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Round robin study of formalin-fixed paraffin-embedded tissues in mass spectrometry imaging

Authors :
Corinna Henkel
Birte Beine
Achim Buck
Liam A. McDonnell
Alberto Cassese
Axel Walch
Bram Heijs
Benjamin Balluff
Ron M. A. Heeren
Jan Schepers
FPN Methodologie & Statistiek
RS: FPN M&S I
Imaging Mass Spectrometry (IMS)
RS: M4I - Imaging Mass Spectrometry (IMS)
Source :
Analytical and Bioanalytical Chemistry, Anal. Bioanal. Chem. 410, 5969–5980 (2018), Analytical and Bioanalytical Chemistry, 410(23). Springer, Analytical and Bioanalytical Chemistry, 410(23), 5969-5980
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

Mass spectrometry imaging (MSI) has provided many results with translational character, which still have to be proven robust in large patient cohorts and across different centers. Although formalin-fixed paraffin-embedded (FFPE) specimens are most common in clinical practice, no MSI multicenter study has been reported for FFPE samples. Here, we report the results of the first round robin MSI study on FFPE tissues with the goal to investigate the consequences of inter- and intracenter technical variation on masking biological effects. A total of four centers were involved with similar MSI instrumentation and sample preparation equipment. A FFPE multi-organ tissue microarray containing eight different types of tissue was analyzed on a peptide and metabolite level, which enabled investigating different molecular and biological differences. Statistical analyses revealed that peptide intercenter variation was significantly lower and metabolite intercenter variation was significantly higher than the respective intracenter variations. When looking at relative univariate effects of mass signals with statistical discriminatory power, the metabolite data was more reproducible across centers compared to the peptide data. With respect to absolute effects (cross-center common intensity scale), multivariate classifiers were able to reach on average > 90% accuracy for peptides and > 80% for metabolites if trained with sufficient amount of cross-center data. Overall, our study showed that MSI data from FFPE samples could be reproduced to a high degree across centers. While metabolite data exhibited more reproducibility with respect to relative effects, peptide data-based classifiers were more directly transferable between centers and therefore more robust than expected. Graphical abstractᅟ Electronic supplementary material The online version of this article (10.1007/s00216-018-1216-2) contains supplementary material, which is available to authorized users.

Details

ISSN :
16182650 and 16182642
Volume :
410
Database :
OpenAIRE
Journal :
Analytical and Bioanalytical Chemistry
Accession number :
edsair.doi.dedup.....5e23aae8165d9eb5451f71679806baeb