|Title||Genomic Correlates to the Newly Proposed Grading Prognostic Groups for Prostate Cancer.|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Rubin MA, Girelli G, Demichelis F|
|Date Published||2016 Apr|
UNLABELLED: Recommendations by the International Society of Urologic Pathology and 2016 World Health Organization blue book propose the use of a five-tiered prostate cancer (PCa) grading system. The five prognostic grade groupings (PGGs) ranging from 1 to 5 are defined as Gleason grades ≤6, 3+4, 4+3, 8, and >8, respectively. Recent work suggests that each group is associated with a distinct risk of biochemical PCa recurrence. In this study, we sought genomic support for PGGs using whole-exome and whole-genome sequencing data for 426 clinically localized PCas treated by radical prostatectomy. After adjustment for tumor purity for the sequencing data, we observed a significant frequency increase in genomic amplifications and deletions (p=0.013) and in nonsynonymous point mutations (p=0.008) with increasing risk group. Interestingly, PGG1 (low risk) was entirely haploid, whereas PGG2-5 exhibited increasing polyploidy frequency. Principal component analysis of genomic profiles revealed that PGG1, PGG2, and PGG3 represent distinct classes, but PGG4 and PGG5 exhibit genomic similarity. Together, these observations for the largest PCa genomic data set to date provide support for increasing genomic alterations with increasing PGG. This is the first genomic correlation of the PGG system. Future work will need to explore the clinical utility of PGGs in prospective studies with long-term follow-up.
PATIENT SUMMARY: Gleason grading for prostate cancer provides important information for guiding clinical care. A new proposal by leading pathologists favors translating Gleason grades into five risk categories. In this study, a comprehensive analysis of the largest genomic data set on prostate cancer to date, we demonstrate molecular support for this new five-tiered system.
|Alternate Journal||Eur. Urol.|