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| Item Type: | Article |
|---|---|
| Title: | Establishment and thorough characterization of xenograft (PDX) models derived from patients with pancreatic cancer for molecular analyses and chemosensitivity testing |
| Creators Name: | Behrens, D. and Pfohl, U. and Conrad, T. and Becker, M. and Brzezicha, B. and Büttner, B. and Wagner, S. and Hallas, C. and Lawlor, R. and Khazak, V. and Linnebacher, M. and Wartmann, T. and Fichtner, I. and Hoffmann, J. and Dahlmann, M. and Walther, W. |
| Abstract: | Patient-derived xenograft (PDX) tumor models are essential for identifying new biomarkers, signaling pathways and novel targets, to better define key factors of therapy response and resistance mechanisms. Therefore, this study aimed at establishing pancreas carcinoma (PC) PDX models with thorough molecular characterization, and the identification of signatures defining responsiveness toward drug treatment. In total, 45 PC-PDXs were generated from 120 patient tumor specimens and the identity of PDX and corresponding patient tumors was validated. The majority of engrafted PDX models represent ductal adenocarcinomas (PDAC). The PDX growth characteristics were assessed, with great variations in doubling times (4 to 32 days). The mutational analyses revealed an individual mutational profile of the PDXs, predominantly showing alterations in the genes encoding KRAS, TP53, FAT1, KMT2D, MUC4, RNF213, ATR, MUC16, GNAS, RANBP2 and CDKN2A. Sensitivity of PDX toward standard of care (SoC) drugs gemcitabine, 5-fluorouracil, oxaliplatin and abraxane, and combinations thereof, revealed PDX models with sensitivity and resistance toward these treatments. We performed correlation analyses of drug sensitivity of these PDX models and their molecular profile to identify signatures for response and resistance. This study strongly supports the importance and value of PDX models for improvement in therapies of PC. |
| Keywords: | Pancreas Carcinoma, PDX Models, In Vivo Chemosensitivity Testing, Molecular Profiling, Animals, Mice |
| Source: | Cancers |
| ISSN: | 2072-6694 |
| Publisher: | MDPI |
| Volume: | 15 |
| Number: | 24 |
| Page Range: | 5753 |
| Date: | 8 December 2023 |
| Official Publication: | https://doi.org/10.3390/cancers15245753 |
| PubMed: | View item in PubMed |
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