Synthetic and systems biology principles in the design of programmable oncolytic virus immunotherapies for glioblastoma.
Synthetic and systems biology principles in the design of programmable oncolytic virus immunotherapies for glioblastoma.
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DOI：
10.3171/2020.12.focus20855
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发表时间：
2021-03
影响因子：
4.1
通讯作者：
Li H
中科院分区：
文献类型：
--
作者：
Monie DD;Bhandarkar AR;Parney IF;Correia C;Sarkaria JN;Vile RG;Li H
溶瘤病毒（OV）是一类免疫治疗药物，在治疗多形性胶质母细胞瘤（GBM）方面具有良好的临床前结果，但在最近的临床试验中取得的成功有限。需要来自合成生物学和系统生物学等学科的先进生物工程原理来克服当前在开发基于 OV 的 GBM 有效免疫疗法时面临的挑战，包括脱靶效应和临床反应不佳。合成生物学是一个新兴领域，专注于开发合成 DNA 结构，这些结构编码基因和蛋白质网络（合成遗传电路）以执行新功能，而系统生物学是一个分析框架，可以研究宿主途径和这些合成遗传电路之间的复杂相互作用。在这篇综述中，我们总结了用于开发可编程、基于逻辑的 OV 来治疗 GBM 的合成和系统生物学概念。可编程 OV 可以增加对肿瘤细胞的选择性，并使用合成遗传电路增强局部免疫反应。在这里，我们讨论开发基于 OV 的可编程免疫疗法的关键原则，包括如何 (1) 选择合适的底盘（携带合成遗传电路的载体）以及 (2) 设计一个合成遗传电路，该电路可以编程以感测 GBM 微环境中的关键信号并触发治疗有效负载的释放。为了说明这些原理，我们提供了一些原始实验室数据，强调了系统生物学研究的必要性，以及一些初步的网络分析，为合成生物学应用做准备。还调查和讨论了可打包到领先候选 OV 追踪中的最先进合成遗传电路文献中的示例。
Oncolytic viruses (OVs) are a class of immunotherapeutic agents with promising preclinical results for the treatment of glioblastoma multiforme (GBM) but limited success in recent clinical trials. Advanced bioengineering principles from disciplines like synthetic and systems biology are needed to overcome the current challenges faced in developing effective OV-based immunotherapies for GBMs, including off-target effects and poor clinical responses. Synthetic biology is an emerging field that focuses on the development of synthetic DNA constructs that encode networks of genes and proteins (synthetic genetic circuits) to perform novel functions, whereas systems biology is an analytic framework that enables the study of complex interactions between host pathways and these synthetic genetic circuits. In this review, we summarize synthetic and systems biology concepts for developing programmable, logic-based OVs to treat GBMs. Programmable OVs can increase selectivity for tumor cells and enhance the local immunological response using synthetic genetic circuits. Here we discuss key principles for developing programmable OV-based immunotherapies including how to (1) select an appropriate chassis—a vector that carries a synthetic genetic circuit—and (2) design a synthetic genetic circuit that can be programmed to sense key signals in the GBM microenvironment and trigger release of a therapeutic payload. To illustrate these principles, we include some original laboratory data highlighting the need for systems biology studies as well as some preliminary network analyses in preparation for synthetic biology applications. Examples from the literature of state-of-the-art synthetic genetic circuits that can be packaged into leading candidate OV chasses are also surveyed and discussed.