Is label-free LC-MS/MS ready for biomarker discovery?

Proteomics - Clinical Applications

Volumn 9, Issue 3-4, 2015, Pages 289-294

  Sandin, Marianne ^a   Chawade, Aakash ^a   Levander, Fredrik ^a  

^a LUND UNIVERSITY   (Sweden)

Author keywords

Label free; Mass spectrometry

Indexed keywords

BIOLOGICAL MARKER;

BLOOD ANALYSIS; DATA ANALYSIS; DATA PROCESSING; FALSE POSITIVE RESULT; HUMAN; IMMUNOHISTOCHEMISTRY; LASER CAPTURE MICRODISSECTION; LIQUID CHROMATOGRAPHY; NOTE; PRIORITY JOURNAL; PROGNOSIS; PROTEIN EXPRESSION; PROTEOMICS; QUANTITATIVE ANALYSIS; REPRODUCIBILITY; TANDEM MASS SPECTROMETRY; MASS SPECTROMETRY; PROCEDURES;

BIOMARKERS; CHROMATOGRAPHY, LIQUID; HUMANS; MASS SPECTROMETRY; TANDEM MASS SPECTROMETRY;

EID: 84928062047     PISSN: 18628346     EISSN: 18628354     Source Type: Journal    
DOI: 10.1002/prca.201400202     Document Type: Note

References (35)

1. Eng, J. K., Searle, B. C., Clauser, K. R., Tabb, D. L., A face in the crowd: recognizing peptides through database search. Mol. Cell. Proteomics 2011, 10, R111 009522.
2. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B. et al., Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 2002, 1, 376-386.
3. Thompson, A., Schafer, J., Kuhn, K., Kienle, S. et al., Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 2003, 75, 1895-1904.
4. Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B. et al., Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell. Proteomics 2004, 3, 1154-1169.
5. Geiger, T., Cox, J., Ostasiewicz, P., Wisniewski, J. R., Mann, M., Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat. Methods 2010, 7, 383-385.
6. Liu, N. Q., Dekker, L. J., Stingl, C., Guzel, C. et al., Quantitative proteomic analysis of microdissected breast cancer tissues: comparison of label-free and SILAC-based quantification with shotgun, directed, and targeted MS approaches. J. Proteome Res. 2013, 12, 4627-4641.
7. Patel, V. J., Thalassinos, K., Slade, S. E., Connolly, J. B. et al., A comparison of labeling and label-free mass spectrometry-based proteomics approaches. J. Proteome Res. 2009, 8, 3752-3759.
8. Li, Z., Adams, R. M., Chourey, K., Hurst, G. B. et al., Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos. J. Proteome Res. 2012, 11, 1582-1590.
9. Wang, H., Alvarez, S., Hicks, L. M., Comprehensive comparison of iTRAQ and label-free LC-based quantitative proteomics approaches using two Chlamydomonas reinhardtii strains of interest for biofuels engineering. J. Proteome Res. 2012, 11, 487-501.
10. Ting, L., Rad, R., Gygi, S. P., Haas, W., MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat. Methods 2011, 8, 937-940.
11. Griffin, N. M., Yu, J., Long, F., Oh, P. et al., Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis. Nat. Biotechnol. 2010, 28, 83-89.
12. Colaert, N., Gevaert, K., Martens, L., RIBAR and xRIBAR: methods for reproducible relative MS/MS-based label-free protein quantification. J. Proteome Res. 2011, 10, 3183-3189.
13. Schmidt, A., Claassen, M., Aebersold, R., Directed mass spectrometry: towards hypothesis-driven proteomics. Curr. Opin. Chem. Biol. 2009, 13, 510-517.
14. Cox, J., Hein, M. Y., Luber, C. A., Paron, I. et al., Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 2014, 13, 2513-2526.
15. Michalski, A., Damoc, E., Hauschild, J. P., Lange, O. et al., Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer. Mol. Cell. Proteomics 2011, 10, M111 011015.
16. Thakur, S. S., Geiger, T., Chatterjee, B., Bandilla, P. et al., Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol. Cell. Proteomics 2011, 10, M110 003699.
17. Pirmoradian, M., Budamgunta, H., Chingin, K., Zhang, B. et al., Rapid and deep human proteome analysis by single-dimension shotgun proteomics. Mol. Cell. Proteomics 2013, 12, 3330-3338.
18. Tabb, D. L., Quality assessment for clinical proteomics. Clin. Biochem. 2013, 46, 411-420.
19. Bereman, M. S., Tools for monitoring systems suitability in LC MS/MS centric proteomic experiments. Proteomics 2014, doi: 10.1002/pmic.201400373.
20. Chawade, A., Sandin, M., Teleman, J., Malmstrom, J., Levander, F., Data processing has major impact on the outcome of quantitative label-free LC-MS analysis. J. Proteome Res. 2014, 14, 676-687.
21. Nahnsen, S., Bielow, C., Reinert, K., Kohlbacher, O., Tools for label-free peptide quantification. Mol. Cell. Proteomics 2013, 12, 549-556.
22. Sandin, M., Teleman, J., Malmstrom, J., Levander, F., Data processing methods and quality control strategies for label-free LC-MS protein quantification. Biochim. Biophys. Acta 2014, 1844, 29-41.
23. Bellew, M., Coram, M., Fitzgibbon, M., Igra, M. et al., A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS. Bioinformatics 2006, 22, 1902-1909.
24. Sandin, M., Ali, A., Hansson, K., Mansson, O. et al., An adaptive alignment algorithm for quality-controlled label-free LC-MS. Mol. Cell. Proteomics 2013, 12, 1407-1420.
25. Hakkinen, J., Vincic, G., Mansson, O., Warell, K., Levander, F., The Proteios software environment: an extensible multiuser platform for management and analysis of proteomics data. J. Proteome Res. 2009, 8, 3037-3043.
26. Chawade, A., Alexandersson, E., Levander, F., Normalyzer: a tool for rapid evaluation of normalization methods for omics data sets. J. Proteome Res. 2014, 13, 3114-3120.
27. Smyth, G. K., in: Gentleman, R., Carey, V., Huber, W., Irizarry, R., Dudoit, S. (Eds.), Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Springer New York 2005, pp. 397-420.
28. Sandin, M., Krogh, M., Hansson, K., Levander, F., Generic workflow for quality assessment of quantitative label-free LC-MS analysis. Proteomics 2011, 11, 1114-1124.
29. Neilson, K. A., Ali, N. A., Muralidharan, S., Mirzaei, M. et al., Less label, more free: approaches in label-free quantitative mass spectrometry. Proteomics 2011, 11, 535-553.
30. Welberry Smith, M. P., Zougman, A., Cairns, D. A., Wilson, M. et al., Serum aminoacylase-1 is a novel biomarker with potential prognostic utility for long-term outcome in patients with delayed graft function following renal transplantation. Kidney Int. 2013, 84, 1214-1225.
31. Liu, N. Q., Stingl, C., Look, M. P., Smid, M. et al., Comparative proteome analysis revealing an 11-protein signature for aggressive triple-negative breast cancer. J. Natl. Cancer Inst. 2014, 106, djt376.
32. Liu, N. Q., Braakman, R. B., Stingl, C., Luider, T. M. et al., Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue. J. Mammary Gland Biol. Neoplasia 2012, 17, 155-164.
33. Cox, J., Mann, M., MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26, 1367-1372.
34. Geiger, T., Madden, S. F., Gallagher, W. M., Cox, J., Mann, M., Proteomic portrait of human breast cancer progression identifies novel prognostic markers. Cancer Res. 2012, 72, 2428-2439.
35. Sandin, M., Quality Control for High-Throughput Quantitative Proteomics-Harnessing the Potential of Label-Free LC-MS, Lund University, Lund 2014.