51
|
Blume-Jensen P, Berman DM, Rimm DL, Shipitsin M, Putzi M, Nifong TP, 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 EA, Magi-Galluzzi C, Latour M, Epstein JI, Kantoff P, Saad F. Development and clinical validation of an in situ biopsy-based multimarker assay for risk stratification in prostate cancer. Clin Cancer Res 2015; 21:2591-600. [PMID: 25733599 DOI: 10.1158/1078-0432.ccr-14-2603] [Citation(s) in RCA: 120] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 02/19/2015] [Indexed: 11/16/2022]
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.
Collapse
Affiliation(s)
| | - David M Berman
- Department of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada
| | - David L Rimm
- Department of Pathology, Yale University Medical School, New Haven, Connecticut
| | | | | | | | | | | | | | | | | | - Aeron Hurley
- Metamark Genetics Inc., Cambridge, Massachusetts
| | | | - Hua Chang
- Metamark Genetics Inc., Cambridge, Massachusetts
| | - Eldar Giladi
- Metamark Genetics Inc., Cambridge, Massachusetts
| | | | - James Dunyak
- Metamark Genetics Inc., Cambridge, Massachusetts
| | - Massimo Loda
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Eric A Klein
- Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio
| | | | - Mathieu Latour
- Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - Jonathan I Epstein
- Department of Pathology, Urology and Oncology, Johns Hopkins Hospital, Baltimore, Maryland
| | | | - Fred Saad
- Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada.
| |
Collapse
|
52
|
Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br J Cancer 2014; 111:1201-12. [PMID: 25032733 PMCID: PMC4453845 DOI: 10.1038/bjc.2014.396] [Citation(s) in RCA: 104] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2014] [Revised: 06/16/2014] [Accepted: 06/20/2014] [Indexed: 12/11/2022] Open
Abstract
Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a ‘high' and a ‘low' tumour microarray, respectively. Results: Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Conclusions: Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.
Collapse
|