利用遗传相互作用来预测癌细胞中的免疫检查点抑制剂反应特征。
Harnessing genetic interactions for prediction of immune checkpoint inhibitors response signature in cancer cells.
发表日期:2024 May 24
作者:
Mingyue Liu, Zhangxiang Zhao, Chengyu Wang, Shaocong Sang, Yanrui Cui, Chen Lv, Xiuqi Yang, Nan Zhang, Kai Xiong, Bo Chen, Qi Dong, Kaidong Liu, Yunyan Gu
来源:
CANCER LETTERS
摘要:
遗传相互作用(GI)是指两个改变的基因具有单独观察不到的综合效应。它们在影响药物功效方面发挥着至关重要的作用。我们利用了 CGIdb 2.0 (http://www.medsysbio.org/CGIdb2/),这是一个全面发布的 GI 信息的更新数据库,涵盖合成致死率 (SL)、合成活力 (SV) 和化学-遗传相互作用。 CGIdb 2.0 通过整合蛋白质-蛋白质物理相互作用来阐明蛋白质复合物模型之间或内部的 GI 关系。此外,我们引入了 GENIUS(基因相互作用介导的药物特征)来利用 GI 来识别免疫检查点抑制剂 (ICIs) 的反应特征。 GENIUS 将高 MAP4K4 表达确定为 ICI 治疗的耐药特征,将高 HERC4 表达确定为 ICI 治疗的敏感性特征。 MAP4K4 高表达的黑色素瘤患者在 ICI 治疗后疗效下降,生存率较差。相反,黑色素瘤患者中 HERC4 的过度表达与 ICI 的阳性反应相关。值得注意的是,HERC4 通过促进抗原呈递来增强对免疫治疗的敏感性。对免疫细胞浸润和单细胞数据的分析表明,表达 MAP4K4 的 B 细胞可能有助于黑色素瘤对 ICI 的抵抗。总体而言,CGIdb 2.0 提供了集成的 GI 数据,因此成为探索药物效应的重要工具。版权所有 © 2024。由 Elsevier B.V. 出版。
Genetic interactions (GIs) refer to two altered genes having a combined effect that is not seen individually. They play a crucial role in influencing drug efficacy. We utilized CGIdb 2.0 (http://www.medsysbio.org/CGIdb2/), an updated database of comprehensively published GIs information, encompassing synthetic lethality (SL), synthetic viability (SV), and chemical-genetic interactions. CGIdb 2.0 elucidates GIs relationships between or within protein complex models by integrating protein-protein physical interactions. Additionally, we introduced GENIUS (GENetic Interactions mediated drUg Signature) to leverage GIs for identifying the response signature of immune checkpoint inhibitors (ICIs). GENIUS identified high MAP4K4 expression as a resistance signature and high HERC4 expression as a sensitivity signature for ICIs treatment. Melanoma patients with high expression of MAP4K4 were associated with decreased efficacy and poorer survival following ICIs treatment. Conversely, overexpression of HERC4 in melanoma patients correlated with a positive response to ICIs. Notably, HERC4 enhances sensitivity to immunotherapy by facilitating antigen presentation. Analyses of immune cell infiltration and single-cell data revealed that B cells expressing MAP4K4 may contribute to resistance to ICIs in melanoma. Overall, CGIdb 2.0, provides integrated GIs data, thus serving as a crucial tool for exploring drug effects.Copyright © 2024. Published by Elsevier B.V.