» Articles » PMID: 28978074

Evaluation of Digital PCR for Detecting Low-level EGFR Mutations in Advanced Lung Adenocarcinoma Patients: a Cross-platform Comparison Study

Overview
Journal Oncotarget
Specialty Oncology
Date 2017 Oct 6
PMID 28978074
Citations 15
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Profiling Cell-Free DNA from Malignant Pleural Effusion for Oncogenic Driver Mutations in Patients with Treatment-Naive Stage IV Adenocarcinoma: A Multicenter Prospective Study.

Chang S, Wei Y, Chen C, Lai Y, Hu P, Hung J Mol Diagn Ther. 2024; 28(6):803-810.

PMID: 39147938 PMC: 11512990. DOI: 10.1007/s40291-024-00736-8.


Overview on Therapeutic Options in Uncommon EGFR Mutant Non-Small Cell Lung Cancer (NSCLC): New Lights for an Unmet Medical Need.

Pretelli G, Claudia Spagnolo C, Ciappina G, Santarpia M, Pasello G Int J Mol Sci. 2023; 24(10).

PMID: 37240224 PMC: 10218597. DOI: 10.3390/ijms24108878.


Chip-based digital Polymerase Chain Reaction as quantitative technique for the detection of mutations in breast cancer patients.

Giannoni-Luza S, Acosta O, Murillo Carrasco A, Danos P, Cotrina Concha J, Guerra Miller H Heliyon. 2022; 8(11):e11396.

PMID: 36387506 PMC: 9650006. DOI: 10.1016/j.heliyon.2022.e11396.


The diagnostic accuracy of digital PCR, ARMS and NGS for detecting KRAS mutation in cell-free DNA of patients with colorectal cancer: A systematic review and meta-analysis.

Ye P, Cai P, Xie J, Wei Y PLoS One. 2021; 16(3):e0248775.

PMID: 33770081 PMC: 7997033. DOI: 10.1371/journal.pone.0248775.


Assessment of gene mutations in circulating free DNA in monitoring of response to EGFR tyrosine kinase inhibitors in patients with lung adenocarcinoma.

Nicos M, Wojas-Krawczyk K, Krawczyk P, Chmielewska I, Wojcik-Superczynska M, Reszka K Arch Med Sci. 2020; 16(6):1496-1500.

PMID: 33224359 PMC: 7667428. DOI: 10.5114/aoms.2019.89217.


References
1.
Zhou Q, Zhang X, Chen Z, Yin X, Yang J, Xu C . Relative abundance of EGFR mutations predicts benefit from gefitinib treatment for advanced non-small-cell lung cancer. J Clin Oncol. 2011; 29(24):3316-21. DOI: 10.1200/JCO.2010.33.3757. View

2.
Thress K, Brant R, Carr T, Dearden S, Jenkins S, Brown H . EGFR mutation detection in ctDNA from NSCLC patient plasma: A cross-platform comparison of leading technologies to support the clinical development of AZD9291. Lung Cancer. 2015; 90(3):509-15. DOI: 10.1016/j.lungcan.2015.10.004. View

3.
Qiu M, Wang J, Xu Y, Ding X, Li M, Jiang F . Circulating tumor DNA is effective for the detection of EGFR mutation in non-small cell lung cancer: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2014; 24(1):206-12. DOI: 10.1158/1055-9965.EPI-14-0895. View

4.
Dietel M, Johrens K, Laffert M, Hummel M, Blaker H, Pfitzner B . A 2015 update on predictive molecular pathology and its role in targeted cancer therapy: a review focussing on clinical relevance. Cancer Gene Ther. 2015; 22(9):417-30. DOI: 10.1038/cgt.2015.39. View

5.
Marusyk A, Polyak K . Tumor heterogeneity: causes and consequences. Biochim Biophys Acta. 2009; 1805(1):105-17. PMC: 2814927. DOI: 10.1016/j.bbcan.2009.11.002. View