Micrometastasis-derived models enable drug testing for early-stage, high-risk melanoma patients

Relapse in melanoma after targeted or immune therapy necessitates the rapid identification of effective alternatives. To address this gap, we investigated whether the timely generation of preclinical models for functional drug testing could reveal additional therapeutic options. Our study focused on: (i) the feasibility of generating in vivo and in vitro models from melanoma lymph node (LN)-derived disseminated cancer cells (DCCs) before relapse, (ii) the implementation of preclinical models to identify therapeutic alternatives, and (iii) the ability to detect patients who could benefit from early functional in vitro drug testing. Successful model generation was significantly associated with DCC quantity, LN origin, and mortality risk. All patient-derived xenograft models were available before patient death and, in 82% of cases, before relapse. Proof-of-concept in vitro drug screening using 315 anti-cancer drugs identified additional candidates, and coculture of DCCs and LN cells revealed specific T-cell activation and responses to immunotherapy. Our data establish a process for selecting melanoma patients at high risk of progression, enabling the timely generation of patient-derived models to support functionally guided treatment decisions at relapse.

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Publication Details

Journal
EMBO Molecular Medicine
Published
2025-12-05
DOI
https://doi.org/10.1038/s44321-025-00339-8
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.00

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article

Micrometastasis-derived models enable drug testing for early-stage, high-risk melanoma patients

Sebastian Haferkamp, Hedayatollah Hosseini, Christian Werno, Parvaneh Mohammadi et al.
EMBO Molecular Medicine
Cancer Cells and Metastasis
article

Micrometastasis-derived models enable drug testing for early-stage, high-risk melanoma patients

Sebastian Haferkamp, Hedayatollah Hosseini, Christian Werno, Parvaneh Mohammadi, Adithi R. Varadarajan, Kathrin Weidele, Silvia Materna‐Reichelt, Jens Warfsmann, Sebastian Scheitler, Florian Weber, Melanie Werner‐Klein, Zbigniew T. Czyż, Christoph A. Klein, Kamran Honarnejad, Catherine Botteron, Steffi Treitschke, Laura Schreieder, Lukas Wöhrl, Marie Katzer, Martin Hoffmann, Giancarlo Feliciello
article en

Abstract

Relapse in melanoma after targeted or immune therapy necessitates the rapid identification of effective alternatives. To address this gap, we investigated whether the timely generation of preclinical models for functional drug testing could reveal additional therapeutic options. Our study focused on: (i) the feasibility of generating in vivo and in vitro models from melanoma lymph node (LN)-derived disseminated cancer cells (DCCs) before relapse, (ii) the implementation of preclinical models to identify therapeutic alternatives, and (iii) the ability to detect patients who could benefit from early functional in vitro drug testing. Successful model generation was significantly associated with DCC quantity, LN origin, and mortality risk. All patient-derived xenograft models were available before patient death and, in 82% of cases, before relapse. Proof-of-concept in vitro drug screening using 315 anti-cancer drugs identified additional candidates, and coculture of DCCs and LN cells revealed specific T-cell activation and responses to immunotherapy. Our data establish a process for selecting melanoma patients at high risk of progression, enabling the timely generation of patient-derived models to support functionally guided treatment decisions at relapse.

EMBO Molecular MedicineVol. 18(1)
University Hospital Regensburg (DE), Fraunhofer Institute for Toxicology and Experimental Medicine (DE), University of Regensburg (DE)
Deutsche Forschungsgemeinschaft, Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst, Deutsche Krebshilfe
Openalex Percentile: Top 46%
Cancer Cells and Metastasis
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