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Wittenzellner, K.* ; Lengl, M.* ; Röhrl, S.* ; Maurer, C.* ; Klenk, C.* ; Papargyriou, A. ; Schmidleitner, L.* ; Kabella, N.* ; Shastri, A.R.* ; Fresacher, D.E.* ; Harb, F.* ; Hafez, N.* ; Bärthel, S.* ; Lucarelli, D.* ; Escorial-Iriarte, C.* ; Orben, F.* ; Öllinger, R.* ; Emken, E.* ; Fricke, L.* ; Madej, J.* ; Wustrow, P.* ; Ekin Demir, I.* ; Friess, H.* ; Lahmer, T.* ; Schmid, R.M.* ; Rad, R.* ; Schneider, G.* ; Kuster, B.* ; Saur, D.* ; Hayden, O.* ; Diepold, K.* ; Reichert, M.

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

JCI insight 10:e169105 (2025)
Verlagsversion Forschungsdaten DOI
Open Access Gold
Creative Commons Lizenzvertrag
Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plasticity and clonal diversity. To develop alternative strategies to overcome this defined mechanism of resistance, tools to monitor and quantify ITH in a rapid and scalable fashion are needed urgently. Here, we employed label-free digital holographic microscopy (DHM) to characterize ITH in PDAC. We established a robust experimental and machine learning analysis pipeline to perform single-cell phenotyping based on DHM-derived phase images of PDAC cells in suspension. Importantly, we were able to detect dynamic changes in tumor cell differentiation and heterogeneity of distinct PDAC subtypes upon induction of epithelial-mesenchymal transition and under treatment-imposed pressure in murine and patient-derived model systems. This platform allowed us to assess phenotypic ITH in PDAC on a single-cell level in real time. Implementing this technology into the clinical workflow has the potential to fundamentally increase our understanding of tumor heterogeneity during evolution and treatment response.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Ductal Adenocarcinoma; Subtypes; Survival
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 2379-3708
e-ISSN 2379-3708
Zeitschrift JCI insight
Quellenangaben Band: 10, Heft: 13, Seiten: , Artikelnummer: e169105 Supplement: ,
Verlag Clarivate
Verlagsort Ann Arbor, Michigan
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Stem Cell Research (ISF)
POF Topic(s) 30204 - Cell Programming and Repair
Forschungsfeld(er) Stem Cell and Neuroscience
PSP-Element(e) G-500800-001
Förderungen BZKF Lighthouse Project: "Preclinical Model Systems"
Deutsche Krebshilfe
Wilhelm Sander Stiftung
German Cancer Aid
Bavarian Ministry of Economic Affairs, Regional Development and Energy
Project EISglobe
Federal Ministry of Education and Research
QuE-MRT
FAIRPACT
DKTK Strategic Initiative Organoid Platform
DFG
DOI 10.1172/jci.insight.169105
WOS ID 001529047000001
Scopus ID 105010689411
Erfassungsdatum 2025-07-22
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