Validation of a 10-gene molecular signature for predicting biochemical recurrence and clinical metastasis in localized prostate cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-05

AUTHORS

Hatem Abou-Ouf, Mohammed Alshalalfa, Mandeep Takhar, Nicholas Erho, Bryan Donnelly, Elai Davicioni, R. Jeffrey Karnes, Tarek A. Bismar

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. More... »

PAGES

883-891

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00432-018-2615-7

DOI

http://dx.doi.org/10.1007/s00432-018-2615-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101359332

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29511883


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