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Comprehensive Characterization of Oncogenic Drivers in Asian Lung Adenocarcinoma  Shiyong Li, BS, Yoon-La Choi, MD, PhD, Zhuolin Gong, PhD, Xiao Liu, PhD,

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Presentation on theme: "Comprehensive Characterization of Oncogenic Drivers in Asian Lung Adenocarcinoma  Shiyong Li, BS, Yoon-La Choi, MD, PhD, Zhuolin Gong, PhD, Xiao Liu, PhD,"— Presentation transcript:

1 Comprehensive Characterization of Oncogenic Drivers in Asian Lung Adenocarcinoma 
Shiyong Li, BS, Yoon-La Choi, MD, PhD, Zhuolin Gong, PhD, Xiao Liu, PhD, Maruja Lira, BS, Zhengyan Kan, PhD, Ensel Oh, PhD, Jian Wang, PhD, Jason C. Ting, PhD, Xiangsheng Ye, PhD, Christoph Reinhart, PhD, Xiaoqiao Liu, PhD, Yunfei Pei, PhD, Wei Zhou, PhD, Ronghua Chen, PhD, Shijun Fu, PhD, Gang Jin, MD, PhD, Awei Jiang, MS, Julio Fernandez, PhD, James Hardwick, PhD, Min Woong Kang, MD, Hoseok I, MD, Hancheng Zheng, PhD, Jhingook Kim, MD, PhD, Mao Mao, MD, PhD  Journal of Thoracic Oncology  Volume 11, Issue 12, Pages (December 2016) DOI: /j.jtho Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

2 Figure 1 Summary of genetic alterations in 33 lung adenocarcinoma tumors. (A) Histograms showing the number or extent of alterations found for each genetic parameter across different subgroups. Tumors were grouped by molecular subtype with a blue dotted line (see Supplementary Fig. 1B) and sorted in descending order according to the number of somatic single nucleotide variations (SNVs) within each group. Starting from the top, the panels show (for each patient) the SNV number, the driver gene, the signature component ratio (used to classify tumors into different groups), and the mutation spectrum. (B) Relative contribution of each mutation type to each of four mutational signatures, as identified by nonnegative matrix factorization analysis (see Methods section). (C and D) Scatter plot with linear fitting between the tumors’ component ratios of signature A to the log2 total SNV mutational number (C) or the ratio of the number of SNVs mutated in the coding sequence (CDS) to the total number of SNVs (D). ERBB2, erb-b2 receptor tyrosine kinase 2 gene; MET, Met proto-oncogene tyrosine kinase. Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

3 Figure 2 Distribution of mutations in cancer genes predicted by whole-genome sequencing. (A) Mutations shown in red represent those that were present in more than one sample. The number of samples with each mutation is indicated in parentheses. (B) Amino acid sequence near the erb-b2 receptor tyrosine kinase 2 gene (ERBB2)/EGFR insertion sites. MET, Met proto-oncogene tyrosine kinase; SETD2, SET domain containing 2 gene; TP53, tumor protein p53 gene. Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

4 Figure 3 Landscape of oncogenes in tumor samples from Asian patients with LUAD. (A) The OncoPlot summarizes the significantly mutated oncogenes found in 229 LUAD tumors. The left panel shows samples detected by Sequenom during the prescreening step, and the right panel shows samples detected by whole-genome sequencing. Exon14_Skipping_Missense indicates samples showing MET exon 14 skipping, as well as a splicing mutation nearest to exon 14. Samples not found to harbor known oncogenes are not represented in (A). The mutational frequency of detected oncogenes is shown in (B), except for NRAS because of its extremely low frequency (one of 271). Sextuple_N indicates samples in which none of the tested oncogenes was detected, but no recurrent erb-b2 receptor tyrosine kinase 2 gene (ERBB2)/EGFR exon 20 insertion mutations were screened for in the samples. Octuple_N indicates samples in which no known oncogenes were detected. The oncogene frequency of nonsmokers/smokers are shown in C and D. The nonsmoker group is divided into two subgroups by sex, and the frequencies of oncogene mutations in these subgroups are shown in E and F. ALK, anaplastic lymphoma receptor tyrosine kinase gene; RET, ret proto-oncogene; MET, Met proto-oncogene tyrosine kinase. Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

5 Figure 4 Distribution of oncogene mutation frequencies in Asians compared with in whites. (A) Differing frequencies of oncogenic mutations in Asian patients and white patients. p Values were calculated by Pearson's chi-square test with the simulated p value method, as shown in the top of the figure. Comparison of oncogene frequencies between the Asian and white populations was also performed across the smoking group (B) and the nonsmoking group (C). Sextuple_N indicates that no known oncogene was detected and that no recurrent erb-b2 receptor tyrosine kinase 2 gene (ERBB2)/EGFR exon 20 insertion mutations were screened for in the samples. Octuple_N indicates samples in which no known oncogenes were detected. MET, Met proto-oncogene tyrosine kinase; RET, ret proto-oncogene; ALK, anaplastic lymphoma receptor tyrosine kinase gene. Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

6 Figure 5 Distribution of mutation (Mut) types in the KRAS oncogene. (A) Comparison between tumors from the Asian and white populations, with or without KRAS mutations. (B) Comparisons between Asian and white smokers, with or without KRAS mutations. p Values were calculated by Pearson's chi-square test with continuity correction. (C) The number of different KRAS mutation types. Type G12other indicates that the 12th amino acid was changed to any amino acid other than A, C, D, S, or V. G13all indicates all mutations occurring at amino acid 13 of KRAS. WT, wild type. Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

7 Supplementary Figure 1 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

8 Supplementary Figure 2 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

9 Supplementary Figure 3 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

10 Supplementary Figure 4 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

11 Supplementary Figure 5 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

12 Supplementary Figure 6 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

13 Supplementary Figure 7 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

14 Supplementary Figure 8 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

15 Supplementary Figure 9 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

16 Supplementary Figure 10 Journal of Thoracic Oncology  , DOI: ( /j.jtho ) Copyright © 2016 International Association for the Study of Lung Cancer Terms and Conditions

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