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Wilhelm, A.D.* ; Flynn, C.* ; Hammer, E.* ; Rössler, J. ; Haller, B.* ; Napieralski, R.* ; Leuthner, M.* ; Tosheska, S.* ; Knoops, K.* ; Mathew, A.* ; Ciarimboli, G.* ; Kranich, J.* ; Flaskamp, L.* ; King, S.* ; Gevensleben, H.* ; Emslander, Q.* ; Pastucha, A.* ; Reisbeck, M.* ; Rief, L.* ; Bronger, H.* ; Dreyer, T.* ; Bausch, A.R.* ; Pichlmair, A.* ; Brocker, T.* ; Zeidler, R. ; Hammerschmidt, W. ; Piedavent-Salomom, M.* ; López-Iglesias, C.* ; Schricker, G.* ; Haydn, O.* ; Kiechle, M.* ; Grill, S.W.* ; Heeren, R.* ; Knolle, P.A.* ; Wilhelm, O.* ; Höchst, B.*

Two-dimensional analysis of plasma-derived extracellular vesicles to determine the HER2 status in breast cancer patients.

Breast Cancer Res. 27:107 (2025)

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	Open Access Gold

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Breast cancer, one of the most common cancers in women, is classified by the expression of hormone receptors and the growth factor receptor HER2, which is important for personalised tumour treatment with HER2-targeted therapies. Tumour biopsies are required for histopathological diagnosis of HER2 expression by breast cancer cells but are subject to sampling error. In this study, we present a method for identifying and analysing cancer-derived EVs from plasma for the detection of HER2 expression in breast cancer without the need for additional processing steps. We detected nano-sized particles through an optimised flow cytometry approach that allows for the identification of HER2-expressing EVs and quantification of their HER2 expression levels. In a clinical study of 115 breast cancer patients, this optimised flow cytometric analysis detected a range of 1.3 to 50 × 10³ HER2⁺EVs per µl of plasma. The number of HER2⁺EVs did not correlate directly with tumour size, grade, or metastasis. However, computational integration of data from the quantification of HER2^pos EVs per µl/plasma and their HER2 expression levels on a single EV basis allowed for the reliable identification of HER2 expression levels in tumours. Our results reveal the potential for analysing cancer-derived EVs from plasma for the diagnosis and personalised therapy in breast cancer patients.

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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

Keywords Biogenesis; Prognosis; Exosomes; Subtypes; Impact

ISSN (print) / ISBN 1465-5411

e-ISSN 1465-542X

Journal Breast Cancer Research

Quellenangaben Volume: 27, Issue: 1, Article Number: 107

Publisher BioMed Central

Publishing Place Campus, 4 Crinan St, London N1 9xw, England

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Research Unit Gene Vector (AGV)
Institute of Structural Biology (STB)

Grants Bundesministerium fr Bildung und Forschung