Patient-derived xenograft models of gastrointestinal stromal tumors provide a ready-to-use platform for translational research.

IF 4 3区 医学 Q2 CELL BIOLOGY
Disease Models & Mechanisms Pub Date : 2025-02-01 Epub Date: 2025-02-21 DOI:10.1242/dmm.052225
Luna De Sutter, Lore De Cock, Chao-Chi Wang, Daniël Gorgels, Karo Wyns, Kimberly Verbeeck, Ulla Vanleeuw, Thomas Douchy, Daphne Hompes, Joris Jaekers, Dirk Van Raemdonck, Isabelle Vanden Bempt, Maria Debiec-Rychter, Raf Sciot, Agnieszka Wozniak, Patrick Schöffski
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引用次数: 0

Abstract

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal malignancy of the gastrointestinal tract. Most GISTs harbor mutations in oncogenes, such as KIT, and are treated with tyrosine kinase inhibitors (TKIs), such as imatinib. Most tumors develop secondary mutations, inducing drug resistance against the available TKIs, requiring novel therapies. We established a GIST patient-derived xenograft (PDX) platform of GIST that can be used for preclinical drug testing. Tumor tissue from consenting GIST patients was transplanted subcutaneously to NMRI nu/nu mice. Once tumor growth was observed, the tumor was re-transplanted to a next generation of mice. Tumors were characterized histopathologically and molecularly at every re-transplantation and compared with the original patient tumor. We transplanted 112 tumor samples from 99 GIST patients, resulting in 12 established and well-characterized GIST models with different mutations and TKI sensitivity. Three models harbor secondary KIT mutations. One model is characterized by a primary, imatinib-resistant PDGFRA exon 18 p.D842V mutation. Our established platform of well-characterized GIST PDX models, covering the most relevant driver mutations, serves as an excellent tool for preclinical drug testing and tumor biology studies.

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来源期刊
Disease Models & Mechanisms
Disease Models & Mechanisms 医学-病理学
CiteScore
6.60
自引率
7.00%
发文量
203
审稿时长
6-12 weeks
期刊介绍: Disease Models & Mechanisms (DMM) is an online Open Access journal focusing on the use of model systems to better understand, diagnose and treat human disease.
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