Figure 1. Plasma next-generation sequencing (NGS) assay workflow, comparison of variant allelic fraction with ... Figure 1. Plasma next-generation sequencing.

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Application of Single-Molecule Amplification and Resequencing Technology for Broad Surveillance of Plasma Mutations in Patients with Advanced Lung Adenocarcinoma

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Figure 1. Plasma next-generation sequencing (NGS) assay workflow, comparison of variant allelic fraction with ... Figure 1. Plasma next-generation sequencing (NGS) assay workflow, comparison of variant allelic fraction with orthogonal plasma ddPCR, and variant detection in cfDNA. (A) Workflow describing the targeted DNA plasma cell-free DNA (cfDNA) assay. Additional details are provided in the ‘Patients and Methods’ section. (B) Allele frequency (AF) in plasma as determined by NGS were compared those calculated by ddPCR in a subset of group 1 and 3 samples with NGS-identified EGFR or KRAS mutations. Plasma AF as measured by NGS (y-axis, log scale) was plotted against plasma AF as measured by ddPCR (x-axis, log scale). Correlation was calculated using Pearson’s correlation coefficient (0.98, P < 0.001). Dotted line indicates a break in the axis to allow representation of variants which were not detected by either assay. (C) Box plot of plasma AF (y-axis) by gene (x-axis) according to mutation type (driver, blue; resistance, orange) depicting median as well as first and third quartiles. Data falling outside the Q1–Q3 range were plotted as outliers (outside of the vertical lines). (D) Correlation of plasma variant AF (y-axis, log scale) and total cfDNA concentration (x-axis, log scale) (Spearman’s correlation = 0.3 P-value = 0.006) for samples in which the driver was detected (blue dots) or missed (gray dots). Dotted line indicates a break in the vertical axis to allow representation of samples in which the driver identified by tissue-based testing was not detected by cfDNA analysis. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) 2019. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Ann Oncol, mdz046, https://doi.org/10.1093/annonc/mdz046 The content of this slide may be subject to copyright: please see the slide notes for details.

Figure 2. Capturing drug resistance mutations in plasma cfDNA Figure 2. Capturing drug resistance mutations in plasma cfDNA. (A) Plot depicting one patient with EGFR and ERBB2 ... Figure 2. Capturing drug resistance mutations in plasma cfDNA. (A) Plot depicting one patient with EGFR and ERBB2 amplifications in plasma after treatment with erlotinib. Normalized sequencing read counts in comparison to healthy samples (y-axis) were plotted against chromosome number (x-axis); each dot represents an exon or intron target region covered by the 37-gene panel. Vertical dotted lines indicate chromosome boundaries. Specific genes are indicated by color: FGFR3, blue; EGFR, red; MET, pink; FGFR1, green; FGFR2, aqua; ERBB2, yellow. (B) Relationship between allelic fraction of driver and resistance mutations detected in plasma. The allele frequency (AF) (percent) of plasma cell-free DNA (cfDNA) variants detected in plasma (y-axis) was plotted for individual samples (x-axis). Driver and resistance mutations detected in tissue and plasma cfDNA are indicated by green and orange dots, respectively; resistance mutations identified in plasma cfDNA but not detected in tissue are indicated in gray. Shapes indicate specific mutations. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) 2019. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) Ann Oncol, mdz046, https://doi.org/10.1093/annonc/mdz046 The content of this slide may be subject to copyright: please see the slide notes for details.