Skip to main content
Download PDF
  • Serum/Plasma Proteome
  • Open access
  • Published:

Analysis of the human serum proteome

Clinical Proteomics volume 1, pages 101–225 (2004)Cite this article

Abstract

Changes in serum proteins that signal histopathological states, such as cancer, are useful diagnostic and prognostic biomarkers. Unfortunately, the large dynamic concentration range of proteins in serum makes it a challenging proteome to effectively characterize. Typically, methods to deplete highly abundant proteins to decrease this dynamic protein concentration range are employed, yet such depletion results in removal of important low abundant proteins.

A multi-dimensional peptide separation strategy utilizing conventional separation techniques combined with tandem mass spectrometry (MS/MS) was employed for a proteome analysis of human serum. Serum proteins were digested with trypsin and resolved into 20 fractions by ampholyte-free liquid phase isoelectric focusing. These 20 peptide fractions were further fractionated by strong cation-exchange chromatography, each of which was analyzed by microcapillary reversed-phase liquid chromatography coupled online with MS/MS analysis.

This investigation resulted in the identification of 1444 unique proteins in serum. Proteins from all functional classes, cellular localization, and abundance levels were identified.

This study illustrates that a majority of lower abundance proteins identified in serum are present as secreted or shed species by cells as a result of signalling, necrosis, apoptosis, and hemolysis. These findings show that the protein content of serum is quite reflective of the overall profile of the human organism and a conventional multidimensional fractionation strategy combined with MS/MS is entirely capable of characterizing a significant fraction of the serum proteome. We have constructed a publicly available human serum proteomic database (http://bpp.nci.nih.gov) to provide a reference resource to facilitate future investigations of the vast archive of pathophysiological content in serum.

References

  1. Aebersold R, Mann M. Mass spectrometry-based proteomics. Nature 2003;422:198–207.

    Article  PubMed  CAS  Google Scholar 

  2. Anderson NL, Anderson NG. The human plasma proteome: history, character, and diagnostic prospects. Mol Cell Proteomics 2002;1:845–867.

    Article  PubMed  CAS  Google Scholar 

  3. Petricoin EF, Ardekani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet 2002;359:572–577.

    Article  PubMed  CAS  Google Scholar 

  4. Conrads TP, Zhou M, Petricoin EF, 3rd, Liotta L, Veenstra TD. Cancer diagnosis using proteomic patterns. Expert Rev Mol Diagn 2003;3:411–420.

    Article  PubMed  CAS  Google Scholar 

  5. Li J, Zhang Z, Rosenzweig J, Wang YY, Chan DW. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem 2002;48:1296–1304.

    PubMed  CAS  Google Scholar 

  6. Adam BL, Qu Y, Davis JW, et al. Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. Cancer Res 2002;62:3609–3614.

    PubMed  CAS  Google Scholar 

  7. Petricoin EF, 3rd, Ornstein DK, Paweletz CP, et al. Serum proteomic patterns for detection of prostate cancer. J Natl Cancer Inst 2002;94:1576–1578.

    PubMed  CAS  Google Scholar 

  8. Adkins JN, Varnum SM, Auberry KJ, et al. Toward a human blood serum proteome: analysis by multidimensional separation coupled with mass spectrometry. Mol Cell Proteomics 2002;1:947–955.

    Article  PubMed  CAS  Google Scholar 

  9. Pieper R, Gatlin CL, Makusky AJ, et al. The human serum proteome: Display of nearly 3700 chromatographically separated protein spots on two-dimensional electrophoresis gels and identification of 325 distinct proteins. Proteomics 2003;3:1345–1364.

    Article  PubMed  CAS  Google Scholar 

  10. Tirumalai RS, Chan KC, Prieto DA, Issaq HJ, Conrads TP, Veenstra TD. Characterization of the low molecular weight human serum proteome. Mol Cell Proteomics 2003;2:1096–1103.

    Article  PubMed  CAS  Google Scholar 

  11. Washburn MP, Wolters D, Yates JR. Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nature Biotechnology 2001;19:242–247.

    Article  PubMed  CAS  Google Scholar 

  12. Grossklaus DJ, Smith JA, Shappell SB, Coffey CS, Chang SS, Cookson MS. The free/total prostate-specific antigen ratio (%fPSA) is the best predictor of tumor involvement in the radical prostatectomy specimen among men with an elevated PSA. Urol Oncol 2002;7:195–198.

    Article  PubMed  CAS  Google Scholar 

  13. Janini GM, Conrads TP, Veenstra TD, Issaq HJ. Development of a two-dimensional protein-peptide separation protocol for comprehensive proteome measurements. J Chromatogr B Analyt Technol Biomed Life Sci 2003;787:43–51.

    Article  PubMed  CAS  Google Scholar 

  14. Yousef GM, Diamandis EP. The new human tissue kallikrein gene family: structure, function, and association to disease. Endocr Rev 2001;22:184–204.

    Article  PubMed  CAS  Google Scholar 

  15. Luo LY, Katsaros D, Scorilas A, et al. The serum concentration of human kallikrein 10 represents a novel biomarker for ovarian cancer diagnosis and prognosis. Cancer Res 2003;63:807–811.

    PubMed  CAS  Google Scholar 

  16. Rumble B, Retallack R, Hilbich C, et al. Amyloid A4 protein and its precursor in Down’s syndrome and Alzheimer’s disease. N Engl J Med 1989;320:1446–1452.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratory of Proteomics and Analytical Technologies, National Cancer Institute at Frederick, SAIC-Frederick, Inc, PO Box B, 21702, Frederick, MD

    King C. Chan, David A. Lucas, Zhen Xiao, George M. Janini, Haleem J. Issaq, Timothy D. Veenstra & Thomas P. Conrads

  2. Center for Bioinformatics, National Cancer Institute, 20892, Bethesda, MD

    Denise Hise, Carl F. Schaefer & Kenneth H. Buetow

Authors
  1. King C. Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David A. Lucas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Denise Hise
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Carl F. Schaefer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhen Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. George M. Janini
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kenneth H. Buetow
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Haleem J. Issaq
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Timothy D. Veenstra
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Thomas P. Conrads
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thomas P. Conrads.

Additional information

These authors contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chan, K.C., Lucas, D.A., Hise, D. et al. Analysis of the human serum proteome. Clin Proteom 1, 101–225 (2004). https://doi.org/10.1385/CP:1:2:101

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1385/CP:1:2:101

Key Words

Clinical Proteomics

ISSN: 1559-0275