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Patient-derived xenograft models in cancer therapy: technologies and applications
Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, P...
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Published in: | Signal transduction and targeted therapy 2023-04, Vol.8 (1), p.160-160, Article 160 |
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description | Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies. |
doi_str_mv | 10.1038/s41392-023-01419-2 |
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Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. 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The Author(s).</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>37045827</pmid><doi>10.1038/s41392-023-01419-2</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 631/67/1059 631/67/70 Animals Cancer Cancer Research Cancer therapies Cell Biology Chemotherapy Clinical trials Deep learning Drug resistance Heterografts Humans Immunotherapy Internal Medicine Medicine Medicine & Public Health Mice Neoplasms - drug therapy Neoplasms - genetics Oncology Pathology Patients Review Review Article Xenografts |
title | Patient-derived xenograft models in cancer therapy: technologies and applications |
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