Assessment of 54 biomarkers for biopsy-detectable prostate cancer

Dipen J. Parekh, Donna Pauler Ankerst, Jacques Baillargeon, Betsy Higgins, Elizabeth A. Platz, Dean Troyer, Javier Hernandez, Robin J. Leach, Anna Lokshin, Ian M. Thompson

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Objective: We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score. Methods: A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls. Results: Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and α-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60%; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPTrisk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls. Conclusions: This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice.

Original languageEnglish (US)
Pages (from-to)1966-1972
Number of pages7
JournalCancer Epidemiology Biomarkers and Prevention
Volume16
Issue number10
DOIs
StatePublished - Oct 1 2007
Externally publishedYes

Fingerprint

Prostatic Neoplasms
Biomarkers
Biopsy
Cluster Analysis
Fetal Proteins
Resistin
Plasminogen Inactivators
Matrix Metalloproteinase 3
Kallikreins
Adipokines
Interleukins
Metalloproteases
Granulocyte Colony-Stimulating Factor
Serum
ROC Curve
Vascular Endothelial Growth Factor A
Case-Control Studies
Intercellular Signaling Peptides and Proteins
Cohort Studies
Logistic Models

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Parekh, D. J., Ankerst, D. P., Baillargeon, J., Higgins, B., Platz, E. A., Troyer, D., ... Thompson, I. M. (2007). Assessment of 54 biomarkers for biopsy-detectable prostate cancer. Cancer Epidemiology Biomarkers and Prevention, 16(10), 1966-1972. https://doi.org/10.1158/1055-9965.EPI-07-0302

Assessment of 54 biomarkers for biopsy-detectable prostate cancer. / Parekh, Dipen J.; Ankerst, Donna Pauler; Baillargeon, Jacques; Higgins, Betsy; Platz, Elizabeth A.; Troyer, Dean; Hernandez, Javier; Leach, Robin J.; Lokshin, Anna; Thompson, Ian M.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 16, No. 10, 01.10.2007, p. 1966-1972.

Research output: Contribution to journalArticle

Parekh, DJ, Ankerst, DP, Baillargeon, J, Higgins, B, Platz, EA, Troyer, D, Hernandez, J, Leach, RJ, Lokshin, A & Thompson, IM 2007, 'Assessment of 54 biomarkers for biopsy-detectable prostate cancer', Cancer Epidemiology Biomarkers and Prevention, vol. 16, no. 10, pp. 1966-1972. https://doi.org/10.1158/1055-9965.EPI-07-0302
Parekh, Dipen J. ; Ankerst, Donna Pauler ; Baillargeon, Jacques ; Higgins, Betsy ; Platz, Elizabeth A. ; Troyer, Dean ; Hernandez, Javier ; Leach, Robin J. ; Lokshin, Anna ; Thompson, Ian M. / Assessment of 54 biomarkers for biopsy-detectable prostate cancer. In: Cancer Epidemiology Biomarkers and Prevention. 2007 ; Vol. 16, No. 10. pp. 1966-1972.
@article{3b58e8e851784b2d83237e9a3e3a5756,
title = "Assessment of 54 biomarkers for biopsy-detectable prostate cancer",
abstract = "Objective: We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score. Methods: A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls. Results: Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and α-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60{\%}; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPTrisk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls. Conclusions: This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice.",
author = "Parekh, {Dipen J.} and Ankerst, {Donna Pauler} and Jacques Baillargeon and Betsy Higgins and Platz, {Elizabeth A.} and Dean Troyer and Javier Hernandez and Leach, {Robin J.} and Anna Lokshin and Thompson, {Ian M.}",
year = "2007",
month = "10",
day = "1",
doi = "10.1158/1055-9965.EPI-07-0302",
language = "English (US)",
volume = "16",
pages = "1966--1972",
journal = "Cancer Epidemiology Biomarkers and Prevention",
issn = "1055-9965",
publisher = "American Association for Cancer Research Inc.",
number = "10",

}

TY - JOUR

T1 - Assessment of 54 biomarkers for biopsy-detectable prostate cancer

AU - Parekh, Dipen J.

AU - Ankerst, Donna Pauler

AU - Baillargeon, Jacques

AU - Higgins, Betsy

AU - Platz, Elizabeth A.

AU - Troyer, Dean

AU - Hernandez, Javier

AU - Leach, Robin J.

AU - Lokshin, Anna

AU - Thompson, Ian M.

PY - 2007/10/1

Y1 - 2007/10/1

N2 - Objective: We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score. Methods: A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls. Results: Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and α-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60%; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPTrisk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls. Conclusions: This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice.

AB - Objective: We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score. Methods: A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls. Results: Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and α-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60%; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPTrisk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls. Conclusions: This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice.

UR - http://www.scopus.com/inward/record.url?scp=35448972867&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35448972867&partnerID=8YFLogxK

U2 - 10.1158/1055-9965.EPI-07-0302

DO - 10.1158/1055-9965.EPI-07-0302

M3 - Article

VL - 16

SP - 1966

EP - 1972

JO - Cancer Epidemiology Biomarkers and Prevention

JF - Cancer Epidemiology Biomarkers and Prevention

SN - 1055-9965

IS - 10

ER -