[患者来源的微肿瘤:治疗反应预测的潜力-一个案例研究]。

Urologie (Heidelberg, Germany) Pub Date : 2022-07-01 Epub Date: 2022-06-08 DOI:10.1007/s00120-022-01851-2
Eva Erne, Nicole Anderle, Christian Schmees, Arnulf Stenzl
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引用次数: 0

摘要

背景:随着肿瘤新方法的不断发展,对肿瘤个性化治疗的需求越来越大。然而,预测个体患者对药物治疗反应的快速有效的功能平台在很大程度上是不可用的。各种有前途的方法已经描述了三维细胞培养模型,代表细胞的复杂性和原始肿瘤组织的几乎相同的结构。目的:基于一个病例报告,我们展示了一种使用患者源性微肿瘤(pdm)和自体肿瘤浸润淋巴细胞(TILs)预测癌症治疗反应的新型测试系统的能力和结果。方法:从肾细胞癌转移的原发肿瘤组织中建立PDMs和TILs。采用免疫组织化学和多重荧光活化细胞分选(FACS)分析,对pdm和TILs进行组织学和免疫表型表征。评估标准护理和研究化合物的肿瘤特异性细胞毒性。结果与患者对治疗的个体体内反应进行了比较。结论:与对照组相比,pdm和TILs对程序性细胞死亡蛋白1 (PD-1)抑制剂和lenvatinib治疗有显著的治疗反应(p = 0.0004)。体外结果与体内数据正相关。在未来,患者衍生的模型可以预测对癌症治疗的反应,并可能有助于优化治疗决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Patient-derived microtumors : Potential for therapeutic response prediction-a case study].

Background: In view of continued development of new oncological approaches, there is a high demand for personalized tumor therapy. However, fast and effective functional platforms for the prediction of individual patient response to drug therapy are largely unavailable. Various promising approaches have already been described for three-dimensional cell culture models, which represent cellular complexity and almost identical structures of the original tumor tissue.

Objectives: Based on a case report, we show the capability and results of a novel test system using patient-derived microtumors (PDMs) and autologous tumor-infiltrating lymphocytes (TILs) for the prediction of response to cancer therapy.

Methods: We established PDMs and TILs from primary tumor tissue of a renal cell carcinoma metastasis. Using immunohistochemistry and multiplex florescence-activated cell sorting (FACS ) analyses, the PDMs and TILs were characterized regarding to histology and immunophenotype. Tumor-specific cytotoxicity of standard of care and investigational compounds were assessed. The results were compared to the patient's individual in vivo response to therapy.

Conclusion: The cytotoxicity assay of PDMs and TILs showed a significant therapeutic response (p = 0.0004) to therapy with a programmed cell death protein 1 (PD-1) inhibitor and lenvatinib compared to the control. The in vitro results correlated positively with the in vivo data. In the future, patient-derived models could predict response to cancer therapy and may help to optimize treatment decision-making.

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