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HLA-A+ tertiary lymphoid structures with reactivated tumor infiltrating lymphocytes are associated with a positive immunotherapy response in esophageal squamous cell carcinoma

British Journal of Cancer (2024)Cite this article

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Abstract

Background

Immune checkpoint blockade (ICB) therapy provides remarkable clinical benefits for multiple cancer types. However, the overall response rate to ICB therapy remains low in esophageal squamous cell carcinoma (ESCC). This study aimed to identify biomarkers of ICB therapy for ESCC and interrogate its potential clinical relevance.

Methods

We investigated gene expression in 42 treatment-naïve ESCC tumor tissues and identified differentially expressed genes, tumor-infiltrating lymphocytes and immune-related genes signatures associated with differential immunotherapy responses. We systematically assessed the tumor microenvironment using the NanoString GeoMx digital spatial profiler, single-cell RNA-seq and multiplex immunohistochemistry in ESCC. Finally, we evaluated the associations between HLA-A-positive tertiary lymphoid structures (TLSs) and patients’ responses to ICB in 60 ESCC patients.

Results

Tumor infiltrating B lymphocytes and several immune-related gene signatures, such as the antigen presenting machinery (APM) signature, are significantly elevated in ICB treatment responders. Multiplex immunohistochemistry identified the presence of HLA-A+ TLSs and showed that TLS-resident cells increasingly express HLA-A as TLSs mature. Most TLS-resident HLA-A+ cells are tumor-infiltrating T (TIL-T) or tumor-infiltrating B (TIL-B) lymphocytes. Digital spatial profiling of spatially distinct TIL-T lymphocytes and single-cell RNA-seq data from 60 ESCC tumor tissues revealed that CXCL13-expressing exhausted TIL-Ts inside TLSs are reactivated with elevated expression of the APM signature as TLSs mature. Finally, we demonstrated that HLA-A+ TLSs and their major cellular components, TIL-Ts and TIL-Bs, are associated with a clinical benefit from ICB treatment for ESCC.

Conclusions

HLA-A+ TLSs are present in ESCC tumor tissues. TLS-resident TIL-Ts with elevated expression of the APM signature may be reactivated. HLA-A+ TLSs and their major cellular components, TIL-Ts and TIL-Bs, may serve as biomarkers for ICB-treated ESCC patients.

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Fig. 1: Tumor-infiltrating B (TIL-B) lymphocytes and the APM expression are elevated in ICB-responsive ESCC patients.
Fig. 2: The presence of HLA-A+ TLSs in treatment-naïve ESCC tumors.
Fig. 3: TLS-resident TIL-Ts begin expressing the APM signature as TLSs mature.
Fig. 4: Exhausted TIL-Ts with elevated expression of the APM signature are reactivated.
Fig. 5: HLA-A+ TLSs are associated with a clinical benefit from ICB treatment for ESCC.

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Data availability

The RNA-seq data can be accessed on the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation / Beijing Institute of Genomics repository (https://ngdc.cncb.ac.cn/gsa-human) under the accession number HRA006820. The scRNA-seq data was downloaded from the GEO repository under the accession number GSE160269 [36].

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.

    Article  PubMed  Google Scholar 

  2. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66:115–32.

    Article  PubMed  Google Scholar 

  3. Liu J, Xie X, Zhou C, Peng S, Rao D, Fu J. Which factors are associated with actual 5-year survival of oesophageal squamous cell carcinoma? Eur J Cardiothorac Surg. 2012;41:e7–11.

    Article  PubMed  Google Scholar 

  4. Peng Q, Qiu X, Zhang Z, Zhang S, Zhang Y, Liang Y, et al. PD-L1 on dendritic cells attenuates T cell activation and regulates response to immune checkpoint blockade. Nat Commun. 2020;11:4835.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kojima T, Shah MA, Muro K, Francois E, Adenis A, Hsu CH, et al. Randomized Phase III KEYNOTE-181 Study of Pembrolizumab Versus Chemotherapy in Advanced Esophageal Cancer. J Clin Oncol. 2020;38:4138–48.

    Article  CAS  PubMed  Google Scholar 

  6. Kato K, Cho BC, Takahashi M, Okada M, Lin CY, Chin K, et al. Nivolumab versus chemotherapy in patients with advanced oesophageal squamous cell carcinoma refractory or intolerant to previous chemotherapy (ATTRACTION-3): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 2019;20:1506–17.

    Article  CAS  PubMed  Google Scholar 

  7. Baba Y, Nomoto D, Okadome K, Ishimoto T, Iwatsuki M, Miyamoto Y, et al. Tumor immune microenvironment and immune checkpoint inhibitors in esophageal squamous cell carcinoma. Cancer Sci. 2020;111:3132–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sautes-Fridman C, Petitprez F, Calderaro J, Fridman WH. Tertiary lymphoid structures in the era of cancer immunotherapy. Nat Rev Cancer. 2019;19:307–25.

    Article  CAS  PubMed  Google Scholar 

  9. Schumacher TN, Thommen DS. Tertiary lymphoid structures in cancer. Science. 2022;375:eabf9419.

    Article  CAS  PubMed  Google Scholar 

  10. Chen Z, Wang X, Jin Z, Li B, Jiang D, Wang Y, et al. Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response. NPJ Precis Oncol. 2024;8:73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Helmink BA, Reddy SM, Gao J, Zhang S, Basar R, Thakur R, et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature. 2020;577:549–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cabrita R, Lauss M, Sanna A, Donia M, Skaarup Larsen M, Mitra S, et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature. 2020;577:561–5.

    Article  CAS  PubMed  Google Scholar 

  13. Petitprez F, de Reynies A, Keung EZ, Chen TW, Sun CM, Calderaro J, et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature. 2020;577:556–60.

    Article  CAS  PubMed  Google Scholar 

  14. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–47.

    Article  CAS  PubMed  Google Scholar 

  15. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34:525–7.

    Article  CAS  PubMed  Google Scholar 

  16. Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation. 2021;2:100141.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Bolotin DA, Poslavsky S, Mitrophanov I, Shugay M, Mamedov IZ, Putintseva EV, et al. MiXCR: software for comprehensive adaptive immunity profiling. Nat Methods. 2015;12:380–1.

    Article  CAS  PubMed  Google Scholar 

  18. de Masson A, O’Malley JT, Elco CP, Garcia SS, Divito SJ, Lowry EL, et al. High-throughput sequencing of the T cell receptor beta gene identifies aggressive early-stage mycosis fungoides. Sci Transl Med. 2018;10:eaar5894.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Hao Y, Hao S, Andersen-Nissen E, Mauck WM 3rd, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data. Cell. 2021;184:3573–3587 e3529.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. McGinnis CS, Murrow LM, Gartner ZJ. DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors. Cell Syst. 2019;8:329–37.e324.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Korsunsky I, Millard N, Fan J, Slowikowski K, Zhang F, Wei K, et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat Methods. 2019;16:1289–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Aran D, Looney AP, Liu L, Wu E, Fong V, Hsu A, et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat Immunol. 2019;20:163–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol. 2014;32:381–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12:453–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA. Profiling Tumor Infiltrating Immune Cells with CIBERSORT. Methods Mol Biol. 2018;1711:243–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Sharonov GV, Serebrovskaya EO, Yuzhakova DV, Britanova OV, Chudakov DM. B cells, plasma cells and antibody repertoires in the tumour microenvironment. Nat Rev Immunol. 2020;20:294–307.

    Article  CAS  PubMed  Google Scholar 

  28. Ayers M, Lunceford J, Nebozhyn M, Murphy E, Loboda A, Kaufman DR, et al. IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. J Clin Invest. 2017;127:2930–40.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Senbabaoglu Y, Gejman RS, Winer AG, Liu M, Van Allen EM, de Velasco G, et al. Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures. Genome Biol. 2016;17:231.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Jiang Y, Li Y, Zhu B. T-cell exhaustion in the tumor microenvironment. Cell Death Dis. 2015;6:e1792.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Gu-Trantien C, Loi S, Garaud S, Equeter C, Libin M, de Wind A, et al. CD4(+) follicular helper T cell infiltration predicts breast cancer survival. J Clin Invest. 2013;123:2873–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zhang Y, Chen H, Mo H, Hu X, Gao R, Zhao Y, et al. Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer. Cancer Cell. 2021;39:1578–93.e1578.

    Article  CAS  PubMed  Google Scholar 

  33. Thommen DS, Koelzer VH, Herzig P, Roller A, Trefny M, Dimeloe S, et al. A transcriptionally and functionally distinct PD-1(+) CD8(+) T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat Med. 2018;24:994–1004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Liu B, Hu X, Feng K, Gao R, Xue Z, Zhang S, et al. Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer. Nat Cancer. 2022;3:108–21.

    Article  CAS  PubMed  Google Scholar 

  35. Groeneveld CS, Fontugne J, Cabel L, Bernard-Pierrot I, Radvanyi F, Allory Y, et al. Tertiary lymphoid structures marker CXCL13 is associated with better survival for patients with advanced-stage bladder cancer treated with immunotherapy. Eur J Cancer. 2021;148:181–9.

    Article  CAS  PubMed  Google Scholar 

  36. Zhang X, Peng L, Luo Y, Zhang S, Pu Y, Chen Y, et al. Dissecting esophageal squamous-cell carcinoma ecosystem by single-cell transcriptomic analysis. Nat Commun. 2021;12:5291.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Jansen CS, Prokhnevska N, Master VA, Sanda MG, Carlisle JW, Bilen MA, et al. An intra-tumoral niche maintains and differentiates stem-like CD8 T cells. Nature. 2019;576:465–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Eberhardt CS, Kissick HT, Patel MR, Cardenas MA, Prokhnevska N, Obeng RC, et al. Functional HPV-specific PD-1(+) stem-like CD8 T cells in head and neck cancer. Nature. 2021;597:279–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Horton BL, Morgan DM, Momin N, Zagorulya M, Torres-Mejia E, Bhandarkar V, et al. Lack of CD8(+) T cell effector differentiation during priming mediates checkpoint blockade resistance in non-small cell lung cancer. Sci Immunol. 2021;6:eabi8800.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Philip M, Schietinger A. CD8(+) T cell differentiation and dysfunction in cancer. Nat Rev Immunol. 2022;22:209–23.

    Article  CAS  PubMed  Google Scholar 

  41. Sade-Feldman M, Yizhak K, Bjorgaard SL, Ray JP, de Boer CG, Jenkins RW, et al. Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma. Cell. 2018;175:998–1013.e1020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Miller BC, Sen DR, Al Abosy R, Bi K, Virkud YV, LaFleur MW, et al. Subsets of exhausted CD8(+) T cells differentially mediate tumor control and respond to checkpoint blockade. Nat Immunol. 2019;20:326–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Brummelman J, Mazza EMC, Alvisi G, Colombo FS, Grilli A, Mikulak J, et al. High-dimensional single cell analysis identifies stem-like cytotoxic CD8(+) T cells infiltrating human tumors. J Exp Med. 2018;215:2520–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kurtulus S, Madi A, Escobar G, Klapholz M, Nyman J, Christian E, et al. Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1(-)CD8(+) Tumor-Infiltrating T Cells. Immunity. 2019;50:181–94.e186.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Prokhnevska N, Cardenas MA, Valanparambil RM, Sobierajska E, Barwick BG, Jansen C, et al. CD8(+) T cell activation in cancer comprises an initial activation phase in lymph nodes followed by effector differentiation within the tumor. Immunity. 2023;56:107–24.e105.

    Article  CAS  PubMed  Google Scholar 

  46. Kwon BS, Weissman SM. cDNA sequences of two inducible T-cell genes. Proc Natl Acad Sci USA. 1989;86:1963–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Melero I, Bach N, Hellstrom KE, Aruffo A, Mittler RS, Chen L. Amplification of tumor immunity by gene transfer of the co-stimulatory 4-1BB ligand: synergy with the CD28 co-stimulatory pathway. Eur J Immunol. 1998;28:1116–21.

    Article  CAS  PubMed  Google Scholar 

  48. Salgado FJ, Lojo J, Fernandez-Alonso CM, Vinuela J, Cordero OJ, Nogueira M. Interleukin-dependent modulation of HLA-DR expression on CD4and CD8 activated T cells. Immunol Cell Biol. 2002;80:138–47.

    Article  CAS  PubMed  Google Scholar 

  49. Alspach E, Lussier DM, Schreiber RD. Interferon gamma and Its Important Roles in Promoting and Inhibiting Spontaneous and Therapeutic Cancer Immunity. Cold Spring Harb Perspect Biol. 2019;11:a028480.

  50. Buchan SL, Dou L, Remer M, Booth SG, Dunn SN, Lai C, et al. Antibodies to Costimulatory Receptor 4-1BB Enhance Anti-tumor Immunity via T Regulatory Cell Depletion and Promotion of CD8 T Cell Effector Function. Immunity. 2018;49:958–70.e957.

    Article  CAS  PubMed  Google Scholar 

  51. Shaikh RB, Santee S, Granger SW, Butrovich K, Cheung T, Kronenberg M, et al. Constitutive expression of LIGHT on T cells leads to lymphocyte activation, inflammation, and tissue destruction. J Immunol. 2001;167:6330–7.

    Article  CAS  PubMed  Google Scholar 

  52. Chen L, Flies DB. Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat Rev Immunol. 2013;13:227–42.

    Article  PubMed  PubMed Central  Google Scholar 

  53. van Dijk N, Gil-Jimenez A, Silina K, Hendricksen K, Smit LA, de Feijter JM, et al. Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer: the NABUCCO trial. Nat Med. 2020;26:1839–44.

    Article  PubMed  Google Scholar 

  54. Gao J, Navai N, Alhalabi O, Siefker-Radtke A, Campbell MT, Tidwell RS, et al. Neoadjuvant PD-L1 plus CTLA-4 blockade in patients with cisplatin-ineligible operable high-risk urothelial carcinoma. Nat Med. 2020;26:1845–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Liu Z, Meng X, Tang X, Zou W, He Y. Intratumoral tertiary lymphoid structures promote patient survival and immunotherapy response in head neck squamous cell carcinoma. Cancer Immunol Immunother. 2023;72:1505–21.

    Article  CAS  PubMed  Google Scholar 

  56. Barros LRC, Souza-Santos PT, Pretti MAM, Vieira GF, Bragatte MAS, Mendes MFA, et al. High infiltration of B cells in tertiary lymphoid structures, TCR oligoclonality, and neoantigens are part of esophageal squamous cell carcinoma microenvironment. J Leukoc Biol. 2020;108:1307–18.

    Article  CAS  PubMed  Google Scholar 

  57. Meylan M, Petitprez F, Becht E, Bougouin A, Pupier G, Calvez A, et al. Tertiary lymphoid structures generate and propagate anti-tumor antibody-producing plasma cells in renal cell cancer. Immunity. 2022;55:527–41.e525.

    Article  CAS  PubMed  Google Scholar 

  58. Hudson WH, Gensheimer J, Hashimoto M, Wieland A, Valanparambil RM, Li P, et al. Proliferating Transitory T Cells with an Effector-like Transcriptional Signature Emerge from PD-1(+) Stem-like CD8(+) T Cells during Chronic Infection. Immunity. 2019;51:1043–58.e1044.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Beltra JC, Manne S, Abdel-Hakeem MS, Kurachi M, Giles JR, Chen Z, et al. Developmental Relationships of Four Exhausted CD8(+) T Cell Subsets Reveals Underlying Transcriptional and Epigenetic Landscape Control Mechanisms. Immunity. 2020;52:825–41.e828.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Mebius RE. Organogenesis of lymphoid tissues. Nat Rev Immunol. 2003;3:292–303.

    Article  CAS  PubMed  Google Scholar 

  61. Bergomas F, Grizzi F, Doni A, Pesce S, Laghi L, Allavena P, et al. Tertiary intratumor lymphoid tissue in colo-rectal cancer. Cancers. 2011;4:1–10.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Di Caro G, Bergomas F, Grizzi F, Doni A, Bianchi P, Malesci A, et al. Occurrence of tertiary lymphoid tissue is associated with T-cell infiltration and predicts better prognosis in early-stage colorectal cancers. Clin Cancer Res. 2014;20:2147–58.

    Article  PubMed  Google Scholar 

  63. Zhou F. Molecular mechanisms of IFN-gamma to up-regulate MHC class I antigen processing and presentation. Int Rev Immunol. 2009;28:239–60.

    Article  CAS  PubMed  Google Scholar 

  64. Zhang S, Kohli K, Black RG, Yao L, Spadinger SM, He Q, et al. Systemic Interferon-gamma Increases MHC Class I Expression and T-cell Infiltration in Cold Tumors: Results of a Phase 0 Clinical Trial. Cancer Immunol Res. 2019;7:1237–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Sznarkowska A, Mikac S, Pilch M. MHC Class I Regulation: The Origin Perspective. Cancers. 2020;12:1155.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Li S, Li K, Tian F, Li H, Xia Q, Li T, et al. A high interferon gamma signature of CD8(+) T cells predicts response to neoadjuvant immunotherapy plus chemotherapy in gastric cancer. Front Immunol. 2022;13:1056144.

    Article  CAS  PubMed  Google Scholar 

  67. Grasso CS, Tsoi J, Onyshchenko M, Abril-Rodriguez G, Ross-Macdonald P, Wind-Rotolo M, et al. Conserved Interferon-gamma Signaling Drives Clinical Response to Immune Checkpoint Blockade Therapy in Melanoma. Cancer Cell. 2020;38:500–15.e503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Karachaliou N, Crespo G, Aldeguer E, Drozdowskyj A, Gimenez Capitan A, Teixido C, et al. Interferon-gamma (INFG), an important marker of response to immune checkpoint blockade (ICB) in non-small cell lung cancer (NSCLC) and melanoma patients. J Clin Oncol. 2017;35:11504.

    Article  Google Scholar 

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Acknowledgements

We thank Shaoyang Sun at Fudan University for the assistance with the experiment.

Funding

This work was supported by funding from the National Key R&D Program of China (2021YFC2501004), the National Natural Science Foundation of China (82171837, 82188102, 82030089, 82225033), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), Non-profit central research institute fund of Chinese Academy of Medical Sciences (2022-RC310-08), the Science and Technology Commission of Shanghai Municipality (23JS1400400), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01 and 2018SHZDZX01) and ZJLab.

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  1. These authors contributed equally: Dandan Zhang, Dongxian Jiang, Liping Jiang, Jiakang Ma

Authors and Affiliations

  1. MOE Key Laboratory of Metabolism and Molecular Medicine, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences and Shanghai Xuhui Central Hospital, Fudan University, Shanghai, China

    Dandan Zhang, Jiakang Ma, Xingyu Xu, Ziqiang Chen, Mengping Jiang, Weida Meng & Yun Liu

  2. State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China

    Dandan Zhang, Jiakang Ma, Xingyu Xu, Ziqiang Chen, Mengping Jiang, Weida Meng & Yun Liu

  3. Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China

    Dongxian Jiang & Yingyong Hou

  4. State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China

    Liping Jiang, Xiaobing Wang, Yuchen Jiao & Zhihua Liu

  5. Division of Rheumatology and Immunology, Huashan Hospital, Fudan University, Shanghai, China

    Wenjing Ye

  6. Departments of Thoracic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China

    Jie Wang

  7. Shanghai Xuhui Central Hospital, Shanghai, China

    Wenqing Qiu

  8. Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Jing Huang

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Contributions

ZL, YL and YJ conceived and supervised the study. DZ performed experiments. DZ, JM and XX analyzed and interpreted the data, with assistance from ZC, MJ, WY, JW, WM and WQ. DJ, LJ and XW recruited patients under the supervision of YH and JH. DJ and LJ gathered clinical data. DZ, JM and YL wrote the manuscript with assistance from all authors. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Yuchen Jiao, Yun Liu or Zhihua Liu.

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The authors declare no competing interests.

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Written informed consent was obtained from each participant. The study was conducted following the principles outlined in the Declaration of Helsinki and was approved by the Ethics Committees of Cancer Hospital, Chinese Academy of Medical Science, Beijing, China (Approval No. 16-008/1087), and Zhongshan Hospital, Fudan University, Shanghai, China (Approval No. B2022-632).

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Zhang, D., Jiang, D., Jiang, L. et al. HLA-A+ tertiary lymphoid structures with reactivated tumor infiltrating lymphocytes are associated with a positive immunotherapy response in esophageal squamous cell carcinoma. Br J Cancer (2024). https://doi.org/10.1038/s41416-024-02712-9

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