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Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Application status and future prospects of the PDX model in lung cancer
Wei Liu1, Yishuang Cui1, Xuan Zheng1
1Department of Hebei Key Laboratory of Medical-Industrial Integration Precision Medicine, School of Public Health, School of Clinical Medicine, Affiliated Hospital, North China University of Science and Technology, Tangshan, China.
Abstract:
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.
Insights
Patient-derived tumor xenograft (PDX) models offer significant advantages over traditional cell line models for lung cancer research. These models better recapitulate human tumors, aiding in drug development and understanding tumor biology.
Area of Science:
- Oncology
- Translational Research
- Biomedical Modeling
Background:
- Lung cancer is a leading cause of mortality, characterized by high heterogeneity and complex genetic underpinnings.
- Current lung cancer treatments include surgery, radiation, chemotherapy, targeted therapy, and immunotherapy.
- Traditional preclinical models like cell lines have limitations in replicating the tumor microenvironment and clinical outcomes.
Purpose of the Study:
- To review the advantages of patient-derived tumor xenograft (PDX) models in lung cancer research.
- To highlight the benefits and potential future applications of PDX models.
- To discuss the limitations and open issues associated with PDX models.
Main Methods:
- Review of existing literature on lung cancer preclinical models.
- Comparison of patient-derived tumor xenograft (PDX) models with traditional cell line models.
- Analysis of the characteristics and applications of PDX models in lung cancer research.
Main Results:
- PDX models accurately recapitulate the histopathology and genetic makeup of parental lung tumors.
- PDX models provide a more reliable platform for screening new cancer drugs and advancing tumor biology understanding.
- PDX models address limitations of cell line models by incorporating aspects of the tumor microenvironment.
Conclusions:
- Patient-derived tumor xenograft models represent a significant advancement over traditional models for lung cancer research.
- PDX models are valuable for preclinical drug efficacy screening and understanding lung cancer biology.
- Further research is needed to address the emerging challenges and optimize the use of PDX models.

