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G. Xu
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JCES01 - Joint IASLC - Chinese Society for Clinical Oncology - Chinese Alliance Against Lung Cancer Session (ID 413)
- Event: WCLC 2016
- Type: Joint Chinese / English Session
- Track:
- Presentations: 1
- Moderators:F.R. Hirsch, C. Bai
- Coordinates: 12/04/2016, 08:00 - 11:45, Stolz 1
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JCES01.22 - Comparison of Four Leading Technologies for Detecting EGFR Mutations in Circulating Tumor DNA from Patients with Non-Small Cell Lung Carcinoma (ID 7064)
11:10 - 11:10 | Author(s): G. Xu
- Abstract
Background:
This study aimed to assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations including L858R, E19-dels, T790M, and G719X from circulating tumor DNA (ctDNA) in patients with non-small cell lung cancer (NSCLC).
Methods:
Plasma samples were collected from 20 patients with NSCLC including detailed clinical information along with data regarding treatment response. ctDNA was extracted from 10 mL plasma using the QIAamp Circulating Nucleic Acid Kit (Qiagen). Extracted ctDNA was analyzed using two real time-amplification refractory mutation system-quantitative PCR platforms (cobas® EGFR Mutation Test: cobas; and AmoyDx® EGFR 29 Mutations Detection Kit: ADx), one digital platform (Droplet Digital[TM] PCR, ddPCR: Bio-rad), and one next-generation sequencing platform (firefly NGS: Accuragen).
Results:
If a positive result was obtained from any one of the four platforms, the sample was categorized as positive. We identified 15 EGFR mutations in 20 patients with NSCLC using the four platforms, for which 7, 11, 10, and 12 mutations were detected by ADx, cobas, ddPCR, and firefly NGS, respectively. Among the 15 EGFR mutations, six and seven EGFRalterations demonstrated an allele frequency of more or less than 1% (group A or B, respectively), and two exhibited unknown allele frequency. In group A, 5, 5, 5, and 6 EGFR mutations were detected by ADx ,cobas, ddPCR, and firefly NGS, respectively. The positive coincidence rate of any two platforms ranged from 66.7% to 100% and the kappa value varied from 0.787 to 1.000 in group A. In group B, 1, 5, 5, and 6 EGFR mutations were detected and the positive coincidence rate of any two platforms ranged from 16.7% to 100% and the kappa value varied from 0.270 to 1.000. The output of cobas, ddPCR, and firefly NGS were highly correlated, whereas ADx displayed weak concordance with these three platforms in group B. In addition, we identified 75 wild-type loci when EGFR alleles identified as negative by one or more platforms were considered as negative. ADx, cobas, ddPCR, and firefly NGS uncovered 73, 69, 70, and 68 EGFR wild-type loci, respectively. The concordance and negative coincidence rates between any two platforms were over 90%.
Conclusion:
The detection rate and concordance were probably affected by the abundance of EGFR mutations and the sensitivity of different platforms. Three platforms, including cobas, ddPCR, and firefly NGS, exhibited higher positive coincidence and detection rates when the allele frequency was lower than 1%.
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P3.02b - Poster Session with Presenters Present (ID 494)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 12/07/2016, 14:30 - 15:45, Hall B (Poster Area)
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P3.02b-011 - Comparison of Four Leading Technologies for Detecting EGFR Mutations in Circulating Tumor DNA from Patients with Non-Small Cell Lung Carcinoma (ID 4534)
14:30 - 14:30 | Author(s): G. Xu
- Abstract
Background:
This study aimed to assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations including L858R, E19-dels, T790M, and G719X from circulating tumor DNA (ctDNA) in patients with non-small cell lung cancer (NSCLC).
Methods:
Plasma samples were collected from 20 patients with NSCLC including detailed clinical information along with data regarding treatment response. ctDNA was extracted from 10 mL plasma using the QIAamp Circulating Nucleic Acid Kit (Qiagen). Extracted ctDNA was analyzed using two real time-amplification refractory mutation system-quantitative PCR platforms (cobas® EGFR Mutation Test: cobas; and AmoyDx® EGFR 29 Mutations Detection Kit: ADx), one digital platform (Droplet Digital[TM] PCR, ddPCR: Bio-rad), and one next-generation sequencing platform (firefly NGS: Accuragen).
Results:
If a positive result was obtained from any one of the four platforms, the sample was categorized as positive. We identified 15 EGFR mutations in 20 patients with NSCLC using the four platforms, for which 7, 11, 10, and 12 mutations were detected by ADx, cobas, ddPCR, and firefly NGS, respectively. Among the 15 EGFR mutations, six and seven EGFR alterations demonstrated an allele frequency of more or less than 1% (group A or B, respectively), and two exhibited unknown allele frequency. In group A, 5, 5, 5, and 6 EGFR mutations were detected by ADx ,cobas, ddPCR, and firefly NGS, respectively. The positive coincidence rate of any two platforms ranged from 66.7% to 100% and the kappa value varied from 0.787 to 1.000 in group A. In group B, 1, 5, 5, and 6 EGFR mutations were detected and the positive coincidence rate of any two platforms ranged from 16.7% to 100% and the kappa value varied from 0.270 to 1.000. The output of cobas, ddPCR, and firefly NGS were highly correlated, whereas ADx displayed weak concordance with these three platforms in group B. In addition, we identified 75 wild-type loci when EGFR alleles identified as negative by one or more platforms were considered as negative. ADx, cobas, ddPCR, and firefly NGS uncovered 73, 69, 70, and 68 EGFR wild-type loci, respectively. The concordance and negative coincidence rates between any two platforms were over 90%.
Conclusion:
The detection rate and concordance were probably affected by the abundance of EGFR mutations and the sensitivity of different platforms. Three platforms, including cobas, ddPCR, and firefly NGS, exhibited higher positive coincidence and detection rates when the allele frequency was lower than 1%.
