Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time
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.
Authors
- Christian Klenk
- Daniele Lucarelli
- Stefan Röhrl (ORCID: https://orcid.org/0000-0001-6277-3816)
- Stefanie Bärthel (ORCID: https://orcid.org/0000-0001-5986-4864)
- David Fresacher (ORCID: https://orcid.org/0000-0002-7650-8033)
- Aristeidis Papargyriou (ORCID: https://orcid.org/0000-0002-2577-4737)
- Manuel Lengl (ORCID: https://orcid.org/0000-0001-8763-6201)
- H. Carlo Maurer (ORCID: https://orcid.org/0000-0002-2193-6014)
- Oliver Hayden (ORCID: https://orcid.org/0000-0002-2678-8663)
- Rupert Öllinger (ORCID: https://orcid.org/0000-0002-2292-5982)
- Felix Orben (ORCID: https://orcid.org/0000-0002-2196-8702)
- Farid Harb
- Bernhard Küster (ORCID: https://orcid.org/0000-0002-9094-1677)
- Tobias Lahmer (ORCID: https://orcid.org/0000-0003-1008-5311)
- Nawal Hafez (ORCID: https://orcid.org/0000-0002-0346-1588)
- Maximilian Reichert (ORCID: https://orcid.org/0000-0002-8611-5639)
- Klaus Diepold (ORCID: https://orcid.org/0000-0003-0439-7511)
- Joanna Madej
- Roland Rad (ORCID: https://orcid.org/0000-0002-6849-9659)
- Günter Schneider (ORCID: https://orcid.org/0000-0003-1840-4508)
- Lisa Fricke
- İhsan Ekin Demir (ORCID: https://orcid.org/0000-0001-8241-1871)
- Dieter Saur (ORCID: https://orcid.org/0000-0001-5874-0210)
- Ellen Emken (ORCID: https://orcid.org/0009-0009-6208-9737)
- Patrick Wustrow
- Roland M. Schmid (ORCID: https://orcid.org/0000-0002-5751-7313)
- Aditi Shastri
- Laura Schmidleitner (ORCID: https://orcid.org/0000-0002-0801-9860)
- Helmut Friess
- Nicole Kabella (ORCID: https://orcid.org/0000-0002-1901-2488)
- Katja Wittenzellner
- Carmen Escorial-Iriarte
Institutions
- Translational Genomics Research Institute (US)
- German Cancer Research Center (DE)
- Center for Integrated Protein Science Munich (DE)
- Heidelberg University (DE)
- TUM Klinikum (DE)
- Pancreatic Cancer Action (GB)
- Helmholtz Zentrum München (DE)
- Bioanalytica (Switzerland) (CH)
- Translational Research in Oncology (FR)
- Universitätsmedizin Göttingen (DE)
- Institute of Clinical Cancer Research (DE)
- DKFZ-ZMBH Alliance (DE)
- Heinz Nixdorf Stiftung (DE)
- Isotopen Technologien München (Germany) (DE)
- Data:Lab Munich (Germany) (DE)
- National Assembly (KR)
- Technical University of Munich (DE)
Publication Details
- Journal
- JCI Insight
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1172/jci.insight.169105
- Citations
- 2
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- Wilhelm Sander-Stiftung
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Deutsche Krebshilfe
- Bayerisches Staatsministerium für Wirtschaft und Medien, Energie und Technologie
- Deutschen Konsortium für Translationale Krebsforschung
- Bayerische Staatsministerium für Wirtschaft, Landesentwicklung und Energie