p‑ SRM, SWATH and HRM – Targeted Proteomics Approaches on TripleTOF 5600+ Mass Spectrometer and Their Applications in Oncology Research
Authors:
J. Faktor 1,2; E. Michalová 1; P. Bouchal 1,2
Authors‘ workplace:
Regionální centrum aplikované molekulární onkologie, Masarykův onkologický ústav, Brno
1; Ústav biochemie, Přírodovědecká fakulta MU, Brno
2
Published in:
Klin Onkol 2014; 27(Supplementum): 110-115
Overview
Development of novel diagnostic and therapeutic approaches in cancer research requires sensitive and quantitative assays for determination of cancer‑associated proteins in clinical samples. Novel quantitative targeted proteomic approaches are overviewed in this communication. A major advantage of selected reaction monitoring (SRM) and pseudo- SRM lies in the selective and sensitive quantification of selected proteins in large sample sets. As such, they represent an alternative to immunochemical approaches. On the other hand, the potential of HRM and SWATH lies in recording of digital fingerprints, which enable post‑acquisition quantitative proteomic data mining on a similar basis to SRM. This article shows applications of targeted proteomics in a number of cancer research studies where they were used for quantification and validation of current or potential protein biomarkers and to study their role in cancer development and progression.
Key words:
proteomics – selected reaction monitoring – oncology – SWATH – biomarkers – molecular diagnostics
This work was supported by the project of Czech Science Foundation No. 14-19250S, by the European Regional Development Fund and the State Budget of the Czech Republic (RECAMO, CZ.1.05/2.1.00/03.0101) and by MH CZ – DRO (MMCI, 00209805) and BBMRI_CZ (LM2010004).
The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manuscript met the ICMJE “uniform requirements” for biomedical papers.
Submitted:
3. 2. 2014
Accepted:
26. 3. 2014
Sources
1. Faktor J, Dvořáková M, Maryáš J et al. Identification and characterisation of pro‑metastatic targets, pathways and molecular complexes using a toolbox of proteomic technologies. Klin onkol 2012; 25 (Suppl 2): 2S70– 2S77.
2. Maryáš J, Faktor J, Dvořáková M et al. Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges. Proteomics 2014; 14(4– 5): 426– 440. doi: 10.1002/ pmic.201300264.
3. Humplíková S, Minář J, Kučerová M et al. Stanovení hladiny celkového homocysteinu v plazmě kapalinovou chromatografií s tandemovou hmotnostní spektrometrií. Klin Biochem Metab 2007; 15(36): 31– 34.
4. Kim K, Kim Y. Preparing multiple reaction monitoring for quantitative clinical proteomics. Expert Rev Proteomics 2009; 6(3): 225– 229. doi: 10.1586/ epr.09.11.
5. Marx V. Targeted proteomics. Nat Methods 2013; 10(1): 19– 22.
6. Faktor J, Struhárová I, Fučíková A et al. Kvantifikace proteinových biomarkerů pomocí hmotnostní spektrometrie pracující v režimu monitorování vybraných reakcí. Chemické listy 2011; 105(11): 846– 850.
7. Kitteringham NR, Jenkins RE, Lane CS et al. Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci 2009; 877(13): 1229– 1239. doi: 10.1016/ j.jchromb.2008.11.013.
8. Gallien S, Duriez E, Domon B. Selected reaction monitoring applied to proteomics. J Mass Spectrom 2011; 46(3): 298– 312. doi: 10.1002/ jms.1895.
9. Picotti P, Bodenmiller B, Mueller LN et al. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics. Cell 2009; 138(4): 795– 806. doi: 10.1016/ j.cell.2009.05.051.
10. Anderson NL, Anderson NG, Haines LR et al. Mass spectrometric quantitation of peptides and proteins using stable isotope standards and capture by anti‑peptide antibodies (SISCAPA). J Proteome Res 2004; 3(2): 235– 244.
11. Lange V, Picotti P, Domon B et al. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol 2008; 4: 222. doi: 10.1038/ msb.2008.61.
12. Whiteaker JR, Lin C, Kennedy J et al. A targeted proteomics‑based pipeline for verification of biomarkers in plasma. Nat Biotechnol 2011; 29(7): 625– 634. doi: 10.1038/ nbt.1900.
13. Schiess R, Wollscheid B, Aebersold R. Targeted proteomic strategy for clinical biomarker discovery. Mol Oncol 2009; 3(1): 33– 44. doi: 10.1016/ j.molonc.2008.12.001.
14. Fortin T, Salvador A, Charrier JP et al. Clinical quantitation of prostate‑ specific antigen biomarker in the low nanogram/ milliliter range by conventional bore liquid chromatography‑ tandem mass spectrometry (multiple reaction monitoring) coupling and correlation with ELISA tests. Mol Cell Proteomics 2009; 8(5): 1006– 1015. doi: 10.1074/ mcp.M800238- MCP200.
15. Hembrough T, Thyparambil S, Liao WL et al. Selected reaction monitoring (SRM) analysis of epidermal growth factor receptor (EGFR) in formalin fixed tumor tissue. Clin Proteomics 2012; 9(1): 5. doi: 10.1186/ 1559- 0275- 9- 5.
16. Pan S, Chen R, Brand RE et al. Multiplex targeted proteomic assay for biomarker detection in plasma: a pancreatic cancer biomarker case study. J Proteome Res 2012; 11(3): 1937– 1948. doi: 10.1021/ pr201117w.
17. Mustafa MG, Petersen JR, Ju H et al. Biomarker discovery for early detection of hepatocellular carcinoma in hepatitis C‑ infected patients. Mol Cell Proteomics 2013; 12(12): 3640– 3652. doi: 10.1074/ mcp.M113.031252.
18. Hüttenhain R, Soste M, Selevsek N et al. Reproducible quantification of cancer‑associated proteins in body fluids using targeted proteomics. Sci Transl Med 2012; 4(142): 142ra94. doi: 10.1126/ scitranslmed.3003989.
19. Wolf‑ Yadlin A, Hautaniemi S, Lauffenburger DA et al. Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks. Proc Natl Acad Sci USA 2007; 104(14): 5860– 5865.
20. Griffiths JR, Unwin RD, Evans CA et al. The application of a hypothesis‑driven strategy to the sensitive detection and location of acetylated lysine residues. J Am Soc Mass Spectrom 2007; 18(8): 1423– 1428.
21. Hülsmeier AJ, Paesold‑ Burda P, Hennet T. N‑ glycosylation site occupancy in serum glycoproteins using multiple reaction monitoring liquid chromatography‑mass spectrometry. Mol Cell Proteomics 2007; 6(12): 2132– 2138.
22. Gillet LC, Navarro P, Tate S et al. Targeted data extraction of the MS/ MS spectra generated by data‑ independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 2012; 11(6): O111.016717. doi: 10.1074/ mcp.O111.016717.
23. Held JM, Schilling B, D‘Souza AK et al. Label‑free quantitation and mapping of the ErbB2 tumor receptor by multiple protease digestion with data‑ dependent (MS1) and data‑ independent (MS2) acquisitions. Int J Proteomics 2013; 2013: 791985. doi: 10.1155/ 2013/ 791985.
24. Liu Y, Hüttenhain R, Surinova S et al. Quantitative measurements of N‑linked glycoproteins in human plasma by SWATH‑ MS. Proteomics 2013; 13(8): 1247– 1256. doi: 10.1002/ pmic.201200417.
25. Collins BC, Gillet LC, Rosenberger G et al. Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3- 3 system. Nat Methods 2013; 10(12): 1246– 1253. doi: 10.1038/ nmeth.2703.
26. Lambert JP, Ivosev G, Couzens AL et al. Mapping differential interactomes by affinity purification coupled with data‑ independent mass spectrometry acquisition. Nat Methods 2013; 10(12): 1239– 1245. doi: 10.1038/ nmeth.2702.
27. Baumann C (ed.). MS/ MSALL with SWATH™ acquisition global quantitative strategies for proteomics & beyond. AB SCIEX Germany; c2012 [cited 2014 February]. Available from: http:/ / proteomics‑ seminar.imp.ac.at/ fileadmin/ imp/ Images/ Proteomics_seminar/ 2012/ Christian_Baumann_MSMSall_with_SWATH_Acquisition.pdf.
Labels
Paediatric clinical oncology Surgery Clinical oncologyArticle was published in
Clinical Oncology
2014 Issue Supplementum
Most read in this issue
- Protein Expression and Purification
- Methods for Studying Tumor Cell Migration and Invasiveness
- Next Generation Sequencing – Application in Clinical Practice
- Analysis of Protein Using Mass Spectrometry