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Prof. Dr. Nicole Rotter

Immunotherapy for Head and Neck Cancer

We have a long-standing interest in 3D culture techniques for head and neck cancer (HNC) and in the establishment of preclinical oncological models to study immune cell/ TME/ tumor interactions in response to treatment.

Immuno-oncological questions are addressed by the employment of
(i) established heterotypic spheroids from patient-derived cancer and stromal cells,
(ii) ex vivo tissue cultures preserving the structural architecture and the TME using patient-derived explants,
(iii) and 3D scaffold-based organotypic co-culture models.

Current projects on HNC models focus on the role of signaling cascades in response to anti-PD-1/PD-L1 immunotherapy and the generation of ex vivo/ immune cell co-cultures. 3D models are characterized in more detail using live-cell imaging. Bioprinting enables rapid high-throughput generation of spatially consistent spheroids.

The models are proposed to function as an innovative experimental platform for future studies aiming to unravel molecular principles of EMT and cancer cell dissemination as well as proof-of-concept for new (immuno) therapeutic concepts.

We actively implement 3R principles (reduce, refine, replace animal research) by optimizing xeno-free culture conditions and step by step superseding animal models by cell culture and explant systems.

The aim is a rapid translation of HNC models into clinical application for drug testing, patient treatment stratification, and monitoring of treatment response.

Head and neck cancer 3D models to address immuno-oncological questions for personalized therapy approaches

(left panel) established heterotypic spheroids from patient-derived cancer and stromal cells,
(middle panel) ex vivo tissue cultures and 3D scaffold-based organotypic co-culture models (Engelmann et al., Cancers 2020, 12(8))
(right panel) bioprinted heterogenic (cancer cells and recapitulated TME) 3D models

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Parts of the figure were drawn by using pictures from Servier Medical Art (, licensed under a Creative Commons Attribution 3.0 Unported License (