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Recurrent ECSIT mutation encoding V140A triggers hyperinflammation and promotes hemophagocytic syndrome in extranodal NK/T cell lymphoma

Nature Medicine volume 24, pages 154164 (2018) | Download Citation


Hemophagocytic syndrome (HPS) is a fatal hyperinflammatory disease with a poorly understood mechanism that occurs most frequently in extranodal natural killer/T cell lymphoma (ENKTL). Through exome sequencing of ENKTL tumor–normal samples, we have identified a hotspot mutation (c.419T>C) in the evolutionarily conserved signaling intermediate in Toll pathway (ECSIT) gene, encoding a V140A variant of ECSIT. ECSIT-V140A activated NF-κB more potently than the wild-type protein owing to its increased affinity for the S100A8 and S100A9 heterodimer, which promotes NADPH oxidase activity. ECSIT-T419C knock-in mice showed higher peritoneal NADPH oxidase activity than mice with wild-type ECSIT in response to LPS. ECSIT-T419C-transfected ENKTL cell lines produced tumor necrosis factor (TNF)-α and interferon (IFN)-γ, which induced macrophage activation and massive cytokine secretion in cell culture and mouse xenografts. In individuals with ENKTL, ECSIT-V140A was associated with activation of NF-κB, higher HPS incidence, and poor prognosis. The immunosuppressive drug thalidomide prevented NF-κB from binding to the promoters of its target genes (including TNF and IFNG), and combination treatment with thalidomide and dexamethasone extended survival of mice engrafted with ECSIT-T419C-transfected ENKTL cells. We added thalidomide to the conventional dexamethasone-containing therapy regimen for two patients with HPS who expressed ECSIT-V140A, and we observed reversal of their HPS and disease-free survival for longer than 3 years. These findings provide mechanistic insights and a potential therapeutic strategy for ENKTL-associated HPS.

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This work was supported by the National Key Research and Development Program of China (2017YFA0505600-04 to Q.L.), the National Natural Science Foundation of China (81630005, 81130040, and 81573025 to Q.L.; 81502594 to H.W.), the Innovative Research Team in University of Ministry of Education of China (IRT13049 to Q.L.), the Natural Science Foundation of Guangdong (2016A030311038 and 2017A030313608 to Q.L.), the Science and Technology Planning Project of Guangzhou (201604020163 to Q.L.), Fundamental Research Funds for the Central Universities (DUT15QY43 to Y.Y.), the Sun Yat-Sen University Clinical Research 5010 Program (2013011 to H.H.), and the National Natural Science Foundation of China (81773166 to Z.W.). We thank X. Zhu at Sun Yat-sen University Cancer Center (SYSUCC) for providing the luciferase–red fluorescent protein plasmid. We thank J. Shao in SYSUCC for T cell receptor gene rearrangement analysis. We thank H. Li from the Institute of Molecular Biophysics at Florida State University for the helpful comments and discussion on the molecular simulation work. We thank all members of the Liu laboratory for their critical comments and technical support.

Author information

Author notes

    • Haijun Wen
    • , Huajuan Ma
    • , Qichun Cai
    • , Suxia Lin
    • , Xinxing Lei
    • , Bin He
    •  & Sijin Wu

    These authors contributed equally to this work.


  1. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

    • Haijun Wen
    • , Huajuan Ma
    • , Qichun Cai
    • , Suxia Lin
    • , Xinxing Lei
    • , Bin He
    • , Zifeng Wang
    • , Yan Gao
    • , Wensheng Liu
    • , Min Yan
    • , Huiqiang Huang
    •  & Quentin Liu
  2. Institute of Cancer Stem Cell, Dalian Medical University, Dalian, China.

    • Haijun Wen
    •  & Quentin Liu
  3. State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.

    • Haijun Wen
  4. School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.

    • Huajuan Ma
  5. Department of Medical Oncology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

    • Qichun Cai
  6. Lymphoma Center, Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.

    • Qichun Cai
    • , Yan Gao
    •  & Huiqiang Huang
  7. Department of Pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, China.

    • Suxia Lin
  8. Center for Molecular Medicine, School of Life Science and Biotechnology, Dalian University of Technology, Dalian, China.

    • Sijin Wu
    •  & Yongliang Yang
  9. Department of Pathology, West-China Hospital of Sichuan University, Chengdu, China.

    • Weiping Liu
  10. State Key Laboratory of Oncology in South China, Department of Clinical Oncology, Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, Hong Kong.

    • Qian Tao
  11. Department of Hematology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

    • Zijie Long
    •  & Quentin Liu
  12. Institute of Biomedical Sciences, East China Normal University, Shanghai, China.

    • Dali Li
  13. Laboratory of Immunophysiology, Department of Animal Sciences, College of Agricultural, Consumer and Environmental Science (ACES) and Department of Pathology, College of Medicine, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA.

    • Keith W. Kelley


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H.W. organized the project, and H.W., H.M., B.H., and X.L. performed functional studies. Q.C. and S.L. performed the pathological studies. Z.W., Z.L., and M.Y. performed the in vitro studies. D.L. constructed the transgenic mice. Wensheng Liu performed the bioinformatics analysis. S.W. and Y.Y. modeled the 3D structures. K.W.K. participated in critical revision of the manuscript. Y.G., Weiping Liu, Q.T., and H.H. performed surgeries, collected subject samples, and managed subject information and tissue samples. Q.L. led the project and oversaw preparation of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Yongliang Yang or Huiqiang Huang or Quentin Liu.

Supplementary information

PDF files

  1. 1.

    Supplementary Figures

    Supplementary Figures 1–20

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    Clinicopathological characteristics of 88 patients with ENKTL.

  2. 2.

    Supplementary Table 2

    Somatic mutations identified by exome-sequencing in 5 ENKTL patients.

  3. 3.

    Supplementary Table 3

    Primer sequences for somatic mutations validation using Sanger sequencing.

  4. 4.

    Supplementary Table 4

    Sequenom MassARRAY survey result of 35 validated somatic mutations.

  5. 5.

    Supplementary Table 5

    Mutation frequency of 8 recurrent somatic mutations in 88 ENKTL samples.

  6. 6.

    Supplementary Table 6

    Primer sequence for survey of previously reported somatic mutations in our cohort using Sanger sequencing.

  7. 7.

    Supplementary Table 7

    Different-expressed genes induced by ECSIT V140A mutation in SNK6 and NKYS cells.

  8. 8.

    Supplementary Table 8

    Mutant ECSIT interacting proteins identified by liquid chromatography mass spectrometry.

  9. 9.

    Supplementary Table 9

    p52 nuclear expression in NK/T-LAHPS patients (at the time of ENKTL diagnosis) revealed by IHC staining.

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    Supplementary Table 10

    Disease progression of the 17 NK/T-LAHPS patients and their therapeutic schedules.

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    Supplementary Table 11

    Therapeutic schedule after the onset of HPS.

  12. 12.

    Supplementary Table 12

    Complete blood count and serum chemistry profile test after the onset of HPS.

  13. 13.

    Supplementary Table 13

    Sequenom MassARRAY Assay Design of 35 validated somatic mutations.

  14. 14.

    Supplementary Table 14

    Primers for qRT-PCR analysis of 10 NF-κB target genes and the internal control GAPDH.

  15. 15.

    Supplementary Table 15

    Primers for qRT-PCR analysis of 6 candidate genes.

  16. 16.

    Supplementary Table 16

    Sequences used in generating ECSIT-T419C knock-in mice.

  17. 17.

    Supplementary Table 17

    Primer sequences used in ChIP assay.

Text files

  1. 1.

    Supplementary Dataset 1

    PDB file of the final homology model of the wild type complex (ECSITWT-S100A8/A9-AA) after MD optimization.

  2. 2.

    Supplementary Dataset 2

    PDB file of the final homology model of the mutant complex (ECSITMU-S100A8/A9-AA) after MD optimization.


  1. 1.

    MD simulation on the S100A8/A9-AA complex

  2. 2.

    MD simulation on the ECSITV140A complexed with S100A8/A9-AA

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