Genomic classifiers for treatment selection in newly diagnosed prostate cancer

Abstract

Objectives To review systematically the literature on genomic tests for prostate cancer (PCa) and to evaluate the current state of the evidence on their use in patients with newly diagnosed PCa. Methods We conducted a systematic review by searching PubMed, Embase, Cochrane Central and conference abstracts from the American Urological Association, published between 2010 and 2018. Studies evaluating Prolaris, Oncotype Dx and Decipher assays were assessed for inclusion by two authors. Studies were excluded if the results were derived from surgical specimens rather than biopsy specimens. A meta‐analysis was not performed owing to significant variations in methodologies, definitions and outcome measures. Results A total of 729 articles were retrieved in our initial search. After removing duplicates (270) and excluding articles deemed not relevant (432), 21 full‐text articles were deemed suitable for inclusion in the present analysis. The full‐text articles comprised eight studies on Prolaris, eight studies on Oncotype Dx and five studies on Decipher. For each genomic test we extracted data regarding the risks of adverse pathology, biochemical recurrence, metastasis and PCa‐specific mortality. Conclusion The results of genomic tests that use biomarkers derived from prostate biopsy can be used in conjunction with clinicopathological variables to improve our ability to risk‐stratify patients with newly diagnosed PCa. Additional data are needed on the impact of using these tests on long‐term patient outcomes and their cost‐effectiveness.

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

“…Decision curve analysis has been postulated as the most informative metric for an incremental predictive benefit [ 100 ]. These results support the view that there is considerable potential for improvement of the current prognostic models based only on clinicopathological factors by including molecular RNA markers [ 17 , 18 , 19 , 20 , 21 ]. Recently, the NCCN Prostate Cancer Guideline Panel suggested that tissue-based tests like Decipher, OncoType, Dx Prostate, Prolaris, and ProMark could be considered for initial PCa risk assessment [ 101 ].…”

“…Although all clinicopathological factors are, to some extent, associated with patient outcome, the prognostic accuracy of these nomograms is generally unsatisfactory [ 12 , 13 , 14 , 15 , 16 ]. In this context, prognostic molecular biomarkers could significantly improve the predictive accuracy of tools based only on clinicopathological factors [ 17 , 18 , 19 , 20 , 21 ]. We recently elaborated a five-microRNA signature that outperforms the BCR scoring systems mentioned above [ 6 ].…”

Transcript analysis of commercial prostate cancer risk stratification panels in hard‐to‐predict grade group 2–4 prostate cancers

“…We are among the first independent groups to compare these panels in patients with primarily intermediate‐risk prostate cancer using clinically relevant endpoints. While the genes in the studied panels were found to independently contribute to risk stratification, their performance here was modest compared to earlier publications 12,18–21 . However, it should be noted, that the studied cohort was extremely challenging, as it was selected based on similar baseline clinical characteristics in cases and controls.…”

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature

“…The NCCN Prostate Cancer Guidelines Panel stated in their 2019 guidelines that these tests might be considered for an initial risk stratification, based on biopsy samples and RP specimens [99]. Other current reports support this view [27,28,29,30,100,101,102]. Yet, the particularly different prognostic outcome results obtained by a head-to-head comparison of three tests (namely Decipher, Prolaris, and Oncotype), obviously complicate the routine implementation of these tests [103].…”

“…As one of the most powerful predictive scoring systems, CAPRAS was found to lack sufficient prediction accuracy in two meta-analyses [25,26]. Therefore, it is hoped that new tissue-based molecular biomarkers could be potential candidates to improve the disease recurrence prediction [27,28,29,30].…”