Lung cancer organoids: a new strategy for precision medicine research.

IF 4 2区 医学 Q2 ONCOLOGY
Translational lung cancer research Pub Date : 2025-02-28 Epub Date: 2025-02-18 DOI:10.21037/tlcr-24-921
Yuan Meng, Xinyi Shu, Jie Yang, Yangyueying Liang, Meiying Zhu, Xuerui Wang, Yue Li, Fanming Kong
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引用次数: 0

Abstract

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.

肺癌类器官:精准医学研究的新策略。
本文讨论了肺癌类器官在精准医学研究中的新策略。精准医学旨在识别和开发针对特定疾病标志物的高选择性药物,以进行精准治疗。鉴于肺癌细胞的遗传多样性,很明显,不同的肿瘤细胞对不同的治疗方案可能有不同的反应。LCOs不仅能忠实地再现样品的病理和基因组特征,保持大部分变异,包括驱动基因突变,还能保留恶性肿瘤细胞的细胞学特征,在体外药物筛选反应中表现出与原发肿瘤突变谱高度相关的反应。现阶段已经建立了几个大型LCO生物库,为研究人员提供了充足的样本资源。基于此,新兴技术的发展有望克服类器官培养过程在成功率、准确性和稳定性方面的局限性,显著提高肺癌精准医疗水平。本文主要介绍LCO模型在基础研究中的应用,包括识别药物靶点、预测治疗疗效、克服耐药性,协助制定个性化治疗方案,提高治疗效果。此外,本文还强调了肿瘤类器官共培养模型在免疫治疗领域的潜力,以及它们在推进精准医学治疗策略发展中的关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
2.50%
发文量
137
期刊介绍: Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.
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