摘要
Background： 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 TKl-resistant lung cancer using Agena iPLEX chemistry and niatrix-assisted laser desorption ionization time-of-flight analysis on the MassARRAY mass spectrometry platform. Methods： 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 LungCartaTM 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. Results： 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 LungCartaTM kit and Sanger sequencing. We also established a method for detection of large-fragment deletions based on single-base extension technology of MassARRAY platform. Conclusions： 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.
Background： 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 TKl-resistant lung cancer using Agena iPLEX chemistry and niatrix-assisted laser desorption ionization time-of-flight analysis on the MassARRAY mass spectrometry platform. Methods： 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 LungCartaTM 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. Results： 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 LungCartaTM kit and Sanger sequencing. We also established a method for detection of large-fragment deletions based on single-base extension technology of MassARRAY platform. Conclusions： 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.
