Research Article

Proteomics cataloging analysis of human expressed prostatic secretions reveals rich source of biomarker candidates

  1. Runsheng Li1,†,
  2. Yan Guo2,†,
  3. Bang Ming Han3,
  4. Xiaowei Yan4,
  5. Angelita G. Utleg4,
  6. Wei Li2,
  7. Lan Chun Tu4,
  8. Jian Wang1,
  9. Leroy Hood4,
  10. Shujie Xia Dr.3,‡,
  11. Biaoyang Lin Dr.2,4,*

Article first published online: 7 MAR 2008

DOI: 10.1002/prca.200780159

Issue

PROTEOMICS - Clinical Applications

PROTEOMICS - Clinical Applications

Volume 2, Issue 4, pages 543–555, No. 4 April 2008

Additional Information

How to Cite

Li, R., Guo, Y., Han, B. M., Yan, X., Utleg, A. G., Li, W., Tu, L. C., Wang, J., Hood, L., Xia, S. and Lin, B. (2008), Proteomics cataloging analysis of human expressed prostatic secretions reveals rich source of biomarker candidates. PROTEOMICS - Clinical Applications, 2: 543–555. doi: 10.1002/prca.200780159

Author Information

  1. 1

    Shanghai Institute of Planned Parenthood Research, Shanghai, China

  2. 2

    Systems Biomedicine Center, Shanghai Jiaotong University, Shanghai, China

  3. 3

    Department of Urology, Shanghai 1st People's Hospital, Shanghai, China

  4. 4

    The Institute for Systems Biology, Seattle, WA, USA

  1. †

    Both these authors contributed equally to this work.

  2. ‡

    Additional corresponding author

*The Institute for Systems Biology, Seattle, WA 98021, USA Fax: +1-206-732-1299

Publication History

  1. Issue published online: 3 APR 2008
  2. Article first published online: 7 MAR 2008
  3. Manuscript Received: 9 MAY 2007

Funded by

  • NIH, USA. Grant Numbers: 5P50GM076547, 5U54CA119347
  • National Basic Research Program of China. Grant Number: 2006CB504005

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Keywords:

  • Biomarker;
  • Expressed prostatic secretions;
  • Mass spectrometry;
  • Prostate cancer

Abstract

Expressed prostatic secretions (EPS) contain proteins of prostate origin that may reflect the health status of the prostate and be used as diagnostic markers for prostate diseases including prostatitis, benign prostatic hyperplasia, and prostate cancer. Despite their importance and potential applications, a complete catalog of EPS proteins is not yet available. We, therefore, undertook a comprehensive analysis of the EPS proteome using 2-D micro-LC combined with MS/MS. Using stringent filtering criteria, we identified a list of 114 proteins with at least two unique-peptide hits and an additional 75 proteins with only a single unique-peptide hit. The proteins identified include kallikrein 2 (KLK2), KLK3 (prostate-specific antigen), KLK11, and nine cluster of differentiation (CD) molecules including CD10, CD13, CD14, CD26, CD66a, CD66c, CD 143, CD177, and CD224. To our knowledge, this list represents the first comprehensive characterization of the EPS proteome, and it provides a candidate biomarker list for targeted quantitative proteomics analysis using a multiple reaction monitoring (MRM) approach. To help prioritize candidate biomarkers, we constructed a protein–protein interaction network of the EPS proteins using Cytoscape (www.cytoscape.org), and overlaid the expression level changes from the Oncomine database onto the network.

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