In metastatic melanoma, 40%–50% of patients harbor a BRAF V600E mutation and are thereby eligible to receive a combined BRAF/MEK inhibitor therapy. Compared to standard-of-care tissue-based genetic testing, analysis of circulating tumor DNA (ctDNA) from blood enables a comprehensive assessment of tumor mutational status in real-time and can be used for monitoring response to therapy. The aim of our study was to directly compare the performance of two highly sensitive methodologies, droplet digital PCR (ddPCR) and a combination of ARMS/asymmetric-rapid PCR/melting curve analysis, for the detection of BRAF V600E in plasma from melanoma patients.
Cell-free DNA (cfDNA) was isolated from 120 plasma samples of stage I to IV melanoma patients. Identical plasma-cfDNA samples were subjected to BRAF V600E mutational analysis using in parallel, ddPCR and the combination of ARMS/asymmetric-rapid PCR/melting curve analysis.
BRAF V600E mutation was detected in 9/117 (7.7%) ctDNA samples by ddPCR and in 22/117 (18.8%) ctDNA samples by the combination of ARMS/asymmetric- rapid PCR/melting curve analysis. The concordance between these two methodologies was 85.5% (100/117). The comparison of plasma-ctDNA analysis using ddPCR and tissue testing revealed an overall agreement of 79.4% (27/34), while the corresponding agreement using the combination of ARMS/asymmetric-rapid PCR/melting curve analysis was 73.5% (25/34). Moreover, comparing the detection of BRAF-mutant ctDNA with the clinics, overall agreement of 87.2% (48/55) for ddPCR and 79.2% (42/53) was demonstrated. Remarkably, the duration of sample storage was negatively correlated with correctness of genotyping results highlighting the importance of pre-analytical factors.
Our direct comparison study has shown a high level of concordance between ddPCR and the combination of ARMS/asymmetric-rapid PCR/melting curve analysis for the detection of BRAF V600E mutations in plasma.
The authors thank RomyEichner for helping to collect samples and Victor Costina for critically reading the manuscript.
Author contributions: Eleni Tzanikou: experiments, manuscript writing and editing, Verena Haselmann: study design, supervising experimental procedures, statistical analysis, manuscript writing and editing, Athina Markou: experiments, Angelika Duda: experiments, Michael Neumaier: study design, Jochen Utikal: patient enrollment, Evi Lianidou: study design, supervising experimental procedures, manuscript writing and editing. All authors contributed to revision of the manuscript and approved it for submission. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. The ethical approval was requires for this study.
Research funding: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1RCI-02935).
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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