How Suitable is Matrix-Assisted Laser Desorption/Ionization-Time-of-Flight for Metabolite Imaging from Clinical Formalin-Fixed and Paraffin-Embedded Tissue Samples in Comparison to Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance Mass Spectrometry?

In research and clinical settings, formalin-fixed and paraffin-embedded (FFPE) tissue specimens are collected routinely and therefore this material constitutes a highly valuable source to gather insight in metabolic changes of diseases. Among mass spectrometry techniques to examine the molecular content of FFPE tissue, mass spectrometry imaging (MSI) is the most appropriate when morphological and histological features are to be related to metabolic information. Currently, high-resolution mass spectrometers are widely used for metabolomics studies. However, with regards to matrix-assisted laser desorption/ionization (MALDI) MSI, no study has so far addressed the necessity of instrumental mass resolving power in terms of clinical diagnosis and prognosis using archived FFPE tissue. For this matter we performed for the first time a comprehensive comparison between a high mass resolution Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer and a time-of-flight (TOF) instrument with lower mass resolving power. Spectra analysis revealed that about one-third of the detected peaks remained unresolved by MALDI-TOF, which led to a 3-5 times lower number of m/z features compared to FTICR measurements. Overlaid peak information and background noise in TOF images made a precise assignment of molecular attributes to morphological features more difficult and limited classification approaches. This clearly demonstrates the need for high-mass resolution capabilities for metabolite imaging. Nevertheless, MALDI-TOF allowed reproducing and verifying individual markers identified previously by MALDI-FTICR MSI. The systematic comparison gives rise to a synergistic combination of the different MSI platforms for high-throughput discovery and validation of biomarkers.