Cited by 179Prostate Cancer Diagnosis and TreatmentProstate Cancer Treatment and ResearchBreast Cancer Treatment Studies

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Development and Clinical Validation of an In Situ Biopsy-Based Multimarker Assay for Risk Stratification in Prostate Cancer

Published version of a preprint

Abstract

Purpose: Prostate cancer aggressiveness and appropriate therapy are routinely determined following biopsy sampling. Current clinical and pathologic parameters are insufficient for accurate risk prediction leading primarily to overtreatment and also missed opportunities for curative therapy. Experimental Design: An 8-biomarker proteomic assay for intact tissue biopsies predictive of prostate pathology was defined in a study of 381 patient biopsies with matched prostatectomy specimens. A second blinded study of 276 cases validated this assay's ability to distinguish “favorable” versus “nonfavorable” pathology independently and relative to current risk classification systems National Comprehensive Cancer Network (NCCN and D'Amico). Results: A favorable biomarker risk score of ≤0.33, and a nonfavorable risk score of >0.80 (possible range between 0 and 1) were defined on “false-negative” and “false-positive” rates of 10% and 5%, respectively. At a risk score ≤0.33, predictive values for favorable pathology in very low-risk and low-risk NCCN and low-risk D'Amico groups were 95%, 81.5%, and 87.2%, respectively, higher than for these current risk classification groups themselves (80.3%, 63.8%, and 70.6%, respectively). The predictive value for nonfavorable pathology was 76.9% at biomarker risk scores >0.8 across all risk groups. Increased biomarker risk scores correlated with decreased frequency of favorable cases across all risk groups. The validation study met its two coprimary endpoints, separating favorable from nonfavorable pathology (AUC, 0.68; P < 0.0001; OR, 20.9) and GS-6 versus non–GS-6 pathology (AUC, 0.65; P < 0.0001; OR, 12.95). Conclusions: The 8-biomarker assay provided individualized, independent prognostic information relative to current risk stratification systems, and may improve the precision of clinical decision making following prostate biopsy. Clin Cancer Res; 21(11); 2591–600. ©2015 AACR.

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Research works printed but not linked: 33

  1. Siegel, 2014, Cancer statistics, 2014, CA Cancer J Clin, 64, 9, 10.3322/caac.21208 · DOI · Paper page
  2. Epstein, 2010, An update of the Gleason grading system, J Urol, 183, 433, 10.1016/j.juro.2009.10.046 · DOI
  3. Barocas, 2008, What percentage of patients with newly diagnosed carcinoma of the prostate are candidates for surveillance? An analysis of the CaPSURE database, J Urol, 180, 1330, 10.1016/j.juro.2008.06.019 · DOI
  4. Loeb, 2014, Overdiagnosis and overtreatment of prostate cancer, Eur Urol, 65, 1046, 10.1016/j.eururo.2013.12.062 · DOI
  5. Sandhu, 2012, Overdiagnosis of prostate cancer, J Natl Cancer Inst Monogr, 2012, 146, 10.1093/jncimonographs/lgs031 · DOI
  6. D'Amico, 1998, Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer, JAMA, 280, 969, 10.1001/jama.280.11.969 · DOI
  7. Bangma, 2012, Defining and predicting indolent and low risk prostate cancer, Crit Rev Oncol Hematol, 83, 235, 10.1016/j.critrevonc.2011.10.003 · DOI
  8. Brimo, 2013, Contemporary grading for prostate cancer: implications for patient care, Eur Urol, 63, 892, 10.1016/j.eururo.2012.10.015 · DOI
  9. Truong, 2013, Development and multi-institutional validation of an upgrading risk tool for Gleason 6 prostate cancer, Cancer, 119, 3992, 10.1002/cncr.28303 · DOI
  10. Epstein, 2012, Upgrading and downgrading of prostate cancer from biopsy to radical prostatectomy: incidence and predictive factors using the modified Gleason grading system and factoring in tertiary grades, Eur Urol, 61, 1019, 10.1016/j.eururo.2012.01.050 · DOI
  11. Pinthus, 2006, Prostate cancers scored as Gleason 6 on prostate biopsy are frequently Gleason 7 tumors at radical prostatectomy: implication on outcome, J Urol, 176, 979, 10.1016/j.juro.2006.04.102 · DOI
  12. Porten, 2011, Changes in prostate cancer grade on serial biopsy in men undergoing active surveillance, J Clin Oncol, 29, 2795, 10.1200/JCO.2010.33.0134 · DOI
  13. Goodman, 2012, Frequency and determinants of disagreement and error in gleason scores: a population-based study of prostate cancer, Prostate, 72, 1389, 10.1002/pros.22484 · DOI
  14. Eggener, 2011, Predicting 15-year prostate cancer specific mortality after radical prostatectomy, J Urol, 185, 869, 10.1016/j.juro.2010.10.057 · DOI
  15. Ross, 2012, Do adenocarcinomas of the prostate with Gleason score (GS) </ = 6 have the potential to metastasize to lymph nodes?, Am J Surg Pathol, 36, 1346, 10.1097/PAS.0b013e3182556dcd · DOI
  16. Stark, 2009, Gleason score and lethal prostate cancer: does 3 + 4 = 4 + 3?, J Clin Oncol, 27, 3459, 10.1200/JCO.2008.20.4669 · DOI
  17. Cooperberg, 2013, Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort, J Clin Oncol, 31, 1428, 10.1200/JCO.2012.46.4396 · DOI
  18. Cuzick, 2012, Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort, Br J Cancer, 106, 1095, 10.1038/bjc.2012.39 · DOI
  19. Donovan, 2008, Systems pathology approach for the prediction of prostate cancer progression after radical prostatectomy, J Clin Oncol, 26, 3923, 10.1200/JCO.2007.15.3155 · DOI
  20. Ding, 2011, SMAD4-dependent barrier constrains prostate cancer growth and metastatic progression, Nature, 470, 269, 10.1038/nature09677 · DOI
  21. Shipitsin, 2014, Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error, Br J Cancer, 111, 1201, 10.1038/bjc.2014.396 · DOI
  22. Shipitsin, 2014, Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality, Proteome Sci, 12, 40, 10.1186/1477-5956-12-40 · DOI
  23. Pierorazio, 2013, Prognostic Gleason grade grouping: data based on the modified Gleason scoring system, BJU Int, 111, 753, 10.1111/j.1464-410X.2012.11611.x · DOI
  24. Mullins, 2012, The impact of anatomical radical retropubic prostatectomy on cancer control: the 30-year anniversary, J Urol, 188, 2219, 10.1016/j.juro.2012.08.028 · DOI
  25. Pencina, 2008, Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond, Stat Med, 27, 157, 10.1002/sim.2929 · DOI · Paper page
  26. Dowsett, 2010, Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study, J Clin Oncol, 28, 1829, 10.1200/JCO.2009.24.4798 · DOI
  27. Vickers, 2006, Decision curve analysis: a novel method for evaluating prediction models, Med Decis Making, 26, 565, 10.1177/0272989X06295361 · DOI · Paper page
  28. Graefen, 2005, Reasonable delay of surgical treatment in men with localized prostate cancer—impact on prognosis?, Eur Urol, 47, 756, 10.1016/j.eururo.2005.02.004 · DOI
  29. Holmstrom, 2010, Outcome of primary versus deferred radical prostatectomy in the National Prostate Cancer Register of Sweden Follow-Up Study, J Urol, 184, 1322, 10.1016/j.juro.2010.06.008 · DOI
  30. Vickers, 2006, Does a delay between diagnosis and radical prostatectomy increase the risk of disease recurrence?, Cancer, 106, 576, 10.1002/cncr.21643 · DOI
  31. Klein, 2014, A 17-gene assay to predict prostate cancer aggressiveness in the context of gleason grade heterogeneity, tumor multifocality, and biopsy undersampling, Eur Urol, 66, 550, 10.1016/j.eururo.2014.05.004 · DOI
  32. Cullen, 2014 29, 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
  33. Crawford, 2014, Cell cycle progression score and treatment decisions in prostate cancer: results from an ongoing registry, Curr Med Res Opin, 30, 1025, 10.1185/03007995.2014.899208 · DOI

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Metadata

Authors
Blume-Jensen, P., Berman, D. M., Rimm, D. L., Shipitsin, M., Putzi, M., Nifong, T. P., Small, C., Choudhury, S., Capela, T., Coupal, L., Ernst, C., Hurley, A., Kaprelyants, A., Chang, H., Giladi, E., Nardone, J., Dunyak, J., Loda, M., Klein, E. A., Magi-Galluzzi, C., Latour, M., Epstein, J. I., Kantoff, P., & Saad, F.
Affiliations
  • 1Metamark Genetics Inc., Cambridge, Massachusetts.
  • Queen's University (CA)
  • Yale University (US)
  • 4Urology Austin, Austin, Texas.
  • 5Impacts Inc., Montreal, Quebec, Canada.
  • Dana-Farber Cancer Institute (US)
  • Cleveland Clinic (US)
  • 8Department of Anatomic Pathology, Cleveland Clinic, Cleveland, Ohio.
  • Centre Hospitalier de l’Université de Montréal (CA)
  • Johns Hopkins University (US)
  • 9Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada.
Venue
Clinical Cancer Research
Published
2015-05-31
Volume
21
Issue
11
Pages
2591-2600
ISSN
  • 1078-0432 (ISSN-L)
  • 1557-3265
OpenAlex
W2025795030
Cited by
179
References
0
Citations by year
2026: 8 · 2025: 6 · 2024: 12 · 2023: 8 · 2022: 23 · 2021: 18 · 2020: 14 · 2019: 19 · 2018: 13 · 2017: 27 · 2016: 24 · 2015: 6
FWCI
21.62
Type
journal article
Language
en
Open access
closed
Locations
  • Clinical Cancer Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Comprehensive Cancer Network
  • National Cancer Institute (P30CA008748)
Topics
  • Health Sciences › Medicine › Urology › Prostate Cancer Diagnosis and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Prostate Cancer Treatment and Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
prostate cancer, risk stratification, proteomic biomarkers, prostate pathology, Gleason score, NCCN risk classification, D'Amico risk classification, prognostic factors, overtreatment, prostatectomy specimens
MeSH terms
Aged, Humans, Male, Middle Aged, Neoplasm Recurrence, Local, Prognosis, Prostatectomy, Prostatic Neoplasms, Biomarkers, Tumor, Gene Expression Regulation, Neoplastic, Prostate-Specific Antigen, Risk Assessment, Proteomics

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