Tognon Cristina E, Sears Rosalie C, Mills Gordon B, Gray Joe W, Tyner Jeffrey W
Division of Hematology & Medical Oncology, Oregon Health & Science University.
Knight Cancer Institute, Oregon Health & Science University.
Annu Rev Cancer Biol. 2021 Mar;5:39-57. doi: 10.1146/annurev-cancerbio-043020-125955. Epub 2020 Dec 8.
The use of drug sensitivity testing to predict drug activity in individual patients has been actively explored for almost 50 years without delivering a generally useful predictive capability. However, extended failure should not be an indicator of futility. This is especially true in cancer research where ultimate success is often preceded by less successful attempts. For example, both immune- and genetic-based targeted therapies for cancer underwent numerous failed attempts before biological understanding, improved targets, and optimized drug development matured to facilitate an arsenal of transformational drugs. Similarly, the concept of directly assessing drug sensitivity of primary tumor biopsies-and the use of this information to help direct therapeutic approaches-has a long history with a definitive learning curve. In this review, we will survey the history of testing as well as the current state of the art for this field. We will present an update on methodologies and approaches, describe the use of these technologies to test cutting-edge drug classes, and describe an increasingly nuanced understanding of tumor types and models for which this strategy is most likely to succeed. We will consider the relative strengths and weaknesses of predicting drug activity across the broad biological context of cancer patients and tumor types. This will include an analysis of the potential for drug sensitivity testing to accurately predict drug activity within each of the biological hallmarks of cancer pathogenesis.
近50年来,人们一直在积极探索利用药物敏感性测试来预测个体患者的药物活性,但尚未获得普遍有用的预测能力。然而,长期失败不应被视为毫无意义的指标。在癌症研究中尤其如此,因为最终的成功往往之前伴随着不太成功的尝试。例如,基于免疫和基因的癌症靶向治疗在生物学认识、改进靶点和优化药物开发成熟以促成一系列变革性药物之前,经历了无数次失败的尝试。同样,直接评估原发性肿瘤活检的药物敏感性以及利用这些信息指导治疗方法的概念也有着悠久的历史,且有明确的学习曲线。在本综述中,我们将审视该测试的历史以及该领域的当前技术水平。我们将介绍方法和途径的最新进展,描述如何使用这些技术测试前沿药物类别,并描述对最有可能成功应用该策略的肿瘤类型和模型的日益细致入微的理解。我们将考虑在癌症患者和肿瘤类型的广泛生物学背景下预测药物活性的相对优势和劣势。这将包括分析药物敏感性测试在癌症发病机制的每个生物学特征内准确预测药物活性的潜力。