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An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments

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Abstract

A standardized workflow for matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging MS) is a prerequisite for the routine use of this promising technology in clinical applications. We present an approach to develop standard operating procedures for MALDI imaging MS sample preparation of formalin-fixed and paraffin-embedded (FFPE) tissue sections based on a novel quantitative measure of dataset quality. To cover many parts of the complex workflow and simultaneously test several parameters, experiments were planned according to a fractional factorial design of experiments (DoE). The effect of ten different experiment parameters was investigated in two distinct DoE sets, each consisting of eight experiments. FFPE rat brain sections were used as standard material because of low biological variance. The mean peak intensity and a recently proposed spatial complexity measure were calculated for a list of 26 predefined peptides obtained by in silico digestion of five different proteins and served as quality criteria. A five-way analysis of variance (ANOVA) was applied on the final scores to retrieve a ranking of experiment parameters with increasing impact on data variance.

MALDI imaging experiments were planned according to fractional factorial design of experiments for the parameters under study. Selected peptide images were evaluated by the chosen quality metric (structure and intensity for a given peak list), and the calculated values were used as an input for the ANOVA. The parameters with the highest impact on the quality were deduced and SOPs recommended.

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References

  1. Stoeckli M, Chaurand P, Hallahan DE, Caprioli RM. Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues. Nat Med. 2001;7:493–6.

    Article  CAS  Google Scholar 

  2. Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem. 1997;69:4751–60.

    Article  CAS  Google Scholar 

  3. McDonnell LA, Corthals GL, Willems SM, van Remoortere A, van Zeijl RJM, et al. Peptide and protein imaging mass spectrometry in cancer research. J Proteomics. 2010;73:1921–44.

    Article  CAS  Google Scholar 

  4. OuYang C, Liang Z, Li L. Mass spectrometric analysis of spatio-temporal dynamics of crustacean neuropeptides. Biochim Biophys Acta Proteins Proteomics. 2015;1854:798–811.

    Article  CAS  Google Scholar 

  5. Burnum KE, Cornett DS, Puolitaival SM, Milne SB, Myers DS, et al. Spatial and temporal alterations of phospholipids determined by mass spectrometry during mouse embryo implantation. J Lipid Res. 2009;50:2290–8.

    Article  CAS  Google Scholar 

  6. Sun N, Fernandez IE, Wei M, Wu Y, Aichler M, et al. Pharmacokinetic and pharmacometabolomic study of pirfenidone in normal mouse tissues using high mass resolution MALDI-FTICR-mass spectrometry imaging. Histochem Cell Biol. 2016;145:201–11.

    Article  CAS  Google Scholar 

  7. Reyzer ML, Caprioli RM. MALDI-MS-based imaging of small molecules and proteins in tissues. Curr Opin Chem Biol. 2007;11:29–35.

    Article  CAS  Google Scholar 

  8. Aichler M, Walch A. MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. Lab Invest. 2015;95:422–31.

    Article  CAS  Google Scholar 

  9. Elsner M, Rauser S, Maier S, Schӧne C, Balluff B, Meding S, et al. MALDI imaging mass spectrometry reveals COX7A2, TAGLN2 and S100-A10 as novel prognostic markers in Barrett’s adenocarcinoma. J Proteomics. 2012;75:4693–703.

    Article  CAS  Google Scholar 

  10. Rauser S, Marquardt C, Balluff B, Deininger S-O, Albers C, et al. Classification of HER2 receptor status in breast cancer tissues by MALDI imaging mass spectrometry. J Proteome Res. 2010;9:1854–63.

    Article  CAS  Google Scholar 

  11. Poté N, Alexandrov T, Le Faouder J, Laouirem S, Léger T, Mebarki M, et al. Imaging mass spectrometry reveals modified forms of histone H4 as new biomarkers of microvascular invasion in hepatocellular carcinomas. Hepatolog. 2013;58:983–94.

    Article  Google Scholar 

  12. Veselkov KA, Mirnezami R, Strittmatter N, Goldin RD, Kinross J, Speller AV, et al. Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer. PNAS. 2014;111:1216–21.

    Article  CAS  Google Scholar 

  13. Cazares LH, Troyer D, Mendrinos S, Lance RA, Nyalwidhe JO, Beydoun HA, et al. Imaging mass spectrometry of a specific fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue. Clin Cancer Res. 2009;15:5541–51.

    Article  CAS  Google Scholar 

  14. Casadonte R, Kriegsmann M, Zweynert F, Friedrich K, Bretton G, Otto M, et al. Imaging mass spectrometry to discriminate breast from pancreatic cancer metastasis in formalin-fixed paraffin-embedded tissues. Proteomics. 2014;14:956–64.

    Article  CAS  Google Scholar 

  15. Casadonte R, Caprioli RM. Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc. 2011;6:1695–709.

    Article  CAS  Google Scholar 

  16. Lemaire R, Desmons A, Tabet J, Day R, Salzet M, Fournier I. Direct analysis and MALDI imaging of formalin-fixed, paraffin-embedded tissue sections. J Proteome Res. 2007;6:1295–305.

    Article  CAS  Google Scholar 

  17. Thavarajah R, Mudimbaimannar VK, Elizabeth J, Rao UK, Ranganathan K. Chemical and physical basics of routine formaldehyde fixation. J Oral Maxillofac Pathol. 2012;16:400–5.

    Article  Google Scholar 

  18. Fowler CB, Evers DL, O’Leary TJ, Mason JT. Antigen Retrieval Causes Protein Unfolding Evidence for a Linear Epitope Model of Recovered Immunoreactivity. J Histochem Cytochem. 2011;59:366–81.

    Article  CAS  Google Scholar 

  19. Diehl HC, Beine B, Elm J, Trede D, Ahrens M, Eisenacher M, et al. The challenge of on-tissue digestion for MALDI MSI—a comparison of different protocols to improve imaging experiments. Anal Bioanal Chem. 2015;407:2223–43.

    Article  CAS  Google Scholar 

  20. Hecht ES, Oberg AL, Muddiman DC. Optimizing mass spectrometry analyses: a tailored review on the utility of design of experiments. J Am Soc Mass Spectrom. 2016;27:767–85.

    Article  CAS  Google Scholar 

  21. Riter LS, Vitek O, Gooding KM, Hodge BD, Julian RK. Statistical design of experiments as a tool in mass spectrometry. J Mass Spectrom. 2005;40:565–79.

    Article  CAS  Google Scholar 

  22. Alexandrov T. MALDI imaging mass spectrometry: statistical data analysis and current computational challenges. BMC Bioinf. 2012;13:S11. doi:10.1186/1471-2105-13-S16-S11.

    CAS  Google Scholar 

  23. Alexandrov T, Bartels A. Testing for presence of known and unknown molecules in imaging mass spectrometry. Bioinformatics. 2013;29:2335–42.

    Article  CAS  Google Scholar 

  24. Palmer A, Ovchinnikova E, Thuné M, Lavigne R, Guével B, Dyatlov A, et al. Using collective expert judgements to evaluate quality measures of mass spectrometry images. Bioinformatics. 2015;31:i375–84.

    Article  CAS  Google Scholar 

  25. Montgomery DC. Design and analysis of experiments. John Wiley & Sons; 2008.

  26. Groseclose MR, Andersson M, Hardesty WM, Caprioli RM. Identification of proteins directly from tissue: in situ tryptic digestions coupled with imaging mass spectrometry. J Mass Spectrom. 2007;42:254–62.

    Article  CAS  Google Scholar 

  27. Groseclose MR, Massion PP, Chaurand P, Caprioli RM. High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics. 2008;8:3715–24.

    Article  CAS  Google Scholar 

  28. Gustafsson JO, Oehler MK, McColl SR, Hoffmann P. Citric acid antigen retrieval (CAAR) for tryptic peptide imaging directly on archived formalin-fixed paraffin-embedded tissue. J Proteome Res. 2010;9:4315–28.

    Article  CAS  Google Scholar 

  29. Deutskens F, Yang J, Caprioli RM. High spatial resolution imaging mass spectrometry and classical histology on a single tissue section. J Mass Spectrom. 2011;46:568–71.

    Article  CAS  Google Scholar 

  30. Schober Y, Schramm T, Spengler B, Rӧmpp A. Protein identification by accurate mass matrix-assisted laser desorption/ionization imaging of tryptic peptides. Rapid Commun Mass Spectrom. 2011;25:2475–83.

    Article  CAS  Google Scholar 

  31. Liebeke M, Strittmatter N, Fearn S, Morgan AJ, Kille P, Fuchser J, et al. Unique metabolites protect earthworms against plant polyphenols. Nat Commun. 2015. doi:10.1038/ncomms8869.

    Google Scholar 

  32. Lauzon N, Dufresne M, Chauhan V, Chaurand P. Development of laser desorption imaging mass spectrometry methods to investigate the molecular composition of latent fingermarks. J Am Soc Mass Spectrom. 2015;26:878–86.

    Article  CAS  Google Scholar 

  33. Mascini NE, Eijkel GB, ter Brugge P, Jonkers J, Wesseling J, Heeren RM. The use of mass spectrometry imaging to predict treatment response of patient-derived xenograft models of triple-negative breast cancer. J Proteome Res. 2015;14:1069–75.

    Article  CAS  Google Scholar 

  34. Kriegsmann J, Kriegsmann M, Casadonte R. MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review). Int J Oncol. 2015;46:893–906.

    Google Scholar 

  35. Balluff B, Elsner M, Kowarsch A, Rauser S, Meding S, Schuhmacher C, et al. Classification of HER2/neu status in gastric cancer using a breast-cancer derived proteome classifier. J Proteome Res. 2010;9:6317–22.

    Article  CAS  Google Scholar 

  36. Clough T, Braun S, Fokin V, Ott I, Ragg S, Schadow G, et al. Statistical design and analysis of label-free LC-MS proteomic experiments: a case study of coronary artery disease. Serum/Plasma Proteomics. 2011;293–319.

  37. Havlivs J, Thomas H, Sebela M, Shevchenko A. Fast-response proteomics by accelerated in-gel digestion of proteins. Anal Chem. 2003;75:1300–6.

    Article  Google Scholar 

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Acknowledgments

We would like to thank Olga Vitek for valuable discussions regarding the statistical design of experiments. The authors gratefully acknowledge the financial support from the European Commission Seventh Framework Program (project 3D-MASSOMICS, grant 305259), the German Science Foundation (DFG core facility MALDI-MULTI), and the German Central Innovation Program for SMEs of the German Federal Ministry of Economic Affairs and Energy (BMWI-ZIM grant 2443904SB4).

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Authors and Affiliations

  1. MALDI Imaging Lab, University of Bremen, Leobener Str./NW2 B2210, 28359, Bremen, Germany

    Janina Oetjen

  2. Center for Industrial Mathematics, University of Bremen, Bibliothekstraße 1, 28359, Bremen, Germany

    Delf Lachmund, Tobias Boskamp & Peter Maass

  3. Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstraße 1, 69117, Heidelberg, Germany

    Andrew Palmer & Theodore Alexandrov

  4. SCiLS GmbH, Fahrenheitstraße 1, 28359, Bremen, Germany

    Theodore Alexandrov, Tobias Boskamp & Peter Maass

  5. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, California, 92093, USA

    Theodore Alexandrov

  6. Bruker Daltonics GmbH, Fahrenheitstraße 4, 28359, Bremen, Germany

    Michael Becker

Authors
  1. Janina Oetjen
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  2. Delf Lachmund
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  3. Andrew Palmer
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  4. Theodore Alexandrov
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  5. Michael Becker
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  7. Peter Maass
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Corresponding author

Correspondence to Janina Oetjen.

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Conflict of interest

Theodore Alexandrov is the Scientific Director, Peter Maass is on the Advisory Board, and Tobias Boskamp is a consultant for SCiLS GmbH, a company that develops and markets software for imaging mass spectrometry. At the time of analysis, Michael Becker was employed at Bruker Daltonics GmbH, a vendor of mass spectrometry instrumentation. All other authors declare no conflict of interest.

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This article does not contain any studies with human participants. All animal care guidelines according to the German animal protection law were met.

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Oetjen, J., Lachmund, D., Palmer, A. et al. An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments. Anal Bioanal Chem 408, 6729–6740 (2016). https://doi.org/10.1007/s00216-016-9793-4

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  • DOI: https://doi.org/10.1007/s00216-016-9793-4

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