Analytical and Bioanalytical Chemistry

, Volume 408, Issue 24, pp 6729–6740 | Cite as

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

  • Janina Oetjen
  • Delf Lachmund
  • Andrew Palmer
  • Theodore Alexandrov
  • Michael Becker
  • Tobias Boskamp
  • Peter Maass
Research Paper


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.

Graphical abstract

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.


MALDI imaging MS Fractional design of experiments SOP 

Supplementary material

216_2016_9793_MOESM1_ESM.pdf (386 kb)
ESM 1(PDF 386 kb)
216_2016_9793_MOESM2_ESM.xlsx (35 kb)
ESM 2(XLSX 35 kb)


  1. 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.CrossRefGoogle Scholar
  2. 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.CrossRefGoogle Scholar
  3. 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.CrossRefGoogle Scholar
  4. 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.CrossRefGoogle Scholar
  5. 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.CrossRefGoogle Scholar
  6. 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.CrossRefGoogle Scholar
  7. 7.
    Reyzer ML, Caprioli RM. MALDI-MS-based imaging of small molecules and proteins in tissues. Curr Opin Chem Biol. 2007;11:29–35.CrossRefGoogle Scholar
  8. 8.
    Aichler M, Walch A. MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. Lab Invest. 2015;95:422–31.CrossRefGoogle Scholar
  9. 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.CrossRefGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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.CrossRefGoogle Scholar
  12. 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.CrossRefGoogle Scholar
  13. 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.CrossRefGoogle Scholar
  14. 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.CrossRefGoogle Scholar
  15. 15.
    Casadonte R, Caprioli RM. Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc. 2011;6:1695–709.CrossRefGoogle Scholar
  16. 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.CrossRefGoogle Scholar
  17. 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.CrossRefGoogle Scholar
  18. 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.CrossRefGoogle Scholar
  19. 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.CrossRefGoogle Scholar
  20. 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.CrossRefGoogle Scholar
  21. 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.CrossRefGoogle Scholar
  22. 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.Google Scholar
  23. 23.
    Alexandrov T, Bartels A. Testing for presence of known and unknown molecules in imaging mass spectrometry. Bioinformatics. 2013;29:2335–42.CrossRefGoogle Scholar
  24. 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.CrossRefGoogle Scholar
  25. 25.
    Montgomery DC. Design and analysis of experiments. John Wiley & Sons; 2008.Google Scholar
  26. 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.CrossRefGoogle Scholar
  27. 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.CrossRefGoogle Scholar
  28. 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.CrossRefGoogle Scholar
  29. 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.CrossRefGoogle Scholar
  30. 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.CrossRefGoogle Scholar
  31. 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. 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.CrossRefGoogle Scholar
  33. 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.CrossRefGoogle Scholar
  34. 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. 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.CrossRefGoogle Scholar
  36. 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.Google Scholar
  37. 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.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.MALDI Imaging LabUniversity of BremenBremenGermany
  2. 2.Center for Industrial MathematicsUniversity of BremenBremenGermany
  3. 3.Structural and Computational Biology UnitEuropean Molecular Biology LaboratoryHeidelbergGermany
  4. 4.SCiLS GmbHBremenGermany
  5. 5.Skaggs School of Pharmacy and Pharmaceutical SciencesUniversity of California San DiegoLa JollaUSA
  6. 6.Bruker Daltonics GmbHBremenGermany

Personalised recommendations