As understanding of the molecular pathways that drive malignancy in human cancer improves, personalized genotype-based therapy in combination with the predictive biomarker for the efficacy of targeted therapy is becoming more popular in cancer management. Sanger sequencing, that has been the gold standard for mutation analysis in cancer since the 1970s, suffers from low sensitivity, complexity, and time-consuming and labor-intensive procedure. Although several PCR based molecular testing methods are being emerged, there is no universal assay available for genotyping of cancer biomarkers. Here we present a rapid, simple and sensitive assay for the detection of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancers (NSCLCs). The assay employs a novel double mis-matched primer (DMP) set to improve the detection ability of isothermal solid-phase amplification/detection (ISAD) based on silicon microring biosensor. We show that the EGFR-DMP can detect EGFR gene mutations within 20. min in a label-free and real-time manner. The EGFR-DMP was able to detect a mutation in a sample containing only 1% of the mutant cells in a mixture of wild-type cells. Furthermore, to validate the proposed assay for potential applications in clinical diagnostics, we examined paraffin-embedded tissue samples from 10 NSCLC patients for the presence of EGFR mutations by performing EGFR-DMP and direct sequencing. The EGFR-DMP assay was able to rapidly detect the mutation, with high sensitivity and specificity. The EGFR-DMP assay offers a robust and sensitive approach for the rapid identification of the EGFR mutation. The high sensitivity and specificity and rapidity of this approach may make it useful for predicting the clinical response to targeted EGFR TKIs as a companion diagnostic.
Bibliographical noteFunding Information:
This work was supported by the Agency for Science, Technology and Research (A*STAR) Joint Council Office (JCO) Development Programme Grant ( 1234e00018 ), Singapore.
© 2014 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Biomedical Engineering