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
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Most commercially available tissue-based genomic assays, including Oncotype DX, Prolaris, and Decipher, are based on RNA expression profiling and quantify gene activity associated with proliferation, androgen receptor signaling, and metastatic potential.
“Most commercially available assays, including Oncotype DX, Prolaris, and Decipher, are based on RNA expression profiling and quantify gene activity associated with proliferation, androgen receptor signaling, and metastatic potential [4, 11–13].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [12]
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Experimental — accuracy not yet measuredOncotype DX and Prolaris are primarily validated in biopsy tissue to inform initial risk stratification and decision-making between active surveillance and definitive treatment.
“Oncotype DX and Prolaris are primarily validated in biopsy tissue to inform initial risk stratification and decision-making between active surveillance and definitive treatment [11–13].”
From A decision-oriented framework for genomic testing across the prostate cancer continuum (2026) · cites this paper as [12]
The Conclusions (p. 131) validate the biopsy-based Genomic Prostate Score for risk assessment to guide treatment decisions in men with newly diagnosed prostate cancer. The Introduction (p. 123) frames active surveillance as an alternative to immediate therapy. But this study does not validate Prolaris in biopsy tissue for that decision; the Discussion (p. 129) mentions a 46-gene cell-cycle signature only in relation to longer-term outcomes and says only GPS had been validated to predict adverse pathology. (LLM, conf=0.88)
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Cites
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674 · see citing works
Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/dji237 · Cited by 2,162 · see citing works
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Research works printed but not linked: 24
- Dall'Era MA, Albertsen PC, Bangma C, et al. Active surveillance for prostate cancer: a systematic review of the literature. Eur Urol 2012;62:976-83.
- Conti SL, Dall'era M, Fradet V, Cowan JE, Simko J, Carroll PR. Pathological outcomes of candidates for active surveillance of prostate cancer. J Urol 2009;181:1628-33.
- Mu ¨ntener M, Epstein JI, Hernandez DJ, et al. Prognostic significance of Gleason score discrepancies between needle biopsy and radical prostatectomy. Eur Urol 2008;53:767-75.
- van den Bergh RC, Ahmed HU, Bangma CH, Cooperberg MR, Villers A, Parker CC. Novel tools to improve patient selection and moni- toring on active surveillance for low-risk prostate cancer: a sys- tematic review. Eur Urol 2014;65:1023-31.
- Sartori DA, Chan DW. Biomarkers in prostate cancer: what's new? Curr Opin Oncol 2014;26:259-64.
- Simon RM, Paik S, Hayes DF. Use of archived specimens in evalua- tion of prognostic and predictive biomarkers. J Natl Cancer Inst 2009;101:1446-52.
- McShane LM, Hayes DF. Publication of tumor marker research results: the necessity for complete and transparent reporting. J Clin Oncol 2012;30:4223-32.
- Brassell SA, Dobi A, Petrovics G, Srivastava S, McLeod D. The Center for Prostate Disease Research (CPDR): a multidisciplinary approach to translational research. Urol Oncol 2009;27:562-9.
- Epstein JI, Allsbrook Jr WC, Amin MB, Egevad LL, ISUP Grading Committee. The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Car- cinoma. Am J Surg Pathol 2005;29:1228-42.
- Knezevic D, Goddard AD, Natraj N, et al. Analytical validation of the Oncotype DX prostate cancer assay-a clinical RT-PCR assay optimized for prostate needle biopsies. BMC Genomics 2013;14: 690.
- Klein EA, Cooperberg MR, Magi-Galuzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersam- pling. Eur Urol 2014;66:550-60.
- Cookson MS, Aus G, Burnett AL, et al. Variation in the definition of biochemical recurrence in patients treated for localized prostate cancer: the American Urological Association Prostate Guidelines for Localized Prostate Cancer Update Panel report and recommenda- tions for a standard in the reporting of surgical outcomes. J Urol 2007;177:540-5.
- Preston MA, Carrie `re M, Raju G, et al. The prognostic significance of capsular incision into tumor during radical prostatectomy. Eur Urol 2011;59:613-8.
- Therneau TM, Grambsch PM, Fleming TR. Martingale-based resi- duals for survival models. Biometrika 1990;77:147-60.
- Freedland SJ, Humphreys EB, Mangold LA, et al. Risk of prostate cancer-specific mortality following biochemical recurrence after radical prostatectomy. JAMA 2005;294:433-9.
- Davis JW. Novel commercially available genomic tests for prostate cancer: a roadmap to understanding their clinical impact. BJU Int 2014;114:320-2.
- Badani KK, Kemeter MJ, Febbo PG, et al. The impact of a biopsy- based 17-gene Genomic Prostate Score on treatment recommen- dations for men with newly diagnosed clinically prostate cancer who are candidates for active surveillance. Urol Pract. In press. http://dx.doi.org/10.1016/j.urpr.2014.10.010 · DOI
- Farrell J, Petrovics G, McLeod DG, Srivastava S. Genetic and molec- ular differences in prostate carcinogenesis between African Ameri- can and Caucasian American men. Int J Mol Sci 2013;14:15510-31.
- Rosen P, Pfister D, Young D, et al. Differences in frequency of ERG oncoprotein expression between index tumors of Caucasian and African American patients with prostate cancer. Urology 2012;80: 749-53.
- Khani F, Mosquera JM, Park K, et al. Evidence for molecular differ- ences in prostate cancer between African American and Caucasian men. Clin Cancer Res 2014;20:4925-34.
- Powell IJ, Dyson G, Land S, et al. Genes associated with prostate cancer are differentially expressed in African American and Euro- pean American men. Cancer Epidemiol Biomarkers Prev 2013;22: 891-7.
- Platz EA, Rimm EB, Willett WC, Kantoff PW, Giovannucci E. Racial variation in prostate cancer incidence and in hormonal system markers among male health professionals. J Natl Cancer Inst 2000;92:2009-17.
- Schlomm T, Hellwinkel OJ, Buness A, et al. Molecular cancer phe- notype in normal prostate tissue. Eur Urol 2009;55:885-90.
- Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144:646-74.
Cited by
Sorted by citations
Phenotype prediction from single-cell RNA-seq data using attention-based neural networks
Mao, Y., Lin, Y.-Y., Wong, N. K. Y., Volik, S., Sar, F., Collins, C., & Ester, M. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae067 · Cited by 31 · see citing works
A decision-oriented framework for genomic testing across the prostate cancer continuum
Cobran, E. K., Samadder, N. J., Schaid, D. J., Conti, D. V., Haiman, C., Vargas, L., Gionfriddo, M. R., & Tilburt, J. C. (2026) · Cancer Genetics · doi:10.1016/j.cancergen.2026.06.002 · Cited by 1 · see citing works
- Authors
- Cullen, J., Rosner, I. L., Brand, T. C., Zhang, N., Tsiatis, A. C., Moncur, J., Ali, A., Chen, Y., Knezevic, D., Maddala, T., Lawrence, H. J., Febbo, P. G., Srivastava, S., Sesterhenn, I. A., & McLeod, D. G.
- Venue
- European Urology
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 68
- Issue
- 1
- Pages
- 123-131
- ISSN
- 0302-2838
- Cited by
- 278
- References
- 2
- Language
- en
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