Journal article
Classification of molecular subtypes of high-grade serous ovarian cancer by maldi-imaging
W Kassuhn, O Klein, S Darb-Esfahani, H Lammert, S Handzik, ET Taube, WD Schmitt, C Keunecke, D Horst, F Dreher, J George, DD Bowtell, O Dorigo, M Hummel, J Sehouli, N Blüthgen, H Kulbe, EI Braicu
Cancers | Published : 2021
Open access
Abstract
Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profile..
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Awarded by Deutsche Forschungsgemeinschaft
Funding Acknowledgements
W.K. is associated to the DFG funded Research Training Group (RTG) 2424/CompCancer. E.I.B. is a participant in the Charite Clinical Scientist Program funded by the Charite Universitatsmedizin Berlin and the Berlin Institute of Health (BIH). The study was supported by a research grant from Deutsche Krebshilfe (Code 70113336) and the BMBF (031L0220A MSTAR).