Naomi Vos (Presenter)
M4I division of IMS, Maastricht University
Bio: My name is Naomi Vos and I am doing my PhD at The Maastricht Multimodal Molecular Imaging Institute (M4I) at Maastricht University in the Netherlands. My research focuses on 3D Pathology and my goal is to acquire 3D mass spectrometry images from human cancer resections. This data will then be used to asses the benefit of 3D imaging over 2D imaging for pathology. Furthermore I hope to find interesting results within a dataset and/or between datasets to also contribute to the clinical research done on the types of cancers I am imaging.
Authorship: D.R.N. Vos (1), I. Jansen (2), M. Lucas (3), M.R.L. Paine (1), B. Balluff (1), O. Boer (4), S. Meijer (4), D. Savci (4), H. Marquering (3), D.M. de Bruin (2), R.M.A Heeren (1) and S.R. Ellis (1)
(1) The Maastricht Multimodal Molecular Imaging Institute (M4I), Maastricht University, 6229 ER Maastricht, The Netherlands (2) Department of Urology and Department of Biomedical Engineering & Physics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands (3) Department of Biomedical Engineering & Physics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands (4) Department of Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
Currently 2D MSI methods provide only a small snapshot of the chemical state of bulk tissue. Currently almost all 3D-MSI studies have been performed on lipids primarily due to their ease of detection and reproducible sample preparation requirements. However FFPE tissues, such as those stored in large biobanks worldwide, are not amenable to lipid analysis but instead require careful sample treatment to enable detection of tryptic peptides. We demonstrate among the first reports of 3D peptide MALDI-MSI of FFPE tissues. Bladder cancer resections from 11 patients were studied with MSI enabling both inter- and intra-tumour heterogeneity to be visualised in 3-dimensions.
Mass spectrometry imaging (MSI) has emerged as a powerful tool to both structurally characterise and reveal the localisation of biomolecules in tissues in a label-free manner. MSI is finding rapid use as a clinical tool to diagnose diseased tissues based on their localised chemical content. Most often MSI is deployed as a 2-dimensional (2D) image technique; however this can pose limitations when studying typically heterogeneous tissues as a complete overview of the 3D context of the tissue is not obtained. With recent improvements in acquisition speed and data analysis 3D MSI is coming to the forefront whereby data from multiple 2D sections is combined into a 3D volume. Currently almost all 3D-MSI studies have been performed on lipids primarily due to their ease of detection and reproducible sample preparation requirements. However FFPE tissues, such as those stored in large biobanks worldwide, are not amenable to lipid analysis but instead require careful sample treatment to enable detection of tryptic peptides. In this work we present results acquired following 3D-MSI of eleven human bladder cancer resection specimens to study the underlying inter- and intra-tumour molecular heterogeneity in the full 3D context of the specimen. The results demonstrate on the first report of 3D-MSI of tryptic peptides from FFPE tissues.
Human FFPE bladder cancer resection specimens from eleven patients were collected, sectioned with a thickness of 5 µm and mounted on indium tin oxide-coated conductive glass slides. Adjacent sections were collected for hematoxylin and eosin (H&E) staining and histological annotation. After deparaffinization and antigen retrieval, porcine trypsin was applied and the sections were incubated for 17 hours. Afterwards, α-Cyano-4-hydroxycinnamic acid (CHCA) matrix was applied before acquisition of MSI data. Both the trypsin and CHCA matrix were applied with a SunCollect pneumatic sprayer (SunChrom GmbH, Germany). On all slides an intact Cytochrome C standard was deposited to evaluate the efficiency of the trypsin digestion and on every third slide a peptide calibration mixture was applied to monitor the quality of the matrix application.
All tissues were imaged at 50 µm spatial resolution on a RapifleX MALDiToF/ToF instrument (Bruker Daltonik GmbH, Bremen, Germany) across an m/z range of m/z 800-3000. 1000 laser shots per pixel were summed. In total 11 datasets were imaged each consisting of 20 sections spaced 10 µm apart. Data analysis and 3D visualization was performed using SCiLS software (SCiLS GmbH, Bremen, Germany). Identification of peptides was performed using on-tissue tandem mass spectrometry on a MALDI-enabled Orbitrap Elite (Thermo Fisher, Bremen, Germany). The combined preparation and acquisition time for each 3D dataset was on average 25 hours.
Using on-tissue peptide signal combined with the quality controls for digestion and matrix application the developed sample preparation method was shown to be robust and reproducible. Multivariate analysis was used to segment the different tissue regions based on their unique proteome. For this probabilistic latent semantic (pLSA) analysis was chosen consisting of 10 components. Co-registration of MSI data with annotated tissues by trained pathologist facilitated correlation of tumour and non-tumour regions to specific molecular patterns. Furthermore, across many datasets common molecular fingerprints were found for the tumour. While interestingly some key differences between tumour regions of a subset of tissues were also observed, highlighting the inherent inter-tumour heterogeneity. A significant observation made in this study is that via 3D-MSI molecular changes occurring within individual tumours in 3-dimensions can be revealed, information that is generally missed in conventional 2-dimensional approaches and that may enable a more accurate chemical understanding and diagnosis of bulk tissue specimens.
Conclusions & Discussion
We demonstrate among the first reports of 3D peptide MALDI-MSI of FFPE tissues. The developed protocol was applied to bladder cancer resections from 11 patients and found to be reproducible with high quality MSI data coming from 80 % of the analysed 220 tissues. This enabled both inter- and intra-tumour heterogeneity to be visualised in 3-dimensions and paves the way for rapid 3D-MSI of FFPE tissues.
References & Acknowledgements:
This work has been made possible with the financial support of the Dutch province of Limburg and has been funded by ITEA and RVO by means of project numbers ITEA151003/ITEA 14001.
IP Royalty: no
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