An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments
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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.
KeywordsMALDI imaging MS Fractional design of experiments SOP
- 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
- 25.Montgomery DC. Design and analysis of experiments. John Wiley & Sons; 2008.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
- 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