with comparable performance for Mets endpoint (GG AUC 0.66, p = 8.1E - 5). HDDA10 prognostic significance was superior to any clinical-pathological parameter within GG2 + 3 (GS7) patients achieving an AUC of 0.74 (p = 0.0037) for BCR compared to Gleason pattern 4 (AUC 0.64) (p = 0.015) and AUC for Mets of 0.68 versus AUC of 0.65 for Gleason pattern 4 (p = 0.01). HDDA10 remained significant for both BCR and Mets in multivariate analysis, suggesting that it can be used to increase accuracy in stratifying patients eligible for active surveillance. CONCLUSION: HDDA10 is of added value to GG and other clinical-pathological parameters in predicting BCR and Mets endpoint, especially in the low to intermediate patients' risk groups. HDDA10 prognostic value should be further validated prospectively in stratifying patients specifically in low to intermediate GS (GG1-2), such as active surveillance programs.
PURPOSE: To validate a previously characterized 10-gene signature in prostate cancer with implication to distinguish aggressive and indolent disease within low and intermediate patients' risk groups. METHODS: A case-control study design used to select 545 patients from the Mayo clinic tumor registry who underwent radical prostatectomy. A training set from this cohort (n = 359) was used to build a 10-gene model, based on high-dimensional discriminant analysis (HDDA10) to predict several endpoints of clinical patients' outcome. An independent set (n = 219) from the same institution was used as validation set. RESULTS: HDDA10 showed significant performance for predicting metastasis (Mets) (AUC 0.68, p = 6.4E - 6) and biochemical recurrence (BCR) (AUC = 0.65, p = 0.003) in the validation set outperforming Gleason grade grouping (GG) for BCR (AUC 0.57, p = 0.03) and with comparable performance for Mets endpoint (GG AUC 0.66, p = 8.1E - 5). HDDA10 prognostic significance was superior to any clinical-pathological parameter within GG2 + 3 (GS7) patients achieving an AUC of 0.74 (p = 0.0037) for BCR compared to Gleason pattern 4 (AUC 0.64) (p = 0.015) and AUC for Mets of 0.68 versus AUC of 0.65 for Gleason pattern 4 (p = 0.01). HDDA10 remained significant for both BCR and Mets in multivariate analysis, suggesting that it can be used to increase accuracy in stratifying patients eligible for active surveillance. CONCLUSION: HDDA10 is of added value to GG and other clinical-pathological parameters in predicting BCR and Mets endpoint, especially in the low to intermediate patients' risk groups. HDDA10 prognostic value should be further validated prospectively in stratifying patients specifically in low to intermediate GS (GG1-2), such as active surveillance programs.
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