Strategies for managing multi-patient 3D mass spectrometry imaging data

Mass spectrometry imaging (MSI) has emerged as a powerful tool in biomedical research to reveal the localization of a broad scale of compounds ranging from metabolites to proteins in diseased tissues, such as malignant tumors. MSI is most commonly used for the two-dimensional imaging of tissues from...

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Veröffentlicht in:Journal of proteomics Jg. 193; S. 184 - 191
Hauptverfasser: Vos, D.R.N., Jansen, I., Lucas, M., Paine, M.R.L., de Boer, O.J., Meijer, S.L., Savci-Heijink, C.D., Marquering, H.A., de Bruin, D.M., Heeren, R.M.A., Ellis, S.R., Balluff, B.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Netherlands Elsevier B.V 20.02.2019
Schlagworte:
3-dimensional
biomarkers
biomedical research
Bladder cancer
Cohort Studies
desorption
Female
Formalin-fixed paraffin-embedded tissue
histology
Humans
image analysis
Imaging, Three-Dimensional
ionization
Male
mass spectrometry
Mass spectrometry imaging
metabolites
Neoplasm Proteins - metabolism
patients
proteins
Sampling bias
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
urinary bladder neoplasms
Urinary Bladder Neoplasms - diagnostic imaging
Urinary Bladder Neoplasms - metabolism
variance
Sampling bias
3-dimensional
Bladder cancer
Mass spectrometry imaging
Formalin-fixed paraffin-embedded tissue
ISSN:1874-3919, 1876-7737, 1876-7737
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Zusammenfassung:Mass spectrometry imaging (MSI) has emerged as a powerful tool in biomedical research to reveal the localization of a broad scale of compounds ranging from metabolites to proteins in diseased tissues, such as malignant tumors. MSI is most commonly used for the two-dimensional imaging of tissues from multiple patients or for the three-dimensional (3D) imaging of tissue from a single patient. These applications are potentially introducing a sampling bias on a sample or patient level, respectively. The aim of this study is therefore to investigate the consequences of sampling bias on sample representativeness and on the precision of biomarker discovery for histological grading of human bladder cancers by MSI. We therefore submitted formalin-fixed paraffin-embedded tissues from 14 bladder cancer patients with varying histological grades to 3D analysis by matrix-assisted laser desorption/ionization (MALDI) MSI. We found that, after removing 20% of the data based on novel outlier detection routines for 3D-MSI data based on the evaluation of digestion efficacy and z-directed regression, on average 33% of a sample has to be measured in order to obtain sufficient coverage of the existing biological variance within a tissue sample. In this study, 3D MALDI-MSI is applied for the first time on a cohort of bladder cancer patients using formalin-fixed paraffin-embedded (FFPE) tissue of bladder cancer resections. This work portrays the reproducibility that can be achieved when employing an optimized sample preparation and subsequent data evaluation approach. Our data shows the influence of sampling bias on the variability of the results, especially for a small patient cohort. Furthermore, the presented data analysis workflow can be used by others as a 3D FFPE data-analysis pipeline working on multi-patient 3D-MSI studies. [Display omitted] •This is the first multi-patient 3D-mass spectrometry imaging study•It is also the first 3D-mass spectrometry imaging study on formalin-fixed paraffin-embedded tissues•Novel outlier detection routines have been established for 3D-mass spectrometry imaging sample preparation•Consequences of sampling bias on biomarker discovery and sample representativeness have been investigated
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:1874-3919
1876-7737
1876-7737
DOI:10.1016/j.jprot.2018.10.008