Evaluation of digital PCR for detecting low-level EGFR mutations in advanced lung adenocarcinoma patients: a cross-platform comparison study

// Jincui Gu 1, * , Wanchun Zang 2, * , Bing Liu 2 , Lei Li 2 , Lixia Huang 1 , Shaoli Li 1 , Guanhua Rao 2 , Yang Yu 2 and Yanbin Zhou 1 1 Department of Respiratory Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China 2 Novogene Bioinformatics Institute, Beijing, China * These authors have contributed equally to this work Correspondence to: Yanbin Zhou, email: sysuzyb@aliyun.com Yang Yu, email: yuyang@novogene.com Keywords: EGFR, NSCLC, digital PCR, circulating tumor DNA Received: January 12, 2017     Accepted: June 02, 2017     Published: June 29, 2017 ABSTRACT 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.