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Application status and future prospects of the PDX model in lung cancer

Lung cancer is one of the most prevalent, fatal, and highly heterogeneous diseases that, seriously threaten human health. Lung cancer is primarily caused by the aberrant expression of multiple genes in the cells. Lung cancer treatment options include surgery, radiation, chemotherapy, targeted therap...

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Autores principales: Liu, Wei, Cui, Yishuang, Zheng, Xuan, Yu, Kunpeng, Sun, Guogui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080030/
https://www.ncbi.nlm.nih.gov/pubmed/37035154
http://dx.doi.org/10.3389/fonc.2023.1098581
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author Liu, Wei
Cui, Yishuang
Zheng, Xuan
Yu, Kunpeng
Sun, Guogui
author_facet Liu, Wei
Cui, Yishuang
Zheng, Xuan
Yu, Kunpeng
Sun, Guogui
author_sort Liu, Wei
collection PubMed
description Lung cancer is one of the most prevalent, fatal, and highly heterogeneous diseases that, seriously threaten human health. Lung cancer is primarily caused by the aberrant expression of multiple genes in the cells. Lung cancer treatment options include surgery, radiation, chemotherapy, targeted therapy, and immunotherapy. In recent decades, significant progress has been made in developing therapeutic agents for lung cancer as well as a biomarker for its early diagnosis. Nonetheless, the alternative applications of traditional pre-clinical models (cell line models) for diagnosis and prognosis prediction are constrained by several factors, including the lack of microenvironment components necessary to affect cancer biology and drug response, and the differences between laboratory and clinical results. The leading reason is that substantial shifts accrued to cell biological behaviors, such as cell proliferative, metastatic, invasive, and gene expression capabilities of different cancer cells after decades of growing indefinitely in vitro. Moreover, the introduction of individualized treatment has prompted the development of appropriate experimental models. In recent years, preclinical research on lung cancer has primarily relied on the patient-derived tumor xenograft (PDX) model. The PDX provides stable models with recapitulate characteristics of the parental tumor such as the histopathology and genetic blueprint. Additionally, PDXs offer valuable models for efficacy screening of new cancer drugs, thus, advancing the understanding of tumor biology. Concurrently, with the heightened interest in the PDX models, potential shortcomings have gradually emerged. This review summarizes the significant advantages of PDXs over the previous models, their benefits, potential future uses and interrogating open issues.
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spelling pubmed-100800302023-04-08 Application status and future prospects of the PDX model in lung cancer Liu, Wei Cui, Yishuang Zheng, Xuan Yu, Kunpeng Sun, Guogui Front Oncol Oncology Lung cancer is one of the most prevalent, fatal, and highly heterogeneous diseases that, seriously threaten human health. Lung cancer is primarily caused by the aberrant expression of multiple genes in the cells. Lung cancer treatment options include surgery, radiation, chemotherapy, targeted therapy, and immunotherapy. In recent decades, significant progress has been made in developing therapeutic agents for lung cancer as well as a biomarker for its early diagnosis. Nonetheless, the alternative applications of traditional pre-clinical models (cell line models) for diagnosis and prognosis prediction are constrained by several factors, including the lack of microenvironment components necessary to affect cancer biology and drug response, and the differences between laboratory and clinical results. The leading reason is that substantial shifts accrued to cell biological behaviors, such as cell proliferative, metastatic, invasive, and gene expression capabilities of different cancer cells after decades of growing indefinitely in vitro. Moreover, the introduction of individualized treatment has prompted the development of appropriate experimental models. In recent years, preclinical research on lung cancer has primarily relied on the patient-derived tumor xenograft (PDX) model. The PDX provides stable models with recapitulate characteristics of the parental tumor such as the histopathology and genetic blueprint. Additionally, PDXs offer valuable models for efficacy screening of new cancer drugs, thus, advancing the understanding of tumor biology. Concurrently, with the heightened interest in the PDX models, potential shortcomings have gradually emerged. This review summarizes the significant advantages of PDXs over the previous models, their benefits, potential future uses and interrogating open issues. Frontiers Media S.A. 2023-03-24 /pmc/articles/PMC10080030/ /pubmed/37035154 http://dx.doi.org/10.3389/fonc.2023.1098581 Text en Copyright © 2023 Liu, Cui, Zheng, Yu and Sun 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
Liu, Wei
Cui, Yishuang
Zheng, Xuan
Yu, Kunpeng
Sun, Guogui
Application status and future prospects of the PDX model in lung cancer
title Application status and future prospects of the PDX model in lung cancer
title_full Application status and future prospects of the PDX model in lung cancer
title_fullStr Application status and future prospects of the PDX model in lung cancer
title_full_unstemmed Application status and future prospects of the PDX model in lung cancer
title_short Application status and future prospects of the PDX model in lung cancer
title_sort application status and future prospects of the pdx model in lung cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080030/
https://www.ncbi.nlm.nih.gov/pubmed/37035154
http://dx.doi.org/10.3389/fonc.2023.1098581
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