Advancements in fourth-generation EGFR TKIs in EGFR-mutant NSCLC: Bridging biological insights and therapeutic development

医学 吉非替尼 肺癌 临床试验 抗药性 T790米 奥西默替尼 肿瘤科 药物开发 癌症研究 药品 药理学 表皮生长因子受体 埃罗替尼 内科学 癌症 遗传学 生物
作者
Carla Corvaja,Antonio Passaro,Ilaria Attili,Pamela Trillo Aliaga,Gianluca Spitaleri,Ester Del Signore,Filippo de Marinis
出处
期刊:Cancer Treatment Reviews [Elsevier BV]
卷期号:130: 102824-102824 被引量:6
标识
DOI:10.1016/j.ctrv.2024.102824
摘要

Third-generation EGFR tyrosine kinase inhibitor (TKIs) have revolutionized the treatment landscape for patients with non-small cell lung cancer (NSCLC) harboring EGFR activating mutations, with improved long-term outcomes compared to first-generation TKIs. Nevertheless, disease progression inevitably occurs, limiting osimertinib long-term efficacy. Indeed, the molecular biology underlying acquired resistance to first-line osimertinib is multifaceted and includes the emergence of on-target and off-target alterations. EGFR-C797S mutation represents the most frequent mechanism of on-target resistance and hinders drug binding to the target site. EGFR-independent resistance includes the activation of alternative signaling pathways, such as MET amplification and HER2 mutations, and histological transformation. In this setting, chemotherapy is the current therapeutic option, with modest clinical outcomes. Therefore, the development of novel therapeutic strategies to overcome resistance to osimertinib is a major challenge. In this setting, fourth-generation TKIs are emerging as an interesting therapeutic option to overcome on-target resistance. Preclinical drug development has led to the discovery of thiazole-amid inhibitors, which activity is mediated by the allosteric inhibition of EGFR, resulting in high specificity towards mutant-EGFR. Early phase 1/2 clinical trials are ongoing to elucidate their activity also in the clinical setting. Aim of this review is to provide a state-of-the-art analysis on preclinical development of fourth-generation EGFR-TKIs and promising preliminary clinical data.
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