= Emerging. More than 5 years before clinical availability. (9.82%)
= Expected to be clinically available in 1 to 4 years. (12.95%)
= Clinically available now. (22.77%)
MSACL 2018 EU : Ísberg

MSACL 2018 EU Abstract

Topic: Tissue Imaging

Podium Presentation in the Ether on Wednesday at 9:20 (Chair: Vladimir Frankevich)

Identifying Biomarkers in FFPE Breast TMAs Using DESI-MSI

Ólöf Gerdur Ísberg (Presenter)
University of Iceland

Presenter Bio(s): I finished a bachelor´s degree in biochemistry in 2012 from University of Iceland. My thesis title was “The role of DNA methylation in epithelial to mesenchymal transition (EMT) in breast epithelial stem cells” and was carried out at a Stem Cell Research Unit at University of Iceland. My thesis work increased my interest for research and molecular biology and therefore, I applied to study M.Sc. in Human biology at University of Copenhagen, Denmark. The M.Sc. in Human Biology is part of the Copenhagen Master of Excellence (COME) program and is one of the Danish elite master´s degrees designed to challenge students at the highest academic level. It is a highly research oriented 2-year interdisciplinary program, offering advanced theoretical and experimental training within the fields of biomedical and natural sciences. I performed my thesis project “Characterization of CD146 as a progenito

Authors: Ólöf Gerdur Ísberg (1-3), Renata Soares (2), James McKenzie (2), Dipa Gurung (2), Hiromi Kudo (2), Rathi Ramakrishnan (2), Jón G Jónasson (4), Sigrídur Klara Bödvarsdóttir (3), Margrét Thorsteinsdóttir (1) 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) Biomedical Center, University of Iceland, Reykjavik, Iceland; (4) Department of Pathology, Landspitali-University Hospital, Reykjavík, Iceland.


Breast cancer is one of the most common cancers in the world among females and accounts for 25% of all cancers. DESI-MSI is a powerful tool to investigate the spatial distribution of biomolecules in tissue sections. The distribution of biomolecules such as metabolites can be correlated with clinicopathological information of tissue samples and thus providing essential information for clinical diagnosis. The project aim was to metabolic phenotype FFPE TMA slides of 30 breast cancer samples and 30 normal samples using DESI-MSI. Preliminary results report that DESI-MSI can discriminate between malignant and normal tissue.

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