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Rational Identification of Novel Antibody-Drug Conjugate with High Bystander Killing Effect against Heterogeneous Tumors
Advanced Science ( IF 14.3 ) Pub Date : 2024-01-25 , DOI: 10.1002/advs.202306309
Yu Guo 1 , Zheyuan Shen 1 , Wenbin Zhao 2 , Jialiang Lu 1 , Yi Song 1 , Liteng Shen 1 , Yang Lu 1 , Mingfei Wu 1 , Qiuqiu Shi 1 , Weihao Zhuang 1 , Yueping Qiu 3 , Jianpeng Sheng 4 , Zhan Zhou 2 , Luo Fang 3 , Jinxin Che 1 , Xiaowu Dong 1, 5, 6
Affiliation  

Bystander-killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody-drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander-killing payloads, this model is utilized for score-directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti-tumor efficacy and bystander-killing effect in vivo and in vitro. The optimal conjugate T-VEd9 exhibited therapeutic efficacy superior to DS-8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity.

中文翻译:


合理鉴定对异质肿瘤具有高旁观者杀伤作用的新型抗体药物偶联物



旁观者杀伤有效载荷可以显着克服肿瘤异质性问题并增强抗体药物偶联物(ADC)的临床潜力,但有效旁观者弹头的合理设计和识别限制了该策略的更广泛实施。在这里,首次构建了图注意力网络(GAT),用于合理的旁观者杀戮评分模型和 ADC 构建工作流程。为了生成有效的旁观者杀伤有效负载,该模型用于分数导向的 exatecan 衍生物设计。其中,Ed9是最有效的有效负载,具有令人满意的渗透性和生物活性,被进一步用于构建ADC。通过连接子优化和缀合,构建了新型ADC,在体内和体外具有优异的抗肿瘤功效和旁观者杀伤作用。最佳结合物 T-VEd9 对异质性肿瘤的治疗效果优于 DS-8201。这些结果表明,有效的评分方法可以为发现新型 ADC 铺平道路,该 ADC 具有有望对抗肿瘤异质性的旁观者有效负载。
更新日期:2024-01-25
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