Liu Wei, Cui Yishuang, Zheng Xuan, Yu Kunpeng, Sun Guogui
Department 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.
Front Oncol. 2023 Mar 24;13:1098581. doi: 10.3389/fonc.2023.1098581. eCollection 2023.
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 . 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.
肺癌是最常见、最致命且高度异质性的疾病之一，严重威胁人类健康。肺癌主要由细胞中多个基因的异常表达引起。肺癌的治疗选择包括手术、放疗、化疗、靶向治疗和免疫治疗。近几十年来，在开发肺癌治疗药物以及早期诊断生物标志物方面取得了重大进展。尽管如此，传统临床前模型（细胞系模型）在诊断和预后预测方面的替代应用受到多种因素的限制，包括缺乏影响癌症生物学和药物反应所需的微环境成分，以及实验室结果与临床结果之间的差异。主要原因是经过数十年无限增殖后，不同癌细胞的细胞生物学行为发生了实质性变化，如细胞增殖、转移、侵袭和基因表达能力。此外，个性化治疗的引入促使了合适实验模型的发展。近年来，肺癌的临床前研究主要依赖于患者来源的肿瘤异种移植（PDX）模型。PDX提供了具有亲本肿瘤特征（如组织病理学和基因蓝图）的稳定模型。此外，PDX为新癌症药物的疗效筛选提供了有价值的模型，从而增进了对肿瘤生物学的理解。与此同时，随着对PDX模型兴趣的增加，潜在的缺点也逐渐显现出来。本综述总结了PDX相对于先前模型的显著优势、其益处、潜在的未来用途以及有待探讨的开放性问题。
