类有机物
精密医学
医学
肺癌
计算生物学
生物信息学
数据科学
计算机科学
肿瘤科
病理
生物
神经科学
作者
Yuan Meng,Xinyi Shu,Jie Yang,Yangyueying Liang,Meiying Zhu,Xuerui Wang,Ting Li,Fanming Kong
摘要
This article discusses new strategies for lung cancer organoids (LCOs) in precision medicine research. Precision medicine aims to identify and develop highly selective drugs targeted at specific disease markers for precise treatment. Given the genetic diversity among lung cancer cells, it is evident that different tumor cells may respond differently to various treatment regimens. LCOs can not only faithfully reproduce the pathological and genomic characteristics of samples, maintaining most variations, including driver gene mutations, but also preserve the cytological features of malignant tumor cells, showing a highly correlated in vitro drug screening response with the mutation spectrum in primary tumors. At this stage, several large-scale LCO biobanks have been established, providing ample sample resources for researchers. Based on this, the development of emerging technologies is expected to overcome limitations in the success rate, accuracy, and stability of the organoid culture process, significantly enhancing the level of precision medicine for lung cancer. This article mainly introduces the applications of LCO models in basic research, including the identification of drug targets, prediction of treatment efficacy, and overcoming drug resistance, assisting in the formulation of personalized treatment plans to improve treatment outcomes. Additionally, the article emphasizes the potential of cancer organoid co-culture models in the field of immunotherapy and their key role in advancing the evolution of precision medicine treatment strategies.
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