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患者来源异种移植瘤的肿瘤组织外植体培养作为靶向治疗的潜在优先排序工具

Tumor Tissue Explant Culture of Patient-Derived Xenograft as Potential Prioritization Tool for Targeted Therapy.

作者信息

Ghosh Susmita, Prasad Manu, Kundu Kiran, Cohen Limor, Yegodayev Ksenia M, Zorea Jonathan, Joshua Ben-Zion, Lasry Batel, Dimitstein Orr, Bahat-Dinur Anat, Mizrachi Aviram, Lazar Vladimir, Elkabets Moshe, Porgador Angel

机构信息

The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.

National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer Sheva, Israel.

出版信息

Front Oncol. 2019 Jan 22;9:17. doi: 10.3389/fonc.2019.00017. eCollection 2019.

Abstract

Despite of remarkable progress made in the head and neck cancer (HNC) therapy, the survival rate of this metastatic disease remain low. Tailoring the appropriate therapy to patients is a major challenge and highlights the unmet need to have a good preclinical model that will predict clinical response. Hence, we developed an accurate and time efficient drug screening method of tumor analysis (TEVA) system, which can predict patient-specific drug responses. In this study, we generated six patient derived xenografts (PDXs) which were utilized for TEVA. Briefly, PDXs were cut into 2 × 2 × 2 mm explants and treated with clinically relevant drugs for 24 h. Tumor cell proliferation and death were evaluated by immunohistochemistry and TEVA score was calculated. and drug efficacy studies were performed on four PDXs and three drugs side-by-side to explore correlation between TEVA and PDX treatment . Efficacy of drug combinations was also ventured. Optimization of the culture timings dictated 24 h to be the time frame to detect drug responses and drug penetrates 2 × 2 × 2 mm explants as signaling pathways were significantly altered. Tumor responses to drugs in TEVA, significantly corresponds with the drug efficacy in mice. Overall, this low cost, robust, relatively simple and efficient 3D tissue-based method, employing material from one PDX, can bypass the necessity of drug validation in immune-incompetent PDX-bearing mice. Our data provides a potential rationale for utilizing TEVA to predict tumor response to targeted and chemo therapies when multiple targets are proposed.

摘要

尽管头颈癌(HNC)治疗取得了显著进展,但这种转移性疾病的生存率仍然很低。为患者量身定制合适的治疗方案是一项重大挑战,凸显了建立一个能够预测临床反应的良好临床前模型的未满足需求。因此,我们开发了一种准确且高效的肿瘤分析药物筛选方法(TEVA)系统,该系统可以预测患者特异性的药物反应。在本研究中,我们生成了六个患者来源的异种移植瘤(PDXs),用于TEVA。简而言之,将PDXs切成2×2×2毫米的外植体,并用临床相关药物处理24小时。通过免疫组织化学评估肿瘤细胞增殖和死亡情况,并计算TEVA评分。并且在四个PDXs和三种药物上并行进行药物疗效研究,以探索TEVA与PDX治疗之间的相关性。还尝试了药物组合的疗效。培养时间的优化表明24小时是检测药物反应的时间框架,并且药物能够穿透2×2×2毫米的外植体,因为信号通路发生了显著改变。TEVA中肿瘤对药物的反应与小鼠体内的药物疗效显著相关。总体而言,这种低成本、稳健、相对简单且高效的基于3D组织的方法,使用来自一个PDX的材料,可以绕过在无免疫能力的携带PDX的小鼠中进行药物验证的必要性。我们的数据为在提出多个靶点时利用TEVA预测肿瘤对靶向治疗和化疗的反应提供了潜在的理论依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb4f/6350270/95b7e2926a3c/fonc-09-00017-g0001.jpg

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