Advances in patient-derived tumor xenografts: From target identification to predicting clinical response rates in oncology
Advances in patient-derived tumor xenografts: From target identification to predicting clinical response rates in oncology
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DOI：
10.1016/j.bcp.2014.06.008
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发表时间：
2014-09-15
影响因子：
5.8
通讯作者：
Gerber, Hans-Peter
中科院分区：
文献类型：
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作者：
Rosfjord, Edward;Lucas, Judy;Gerber, Hans-Peter
大多数进入临床开发的肿瘤化合物都通过了严格的临床前药理学评估标准。然而，只有一小部分实验药物在临床上产生有意义的抗肿瘤活性。传统临床前药理学模型的低可预测性经常被认为是肿瘤学治疗化合物临床损耗率异常高的主要原因。因此，提高临床前疗效模型对临床结果的预测值，有望降低实验化合物的临床损耗率。最近的报告表明，与传统的细胞系来源的异种移植（CDX）模型相比，用患者来源的异种移植（PDX）肿瘤进行的药理学研究更能预测临床结果，特别是当以临床相关剂量测试治疗化合物时 （CRD）。此外，对肿瘤内最恶性的细胞类型（肿瘤起始细胞（TIC））的研究依赖于模拟肿瘤内细胞谱系层次结构的临床前模型的可用性。 PDX 模型被证明能够更准确地再现患者肿瘤的异质性，并在小鼠连续传代的早期阶段维持人类肿瘤的分子、遗传和组织学复杂性，使其成为研究 TIC、肿瘤细胞和基质细胞对治疗干预的反应的理想工具。在这篇评论中，我们回顾了 PDX 模型在肿瘤学研究关键领域（包括靶点识别）的开发进展。 和验证、肿瘤适应症搜索以及生物标志物假设的发展，该假设可以在临床上进行测试，以确定将从治疗干预中受益最大的患者。 (C) 2014 Elsevier Inc. 保留所有权利。
Most oncology compounds entering clinical development have passed stringent preclinical pharmacology evaluation criteria. However, only a small fraction of experimental agents induce meaningful antitumor activities in the clinic. Low predictability of conventional preclinical pharmacology models is frequently cited as a main reason for the unusually high clinical attrition rates of therapeutic compounds in oncology. Therefore, improvement in the predictive values of preclinical efficacy models for clinical outcome holds great promise to reduce the clinical attrition rates of experimental compounds.Recent reports suggest that pharmacology studies conducted with patient derived xenograft (PDX) tumors are more predictive for clinical outcome compared to conventional, cell line derived xenograft (CDX) models, in particular when therapeutic compounds were tested at clinically relevant doses (CRDs). Moreover, the study of the most malignant cell types within tumors, the tumor initiating cells (TICs), relies on the availability of preclinical models that mimic the lineage hierarchy of cells within tumors. PDX models were shown to more closely recapitulate the heterogeneity of patient tumors and maintain the molecular, genetic, and histological complexity of human tumors during early stages of sequential passaging in mice, rendering them ideal tools to study the responses of TICs, tumor- and stromal cells to therapeutic intervention.In this commentary, we review the progress made in the development of PDX models in key areas of oncology research, including target identification and validation, tumor indication search and the development of a biomarker hypothesis that can be tested in the clinic to identify patients that will benefit most from therapeutic intervention. (C) 2014 Elsevier Inc. All rights reserved.