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Title: | Optimization of PCR-Based Mutation Detection Kit for Detecting L858R Mutation in EGFR Gene |
Authors: | Salim, Velecia |
Keywords: | lung cancer NSCLC EGFR PCR Mutation detection kit |
Issue Date: | 1-Jan-2023 |
Publisher: | Indonesia International Institute for Life Sciences |
Series/Report no.: | EP BT016;EP23051 |
Abstract: | Non-small-cell lung cancer (NSCLC) comprises the majority of lung cancer about 75-80%, and a quarter of NSCLC cases have mutations in the epidermal growth factor receptor (EGFR) gene. Adenocarcinomas of the lung harboring the L858R mutation in exon 21 have proven to be more adverse in terms of prognosis than exon 19 mutations. Therefore, developing highly sensitive and selective methods to detect L858R EGFR mutations is urgently required. Existing tests for detection, including PCR, have limitations regarding the specificity of the fluorophore-labeled probes. Moreover, the PCR system requires high amplification efficiency and specificity to ensure the accuracy of the L858R mutation detection from the EGFR gene. Here, optimized PCR conditions are proposed by altering the cycle conditions and reagent concentrations using a systematic approach and scientific method. Optimization of the different variables in the reaction system included primer selection, annealing temperature, the addition of wild-type blocker, Mg concentration, and primer concentration. Several tests were carried out in different samples with variations in the percentage of mutant allele frequencies (MAF) and DNA concentration to evaluate the sensitivity of the optimized reaction system. The results showed that the PCR assay under optimal conditions facilitated the detection of L858R with a sensitivity as low as 1.4% MAF and DNA concentration as low as 2.5 ng/µl. Conclusively, the current PCR strategy could precisely detect L858R mutation with high sensitivity and specificity. |
URI: | http://repository.i3l.ac.id/jspui/handle/123456789/652 |
Appears in Collections: | BT |
Files in This Item:
File | Description | Size | Format | |
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EP BT015_Ryan Matthew.pdf Restricted Access | Full Text | 2.26 MB | Adobe PDF | View/Open Request a copy |
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