MSACL 2019 EU Abstract

High-Throughput Analysis on FFPE Breast Cancer TMAs with DESI-MSI

Ólöf Gerdur Ísberg(1,2,4), Dipa Gurung(2), Hiromi Kudo(2), Paolo Inglese(2), Rathi Ramakrishnan(2), Jón G. Jónasson(3), Sigrídur Klara Bödvarsdóttir(4), Margrét Thorsteinsdóttir(1,4) and Zoltan Takats(2)
(1)Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavík, Iceland; (2)Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College, London, UK; (3)Department of Pathology, Landspitali University Hospital, Reykjavík, Iceland; (4)Biomedical Center, University of Iceland, Reykjavík, Iceland

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Olof Gerdur Isberg (Presenter) University of Iceland

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Introduction: Today, most pathological tissue samples are stored as formalin-fixed paraffin embedded (FFPE) tissue blocks, which is the gold standard for histopathological analysis. This form preserves the tissue very well as formalin fixation forms methylene cross-bridges between proteins. Additionally, by paraffin embedding the tissue it allows for indefinite storage at room temperature so there are a number of large FFPE tissue archives around the world. Tissue microarrays (TMAs) is one of the most important forms of FFPE categories. TMAs are blocks that contain tissue cores from multiple sources in an array which allows for high-throughput analysis of many tissue samples. Mass spectrometry imaging (MSI) is a powerful tool that enables us to investigate the regional distribution of a variety of molecules in biological samples. It is crucial to have knowledge of the spatial distribution of biomolecules to understand the biological processes that take place within the tissues. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI). particularly suited to investigate the spatial distribution of metabolites. Metabolite measurements are growing in importance as altered metabolism is a hallmark of many diseases, such as cancer. Currently, fresh frozen (FF) samples are preferred over FFPE samples in tissue based MSI studies. This is primarily due to the concern that small molecules will be lost during fixation and chemical processing as well as the belief that that paraffin will cause ion suppression.
Methods: Breast cancer tissue was obtained from approximately 30 breast cancer patients undergoing mastectomy as well as normal control tissue was acquired from around 20 individuals. The tissue samples were formalin fixed and paraffin embedded (FFPE). Tissue microarrays (TMAs) cores from regions of interest were collected from the FFPE tissue samples, inserted in a recipient paraffin block and stored at room temperature. TMAs were dewaxed and spectra was collected for area of interest using DESI MSI. Following DESI-MSI, the TMAs slides were haematoxylin and eosin (H&E) stained for histopathological validation. Data analysis was performed using a new in-house toolbox where areas of interest were annotated. Additionally multivariate and univariate analysis were performed.
Results: DESI-MSI analysis was performed on FFPE TMAs from approximately 30 breast cancer samples and around 20 normal breast tissue samples. Most metabolites detected were small metabolites in the range 50-500 m/z for both positive and negative mode.
Conclusions: Our results indicate that DESI-MSI shows a potential to differentiate between different FFPE breast tissue types based on their metabolic profile. Additionally, our results show that inspite of formalin-fixation and paraffin embedding of the tissue we still have enough information to characterize the tissue.