Skip to main content
SpringerLink
Log in

Clinical Proteomics: Liquid Chromatography–Mass Spectrometry (LC–MS) Purification Systems

  • Protocol
  • First Online:
Protein Chromatography

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1485))

Abstract

Liquid chromatography–mass spectrometry (LC–MS) has become a routine powerful technology in clinical proteomic studies for protein identification, protein characterization and the discovery of biomarkers. In this chapter, we describe two protocol methods to analyze clinical patient samples using a resin based depletion column followed by either protein In-gel enzymatic digestion or protein in-solution enzymatic digestion and then analysis by one-dimensional reverse-phase chromatography or two-dimensional strong cation exchange (SCX)—reverse-phase chromatography (RPC).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Abersold R, Mann M (2003) Mass spectrometry-based proteomics. Nature 422:198–207

    Article  Google Scholar 

  2. Linge A, Maurya P, Friedrich K, Baretton GB, Kelly S, Henry M, Clynes M, Larkin A, Meleady P (2014) Identification and functional validation of RAD23B as a potential protein in human breast cancer progression. J Proteome Res 13(7):3212–3222

    Article  CAS  PubMed  Google Scholar 

  3. Brunoro GV, Carvalho PC, Ferreira AT, Perales J, Valente RH, de Moura Gallo CV, Pagnoncelli D, Neves-Ferreira AG (2015) Proteomic profiling of nipple aspirate fluid (NAF): exploring the complementarity of different peptide fractionation strategies. J Proteomics 18(117):86–94

    Article  Google Scholar 

  4. Martin-Lorenzo M, Gonzalez-Calero L, Zubiri I, Diaz-Payno PJ, Sanz-Maroto A, Posada-Ayala M, Oritz A, Vivanco F, Alvarez-Llamas G (2014) Urine 2DE proteome analysis in healthy condition and kidney disease. Electrophoresis 35(18):2634–2641

    Article  CAS  PubMed  Google Scholar 

  5. Ohmine K, Kawaguchi K, Ohtsuki S, Motoi F, Ohtsuka H, Kamiie J, Abe T, Unno M, Terasaki T (2015) Quantitative targeted proteomics of pancreatic cancer: deoxycytidine kinase protein level correlates to progression-free survival of patients receiving gemcitabine treatment. Mol Pharm 12(9):3282–3291

    Article  CAS  PubMed  Google Scholar 

  6. Magni R, Espins BH, Liotta LA, Luchini A, Espina V (2014) Hydrogel nanoparticle harvesting of plasma or urine for detecting low abundance proteins. J Vis Exp 90:e51789

    PubMed  Google Scholar 

  7. Monari E, Casali C, Cuoghi A, Nesci J, Bellei E, Bergamini S, Fantoni L, Natali P, Morandi U, Tomasi A (2011) Enriched sera protein profiling for detection of non-small cell lung cancer biomarkers. Proteome Sci 9(1):55

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Stebbing J, Zhang H, Xu Y, Grothey A, Ajuh P, Angelopoulos N, Giamas G (2015) Characterisation of the tyrosine kinase-regulated proteome in breast cancer by combined use of RNA interference (RNAi) and stable isotope labelling with amino acids in cell culture (SILAC) quantitative proteomics. Mol Cell Proteomics 14(9):2479–2492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Shilo Y, Aebersold R (2006) Quantitative proteome analysis using isotope coded affinity tags and mass spectrometry. Nat Protoc 1(1):139–145

    Article  Google Scholar 

  10. Crabb JW, Hu B, Crabb JS, Triozzi P, Saunthararajah Y, Tubbs R, Singh AD (2015) iTRAQ quantitative proteomic comparison of metastatic and non-metastatic uveal melanoma tumors. PLoS One 10(8):e013543

    Article  Google Scholar 

  11. Sinclair J, Timms JF (2013) Proteomic profiling of ovarian cancer models using TMT-LC-MS/MS. Methods Mol Biol 1049:271–284

    Article  CAS  PubMed  Google Scholar 

  12. Capuano F, Bond NJ, Gatto L, Beaudoin F, Napier JA, Benvenuto E, Lilley KS, Bacschieri S (2011) LC-MS/MS methods for absolute quantification of proteins associated with chimeric plant oil bodies. Anal Chem 83(24):9267–9272

    Article  CAS  PubMed  Google Scholar 

  13. Holland A, Henry M, Meleady P, Winkler CK, Krautwald M, Brinkmeier H, Ohlendieck K (2015) Comparative label-free mass spectrometric analysis of mildly versus severely affected mdx mouse skeletal muscles identifies annexin, lamin, and vimentin as universal dystrophic markers. Molecules 20(6):11317–11344

    Article  CAS  PubMed  Google Scholar 

  14. Dowling P, Pollard D, Larkin A, Henry M, Meleady P, Gately K, O'Byrne K, Barr MP, Lynch V, Ballot J, Crown J, Moriarty M, O'Brien E, Morgan R, Clynes M (2015) Abnormal levels of heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) in tumour tissue and blood samples from patients diagnosed with lung cancer. Mol Biosyst 11(3):743–752

    Article  CAS  PubMed  Google Scholar 

  15. Dowling P, Wormald R, Meleady P, Henry M, Curran A, Clynes M (2008) Analysis of the saliva proteome from patients with head and neck squamous cell carcinoma reveals differences in abundance levels of proteins associated with tumour progression and metastasis. J Proteomics 71(2):168–175

    Article  CAS  PubMed  Google Scholar 

  16. Dowling P, Hughes DJ, Larkin A, Meiller J, Henry M, Meleady P, Lynch V, Pardini B, Naccarati A, Levy M, Vodicka P, Neary P, Clynes M (2015) Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer. Clin Chim Acta 441:133–141

    Article  CAS  PubMed  Google Scholar 

  17. Nijenhuis CM, Lucas L, Rosing H, Schellens JH, Beijnen JH, Gorman SH, Burke SM, Campbell DA, Chapple MW, Yousey TH, Mulvana DE (2015) Validation of high-performance liquid chromatography-tandem mass spectrometry assays quantifying omacetaxine mepesuccinate and its 4′-des-methyl and cephalotaxine metabolites in human plasma and urine. J Chromatogr B Analyt Technol Biomed Life Sci 1002:152–159

    Article  CAS  PubMed  Google Scholar 

  18. Dowling P, Hayes C, Ting KR, Hameed A, Meiller J, Mitsiades C, Anderson KC, Clynes M, Clarke C, Richardson P, O’Gorman P (2014) Identification of proteins found to be significantly altered when comparing the serum proteome from Multiple Myeloma patients with varying degrees of bone disease. BMC Genomics 15:904. doi:10.1186/1471-2164-15-904

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hakimi A, Auluck J, Jones GD, Ng LL, Jones DJ (2014) Assessment of reproducibility in depletion and enrichment workflows for plasma proteomics using label-free quantitative data-independent LC-MS. Proteomics 14(1):4–13

    Article  CAS  PubMed  Google Scholar 

  20. Tu C, Rudnick PA, Martinez MY, Cheek KL, Stein SE, Slebos RJ, Liebler DC (2010) Depletion of abundant plasma proteins and limitations of plasma proteomics. J Proteome Res 9(10):4982–4991

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Omenn GS, States DJ, Adamski M, Blackwell TW, Menon R, Hermkakob H, Apweiler R, Haab BB, Simpson RJ, Eddes JS, Kapp EA, Moritz RL, Chan DW, Rai AJ, Admon A, Aebersold R, Eng J, Hancock WS, Hefta SA, Meyer H, Paik YK, Yoo JS, Ping P, Pounds J, Adkins J, Qian X, Wang R, Wasinger V, Wu CY, Zhao X, Zeng R, Archakov A, Tsugita A, Beer I, Pandey A, Pisano M, Andrews P, Tammen H, Speicher DW, Hanash SM (2005) Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5(13):3226–3245

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Institute for Cellular Biotechnology, Dublin City University, Glasnevin, Dublin 9, Ireland

    Michael Henry & Paula Meleady

Authors
  1. Michael Henry
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paula Meleady
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paula Meleady .

Editor information

Editors and Affiliations

  1. School of Biotechnology, Dublin City University, Dublin, Ireland

    Dermot Walls

  2. Department of Applied Sciences, Dundalk Institute of Technology, Dublin, Ireland

    Sinéad T. Loughran

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media New York

About this protocol

Cite this protocol

Henry, M., Meleady, P. (2017). Clinical Proteomics: Liquid Chromatography–Mass Spectrometry (LC–MS) Purification Systems. In: Walls, D., Loughran, S. (eds) Protein Chromatography. Methods in Molecular Biology, vol 1485. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6412-3_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6412-3_20

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6410-9

  • Online ISBN: 978-1-4939-6412-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation