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Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model

Breast cancer is one of the most common tumors in women. Despite various treatments, the survival of patients with advanced breast cancer is still disappointing. Furthermore, finding an effective individualized treatment for different kinds of patients is a thorny problem. Patient-derived tumor-like...

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Autores principales: Xia, Wenjie, Chen, Wuzhen, Fang, Shan, Wu, Jun, Zhang, Jingxia, Yuan, Hongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659609/
https://www.ncbi.nlm.nih.gov/pubmed/36387193
http://dx.doi.org/10.3389/fonc.2022.897984
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author Xia, Wenjie
Chen, Wuzhen
Fang, Shan
Wu, Jun
Zhang, Jingxia
Yuan, Hongjun
author_facet Xia, Wenjie
Chen, Wuzhen
Fang, Shan
Wu, Jun
Zhang, Jingxia
Yuan, Hongjun
author_sort Xia, Wenjie
collection PubMed
description Breast cancer is one of the most common tumors in women. Despite various treatments, the survival of patients with advanced breast cancer is still disappointing. Furthermore, finding an effective individualized treatment for different kinds of patients is a thorny problem. Patient-derived tumor-like cell clusters were reported to be used for personalized drug testing in cancer therapy and had a prediction accuracy of 93%. However, there is still a lack of case reports about its application in the individualized treatment of breast cancer patients. Here, we described four cases of individualized treatment for advanced breast cancer using the patient-derived tumor-like cell cluster model (PTC model). In these four cases, the PTC model showed a good predictive effect. The tumor size was reduced significantly or even disappeared completely through clinical, radiological, or pathological evaluation with the help of the PTC model for selecting an individualized therapy regimen. Furthermore, the drug sensitivity test results of the PTC model were consistent with pathological molecular typing and the actual clinical drug resistance of the patients. In summary, our case report first evaluated the application value of the PTC model in advanced breast cancer, and the PTC model might be used as an efficient tool for drug resistance screening and for selecting a better personalized treatment, although further study is needed to prove the validity and stability of the PTC model in drug screening.
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spelling pubmed-96596092022-11-15 Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model Xia, Wenjie Chen, Wuzhen Fang, Shan Wu, Jun Zhang, Jingxia Yuan, Hongjun Front Oncol Oncology Breast cancer is one of the most common tumors in women. Despite various treatments, the survival of patients with advanced breast cancer is still disappointing. Furthermore, finding an effective individualized treatment for different kinds of patients is a thorny problem. Patient-derived tumor-like cell clusters were reported to be used for personalized drug testing in cancer therapy and had a prediction accuracy of 93%. However, there is still a lack of case reports about its application in the individualized treatment of breast cancer patients. Here, we described four cases of individualized treatment for advanced breast cancer using the patient-derived tumor-like cell cluster model (PTC model). In these four cases, the PTC model showed a good predictive effect. The tumor size was reduced significantly or even disappeared completely through clinical, radiological, or pathological evaluation with the help of the PTC model for selecting an individualized therapy regimen. Furthermore, the drug sensitivity test results of the PTC model were consistent with pathological molecular typing and the actual clinical drug resistance of the patients. In summary, our case report first evaluated the application value of the PTC model in advanced breast cancer, and the PTC model might be used as an efficient tool for drug resistance screening and for selecting a better personalized treatment, although further study is needed to prove the validity and stability of the PTC model in drug screening. Frontiers Media S.A. 2022-10-31 /pmc/articles/PMC9659609/ /pubmed/36387193 http://dx.doi.org/10.3389/fonc.2022.897984 Text en Copyright © 2022 Xia, Chen, Fang, Wu, Zhang and Yuan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Xia, Wenjie
Chen, Wuzhen
Fang, Shan
Wu, Jun
Zhang, Jingxia
Yuan, Hongjun
Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title_full Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title_fullStr Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title_full_unstemmed Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title_short Case report: Individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
title_sort case report: individualized treatment of advanced breast cancer with the use of the patient-derived tumor-like cell cluster model
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659609/
https://www.ncbi.nlm.nih.gov/pubmed/36387193
http://dx.doi.org/10.3389/fonc.2022.897984
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