Capture-Based Targeted Ultradeep Sequencing in Paired Tissue and Plasma Samples Demonstrates Differential Subclonal ctDNA-Releasing Capability in Advanced.

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Capture-Based Targeted Ultradeep Sequencing in Paired Tissue and Plasma Samples Demonstrates Differential Subclonal ctDNA-Releasing Capability in Advanced Lung Cancer Xiaowei Mao, MD, Zhou Zhang, PhD, Xiaoxuan Zheng, MD, Fangfang Xie, MD, Feidie Duan, PhD, Liyan Jiang, MD, PhD, Shannon Chuai, PhD, Han Han-Zhang, PhD, Baohui Han, MD, PhD, Jiayuan Sun, MD, PhD Journal of Thoracic Oncology Volume 12, Issue 4, Pages 663-672 (April 2017) DOI: 10.1016/j.jtho.2016.11.2235 Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Figure 1 Schematic design of the clinical study. A total of 49 patients were enrolled in this study, including 41 who underwent a primary biopsy and eight who underwent a repeat tumor biopsy. Tissue samples and matching plasma samples were collected from each patient. Nine patients were excluded from next-generation sequencing (NGS) analysis: six had no tumor cells in their biopsy samples, the disease of two was diagnosed as early stage, and the disease of one was diagnosed as pleural endothelioma. cfDNA, cell-free DNA. Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Figure 2 Mutations detected in tissue biopsy samples and/or plasma samples. (A) By-variant comparison of somatic mutations detected in tumor tissue samples and/or their matching plasma samples. Green represents mutations detected from both sources, purple represents mutations present only in the plasma samples, and yellow represents mutations that are present only in the tissue samples. Different shapes represent different types of mutations. Circles represent silent mutations. Squares represent nonsilent mutations, and diamonds represent copy number variations. Patient identification numbers are listed at the bottom of the graph. The number of patients having a certain mutation is represented by the bar on the right. The number of mutations that each patient has is represented by the bar on the top of the graph. (B) Sensitivities of driver genes, cell cycle–related genes, and other genes, with mutations detected in either tissue biopsy samples (blue) or plasma samples (yellow) used as references. ctDNA, circulating tumor DNA. Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Figure 3 Normalized relative allelic fraction score (NRAFS) varies among subclones harboring distinct mutations. (A) The boxplot demonstrates subclones harboring distinct mutations that have significantly different NRAFSs. Subclones carrying driver mutations have the highest NRAFSs and subclones carrying cell cycle–related mutations have the lowest NRAFSs. (B) Heatmap of patients harboring both driver gene mutations and cell cycle–related gene mutations. Subclones with driver gene mutations have higher NRAFSs than subclones with cell cycle–related gene mutations. RET, rearranged during transfection gene; ARID1A, AT-rich interaction domain 1 gene; KEAP1, kelch like ECH associated protein 1 gene; OR4C6, olfactory receptor family 4 subfamily C member 6 gene; OR4A15, olfactory receptor family 4 subfamily A member 15 gene; ADAMTS16, ADAM metallopeptidase with thrombospondin type 1 motif 16 gene; BRCA1, BRCA1 associated RING domain 1 gene; BRINP3, BMP/retinoic acid inducible neural specific C gene; NFE2L2, nuclear factor erythroid 2, like 2 gene; STK11, serine/threonine kinase 11 gene; FGFR1, fibroblast growth factor receptor 1 gene; KDM5A, lysine demethylase 5A gene; NAV3, neuron navigator 3; U2AF1, U2 small nuclear RNA auxiliary factor 1 gene; TP53, tumor protein p53 gene; RB1, retinoblastoma 1 gene; SMAD4, SMAD family member 4 gene. Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Figure 4 Correlation between circulating tumor DNA (ctDNA) abundance and clinical features. The t test and Pearson correlation test were applied for continuous variables and binary variables, respectively. Boxplots of both variables over the dichotomized clinical features are shown. ADC, adenocarcinoma; NOS, not otherwise specified; SQCC, squamous cell carcinoma; CT, computed tomography; EBUS, endobronchial ultrasound; TBB, transbronchial biopsy; US, ultrasound, MLN, metastatic lymph nodes; PT, primary tumor. Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Supplementary Figure 1 Distribution of library complexity and insert size. Library complexity and insert size are shown for plasma (red), tissue (green) and white blood cells (blue). Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Supplementary Figure 2 Quantitation ability. Serial dilutions of STK11, TSC1, KRAS and TP53 from 100% to 1%. Excellent positive correlation between observed and expected allele frequency was observed Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Supplementary Figure 3 Correlation between the mutation allele frequency in tumor tissue and ctDNA. Correlation between allele frequencies detected in tissue and its matching plasma Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

Supplementary Figure 4 Concordance between conventional methods and NGS. EGFR, ALK, ROS1 mutations were detected by conventional methods ARMS-PCR, FISH and RT-PCR, respectively and NGS in 37 non-small cell lung cancer patients. A-C. Summary of comparisons between NGS and conventional methods D. Details of comparisons between NGS and conventional methods. Top panel denotes the pathology of each sample. Journal of Thoracic Oncology 2017 12, 663-672DOI: (10.1016/j.jtho.2016.11.2235) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions