Overcoming Resistance in EGFR‐Mutant Cancers: A Comprehensive Review of Inhibitor Evolution and SAR‐Based Design

背景(考古学) 表皮生长因子受体 表皮生长因子受体抑制剂 抗药性 变构调节 后天抵抗 药物开发 计算生物学 药物发现 个性化医疗 受体酪氨酸激酶 生物 药品 生物信息学 癌症 信号转导 机制(生物学) 酪氨酸激酶 精密医学 酪氨酸激酶抑制剂 药理学 癌症研究 系统生物学 肺癌 医学 合理设计 激酶 埃罗替尼 癌症治疗 受体蛋白酪氨酸激酶 靶向治疗 神经科学 生长因子受体
作者
Hemlata Naykwadi,Rajasekhar Reddy Alavala
出处
期刊:Drug Development Research [Wiley]
卷期号:87 (1): e70220-e70220 被引量:3
标识
DOI:10.1002/ddr.70220
摘要

The epidermal growth factor receptor (EGFR) is a key target in cancer therapy, mainly in non-small cell lung cancer (NSCLC). Though, the efficacy of EGFR-targeted therapies is limited by the development of resistance. This comprehensive review details the structural biology of EGFR and its role in oncogenic signaling, elucidating the major activating mutations, particularly exon 19 deletions and L858R point mutations, and acquired resistance. The progressive development of EGFR tyrosine kinase inhibitors (TKIs), from first-generation ATP-competitive inhibitors (e.g., gefitinib, erlotinib) to third-generation covalent agents (e.g., osimertinib) and emerging fourth-generation allosteric and degradation approaches, are critically examined for their mechanisms, efficacy, and clinical limitations. We have also discussed about the intrinsic and acquired resistance mechanisms, including alternative oncogenic drivers (KRAS, ALK), bypass pathway activations (MET, HER2), and phenotypic changes like epithelial-mesenchymal transition. Additionally, we emphasize the role of computational modeling, high-throughput SAR studies, and preclinical models, including patient-derived xenografts and organoids, in guiding rational drug design. Emerging approaches integrating artificial intelligence, machine learning, and precision oncology hold potential to accelerate EGFR-targeted drug discovery. The combination strategies with immunotherapy, and anti-angiogenic agents are considered in the context of improving patient outcomes. Together, ongoing advances in understanding EGFR signaling and resistance mechanisms are driving the development of next-generation inhibitors and personalized therapies, with the ultimate goal of overcoming drug resistance and improve patient outcomes in EGFR-mutant cancers.
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