plos PLoS Currents: Evidence on Genomic Tests 2157-3999 Public Library of Science San Francisco, USA 10.1371/currents.eogt.761b81608129ed61b0b48d42c04f92a4 Evidence on Genomic Tests A 22 Gene-expression Assay, Decipher® (GenomeDx Biosciences) to Predict Five-year Risk of Metastatic Prostate Cancer in Men Treated with Radical Prostatectomy Marrone Michael Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Rockville, Maryland, USA Potosky Arnold L. Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, USA Penson David Department of Urology, Vanderbilt University Medical Center, Nashville, Tennessee, USA Freedman Andrew N. Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Rockville, Maryland, USA 17 11 2015 ecurrents.eogt.761b81608129ed61b0b48d42c04f92a4 2019 Marrone, Potosky, Penson, Freedman, et al This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Among the estimated 230,000 men diagnosed with prostate cancer in the US each year there has been a rise in the number of radical prostatectomies (RP). There is some debate over the value of immediate adjuvant therapy following RP in men with high-risk pathological features versus delayed salvage radiation therapy when signs of disease progression are observed. Thus, it would be potentially useful to inform post-RP management strategies by more clearly identifying those patients at higher risk of progression and death from prostate cancer. A 22 gene-expression assay, Decipher® (GenomeDx Biosciences), has been developed in men treated with radical prostatectomy to predict the five-year risk of metastatic prostate cancer. Published and unpublished literature was evaluated to determine the analytic validity, clinical validity and clinical utility of Decipher. Limited information is available on the analytic validity of Decipher. In both discovery and validation studies, Decipher was shown to have good performance in discriminating men with metastasis from men without metastasis five years after surgery (AUC 0.75 to 0.90). In terms of clinical utility, no evidence was found reporting improved outcomes (lower prostate cancer specific mortality and treatment related adverse effects) from using this test to guide post-operative treatment. Four studies provided weak indirect evidence of clinical utility in which 31% to 43% of post-operative treatment recommendations were changed in men with high-risk prostate cancer based on test results, with 27% to 52% of treatment recommendations changing from any treatment to no treatment.

No external sources of funding.
Clinical scenario

In men diagnosed with prostate cancer in the US, prognosis is generally excellent following radical prostatectomy (RP) with 15-year disease free survival of 93%.1 However, RP may be associated with significant complications and adverse-effects, primarily sexual dysfunction and urinary incontinence. Furthermore, between 19% and 30% of men experience biochemical recurrence (rise in PSA over 0.2 ng/ml) 5 to 10 years after surgery, and these men have a 37% risk of developing distant metastasis within five years if not treated and have a 17% risk of dying from prostate cancer within six years of biochemical recurrence.2,3 The most appropriate course of treatment is based on standard risk assessment that incorporates clinical characteristics such as cancer stage, grade, and size as well as histopathological features including PSA and Gleason score to estimate risk of recurrence from nomograms.4 Current post-RP practice includes observation for low risk disease, adjuvant therapy for adverse pathology and salvage therapy after biochemical recurrence.4 However, not all men with high-risk prostate cancer with adverse pathological features will require or will benefit from adjuvant therapy. Furthermore, the adverse events and complications associated with postoperative adjuvant therapy are not insignificant and range from incontinence, bowel complications as well as urogenital toxicities resulting from radiotherapy.5 Thus, there remains a need for increased accuracy in estimating a man's prognosis (risk of metastasis) to ensure appropriate follow up care is given in a timely manner.

Test Description

Decipher® (GenomeDx Biosciences) is a genomic test that was developed to predict the risk of metastatic prostate cancer within five years of RP in men at high risk of recurrence (extraprostatic extension, seminal vesicle invasion, positive margins, or biochemical recurrence).6 A genomic classifier score calculated from a gene-expression microarray analysis of 22 genes on formalin-fixed, paraffin embedded (FFPE) prostate tumor tissue ranges between 0 and 1 and classifies patients as high risk (1 in 5 risk of metastasis), average risk, or low risk (1 in 42 risk of metastasis).6 No information was available on the specific genes included in the 22-geen analysis. Decipher is available as a laboratory developed test through physicians or as part of clinical investigations sponsored by GenomDx, which is licensed under the Clinical Laboratory Improvement Act (CLIA).

Public Health Importance

In the US, prostate cancer is the most common cancer in men with estimates showing over 230,000 cases will be diagnosed in 2014 and just under 30,000 men will die from the disease.7 For men with high-risk prostate cancer based on post-RP pathological findings the strongest predictors of prostate cancer metastasis and death are baseline Gleason score, time of biochemical recurrence after RP, and PSA doubling-time.2,3 Within this high-risk group of men with prostate cancer the benefit of adjuvant or salvage therapy varies, and the high costs and complications associated with adjuvant radiotherapy underscore the need for improved prognostic markers.5

Methods

PubMed was searched (14 July 2015) to identify published reports of studies investigating the analytic validity, clinical validity and clinical utility of Decipher. Supplemental searches for grey literature, guidelines, and coverage decisions included Google, Genetic Testing Registry (GTR), guidelines.gov, and the Centers for Medicare and Medicaid using the terms “Decipher genomic classifier” and “Decipher”. Websites for Decipher6 and GenomeDx8 were also reviewed to identified additional published and unpublished information. No trial registries were searched, which is a possible limitation.

PubMed search strategy:

((classifier[tiab]) AND ((genomic*[tiab]) OR (genome*[tiab]))) AND ((prostate[tiab] OR prostatic[tiab] OR (prostatic neoplasm[mesh]) OR (biochemical recurrence[tiab]))

Published Reviews, Recommendations, and Guidelines

No published reviews, recommendations or guidelines describing the Decipher genomic classifier were identified from the methods described above. One local coverage decision from Palmetto GBA was identified providing limited coverage for Decipher in order to determine which patients at high-risk of recurrence following RP should receive radiation therapy vs. continued observation.9

Analytic Validity

Data reported in a conference abstract10 showed RNA was successfully extracted from 91% (63/69) FFPE biopsies and 100% (69/69) of RP tissue samples, and 98% (62/63) and 99% (68/69) of the FFPE and RP samples passed gene-expression data quality control, respectively. In this study, the correlation between matched biopsy FFPE tissue and RP tissue samples in the genomic classifier scores predicting metastasis was 0.74 (p=0.0003).

Two other studies are listed on the Decipher website under ‘Analytic Validity’,11,12 but it is unclear whether the methods and procedures described in these reports are integrated into the Decipher analytic pipeline.

Clinical Validity

Eight published studies were identified evaluating the clinical validity of the genomic classifier, based on its ability to predict clinical metastasis13,14,15,16,17,18,19,20. The first study used data from a Mayo Clinic patient registry to compare men with evidence of clinical metastasis following RP (cases) to men with no evidence of metastasis after RP (controls) with median follow-up greater than five years. One publication reported results from the initial training and validation datasets in which participants with no evidence of disease recurrence and those with biochemical recurrence (PSA > 0.20 ng/ml within 30 days of RP) served as controls due to “very limited differential expression” between these two groups.16 Therefore, the genomic classifier was developed to discriminate men who develop clinical metastasis from men who have no evidence of disease recurrence (clinical or biochemical) within five years of RP. Two additional studies using data from the Mayo Clinic registry described subsequent validation of the genomic classifier in men with biochemical recurrence after RP19 and in men with high-risk prostate cancer (pre-RP PSA > 20ng/mL, Gleason score > 8, pT3b, or Mayo Clinic nomogram score > 10).17

Overall, the genomic classifier had good discriminatory ability (e.g. ability to predict clinical metastasis) in both the discovery and validation studies (Table 1). Across the nine analyses, the area under the receiver operating curve (AUC) ranged between 0.75 and 0.90. None of the studies examining the predictive accuracy of the genomic classifier explicitly reported whether the gene-expression analysis was performed on tissue collected at the time of surgery or at the time of clinical end point (e.g. metastasis). There was potential overlap in participants used to develop and validate the genomic classifier across four studies interrogating a patient registry13,16,17,19. In three full-text validation studies16,17,19 there were noticeable differences between cases and controls in the frequency of high-risk pathological features, risk factors for metastasis, and adjuvant and salvage therapy (Table 2). The possibility of confounding due to these differences may have yielded an overestimate of the prognostic ability of the genomic classifier. Another limitation is the change in risk of metastasis with more follow up time. The 5-year risk of metastasis among men with biochemical recurrence is only 4%, whereas the 10- and 15-year risk increases dramatically (11% and 19%)21, suggesting the genomic classifier may lead to false-negative results for those men who experience metastasis beyond five years. In terms of prostate cancer-specific mortality, one study reported an AUC of 0.78 (95% CI: 0.68 to 0.87) among high-risk patients13. In a group of men treated with adjuvant radiation therapy, the AUC for metastasis was 0.83 (95% CI: 0.27 to 0.89).15

A conference abstract22 reported that the genomic classifier could predict metastasis in a subset of prostate cancer tumors with ETS gene overexpression, PTEN-loss, or both very well. Among the tumors with ETS gene overexpression and PTEN loss the genomic classifier had an AUC of 0.82 and 0.85, respectively. In tumors with both ETS overexpression and PTEN loss, the AUC was 0.85.

The cumulative incidence of metastasis five years after RP was 2.4%, 6.0%, and 22.5% for the low, intermediate, and high risk groups defined by the genomic classifier respectively17 and 0%, 12%, 17% eight years after RP14 and 12%, 31% and 47% 10 years after RP for the same three risk groups respectively20.

Table 1: Performance characteristics of the genomic classifier

Table1

Table 2: Participant characteristics in clinical validation studies

Table2

Clinical Utility

No direct evidence for clinical utility for the genomic classifier is currently available showing changes in selection of primary or adjuvant treatment based on the genomic classifier or showing that the genomic classifier can successfully predict treatment outcomes. There is only limited evidence of clinical utility from four publications23,24,25,26 and one conference abstract27 comparing physician’s treatment recommendations before and after knowledge of the results from the genomic classifier. Study investigators recruited physicians to review the medical records of selected patients from an actual practice with high-risk prostate cancer in the adjuvant setting (no evidence of biochemical recurrence after RP) and salvage setting (evidence of biochemical recurrence after RP). Physicians were asked to make treatment recommendations based on their reviews. The overall change in treatment recommendations, after asking physicians to consider the scores from the genomic classifier, ranged between 31% and 43% in the adjuvant setting and 53% in the salvage setting (Table 3). The change from no treatment (observation) to any therapy ranged from 8% to 38%, and from any treatment to no treatment ranged from 27% to 52%. All study reports included case histories of high-risk prostate cancer in which the most significant change in treatment recommendations was from any adjuvant therapy to no treatment. These studies provide indirect evidence that only suggests some potential for the genomic classifier to achieve clinical utility.

Table 3: Change in treatment recommendation in high-risk prostate cancer based on knowledge of the genomic classifier

Table3

Conclusions

The recently introduced genomic classifier was developed to identify men with increased risk for metastatic prostate cancer following radical prostatectomy. The genomic classifier was shown to have good discrimination in detecting men at risk for metastatic prostate cancer five years after surgery (AUC 0.75 to 0.90). However, these estimates may be biased given differences in important prognostic characteristics between cases and controls. Independent validation in patients with high-risk prostate cancer may provide more reliable estimates of the prognostic ability of the genomic classifier. At this time it is unclear what the most appropriate clinical actions are based on test results. No studies yet published have reported the ability of the genomic classifier to predict significant clinical outcomes from any of the available adjuvant therapies. In order to demonstrate clinical utility additional evidence is needed showing improved outcomes (clinical metastasis or prostate cancer-specific mortality) in men whose post-operative treatment was guided by the genomic classifier compared to standard practice.

Competing Interests

The authors have declared that no competing interests exist. The findings and conclusions are those of authors, including NIH co-authors, and do not necessarily represent the views of the National Institutes of Health (NIH). The information provided in this manuscript does not constitute an endorsement of any of the commercially available tests described in this report by NIH nor the Department of Health and Human Services of the U.S. government.

References Eggener SE, Scardino PT, Walsh PC, Han M, Partin AW, Trock BJ, Feng Z, Wood DP, Eastham JA, Yossepowitch O, Rabah DM, Kattan MW, Yu C, Klein EA, Stephenson AJ. Predicting 15-year prostate cancer specific mortality after radical prostatectomy. J Urol. 2011 Mar;185(3):869-75. PubMed PMID:21239008. 21239008 Pound CR, Partin AW, Eisenberger MA, Chan DW, Pearson JD, Walsh PC. Natural history of progression after PSA elevation following radical prostatectomy. JAMA. 1999 May 5;281(17):1591-7. PubMed PMID:10235151. 10235151 Freedland SJ, Humphreys EB, Mangold LA, Eisenberger M, Dorey FJ, Walsh PC, Partin AW. Risk of prostate cancer-specific mortality following biochemical recurrence after radical prostatectomy. JAMA. 2005 Jul 27;294(4):433-9. PubMed PMID:16046649. 16046649 NCCN Guidelines for patients - prostate cancer.1.2014. Nielsen ME, Trock BJ, Walsh PC. Salvage or adjuvant radiation therapy: counseling patients on the benefits. J Natl Compr Canc Netw. 2010 Feb;8(2):228-37. PubMed PMID:20141679. 20141679 Decipher prostate cancer classifier. http://deciphertest.com/. Accessed July, 2015 Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014 Jan-Feb;64(1):9-29. PubMed PMID:24399786. 24399786 GenomeDx Biosciences. http://genomedx.com/. Accessed July, 2015. Centers for Medicare & Medicaid Services. MolDX: Decpiher Prostate Cancer Classifier Assay. Local coverage document (L35650). Medicare Coverage Database (https://www.cms.gov/medicare-coverage-database/overview-and-quick-search.aspx?CoverageSelection=Local&ArticleType=All&PolicyType=Final&s=All&KeyWord=decipher&KeyWordLookUp=Title&KeyWordSearchType=And&bc=gAAAAAAAAAAAAA%3d%3d&=&). Accessed August 2015 Knudsen B, Simko JP, Lam LL, et al. Transcriptome-wide analysis of matched biopsy and prostatectomy to measure genomic classifiers of prostate cancer progression and field effect. J Clin Oncol. 2014;32(suppl 4). Abdueva D, Wing M, Schaub B, Triche T, Davicioni E. Quantitative expression profiling in formalin-fixed paraffin-embedded samples by affymetrix microarrays. J Mol Diagn. 2010 Jul;12(4):409-17. PubMed PMID:20522636. 20522636 Erho N, Buerki C, Triche TJ, Davicioni E, Vergara IA. Transcriptome-wide detection of differentially expressed coding and non-coding transcripts and their clinical significance in prostate cancer. J Oncol. 2012;2012:541353. PubMed PMID:22956952. 22956952 Cooperberg MR, Davicioni E, Crisan A, Jenkins RB, Ghadessi M, Karnes RJ. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. Eur Urol. 2015 Feb;67(2):326-33. PubMed PMID:24998118. 24998118 Den RB, Feng FY, Showalter TN, Mishra MV, Trabulsi EJ, Lallas CD, Gomella LG, Kelly WK, Birbe RC, McCue PA, Ghadessi M, Yousefi K, Davicioni E, Knudsen KE, Dicker AP. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys. 2014 Aug 1;89(5):1038-46. PubMed PMID:25035207. 25035207 Den RB, Yousefi K, Trabulsi EJ, Abdollah F, Choeurng V, Feng FY, Dicker AP, Lallas CD, Gomella LG, Davicioni E, Karnes RJ. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015 Mar 10;33(8):944-51. PubMed PMID:25667284. 25667284 Erho N, Crisan A, Vergara IA, Mitra AP, Ghadessi M, Buerki C, Bergstralh EJ, Kollmeyer T, Fink S, Haddad Z, Zimmermann B, Sierocinski T, Ballman KV, Triche TJ, Black PC, Karnes RJ, Klee G, Davicioni E, Jenkins RB. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8(6):e66855. PubMed PMID:23826159. 23826159 Karnes RJ, Bergstralh EJ, Davicioni E, Ghadessi M, Buerki C, Mitra AP, Crisan A, Erho N, Vergara IA, Lam LL, Carlson R, Thompson DJ, Haddad Z, Zimmermann B, Sierocinski T, Triche TJ, Kollmeyer T, Ballman KV, Black PC, Klee GG, Jenkins RB. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. 2013 Dec;190(6):2047-53. PubMed PMID:23770138. 23770138 Klein EA, Yousefi K, Haddad Z, Choeurng V, Buerki C, Stephenson AJ, Li J, Kattan MW, Magi-Galluzzi C, Davicioni E. A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. Eur Urol. 2015 Apr;67(4):778-86. PubMed PMID:25466945. 25466945 Ross AE, Feng FY, Ghadessi M, Erho N, Crisan A, Buerki C, Sundi D, Mitra AP, Vergara IA, Thompson DJ, Triche TJ, Davicioni E, Bergstralh EJ, Jenkins RB, Karnes RJ, Schaeffer EM. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014 Mar;17(1):64-9. PubMed PMID:24145624. 24145624 Ross AE, Johnson MH, Yousefi K, Davicioni E, Netto GJ, Marchionni L, Fedor HL, Glavaris S, Choeurng V, Buerki C, Erho N, Lam LL, Humphreys EB, Faraj S, Bezerra SM, Han M, Partin AW, Trock BJ, Schaeffer EM. Tissue-based Genomics Augments Post-prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men. Eur Urol. 2015 Jun 6. PubMed PMID:26058959. 26058959 Han M, Partin AW, Zahurak M, Piantadosi S, Epstein JI, Walsh PC. Biochemical (prostate specific antigen) recurrence probability following radical prostatectomy for clinically localized prostate cancer. J Urol. 2003 Feb;169(2):517-23. PubMed PMID:12544300. 12544300 Alshalalfa M, Vergara IA, Erho N, Davicioni E, Jenkins RB, Kollmeyer T. Evaluation of a genomic classifier (Decipher®) in subsets of primary tumors with common prostate cancer genomic alterations. AACR Annual Meeting; April 5-9, 2014; San Diego, CA Badani K, Thompson DJ, Buerki C, Davicioni E, Garrison J, Ghadessi M, Mitra AP, Wood PJ, Hornberger J. Impact of a genomic classifier of metastatic risk on postoperative treatment recommendations for prostate cancer patients: a report from the DECIDE study group. Oncotarget. 2013 Apr;4(4):600-9. PubMed PMID:23592338. 23592338 Badani KK, Thompson DJ, Brown G, Holmes D, Kella N, Albala D, Singh A, Buerki C, Davicioni E, Hornberger J. Effect of a genomic classifier test on clinical practice decisions for patients with high-risk prostate cancer after surgery. BJU Int. 2015 Mar;115(3):419-29. PubMed PMID:24784420. 24784420 Michalopoulos SN, Kella N, Payne R, Yohannes P, Singh A, Hettinger C, Yousefi K, Hornberger J. Influence of a genomic classifier on post-operative treatment decisions in high-risk prostate cancer patients: results from the PRO-ACT study. Curr Med Res Opin. 2014 Aug;30(8):1547-56. PubMed PMID:24803160. 24803160 Nguyen PL, Shin H, Yousefi K, Thompson DJ, Hornberger J, Hyatt AS, Badani KK, Morgan TM, Feng FY. Impact of a Genomic Classifier of Metastatic Risk on Postprostatectomy Treatment Recommendations by Radiation Oncologists and Urologists. Urology. 2015 Jul;86(1):35-40. PubMed PMID:26142578. 26142578 Badani KK, Thompson DJ, Buerki C, Singh A. Effect of a genomic classifier on adjuvant radiation recommendations after prostate cancer surgery. J Clin Oncol. 2014;32(suppl 4).