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Patients Lung Derived Tumoroids (PLDTs) to model therapeutic response.
Biochimica et Biophysica Acta (BBA) - Molecular Cell Research ( IF 4.6 ) Pub Date : 2020-08-08 , DOI: 10.1016/j.bbamcr.2020.118808
Frederic Delom 1 , Inaki Begiristain 1 , Thomas Grenier 1 , Hugues Begueret 2 , Fabienne Soulet 3 , Geraldine Siegfried 3 , Abdel-Majid Khatib 3 , Jacques Robert 1 , Delphine Fessart 4
Affiliation  

Preclinical lung cancer models are essential for a basic understanding of lung cancer biology and its translation into efficient treatment options for affected patients. Lung cancer cell lines and xenografts derived directly from human lung tumors have proven highly valuable in fundamental oncology research and anticancer drug discovery. Both models inherently comprise advantages and caveats that have to be accounted for. Recently, we have enabled reliable in vitro culture techniques from lung cancer biopsies as Patients Lung Derived Tumoroids (PLDTs). This breakthrough provides the possibility of high-throughput drug screening covering the spectrum of lung cancer phenotypes seen clinically. We have adapted and optimized our in vitro three-dimensional model as a preclinical lung cancer model to recapitulate the tumor microenvironment (TME) using matrix reconstitution. Hence, we developed directly PLDTs to screen for chemotherapeutics and radiation treatment. This original model will enable precision medicine to become a reality, allowing a given patient sample to be screened for effective ex vivo therapeutics, aiming at tailoring of treatments specific to that individual. Hence, this tool can enhance clinical outcomes and avoid morbidity due to ineffective therapies.



中文翻译:

患者肺源性类癌(PLDT)可模拟治疗反应。

临床前肺癌模型对于基本了解肺癌生物学及其将其转化为受影响患者的有效治疗选择至关重要。直接来自人肺肿瘤的肺癌细胞系和异种移植物在基础肿瘤学研究和抗癌药物发现中被证明具有很高的价值。两种模型都固有地包含必须考虑的优点和警告。最近,我们已经从肺癌活组织检查中获得了可靠的体外培养技术,即患者肺源性类肿瘤(PLDT)。这一突破提供了高通量药物筛查的可能性,该筛查涵盖了临床上见到的肺癌表型。我们已经调整并优化了体外三维模型作为临床前肺癌模型,使用基质重构来概括肿瘤微环境(TME)。因此,我们直接开发了PLDT来筛选化学疗法和放射治疗。这种原始模型将使精密医学成为现实,从而可以筛查给定的患者样品以进行有效的离体治疗,从而针对该患者量身定制治疗方案。因此,该工具可以提高临床效果并避免因无效疗法而导致的发病率。

更新日期:2020-08-08
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