Exome sequencing identifies somatic mutations of DDX3X in natural killer/T-cell lymphoma (original) (raw)
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Gene Expression Omnibus
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Acknowledgements
This work was supported by the Chinese National Key Basic Research Project 973 (2013CB966800 to S.-J.C.); the Chinese Ministry of Health (201202003 to S.-J.C.); the Mega-projects of Scientific Research for the 12th Five-Year Plan (2013ZX09303302 to S.-J.C.); the State Key Laboratories Project of Excellence (81123005 to S.-J.C.); the National Natural Science Foundation of China (81325003 and 81172254 to W.-L.Z.); the Shanghai Commission of Science and Technology (11JC1407300 to W.-L.Z.); the Program of Shanghai Subject Chief Scientist (13XD1402700 to W.-L.Z.); the Doctoral Innovation Fund Projects from SJTU School of Medicine (BXJ201312 to Z.-X.Y.); the Samuel Waxman Cancer Research Foundation Co-PI Program; and the Multi-center Hematology-Oncology Protocols Evaluation System (M-HOPES). We are grateful to Y. Zhao, J. Xu and F. Yang for sample preparation, E.-D. Wang for experimental guidance and X.-C. Fei, L.-L. Wu and X.-Q. Li for pathological analysis.
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Author notes
- Lu Jiang, Zhao-Hui Gu, Zi-Xun Yan and Xia Zhao: These authors contributed equally to this work.
Authors and Affiliations
- State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine and Collaborative Innovation Center of Systems Biomedicine, Shanghai, China
Lu Jiang, Zhao-Hui Gu, Zi-Xun Yan, Xia Zhao, Yin-Yin Xie, Zi-Guan Zhang, Chun-Ming Pan, Jin-Yan Huang, Li Wang, Yang Shen, Guoyu Meng, Jing-Yi Shi, Lan Xu, Yang Li, Jing Lu, Zhong Zheng, Wen Xue, Wei-Li Zhao, Zhu Chen & Sai-Juan Chen - Department of Otorhinolaryngology, Rui Jin Hospital, SJTU School of Medicine, Shanghai, China
Yuan Hu & Chang-Ping Cai - Department of Oncology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
Ying Dong - Department of Hematology, Tongji Medical College, Huazhong University of Science and Technology, Tongji Hospital, Wuhan, China
Jian-Feng Zhou - Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
Jian-Da Hu - Department of Pathology, Shanxi Oncology Hospital, Taiyuan, China
Jin-Fen Wang - Department of Oncology, Jiangsu Cancer Hospital, Nanjing, China
Yuan-Hua Liu - Department of Hematology, Second Affiliated Hospital of Shanxi Medical University, Taiyuan, China
Lin-Hua Yang - Department of Hematology, Anhui Oncology Hospital, Bengbu Medical College, Bengbu, China
Feng Zhang - Department of Hematology, Changhai Hospital, Second Military Medical University, Shanghai, China
Jian-Min Wang - Department of Hematology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
Zhao Wang - Department of Hematology, First Affiliated Hospital of Guangxi Medical University, Nanning, China
Zhi-Gang Peng - Department of Hematology, Renji Hospital, SJTU School of Medicine, Shanghai, China
Fang-Yuan Chen - Department of Hematology, Anhui Provincial Hospital, Hefei, China
Zi-Min Sun - Department of Radiation Oncology, Eye and ENT Hospital of Fudan University, Shanghai, China
Hao Ding - Department of Hematology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
Ju-Mei Shi - Department of Hematology, Changzheng Hospital, Second Military Medical University, Shanghai, China
Jian Hou - Department of Hematology, Second Hospital of Dalian Medical University, Dalian, China
Jin-Song Yan - Pôle de Recherches Sino-Français en Science du Vivant et Génomique, Laboratory of Molecular Pathology, Shanghai, China
Wei-Li Zhao, Zhu Chen & Sai-Juan Chen
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Contributions
L.J., Z.-X.Y., Y.-Y.X., L.W., Z.Z. and W.X. performed experiments. Z.-H.G., Z.-G.Z. and J.-Y.H. were responsible for bioinformatics investigation. X.Z. and Y.S. gathered detailed clinical information for the study and carried out clinical analysis. C.-M.P., J.-Y.S., L.X., Y.L. and J.L. carried out the exome sequencing and participated in the validation experiments. Y.H. and C.-P.C. gave technical support. Y.D., J.-F.Z., J.-D.H., J.-F.W., Y.-H.L., L.-H.Y., F.Z., J.-M.W., Z.W., Z.-G.P., F.-Y.C., Z.-M.S., H.D., J.-M.S., J.H. and J.-S.Y. participated in the preparation of biological samples. G.M. carried out the structural analysis. S.-J.C., Z.C. and W.-L.Z. conceived the study, directed and supervised research and wrote the manuscript.
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Correspondence toWei-Li Zhao, Zhu Chen or Sai-Juan Chen.
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Integrated supplementary information
Supplementary Figure 1 Correlation of nonsilent somatic mutations with the age and the disease stage of 25 people with NKTCL, subjected to whole-exome sequencing.
(a) Distribution of non-silent somatic mutations according to the age of the patients. P value was calculated by two-sided F-test (n = 25 subjects). (b) Distribution of non-silent somatic mutations according to the disease stage of the patients. P value was calculated by two-sided Student’s t test (mean ± s.d.; n = 25 subjects).
Supplementary Figure 2 Distribution of reads mapped to the EBV genome in tumor and matched peripheral blood samples of 25 people with NKTCL, subjected to whole-exome sequencing.
Supplementary Figure 3 Somatic copy-number alterations (CNAs) and uniparental disomies (UPDs) in 25 people with NKTCL, subjected to whole-exome sequencing.
(a) Types and genomic distribution of somatic copy number alterations (CNAs) and uniparental disomies (UPDs) in each patient. (b) Types and genomic distribution of somatic CNAs and UPDs according to the chromosomes.
Supplementary Figure 4 Functional categories of somatic mutations in 25 people with NKTCL, subjected to whole-exome sequencing.
(a) Gene ontology analysis of 795 somatic mutations expected to alter the function or structure of the encoded protein. Adjusted P value < 0.01 and False Discover Rate < 0.1 (Online Methods ). (b) Functional categories of 26 candidate gene mutations according to 6q21 deletions.
Supplementary Figure 5 Relationship between mutations of DDX3X, tumor suppressors, JAK-STAT-pathway molecules and epigenetic modifiers in NKTCL.
(a) Distribution of mutations in DDX3X, tumor suppressors (TP53 and MGA), JAK-STAT pathway (STAT3 and STAT5B) and epigenetic modifiers (MLL2, ARID1A, EP300 and ASXL3) in NKTCL. (b) Comparison of the allele frequencies of selected mutations in samples harboring mutations in DDX3X and tumor suppressors. (c) Comparison of the allele frequencies of selected mutations in samples harboring mutations in DDX3X and JAK-STAT pathway molecules. (d) Comparison of the allele frequencies of selected mutations in samples harboring mutations in and DDX3X and epigenetic modifiers. Each axis showed the frequencies of the mutant alleles. When a single gene had 2-Hit mutation, the frequencies of major alleles were indicated. Data were analyzed statistically by two-sided Wilcoxon rank-sum test.
Supplementary Figure 6 Cellular localizations of DDX3X and EBV-associated RNA or protein in EBV-infected natural killer cell line KAI3.
(a) Cellular localizations of DDX3X and EBV-Encoded RNA (EBER). (b) Cellular localizations of DDX3X and latent membrane protein 1 (LMP-1). Images were visualized by confocal laser scanning microscopy. Scale bar, 5 μm.
Supplementary Figure 8 shRNA-mediated knockdown of DDX3X enhanced the growth of DDX3X wild-type natural killer cell line KAI3.
(a) Flow cytometric plots showing the percentage of GFP+ KAI3 cells 3 days (considered as day 0 for cell growth evaluation) and 15 days (considered day 12 for cell growth evaluation) post transduction of cells with scrambled shRNA (Scrambled shRNA) or shRNA targeting DDX3X (DDX3X shRNA1). Cells were switched to natural killer culture medium with reduced IL-2 (25 U/mL). (b) Quantification of the percentages of GFP+ KAI3 cells transfected with scrambled shRNA or DDX3X shRNA1 at regular time intervals, as normalized to the levels at day 0. **: P < 0.01 as compared to the scrambled shRNA. P values were calculated using two-sided Student’s t test (mean ± s.d.; n = 3 per group). (c) Western blot images of DDX3X levels in shRNA-transfected, GFP+ sorted cells post transduction with the scrambled shRNA or DDX3X shRNA1. (d) Flow cytometric plots showing the percentage of GFP+ KAI3 cells 3 days (considered as day 0 for cell growth evaluation) and 15 days (considered day 12 for cell growth evaluation) post transduction of cells with scrambled shRNA (Scrambled shRNA) or shRNA targeting DDX3X (DDX3X shRNA2). Cells were switched to natural killer culture medium with reduced IL-2 (25 U/mL). (e) Quantification of the percentages of GFP+ KAI3 cells transfected with scrambled shRNA or DDX3X shRNA2 at regular time intervals, as normalized to the levels at day 0. **: P < 0.01; ***: P < 0.001, as compared to the scrambled shRNA. P values were calculated using two-sided Student’s t test (mean ± s.d.; n = 3 per group). (f) Western blot images of DDX3X levels in shRNA-transfected, GFP+ sorted cells post transduction with the scrambled shRNA or DDX3X shRNA2.
Supplementary Figure 9 Gene-expression profiles of NF-κB and MAPK pathways in NKTCL.
(a) Significantly upregulated and downregulated genes of NF-κB pathway in _DDX3X_-mutated tumors, as compared to those in _DDX3X_-wild-type (wt) tumors of NKTCL. (b) Significantly upregulated and downregulated genes of MAPK pathway in _DDX3X_-mutated tumors, as compared to those in _DDX3X_-wild-type (wt) tumors of NKTCL.
Supplementary Figure 10 Kaplan-Meier analysis of the survival of people with NKTCL, excluding extranasal cases or stage III and stage IV cases.
(a) Overall survival (OS) and progression-free survival (PFS) of NKTCL patients excluding extranasal cases according to mutation status of DDX3X and TP53 (upper panel) and according to risk stratification combining International Prognostic Index (IPI) and mutation status of DDX3X and TP53 (lower panel). (b) OS and PFS of NKTCL patients excluding stage III–IV cases according to mutation status of DDX3X and TP53 (upper panel) and according to risk stratification combining IPI and mutation status of DDX3X and TP53 (lower panel). Risk stratification combining IPI and mutation status of DDX3X and TP53: Group 1: IPI0–1 and wt_DDX3X_/wt_TP53_; Group 2: IPI0–1 and mut_DDX3X_/mut_TP53_ or IPI2–5 and wt_DDX3X_/wt_TP53_; Group 3: IPI2–5 and mut_DDX3X_/mut_TP53_. wt: wild-type, individuals without DDX3X or TP53 mutations; mut: mutation, individuals with DDX3X or TP53 mutations. One individual with both DDX3X and TP53 mutations was grouped into two cohorts with mutations.
Supplementary Figure 12 Flow chart for identification of somatic single-nucleotide variations and indels from paired whole-exome-sequencing data.
Supplementary Figure 13 Representative GeneScanning results of TRB or TRG rearrangement in NKTCL.
(a) TCRB rearrangement negative. (b) TCRG rearrangement negative. (c) TCRG rearrangement positive. The control gene peaks were shown at 101, 200, 300 and 395nt.
Supplementary Figure 14 Representative GeneScanning results of TRD rearrangement in NKTCL.
(a) TCRD rearrangement negative. (b) TCRD rearrangement positive. The control gene peaks were shown at 101, 200, 300 and 395nt.
Supplementary Figure 15 Positive controls of immunohistochemistry of human anti-RelB antibody and human anti-p-ERK antibody.
(a) The positive control of immunohistochemistry of human colon cancer tissue using anti-RelB antibody (Proteintech, 25027-1-AP). (b) The positive control of immunohistochemistry of human lung cancer tissue using anti-p-ERK antibody (Cell Signaling, 4370S). Scale bar, 20 μm.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–15 and Supplementary Tables 4 and 6–12 (PDF 2826 kb)
Supplementary Table 1
Clinicopathological characteristics of 105 subjects with NKTCL (XLSX 48 kb)
Supplementary Table 2
Somatic nonsilent mutations identified in 25 subjects with NKTCL, subjected to whole-exome sequencing (XLSX 149 kb)
Supplementary Table 3
Somatic copy-number alterations and uniparental disomies in 25 subjects with NKTCL, subjected to whole-exome sequencing (XLSX 21 kb)
Supplementary Table 5
Mutation screening in test and validation cohorts of NKTCL (n = 105) (XLSX 22 kb)
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Jiang, L., Gu, ZH., Yan, ZX. et al. Exome sequencing identifies somatic mutations of DDX3X in natural killer/T-cell lymphoma.Nat Genet 47, 1061–1066 (2015). https://doi.org/10.1038/ng.3358
- Received: 11 February 2015
- Accepted: 24 June 2015
- Published: 20 July 2015
- Issue Date: September 2015
- DOI: https://doi.org/10.1038/ng.3358