Consecutive and automatic detection of multi-gene mutations from colorectal cancer samples by coupling droplet array-based capillary electrophoresis and PCR-RFLP
- 6 April 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Analytical and Bioanalytical Chemistry
- Vol. 412 (13), 3037-3049
- https://doi.org/10.1007/s00216-020-02567-y
Abstract
The efficacy of targeted therapy is associated with multi-gene mutation status. Carrying out effective multi-genotyping analysis in combination has been a challenge in clinical settings. We therefore developed a droplet-based capillary electrophoresis (CE) system coupled with PCR-restriction fragment length polymorphism (PCR-RFLP) technology to detect multi-gene mutations from a small volume of samples. A 16 × 16 200-nL droplet array for sample encapsulation was constructed on a glass chip. The electrophoresis system consisted of a tapered vertical capillary filled with polyvinylpyrrolidone, a laser-induced fluorescence detector, and a high voltage power supply. Notably, a droplet-based electrokinetic sample introduction method and a “∩” shape capillary were developed to facilitate consecutive droplet sampling using a home-made automatic control module. The DL2000 DNA marker was consecutively separated, achieving high migration time and plate number reproducibility. The system was further applied to detect PCR-RFLP products. For colorectal cancer (CRC) cell lines, KRAS, BRAF, and PIK3CA were genotyped with a sensitivity of 0.25%. For CRC patient specimens, 30 samples were consecutively and automatically multi-genotyped without inter-sample contamination, with a lowest mutation frequency of 0.37%. For the first time, we developed a droplet-based CE system for consecutive DNA analysis with low sample consumption. This automated CE system could be further developed to integrate the full process of gene mutation detection, serving as a more effective platform for individualised therapy.Keywords
Funding Information
- National Natural Science Foundation of China (81672920)
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