Evaluation of digital PCR for detecting low-level EGFR mutations in advanced lung adenocarcinoma patients: a cross-platform comparison study
Metrics: PDF 1451 views | HTML 2186 views | ?
Jincui Gu1,*, Wanchun Zang2,*, Bing Liu2, Lei Li2, Lixia Huang1, Shaoli Li1, Guanhua Rao2, Yang Yu2 and Yanbin Zhou1
1Department of Respiratory Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
2Novogene Bioinformatics Institute, Beijing, China
*These authors have contributed equally to this work
Yanbin Zhou, email: [email protected]
Yang Yu, email: [email protected]
Keywords: EGFR, NSCLC, digital PCR, circulating tumor DNA
Received: January 12, 2017 Accepted: June 02, 2017 Published: June 29, 2017
Emerging evidence has indicated that circulating tumor DNA (ctDNA) from plasma could be used to analyze EGFR mutation status for NSCLC patients; however, due to the low level of ctDNA in plasma, highly sensitive approaches are required to detect low frequency mutations. In addition, the cutoff for the mutation abundance that can be detected in tumor tissue but cannot be detected in matched ctDNA is still unknown. To assess a highly sensitive method, we evaluated the use of digital PCR in the detection of EGFR mutations in tumor tissue from 47 advanced lung adenocarcinoma patients through comparison with NGS and ARMS. We determined the degree of concordance between tumor tissue DNA and paired ctDNA and analyzed the mutation abundance relationship between them. Digital PCR and Proton had a high sensitivity (96.00% vs. 100%) compared with that of ARMS in the detection of mutations in tumor tissue. Digital PCR outperformed Proton in identifying more low abundance mutations. The ctDNA detection rate of digital PCR was 87.50% in paired tumor tissue with a mutation abundance above 5% and 7.59% in paired tumor tissue with a mutation abundance below 5%. When the DNA mutation abundance of tumor tissue was above 3.81%, it could identify mutations in paired ctDNA with a high sensitivity. Digital PCR will help identify alternative methods for detecting low abundance mutations in tumor tissue DNA and plasma ctDNA.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.