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Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study
Predicting the clinical response to chemotherapeutic or targeted treatment in patients with locally advanced or metastatic lung cancer requires an accurate and affordable tool. Tumor organoids are a potential approach in precision medicine for predicting the clinical response to treatment. However,...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975107/ https://www.ncbi.nlm.nih.gov/pubmed/36657446 http://dx.doi.org/10.1016/j.xcrm.2022.100911 |
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author | Wang, Han-Min Zhang, Chan-Yuan Peng, Kai-Cheng Chen, Ze-Xin Su, Jun-Wei Li, Yu-Fa Li, Wen-Feng Gao, Qing-Yun Zhang, Shi-Ling Chen, Yu-Qing Zhou, Qing Xu, Cong Xu, Chong-Rui Wang, Zhen Su, Jian Yan, Hong-Hong Zhang, Xu-Chao Chen, Hua-Jun Wu, Yi-Long Yang, Jin-Ji |
author_facet | Wang, Han-Min Zhang, Chan-Yuan Peng, Kai-Cheng Chen, Ze-Xin Su, Jun-Wei Li, Yu-Fa Li, Wen-Feng Gao, Qing-Yun Zhang, Shi-Ling Chen, Yu-Qing Zhou, Qing Xu, Cong Xu, Chong-Rui Wang, Zhen Su, Jian Yan, Hong-Hong Zhang, Xu-Chao Chen, Hua-Jun Wu, Yi-Long Yang, Jin-Ji |
author_sort | Wang, Han-Min |
collection | PubMed |
description | Predicting the clinical response to chemotherapeutic or targeted treatment in patients with locally advanced or metastatic lung cancer requires an accurate and affordable tool. Tumor organoids are a potential approach in precision medicine for predicting the clinical response to treatment. However, their clinical application in lung cancer has rarely been reported because of the difficulty in generating pure tumor organoids. In this study, we have generated 214 cancer organoids from 107 patients, of which 212 are lung cancer organoids (LCOs), primarily derived from malignant serous effusions. LCO-based drug sensitivity tests (LCO-DSTs) for chemotherapy and targeted therapy have been performed in a real-world study to predict the clinical response to the respective treatment. LCO-DSTs accurately predict the clinical response to treatment in this cohort of patients with advanced lung cancer. In conclusion, LCO-DST is a promising precision medicine tool in treating of advanced lung cancer. |
format | Online Article Text |
id | pubmed-9975107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99751072023-03-02 Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study Wang, Han-Min Zhang, Chan-Yuan Peng, Kai-Cheng Chen, Ze-Xin Su, Jun-Wei Li, Yu-Fa Li, Wen-Feng Gao, Qing-Yun Zhang, Shi-Ling Chen, Yu-Qing Zhou, Qing Xu, Cong Xu, Chong-Rui Wang, Zhen Su, Jian Yan, Hong-Hong Zhang, Xu-Chao Chen, Hua-Jun Wu, Yi-Long Yang, Jin-Ji Cell Rep Med Article Predicting the clinical response to chemotherapeutic or targeted treatment in patients with locally advanced or metastatic lung cancer requires an accurate and affordable tool. Tumor organoids are a potential approach in precision medicine for predicting the clinical response to treatment. However, their clinical application in lung cancer has rarely been reported because of the difficulty in generating pure tumor organoids. In this study, we have generated 214 cancer organoids from 107 patients, of which 212 are lung cancer organoids (LCOs), primarily derived from malignant serous effusions. LCO-based drug sensitivity tests (LCO-DSTs) for chemotherapy and targeted therapy have been performed in a real-world study to predict the clinical response to the respective treatment. LCO-DSTs accurately predict the clinical response to treatment in this cohort of patients with advanced lung cancer. In conclusion, LCO-DST is a promising precision medicine tool in treating of advanced lung cancer. Elsevier 2023-01-18 /pmc/articles/PMC9975107/ /pubmed/36657446 http://dx.doi.org/10.1016/j.xcrm.2022.100911 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Wang, Han-Min Zhang, Chan-Yuan Peng, Kai-Cheng Chen, Ze-Xin Su, Jun-Wei Li, Yu-Fa Li, Wen-Feng Gao, Qing-Yun Zhang, Shi-Ling Chen, Yu-Qing Zhou, Qing Xu, Cong Xu, Chong-Rui Wang, Zhen Su, Jian Yan, Hong-Hong Zhang, Xu-Chao Chen, Hua-Jun Wu, Yi-Long Yang, Jin-Ji Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title | Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title_full | Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title_fullStr | Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title_full_unstemmed | Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title_short | Using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: A real-world study |
title_sort | using patient-derived organoids to predict locally advanced or metastatic lung cancer tumor response: a real-world study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975107/ https://www.ncbi.nlm.nih.gov/pubmed/36657446 http://dx.doi.org/10.1016/j.xcrm.2022.100911 |
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