Performance of the Genomic Evaluators of Metastatic
Prostate Cancer (GEMCaP) Tumor Biomarker for Identifying
Recurrent Disease in African American Patients
DNA. We assessed the ability of the biomarker panel Genomic Evaluators of Metastatic Prostate Cancer
(GEMCaP) to predict biochemical recurrence in 33 European American and 28 African American prostate
?20% of the 38 constituent copy number gain/loss GEMCaP loci affected in a given tumor; based on this
threshold, thefrequencyofapositivebiomarkerwassignificantly lowerinAfricanAmericans(n¼2;7%)than
European Americans (n ¼ 11; 33%; P ¼ 0.013). GEMCaP positivity was associated with risk of recurrence
[hazard ratio (HR), 5.92; 95% confidence interval (CI), 2.32–15.11; P ¼ 3 ? 10?4] in the full sample and among
to the low rate of GEMCaP positivity. Overall, the GEMCaP recurrence positive predictive value (PPV) was
85%; in African Americans, PPV was 100%. When we expanded the definition of loss to include copy-neutral
loss of heterozygosity (i.e., loss of one allele with concomitant duplication of the other), recurrence PPV was
83% for European American subjects. Under this definition, 5 African American subjects had a positive
GEMCaP test value; 4 went on to develop biochemical recurrence (PPV ¼ 80%). Our results suggest that the
GEMCaP biomarker set could be an effective predictor for both European American and African American
men diagnosed with localized prostate cancer who may benefit from immediate aggressive therapy after
radical prostatectomy. Cancer Epidemiol Biomarkers Prev; 23(8); 1677–82. ?2014 AACR.
Accurate risk assessment of prostate cancer recurrence
and outcome is vital for men who receive treatment with
curative intent, such as radical prostatectomy. Many risk
models use clinical disease-associated variables to cate-
gorize recurrence risk. Two of the most widely used tools
are a three-level categorization published by D’Amico
and colleagues (1) and a continuous nomogram devised
by Stephenson and colleagues (2) However, concordance
pathologic data alone are insufficient in predicting the
biologic course of a tumor.
Histologically similar prostate cancer may follow dras-
tically different disease courses—better tools are needed
to identify which patients have more aggressive tumors
and should receive adjuvant therapy. We discovered a
suite of DNA-based biomarkers that predict prostate
cancer recurrence and metastasis (4) called the Genomic
Evaluators of Metastatic Prostate Cancer (GEMCaP).
Evaluation of prostate tumors from an independent
cohort of 27 patients found that GEMCaPclassified recur-
rent cases slightly better than the Kattan nomogram (78%
vs. 75%); ref. 5). In a more recent high-risk cohort of 54
patients who received only radical prostatectomy for
initial treatment for localized disease, GEMCaP’s risk
prediction accuracy was slightly higher than that of the
Kattan postoperative nomogram (67% vs. 65%; ref. 6).
More importantly, GEMCaP accurately predicted unfa-
vorable outcomes in lymph node–negative patients that
the nomogram had classified as being at low risk of
African Americans have a higher incidence of prostate
pean Americans (7). Although studies comparing racial
differences in prostate tumor DNA copy number
Authors' Affiliations:1Department of Public Health Sciences, Henry Ford
Health System, Detroit, Michigan;2Department of Epidemiology and Bio-
statistics; and3DepartmentofUrology,HelenDiller FamilyComprehensive
Cancer Center, University of California at San Francisco, San Francisco,
Note: Supplementary data for this article are available at Cancer Epide-
miology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).
A.M. Levin, P.L. Paris, and B.A. Rybicki contributed equally to this work.
Corresponding Authors: Benjamin A.Rybicki,HenryFord HealthSystem,
3E One Ford Place, Detroit, MI 48202. Phone: 313-874-6399; Fax: 313-
874-6730; E-mail: email@example.com; and Pamela L. Paris, Department of
Urology, Helen Diller Family Comprehensive Cancer Center, University of
California at San Francisco, San Francisco, CA 94143. Phone: 415-514-
2559; Fax: 415-514-4927; E-mail: firstname.lastname@example.org
?2014 American Association for Cancer Research.
Stephenson AJ, Scardino PT, Eastham JA, Bianco FJ Jr, Dotan ZA,
Diblasio CJ, et al. Postoperative nomogram predicting the 10-year
probability of prostate cancer recurrence after radical prostatectomy.
J Clin Oncol 2005;23:7005–12.
Ross PL, Scardino PT, Kattan MW. A catalog of prostate cancer
nomograms. J Urol 2001;165:1562–8.
Paris PL, Andaya A, Fridlyand J, Jain AN, Weinberg V, Kowbel D, et al.
Whole genome scanning identifies genotypes associated with recur-
rence and metastasis in prostate tumors. Hum Mol Genet 2004;13:
Paris PL, Weinberg V, Simko J, Andaya A, Albo G, Rubin MA, et al.
Preliminary evaluation of prostate cancer metastatic risk biomarkers.
Int J Biol Markers 2005;20:141–5.
genome-based biomarkers that add to a Kattan nomogram for pre-
dicting progression in men with high-risk prostate cancer. Clin Cancer
Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J
Rose AE, Satagopan JM, Oddoux C, Zhou Q, Xu R, Olshen AB, et al.
Castro P, Creighton CJ, Ozen M, Berel D, Mims MP, Ittmann M.
Genomic profiling of prostate cancers from African American men.
10. Cheng I, Levin AM, Tai YC, Plummer S, Chen GK, Neslund-Dudas C,
et al. Copy number alterations in prostate tumors and disease aggres-
siveness. Genes Chromosomes Cancer 2012;51:66–76.
11. Rybicki BA, Neslund-Dudas C, Nock NL, Schultz LR, Eklund L,
Rosbolt J, et al. Prostate cancer risk from occupational exposure
to polycyclic aromatic hydrocarbons interacting with the GSTP1
Ile105Val polymorphism. Cancer Detect Prev 2006;30:412–22.
forward tool for improved prediction of outcomes after radical pros-
tatectomy. Cancer 2011;117:5039–46.
13. Staaf J,Vallon-Christersson J, LindgrenD, JuliussonG,RosenquistR,
Hoglund M, et al. Normalization of Illumina Infinium whole-genome
SNP data improves copy number estimates and allelic intensity ratios.
BMC Bioinformatics 2008;9:409.
14. Engel E. A new genetic concept: uniparental disomy and its potential
effect, isodisomy. Am J Med Genet 1980;6:137–43.
15. Bacolod MD, Schemmann GS, Giardina SF, Paty P, Notterman DA,
Barany F. Emerging paradigms in cancer genetics: some important
ies. Cancer Res 2009;69:723–7.
16. Bland JM, Altman DG. Statistical methods for assessing agreement
between two methods of clinical measurement. Lancet 1986;1:
the efficacy of local therapies for localized prostate cancer in the
radical prostatectomy and external-beam radiotherapy. J Clin Oncol
18. Freedland SJ, Sutter ME, Dorey F, Aronson WJ. Defining the ideal
cutpoint for determining PSA recurrence after radical prostatectomy.
Prostate-specific antigen. Urology 2003;61:365–9.
19. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich
wide association studies. Nat Genet 2006;38:904–9.
growth rate and/or earlier transformation to clinically significant pros-
tate cancer in black than in white American men, and influences racial
progression and mortality disparity. J Urol 2010;183:1792–6.
21. Powell IJ, Dyson G, Land S, Ruterbusch J, Bock CH, Lenk S, et al.
Genes associated with prostate cancer are differentially expressed in
African American and European American men. Cancer Epidemiol
Biomarkers Prev 2013;22:891–7.
22. Lapointe J, Li C, Giacomini CP, Salari K, Huang S, Wang P, et al.
Genomic profiling reveals alternative genetic pathways of prostate
tumorigenesis. Cancer Res 2007;67:8504–10.
Cancer Epidemiol Biomarkers Prev; 23(8) August 2014Cancer Epidemiology, Biomarkers & Prevention
Levin et al.