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Validation of protein biomarker signatures of prostate cancer aggressiveness

Principal Investigator
Name
Stephen Schmechel
Degrees
-
Institution
University of Minnesota
Position Title
-
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
2012-0286
Initial CDAS Request Approval
Oct 22, 2012
Title
Validation of protein biomarker signatures of prostate cancer aggressiveness
Summary
Recently published clinical trials have highlighted concerns about overtreatment of men with PCa identified by PSA screening and biopsy since many patients may have indolent tumors that would never produce clinical signs or symptoms even if untreated [1-5]. Well-validated prognostic biomarkers may facilitate discrimination between tumors likely to have indolent versus aggressive biologic behavior. In addition to being used to triage patients to precise therapies directed by an estimate of PCa aggressiveness, validated biomarkers may be used immediately as gold standards in development of MR methods to assess PCa aggressiveness preoperatively in vivo. We have used computer-aided IHC analysis on a UMN cohort of 170 PCa patients to short-list 16 promising biomarkers of PCa aggressiveness. We hypothesize that an n-biomarker (n less than or equal to 16) signature assessed at the protein level by IHC will predict PCa aggressiveness (shorter time to PSA failure) after prostatectomy. Our study has two specific aims: (1) to perform IHC using antibodies directed against 16 strong candidate prognostic biomarkers (CCND1, CD34, CD44, CD44v6, CHGA, HA, HAS2, HMMR, HOXC6, IGF1, IQCK, MAP4K4, MKI67, PAGE4, SIAH2, and SMAD4) on the large and appropriately powered (greater than 720-patient) PLCO cohort and quantify the IHC staining intensity using computer-aided methods previously developed, and (2) to develop and test the prognostic capabilities of an n-biomarker signature of PCa aggressiveness. A validated multi-biomarker signature will be immediately useful in NCI-funded work to develop MR methods to assess PCa aggressiveness preoperatively in vivo.
Aims

Although prostate cancer (PCa) is the most commonly diagnosed non-cutaneous cancer of men in the United States, few prognostic biomarkers are in routine clinical use. Biomarkers to predict the risk of disease aggressiveness leading to prostate specific antigen (PSA) failure after prostatectomy may assist clinicians in selecting adjuvant therapies following prostatectomy. Further, validated prognostic biomarkers will be highly useful as gold standard against which to develop non-invasive imaging methods to assess disease preoperatively. We hypothesize that a multiplexed biomarker signature assessed at the protein level by immunohistochemistry (IHC) will be prognostic of PCa aggressiveness (shorter time to PSA failure) after prostatectomy. After analysis of multiple gene expression datasets and current literature, we identified 33 potentially prognostic biomarkers. Using tissue microarrays (TMAs) containing PCa tissue from prostatectomy specimens of 170 UMN patients and quantifying IHC expression using computer-aided methods, we short-listed 16 strong candidate biomarkers from among these 33, based on significant association with time to PSA failure or frequent (greater than or equal to 80%) presence in simulated models predicting time to PSA failure. Using an appropriately powered (greater than 720 patient) PLCO TMA cohort of PCa tissues from prostatectomy specimens with long-term detailed PSA follow-up, we aim to develop and validate an optimized n-biomarker (n less than or equal to 16) signature of PCa aggressiveness. Funding for this project is provided by NCI R01-CA131013 (PI: G. Metzger) and departmental funds (PI: S. Schmechel). In parallel, Dr. Metzger has generated whole organ, preoperative MR spectroscopy datasets from 50+ patients. Drs. Schmechel, Metzger, and colleagues have produced software tools to construct multi-biomarker IHC signature maps throughout tumor areas in virtually reconstructed (from pathology slides) prostatectomy specimens. By co-registration of preoperative MR data to postoperative pathology data including IHC signature map data, our results will be immediately useful as a gold standard against which to assess MR methods to survey PCa aggressiveness preoperatively in vivo.

Collaborators

Joseph Koopmeiners (University of Minnesota)
Jim McCarthy (University of Minnesota)
Gregory Metzger (University of Minnesota)
Rachel Isaksson Vogel (University of Minnesota)
Sarah Daugherty (Division of Cancer Epidemiology and Genetics)