Evaluation of protein biomarkers of prostate cancer aggressiveness

Anthony E. Rizzardi, Nikolaus K. Rosener, Joseph S. Koopmeiners, Rachel Isaksson Vogel, Gregory J. Metzger, Colleen L. Forster, Lauren O. Marston, Jessica R. Tiffany, James B. McCarthy, Eva A. Turley, Christopher A. Warlick, Jonathan C. Henriksen, Stephen C. Schmechel

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Background: Prognostic multibiomarker signatures in prostate cancer (PCa) may improve patient management and provide a bridge for developing novel therapeutics and imaging methods. Our objective was to evaluate the association between expression of 33 candidate protein biomarkers and time to biochemical failure (BF) after prostatectomy.Methods: PCa tissue microarrays were constructed representing 160 patients for whom clinicopathologic features and follow-up data after surgery were available. Immunohistochemistry for each of 33 proteins was quantified using automated digital pathology techniques. Relationships between clinicopathologic features, staining intensity, and time to BF were assessed. Predictive modeling using multiple imputed datasets was performed to identify the top biomarker candidates.Results: In univariate analyses, lymph node positivity, surgical margin positivity, non-localized tumor, age at prostatectomy, and biomarkers CCND1, HMMR, IGF1, MKI67, SIAH2, and SMAD4 in malignant epithelium were significantly associated with time to BF. HMMR, IGF1, and SMAD4 remained significantly associated with BF after adjusting for clinicopathologic features while additional associations were observed for HOXC6 and MAP4K4 following adjustment. In multibiomarker predictive models, 3 proteins including HMMR, SIAH2, and SMAD4 were consistently represented among the top 2, 3, 4, and 5 most predictive biomarkers, and a signature comprised of these proteins best predicted BF at 3 and 5 years.Conclusions: This study provides rationale for investigation of HMMR, HOXC6, IGF1, MAP4K4, SIAH2, and SMAD4 as biomarkers of PCa aggressiveness in larger cohorts.

Original languageEnglish (US)
Article number244
JournalBMC Cancer
Issue number1
StatePublished - Apr 5 2014

Bibliographical note

Funding Information:
This work was supported by NIH grants R01-CA119092 (JBM, EAT), R01-CA131013 (GJM), University of Minnesota (UMN) Chairman’s Fund Endowed Chair in Cancer Biology (JBM), UMN Biostatistics and BioNet core facilities (supported by P30-CA77598, P50-CA101955, KL2-RR033182, UMN Academic Health Center), Fred Hutchinson/University of Washington Cancer Consortium’s Northwest BioTrust core facility (supported by P30-CA015704), UMN Department of Laboratory Medicine and Pathology, and University of Washington Department of Pathology (SCS). The authors thank Dr. Timothy Schacker (supported by NIH grants P01-AI074340, R01-AI093319) for providing computer resources used in this study.


  • Aggressiveness
  • Biomarker
  • Prostate cancer
  • Signature


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