美国宾夕法尼亚州立大学Justin R. Pritchard团队近期取得重要工作进展，他们提出，通过选择基因驱动编程肿瘤演化来积极对抗耐药性的产生。相关研究成果2024年7月4日在线发表于《自然—生物技术》上。

据介绍，大多数靶向抗癌疗法由于耐药性的演化而失败。

研究人员表明，无论先前存在的遗传异质性的确切集合如何，肿瘤演化都可以被可复制地重新定向，以设计治疗机会。研究人员开发了一种选择基因驱动系统，该系统稳定地引入癌症细胞，由两个基因或开关组成，将可诱导的适应优势与共同的适应成本相结合。使用演化动力学的随机模型，研究人员确定了选择基因驱动的设计标准。

随后，研究人员建立原型，利用多种已获批的酪氨酸激酶抑制剂的选择性压力，并采用原药催化和免疫活性诱导等多种治疗机制。研究人员证明，选择基因驱动可以在体外消除多种形式的遗传抗性。最后，研究人员证明了模型切换参与能有效地靶向实体瘤小鼠模型中预先存在的耐药性。

总之，这些结果确立了选择基因驱动作为演化指导抗癌治疗的有效框架。

附：英文原文

Title: Programming tumor evolution with selection gene drives to proactively combat drug resistance

Author: Leighow, Scott M., Reynolds, Joshua A., Sokirniy, Ivan, Yao, Shun, Yang, Zeyu, Inam, Haider, Wodarz, Dominik, Archetti, Marco, Pritchard, Justin R.

Issue&Volume: 2024-07-04

Abstract: Most targeted anticancer therapies fail due to drug resistance evolution. Here we show that tumor evolution can be reproducibly redirected to engineer therapeutic opportunity, regardless of the exact ensemble of pre-existing genetic heterogeneity. We develop a selection gene drive system that is stably introduced into cancer cells and is composed of two genes, or switches, that couple an inducible fitness advantage with a shared fitness cost. Using stochastic models of evolutionary dynamics, we identify the design criteria for selection gene drives. We then build prototypes that harness the selective pressure of multiple approved tyrosine kinase inhibitors and employ therapeutic mechanisms as diverse as prodrug catalysis and immune activity induction. We show that selection gene drives can eradicate diverse forms of genetic resistance in vitro. Finally, we demonstrate that model-informed switch engagement effectively targets pre-existing resistance in mouse models of solid tumors. These results establish selection gene drives as a powerful framework for evolution-guided anticancer therapy.

DOI: 10.1038/s41587-024-02271-7

Source: https://www.nature.com/articles/s41587-024-02271-7