The potential role of next-generation sequencing in identifying MET amplification and disclosing resistance mechanisms in NSCLC patients with osimertinib resistance.

IF 3.5 3区 医学 Q2 ONCOLOGY Frontiers in Oncology Pub Date : 2024-10-21 eCollection Date: 2024-01-01 DOI:10.3389/fonc.2024.1470827
Xiao Xiao, Ren Xu, Jun Lu, Beibei Xin, Chenyang Wang, Kexin Zhu, Hao Zhang, Xinyu Chen
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Abstract

Purposes: Osimertinib, one of the third-generation EGFR-tyrosine kinase inhibitors (TKIs) designed to target EGFR T790M mutation, significantly improves the prognosis of lung cancer. However, drug resistance still happens and MET amplification is responsible for one of the main causes. Fluorescence in situ hybridization (FISH) is the gold standard for MET amplification detection, but fundamentally limited by observer subjectivity. Herein, we assessed the value of next-generation sequencing (NGS) method in MET amplification detection in non-small cell lung cancer (NSCLC), as well as revealed the mutation profiling of NSCLC patients with osimertinib resistance to provide some valuable clues to the mechanisms of resistance.

Methods: A total of 317 cancer tissue samples from 317 NSCLC patients at time of progression following osimertinib were submitted to NGS and only 96 tissues were tested by FISH simultaneously. With FISH results as gold standard, enumeration algorithm was applied to establish the optimal model for identifying MET amplification using gene copy number (GCN) data.

Results: The optimal model for identifying MET amplification was constructed based on the GCN of MET, BRAF, CDK6 and CYP3A4, which achieved a 74.0% overall agreement with FISH and performed well in identifying MET amplification except polysomy with a sensitivity of 85.7% and a specificity of 93.9%. The inconsistency between NGS and FISH occurred mainly in polysomy subtype, while MET GCN ≥ 5 could be reliably recognized by NGS. Moreover, the most frequently mutated genes in NSCLC patients with osimertinib resistance were EGFR (59.94%), followed by TP53 (43.85%), NRG1 (9.46%), PIK3CA (6.31%), and ATM (5.36%). The known resistance mechanisms, including MET amplification, EGFR (C797S, L718Q/R), TP53, CDK4, CDK6, CDKN2A, BRAF, KRAS, NRAS and PIK3CA mutations were also disclosed in our cohort.

Conclusions: NGS assay can achieve a high concordance with FISH in MET amplification detection and has advantages in portraying various genetic alterations, which is of worthy in clinical promotion.

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新一代测序技术在确定奥希替尼耐药的 NSCLC 患者的 MET 扩增和揭示耐药机制方面的潜在作用。
目的:奥希替尼是针对表皮生长因子受体 T790M 突变而设计的第三代表皮生长因子受体酪氨酸激酶抑制剂(TKIs)之一,可显著改善肺癌的预后。然而,耐药性仍时有发生,MET扩增是主要原因之一。荧光原位杂交(FISH)是检测 MET 扩增的金标准,但从根本上受到观察者主观性的限制。在此,我们评估了新一代测序(NGS)方法在非小细胞肺癌(NSCLC)MET扩增检测中的价值,并揭示了奥希替尼耐药NSCLC患者的突变谱,为耐药机制提供了一些有价值的线索:方法:将 317 例 NSCLC 患者在奥希替尼治疗进展期的 317 例癌症组织样本提交 NGS 检测,其中只有 96 例组织同时进行了 FISH 检测。以 FISH 结果为金标准,采用枚举算法,利用基因拷贝数(GCN)数据建立识别 MET 扩增的最佳模型:结果:根据 MET、BRAF、CDK6 和 CYP3A4 的 GCN 构建了识别 MET 扩增的最佳模型,该模型与 FISH 的总体吻合度为 74.0%,在识别除多体症以外的 MET 扩增方面表现良好,灵敏度为 85.7%,特异度为 93.9%。NGS 与 FISH 的不一致性主要发生在多体亚型,而 MET GCN ≥ 5 可被 NGS 可靠识别。此外,在奥希替尼耐药的 NSCLC 患者中,最常见的突变基因是表皮生长因子受体(59.94%),其次是 TP53(43.85%)、NRG1(9.46%)、PIK3CA(6.31%)和 ATM(5.36%)。我们的队列中还发现了已知的耐药机制,包括 MET 扩增、表皮生长因子受体(C797S、L718Q/R)、TP53、CDK4、CDK6、CDKN2A、BRAF、KRAS、NRAS 和 PIK3CA 突变:结论:在 MET 扩增检测中,NGS 检测与 FISH 检测的一致性较高,在描述各种基因改变方面具有优势,值得临床推广。
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
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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