TY - JOUR
T1 - Two-dimensional analysis of plasma-derived extracellular vesicles to determine the HER2 status in breast cancer patients
AU - Wilhelm, Alexis
AU - Flynn, Charlotte
AU - Hammer, Evelyn
AU - Roessler, Johannes
AU - Haller, Bernhard
AU - Napieralski, Rudolf
AU - Leuthner, Moritz
AU - Tosheska, Sanja
AU - Knoops, Kèvin
AU - Mathew, Anjusha
AU - Ciarimboli, Giuliano
AU - Kranich, Jan
AU - Flaskamp, Lavinia
AU - King, Siobhan
AU - Gevensleben, Heidrun
AU - Emslander, Quirin
AU - Pastucha, Anna
AU - Reisbeck, Mathias
AU - Rief, Lukas
AU - Bronger, Holger
AU - Dreyer, Tobias
AU - Bausch, Andreas R.
AU - Pichlmair, Andreas
AU - Brocker, Thomas
AU - Zeidler, Reinhard
AU - Hammerschmidt, Wolfgang
AU - Piedavent-Salomom, Melanie
AU - López-Iglesias, Carmen
AU - Schricker, Gabrielle
AU - Haydn, Oliver
AU - Kiechle, Marion
AU - Grill, Sabine
AU - Heeren, Ron
AU - Knolle, Percy A.
AU - Wilhelm, Olaf
AU - Höchst, Bastian
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - 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 HER2pos 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.
AB - 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 HER2pos 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.
UR - https://www.scopus.com/pages/publications/105008111179
U2 - 10.1186/s13058-025-02056-z
DO - 10.1186/s13058-025-02056-z
M3 - Article
AN - SCOPUS:105008111179
SN - 1465-5411
VL - 27
JO - Breast Cancer Research
JF - Breast Cancer Research
IS - 1
M1 - 107
ER -
