Novel 100 000 hexagonal microchamber chip digital PCR for absolute quantification of gene mutations in lung cancer

Abstract

Objective To construct a novel 100 000 hexagonal microchamber chip (NHMC) digital PCR (dPCR) platform for absolute quantification analysis of gene mutations in lung cancer based on epidermal growth factor receptor (EGFR) G719S mutation as an object. Methods First, a PCR detection system for EGFR G719S mutation was constructed and optimized. And then 8 concentration gradients of EGFR G719S standard plasmids and 4 interfering substances were detected by the NHMC-dPCR platform, and the sensitivity, specificity and anti-interference ability of the platform were evaluated. Finally, 6 tissue samples of lung cancer with EGFR G719X mutation were detected by NHMC-dPCR, droplet digital PCR (ddPCR) and DNA sequencing, and the reliability of NHMC-dPCR in clinical sample testing was verified. Results The minimum detection concentration of EGFR G719S detected by NHMC-dPCR is 3.01 copies/μL. The linear equation between the detected value and the expected value is Y=0.725X-0.581, and the correlation coefficient is R2=0.984. Four interfering substances were tested by this platform and no positive holes were found. The results of the G719S mutant plasmids and the mixture of 4 interferences were 23 194.4 copies and 22 095.7 copies, respectively. The qualitative results of 6 clinical samples tested by NHMC-dPCR, ddPCR and DNA sequencing had a coincidence rate of 100%. Among them, the quantitative results of 2 cases by NHMC-dPCR were 1 822.4 copies and 451.7 copies, and their corresponding quantitative results by ddPCR were 1 581.8 copies and 218.3 copies, respectively. Conclusion The nucleic acid absolute quantification technology established in this study, namely NHMC-dPCR, has the advantages of low cost, simple operation, fast speed, and strong anti-interference ability, and can be used for absolute quantification analysis of gene mutations in lung cancer.

Keywords

• microfluidic chip
• dpcr
• lung cancer
• gene mutation
• nucleic acid detection