Transcriptomic Features of Cribriform and Intraductal Carcinoma of the Prostate

This is the largest series looking at the association between Decipher and unfavorable pathologic features in prostate cancer. Molecular subtyping and gene set enrichment identified candidate pathways that might drive the pathogenesis of these outcomes. Cribriform (CF) and/or intraductal carcinoma (...

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Published in:European urology focus 2022-11, Vol.8 (6), p.1575-1582
Main Authors: Lone, Zaeem, Benidir, Tarik, Rainey, Magdalena, Nair, Monica, Davicioni, Elai, Gibb, Ewan A., Williamson, Sean, Gupta, Shilpa, Chaim Ornstein, Moshe, Tendulkar, Rahul, Weight, Christopher, Nguyen, Jane K., Klein, Eric A., Mian, Omar Y.
Format: Article
Language:English
Subjects:
Carcinoma, Intraductal, Noninfiltrating - genetics
Carcinoma, Intraductal, Noninfiltrating - surgery
Cribriform
Decipher
Genomic classifier
Genomics
Humans
Male
Prostate
Prostate cancer
Prostatic Neoplasms - genetics
Prostatic Neoplasms - surgery
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Summary:This is the largest series looking at the association between Decipher and unfavorable pathologic features in prostate cancer. Molecular subtyping and gene set enrichment identified candidate pathways that might drive the pathogenesis of these outcomes. Cribriform (CF) and/or intraductal carcinoma (IDC) are associated with more aggressive prostate cancer (CaP) and worse outcomes. The transcriptomic features that typify CF/IDC are not well described and the capacity for clinically utilized genomic classifiers to improve risk modeling for CF/IDC remains undefined. We performed a retrospective review of CaP patients who had Decipher testing at a single high-volume institution. Index lesions from radical prostatectomy specimens were identified by genitourinary pathologists who simultaneously reviewed prostatectomy specimens for the presence of CF and IDC features. Patients were grouped based on pathologic features, specifically the absence of CF/IDC (CF–/IDC–), CF positive only (CF+/IDC–), and CF/IDC positive (CF+/IDC+). Clinical, pathologic, and genomic categorical variables were assessed using the Pearson chi-square test, while quantitative variables were assessed with the Kruskal-Wallis test. Multivariable logistic regression was used to identify the predictors of high-risk Decipher scores (>0.60). A gene set enrichment analysis was performed to identify genes and gene networks associated with CF/IDC status. A total of 463 patients were included. Patients who were CF+/IDC+ had the highest Decipher risk scores (CF+/IDC+: 0.79 vs CF+/IDC–: 0.71 vs CF–/IDC–: 0.56, p 
ISSN:2405-4569
2405-4569
DOI:10.1016/j.euf.2022.05.005