Tian Hong-Xia, Zhang Xu-Chao, Wang Zhen, Yang Jin-Ji, Guo Wei-Bang, Chen Zhi-Hong, Wu Yi-Long
Medical Research Center, Guangdong Lung Cancer Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
Division of Pulmonary Oncology, Guangdong Lung Cancer Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China.
Chin Med J (Engl). 2017 Jun 20;130(12):1446-1453. doi: 10.4103/0366-6999.207478.
Drug resistance to targeted therapies occurs in lung cancer, and resistance mechanisms related to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are continuously being discovered. We aimed to establish a novel method for highly parallel multiplexed detection of genetic mutations related to EGFR TKI-resistant lung cancer using Agena iPLEX chemistry and matrix-assisted laser desorption ionization time-of-flight analysis on the MassARRAY mass spectrometry platform.
A review of the literature revealed 60 mutation hotspots in seven target genes (EGFR, KRAS, PIK3CA, BRAF, ERBB2, NRAS, and BIM) that are closely related to EGFR TKI resistance to lung cancer. A total of 183 primers comprised 61 paired forward and reverse amplification primers, and 61 matched extension primers were designed using Assay Design Software. The detection method was established by analyzing nine cell lines, and by comparison with LungCarta™ kit in ten lung cancer specimens. EGFR, KRAS, and BIM genes in all cell lines and clinical samples were subjected to Sanger sequencing for confirming reproducibility.
Our data showed that designed panel was a high-throughput and robust tool, allowing genotyping for sixty hotspots in the same run. Moreover, it made efficient use of patient diagnostic samples for a more accurate EGFR TKIs resistance analysis. The proposed method could accurately detect mutations in lung cancer cell lines and clinical specimens, consistent with those obtained by the LungCarta™ kit and Sanger sequencing. We also established a method for detection of large-fragment deletions based on single-base extension technology of MassARRAY platform.
We established an effective method for high-throughput detection of genetic mutations related to EGFR TKI resistance based on the MassARRAY platform, which could provide more accurate information for overcoming cancers with de novo or acquired resistance to EGFR-targeted therapies.
肺癌中会出现对靶向治疗的耐药性，与表皮生长因子受体（EGFR）酪氨酸激酶抑制剂（TKIs）相关的耐药机制也在不断被发现。我们旨在利用Agena iPLEX化学技术和基质辅助激光解吸电离飞行时间分析，在MassARRAY质谱平台上建立一种用于高度平行多重检测与EGFR TKI耐药肺癌相关基因突变的新方法。
文献综述揭示了七个与EGFR TKI对肺癌耐药密切相关的靶基因（EGFR、KRAS、PIK3CA、BRAF、ERBB2、NRAS和BIM）中的60个突变热点。使用检测设计软件设计了总共183条引物，其中包括61对正向和反向扩增引物以及61条匹配的延伸引物。通过分析九种细胞系并与十种肺癌标本中的LungCarta™试剂盒进行比较，建立了检测方法。对所有细胞系和临床样本中的EGFR、KRAS和BIM基因进行Sanger测序以确认可重复性。
我们的数据表明，设计的检测板是一种高通量且稳健的工具，能够在同一次运行中对60个热点进行基因分型。此外，它有效地利用了患者诊断样本进行更准确的EGFR TKIs耐药性分析。所提出的方法能够准确检测肺癌细胞系和临床标本中的突变，与通过LungCarta™试剂盒和Sanger测序获得的结果一致。我们还基于MassARRAY平台的单碱基延伸技术建立了一种检测大片段缺失的方法。
我们基于MassARRAY平台建立了一种有效检测与EGFR TKI耐药相关基因突变的方法，可为克服对EGFR靶向治疗具有原发性或获得性耐药的癌症提供更准确的信息。
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