当前位置: X-MOL 学术J. Thorac. Oncol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Computational analysis of epidermal growth factor receptor mutations predicts differential drug sensitivity profiles towards kinase inhibitors
Journal of Thoracic Oncology ( IF 20.4 ) Pub Date : 2018-05-01 , DOI: 10.1016/j.jtho.2018.01.003
Sravani Akula , Swapna Kamasani , Sree Kanth Sivan , Vijjulatha Manga , Dashavantha Reddy Vudem , Rama Krishna Kancha

Introduction: A significant proportion of patients with lung cancer carry mutations in the EGFR kinase domain. The presence of a deletion mutation in exon 19 or L858R point mutation in the EGFR kinase domain has been shown to cause enhanced efficacy of inhibitor treatment in patients with NSCLC. Several less frequent (uncommon) mutations in the EGFR kinase domain with potential implications in treatment response have also been reported. The role of a limited number of uncommon mutations in drug sensitivity was experimentally verified. However, a huge number of these mutations remain uncharacterized for inhibitor sensitivity or resistance. Methods: A large‐scale computational analysis of clinically reported 298 point mutants of EGFR kinase domain has been performed, and drug sensitivity profiles for each mutant toward seven kinase inhibitors has been determined by molecular docking. In addition, the relative inhibitor binding affinity toward each drug as compared with that of adenosine triphosphate was calculated for each mutant. Results: The inhibitor sensitivity profiles predicted in this study for a set of previously characterized mutants correlated well with the published clinical, experimental, and computational data. Both the single and compound mutations displayed differential inhibitor sensitivity toward first‐ and next‐generation kinase inhibitors. Conclusions: The present study provides predicted drug sensitivity profiles for a large panel of uncommon EGFR mutations toward multiple inhibitors, which may help clinicians in deciding mutant‐specific treatment strategies.

中文翻译:

表皮生长因子受体突变的计算分析预测对激酶抑制剂的不同药物敏感性谱

简介:很大一部分肺癌患者携带 EGFR 激酶结构域的突变。外显子 19 中的缺失突变或 EGFR 激酶域中的 L858R 点突变的存在已被证明可提高抑制剂治疗对非小细胞肺癌患者的疗效。EGFR 激酶结构域中的几个不太频繁(不常见)的突变也有报道,这些突变对治疗反应有潜在影响。有限数量的罕见突变在药物敏感性中的作用得到了实验验证。然而,大量这些突变仍然没有对抑制剂敏感性或抗性进行表征。方法:对临床报告的 298 个 EGFR 激酶结构域点突变体进行了大规模计算分析,并且通过分子对接确定了每个突变体对七种激酶抑制剂的药物敏感性曲线。此外,计算每个突变体与三磷酸腺苷相比对每种药物的相对抑制剂结合亲和力。结果:本研究中预测的一组先前表征的突变体的抑制剂敏感性曲线与已发表的临床、实验和计算数据相关。单一突变和复合突变都显示出对第一代和下一代激酶抑制剂的不同抑制剂敏感性。结论:本研究为一大组罕见的 EGFR 突变对多种抑制剂提供了预测的药物敏感性谱,这可能有助于临床医生决定突变特异性治疗策略。
更新日期:2018-05-01
down
wechat
bug