| 引用本文: | 石禹龙,谢冬,徐志建,朱维良.计算机辅助预测EGFR突变的非小细胞肺癌药物敏感性的研究进展[J].中国现代应用药学,2022,39(21):2834-2841. |
| SHI Yulong,XIE Dong,XU Zhijian,ZHU Weiliang.Research Progress of Computer-aided Drug Sensitivity Prediction for Non-small Cell Lung Cancer with EGFR Mutation[J].Chin J Mod Appl Pharm(中国现代应用药学),2022,39(21):2834-2841. |
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| 摘要: |
| 表皮生长因子受体(epidermal growth factor receptor，EGFR)既是非小细胞肺癌(non-small cell lung cancer，NSCLC)的常见驱动基因，也是临床上NSCLC的重要治疗靶标。但EGFR突变导致的耐药性问题严重影响了靶向药物的治疗效果，限制了精准医疗的发展。本文对目前上市的EGFR酪氨酸激酶抑制剂(EGFR-tyrosine kinase inhibitors，EGFR-TKIs)的靶标结合模式进行综述，旨在为新型EGFR-TKIs开发提供理论依据，并回顾总结应用计算机预测EGFR突变体的药物敏感性的研究进展，以期推动发展临床决策的辅助工具来帮助临床医师设计个性化治疗方案。 |
| 关键词: 非小细胞肺癌 表皮生长因子受体 酪氨酸激酶抑制剂 药物敏感性预测 |
| DOI：10.13748/j.cnki.issn1007-7693.2022.21.020 |
| 分类号:R966 |
| 基金项目:国家自然科学基金项目(31870717) |
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| Research Progress of Computer-aided Drug Sensitivity Prediction for Non-small Cell Lung Cancer with EGFR Mutation |
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SHI Yulong1,2,3, XIE Dong4, XU Zhijian1,2,3, ZHU Weiliang1,2,3
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1.State Key Laboratory of Drug Research;2.Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China;3.School of Pharmacy, University of Chinese Academy of Sciences, Beijing 100049, China;4.Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China
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| Abstract: |
| Epidermal growth factor receptor(EGFR) is not only a common driver gene of non-small cell lung cancer (NSCLC), but also an important therapeutic target for NSCLC in clinical practice. However, the drug resistance problem caused by EGFR mutation seriously affects the therapeutic effect of targeted drugs and limits the development of precision medicine. In this paper, the target binding mode of the currently marketed EGFR tyrosine kinase inhibitors(EGFR-TKIs) is described to provide a theoretical basis for the development of novel EGFR-TKIs. And the research progress of applying computer to predict the drug sensitivity of EGFR mutants is reviewed, with the aim of promoting the development of auxiliary clinical decision-making tools for personalized treatment planning. |
| Key words: non-small cell lung cancer(NSCLC) epidermal growth factor receptor(EGFR) tyrosine kinase inhibitors(TKIs) drug sensitivity prediction |
