Athens, Greece (Urotoday.com) In this talk, Dr. Tilki reviewed several prognostic biomarkers in the setting of localized prostate cancer management. 

The currently available prognostic biomarkers include: 

  • Oncotype Dx (GPS) 
  • Prolaris 
  • Decipher 
  • Decipher Biopsy 

According to the EAU guidelines, the results of prospective multicenter studies are awaited before a recommendation can be made regarding the routine application of currently available prognostic biomarkers. This means more evidence is required before these biomarkers can be used in a standardized manner. 

The first biomarker discussed was the Oncotype DX (GPS) which has been developed to better understand multiple key biology pathways, and thus improve the prognosis of outcomes. It assesses 12 genes in 4 distinct biological pathways – specific to prostate cancer (Figure 1). The GPS result is a measure of 17 gene expression levels with a score of 0-100. The GPS biomarker adds independent information beyond conventional tools, predicting adverse pathology and biochemical recurrence, after adjusting for clinical risk factors.1 The cost-effectiveness of this biomarker has been performed showing significant savings with its usage. 

Figure 1 – Oncotype Dx (GPS) biomarker genes: 

SIU 2019 Oncotype Dx GPS biomarker genes

Prolaris (Myriad, Inc) is a biomarker-based on 31-gene cell cycle progression (CCP) signature, normalized to 15 housekeeper genes. It used on prostate biopsy tissue (formalin-fixed) and the score is expressed as average center expression of CCP genes relative to housekeeping genes. This means that a negative score = less active CCP, and a positive score = more active CCP.

It has been assessed in prostate cancer-specific death,2 biochemical recurrence (BCR),2,3 and decision making for choice of treatment.4,5

Budget impact analyses showed that the test would add about 41.3 million dollars to provincial health costs over the next 5 years. The relatively small cost savings (7.3 million dollars) due to treatment change was deemed not large enough to offset the high cost of this test.

Decipher was originally developed to predict the risk of metastases. This test does not incorporate any clinical features in predicting individualized risk. It is indicated for patients after radical prostatectomy with adverse pathology features, such as pathological stage T3 or positive margins or biochemical recurrence. It provides an absolute risk of metastases 5 years post-surgery. It is a prognostic 22-gene genomic classifier (GC) that captures multiple biological pathways involved in aggressive prostate cancer. These include cell proliferation, cell structure, immune system modulation, cell cycle progression, and androgen signaling.6 

Decipher GC has been shown to independently predict metastasis and PC-specific mortality in men at high risk of recurrence following radical prostatectomy (RP).7,8

Decipher has also been shown to reclassify 80% of patients reflecting the biological heterogeneity of high-risk prostate cancer7 (Figure 2). It has an AUC 0f 0.79, achieving the highest specificity at any level of sensitivity.7 

Figure 2- Decipher test reclassifies 80% of patients reflecting the biological heterogeneity of high-risk prostate cancer:

SIU 2019 Decipher test

Cost-effectiveness studies have shown that it is more effective and less costly than 100% adjuvant radiation therapy. Cost savings up to an assay cost of 11,402$ have been reported. It has been associated with resulting in a 16% reduction in the percentage of patients with distant metastases at 5 years compared with usual care.

The Decipher score gives a low, intermediate and high- risk score and the distribution of the biopsy Decipher score by NCCN risk groups is shown in Figure 3. Table 1 shows the treatment recommendations according to the Decipher score.

Figure 3 – Distribution of Biopsy Decipher score by NCCN risk groups:

SIU 2019 Distribution of Biopsy Decipher score

Table 1 – Treatment recommendations according to the Decipher score:

SIU 2019 Treatment recommendations

Dr. Tilki concluded her talk stating that it is still unclear how to optimally use these available prognostic biomarkers in daily practice, and how to combine them with novel imaging. It is also still unknown if treatment selection based on these biomarkers will indeed influence progression-free survival, overall survival, or quality of life.

Presented by: Derya Tilki, MD, Associate Professor of Urology, Department of Urology, Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany

Written by: Hanan Goldberg, MD, Urology Department, SUNY Upstate Medical University, Syracuse, New York, USA, Twitter: @GoldbergHanan at the 39th Congress of the Société Internationale d’Urologie, SIU 2019, #SIUWorld #SIU2019, October 17-20, 2019, Athens, Greece    

References:
1. Cullen J, Rosner IL, Brand TC, et al. A Biopsy-based 17-gene Genomic Prostate Score Predicts Recurrence After Radical Prostatectomy and Adverse Surgical Pathology in a Racially Diverse Population of Men with Clinically Low- and Intermediate-risk Prostate Cancer. Eur Urol 2015; 68(1): 123-31.
2. Cuzick J, Swanson GP, Fisher G, et al. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. The Lancet Oncology 2011; 12(3): 245-55.
3. Cooperberg MR, Simko JP, Cowan JE, et al. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2013; 31(11): 1428-34.
4. Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Current medical research and opinion 2014; 30(4): 547-53.
5. Crawford ED, Scholz MC, Kar AJ, et al. Cell cycle progression score and treatment decisions in prostate cancer: results from an ongoing registry. Current medical research and opinion 2014; 30(6): 1025-31.
6. Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PloS one 2013; 8(6): e66855.
7. Karnes RJ, Bergstralh EJ, Davicioni E, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. The Journal of urology 2013; 190(6): 2047-53.
8. Spratt DE, Yousefi K, Deheshi S, et al. Individual Patient-Level Meta-Analysis of the Performance of the Decipher Genomic Classifier in High-Risk Men After Prostatectomy to Predict Development of Metastatic Disease. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2017; 35(18): 1991-8.
9. Lobo JM, Trifiletti DM, Sturz VN, et al. Cost-effectiveness of the Decipher Genomic Classifier to Guide Individualized Decisions for Early Radiation Therapy After Prostatectomy for Prostate Cancer. Clinical genitourinary cancer 2017; 15(3): e299-e309

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