EGFR and ALK Targeted Therapy Response in Non-Small Cell Lung Cancer Harboring Rare or Resistant Mutations: A Case Report and Molecular Insights.

IF 3.5 4区 医学 Q3 ONCOLOGY
Anju Farsana Abdul Gafoor, Preena S Parvathy, C Gopi Mohan, Keechilat Pavithran
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引用次数: 0

Abstract

Introduction: The Non-Small Cell Lung Cancer (NSCLC) with rare genomic alterations poses a significant clinical challenge due to a lack of established therapeutic guidelines.

Case presentation: We report the application of a precision medicine strategy integrating genomic profiling with in silico molecular docking to guide therapy for two patients harboring such rare mutations. Genomic analysis identified a rare EGFR exon 18/20 insertion in one patient and a resistant ALK C1156Y mutation in another. Selection of the appropriate drug was carried out using molecular docking simulations, which predicted high binding affinity of the irreversible EGFR inhibitor afatinib for the unique EGFR insertion and of the ALK inhibitor alectinib for the C1156Y-mutated kinase. We observed that the computationally-informed choices of afatinib and alectinib subsequently led to notable clinical and radiological improvements in the respective patients.

Conclusion: The association between the docking predictions and clinical outcomes corroborates the utility of computational modeling for tailoring therapies, although the structural models provide mechanistic insight into drug efficacy against these rare mutations. The present integrated approach emphasizes the value of merging in silico methods into clinical decision-making to overcome the therapeutic uncertainty of uncommon oncogenic driver alterations.

含有罕见或耐药突变的非小细胞肺癌EGFR和ALK靶向治疗反应:一个病例报告和分子见解。
非小细胞肺癌(NSCLC)罕见的基因组改变提出了重大的临床挑战,由于缺乏既定的治疗指南。病例介绍:我们报告了将基因组分析与硅分子对接相结合的精准医学策略的应用,以指导两名携带此类罕见突变的患者的治疗。基因组分析在一名患者中发现罕见的EGFR外显子18/20插入,在另一名患者中发现耐药ALK C1156Y突变。通过分子对接模拟选择合适的药物,预测不可逆的EGFR抑制剂afatinib对独特的EGFR插入具有高结合亲和力,ALK抑制剂alectinib对c1156y突变的激酶具有高结合亲和力。我们观察到,根据计算选择阿法替尼和阿勒替尼随后导致各自患者的临床和放射学显著改善。结论:对接预测与临床结果之间的关联证实了计算模型在定制治疗中的效用,尽管结构模型提供了针对这些罕见突变的药物疗效的机制见解。目前的综合方法强调了将计算机方法合并到临床决策中的价值,以克服罕见的致癌驱动改变的治疗不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Current cancer drug targets
Current cancer drug targets 医学-肿瘤学
CiteScore
5.40
自引率
0.00%
发文量
105
审稿时长
1 months
期刊介绍: Current Cancer Drug Targets aims to cover all the latest and outstanding developments on the medicinal chemistry, pharmacology, molecular biology, genomics and biochemistry of contemporary molecular drug targets involved in cancer, e.g. disease specific proteins, receptors, enzymes and genes. Current Cancer Drug Targets publishes original research articles, letters, reviews / mini-reviews, drug clinical trial studies and guest edited thematic issues written by leaders in the field covering a range of current topics on drug targets involved in cancer. As the discovery, identification, characterization and validation of novel human drug targets for anti-cancer drug discovery continues to grow; this journal has become essential reading for all pharmaceutical scientists involved in drug discovery and development.
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