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Establishment and application of a multiplex genetic mutation-detection method of lung cancer based on MassARRAY platform

摘要Objective:This study aims to establish a method for highly parallel multiplexed detection of genetic mutations in Chinese lung cancer samples through Agena iPLEX chemistry and matrix-assisted laser desorption ionization time-of-flight analysis on MassARRAY mass spectrometry platform. Methods:We reviewed the related literature and data on lung cancer treatments. We also identified 99 mutation hot spots in 13 target genes closely related to the pathogenesis, drug resistance, and metastasis of lung cancer. A total of 297 primers, composed of 99 paired forward and reverse amplification primers and 99 matched extension primers, were designed using Assay Design software. The detection method was established by analyzing eight cell lines and six lung cancer specimens. The proposed method was then validated through comparisons by using a LungCartaTM kit. The sensitivity and specificity of the proposed method were evaluated by directly sequencingEGFR andKRAS genes in 100 lung cancer cases. Results:The proposed method was able to detect multiplex genetic mutations in lung cancer cell lines. This finding was consistent with the observations on previously reported mutations. The proposed method can also detect such mutations in clinical lung cancer specimens. This result was consistent with the observations with LungCartaTM kit. However, anFGFR2 mutation was detected only through the proposed method. The measured sensitivity and specificity were 100% and 96.3%, respectively. Conclusions:The proposed MassARRAY technology-based multiplex method can detect genetic mutations in Chinese lung cancer patients. Therefore, the proposed method can be applied to detect mutations in other cancer tissues.

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作者单位 Medical Research Center, Guangdong Lung Cancer Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China [1]
DOI 10.28092/j.issn.2095-3941.2015.0094
发布时间 2016-05-09(万方平台首次上网日期,不代表论文的发表时间)
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癌症生物学与医学(英文版)

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