School of Medicine and Pharmacology and National Centre for Asbestos Related Diseases, University of Western Australia, 5th Floor QQ Block, 6 Verdun Street, Nedlands, Perth, Western Australia 6009, Australia.
Telethon Kids Institute, University of Western Australia, PO Box 855, West Perth, Western Australia 6872, Australia.
Nat Rev Drug Discov. 2017 Apr;16(4):264-272. doi: 10.1038/nrd.2016.233. Epub 2017 Jan 6.
Recently, there has been a coordinated effort from academic institutions and the pharmaceutical industry to identify biomarkers that can predict responses to immune checkpoint blockade in cancer. Several biomarkers have been identified; however, none has reliably predicted response in a sufficiently rigorous manner for routine use. Here, we argue that the therapeutic response to immune checkpoint blockade is a critical state transition of a complex system. Such systems are highly sensitive to initial conditions, and critical transitions are notoriously difficult to predict far in advance. Nevertheless, warning signals can be detected closer to the tipping point. Advances in mathematics and network biology are starting to make it possible to identify such warning signals. We propose that these dynamic biomarkers could prove to be useful in distinguishing responding from non-responding patients, as well as facilitate the identification of new therapeutic targets for combination therapy.
最近，学术机构和制药行业已经协同努力，以确定可以预测癌症免疫检查点阻断反应的生物标志物。已经确定了一些生物标志物；但是，没有一个能够以足够严格的方式可靠地预测反应，因此无法常规使用。在这里，我们认为免疫检查点阻断的治疗反应是一个复杂系统的关键状态转变。此类系统对初始条件非常敏感，而众所周知，临界点很难提前准确预测。尽管如此，仍然可以在更接近临界点的地方检测到警告信号。数学和网络生物学的进步开始使识别此类警告信号成为可能。我们提出，这些动态生物标志物可能有助于区分有反应的患者和无反应的患者，并有助于确定联合治疗的新治疗靶点。
