Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma
Abstract Angioimmunoblastic T-cell lymphoma (AITL) is a kind of aggressive T-cell lymphoma with significant enrichment of non-malignant tumor microenvironment (TME) cells. However, the complexity of TME in AITL progression is poorly understood. We performed single-cell RNA-Seq (scRNA-seq) and imagin...
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| Format: | Article |
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Nature Publishing Group
2024-12-01
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| Series: | Blood Cancer Journal |
| Online Access: | https://doi.org/10.1038/s41408-024-01199-0 |
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| author | Mengyan Zhu Ning Li Lei Fan Rongrong Wu Lei Cao Yimin Ren Chuanyang Lu Lishen Zhang Yun Cai Yuzhu Shi Zihan Lin Xueying Lu Jiayan Leng Shiyang Zhong Xingfei Hu Bin Huang Runheng Huang Wanting Zhou Diru Yao Lingxiang Wu Wei Wu Quanzhong Liu Peng Xia Ruize Chen Wenyu Shi Ruohan Zhang Sali Lv Chunling Wang Liang Yu Jianyong Li Qianghu Wang Kening Li Hui Jin |
| author_facet | Mengyan Zhu Ning Li Lei Fan Rongrong Wu Lei Cao Yimin Ren Chuanyang Lu Lishen Zhang Yun Cai Yuzhu Shi Zihan Lin Xueying Lu Jiayan Leng Shiyang Zhong Xingfei Hu Bin Huang Runheng Huang Wanting Zhou Diru Yao Lingxiang Wu Wei Wu Quanzhong Liu Peng Xia Ruize Chen Wenyu Shi Ruohan Zhang Sali Lv Chunling Wang Liang Yu Jianyong Li Qianghu Wang Kening Li Hui Jin |
| author_sort | Mengyan Zhu |
| collection | DOAJ |
| description | Abstract Angioimmunoblastic T-cell lymphoma (AITL) is a kind of aggressive T-cell lymphoma with significant enrichment of non-malignant tumor microenvironment (TME) cells. However, the complexity of TME in AITL progression is poorly understood. We performed single-cell RNA-Seq (scRNA-seq) and imaging mass cytometry (IMC) analysis to compare the cellular composition and spatial architecture between relapsed/refractory AITL (RR-AITL) and newly diagnosed AITL (ND-AITL). Our results showed that the malignant T follicular helper (Tfh) cells showed significantly increased proliferation driven by transcriptional activation of YY1 in RR-AITL, which is markedly associated with the poor prognosis of AITL patients. The CD8+ T cell proportion and cytotoxicity decreased in RR-AITL TME, resulting from elevated expression of the inhibitory checkpoints such as PD-1, TIGIT, and CTLA4. Notably, the transcriptional pattern of B cells in RR-AITL showed an intermediate state of malignant transformation to B-cell-lymphoma, and contributed to immune evasion by highly expressing CD47 and PD-L1. Besides, compared to ND-AITL samples, myeloid-cells-centered spatial communities were more prevalent but showed reduced phagocytic activity and impaired antigen processing and presentation in RR-AITL TME. Furthermore, specific inhibitory ligand-receptor interactions, such as CLEC2D-KLRB1, CTLA4-CD86, and MIF-CD74, were exclusively identified in the RR-AITL TME. Our study provides a high-resolution characterization of the immunosuppression ecosystem and reveals the potential therapeutic targets for RR-AITL patients. |
| format | Article |
| id | doaj-art-35eed1df424d4d7f92603f4db0eca8b4 |
| institution | Kabale University |
| issn | 2044-5385 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Blood Cancer Journal |
| spelling | doaj-art-35eed1df424d4d7f92603f4db0eca8b42024-12-22T12:16:08ZengNature Publishing GroupBlood Cancer Journal2044-53852024-12-0114111810.1038/s41408-024-01199-0Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphomaMengyan Zhu0Ning Li1Lei Fan2Rongrong Wu3Lei Cao4Yimin Ren5Chuanyang Lu6Lishen Zhang7Yun Cai8Yuzhu Shi9Zihan Lin10Xueying Lu11Jiayan Leng12Shiyang Zhong13Xingfei Hu14Bin Huang15Runheng Huang16Wanting Zhou17Diru Yao18Lingxiang Wu19Wei Wu20Quanzhong Liu21Peng Xia22Ruize Chen23Wenyu Shi24Ruohan Zhang25Sali Lv26Chunling Wang27Liang Yu28Jianyong Li29Qianghu Wang30Kening Li31Hui Jin32Department of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Hematology of the Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University, Northern Jiangsu Institute of Clinical MedicineDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Oncology, Affiliated Hospital of Nantong UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Hematology of the Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University, Northern Jiangsu Institute of Clinical MedicineDepartment of Hematology of the Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University, Northern Jiangsu Institute of Clinical MedicineLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityDepartment of Bioinformatics, Nanjing Medical UniversityLymphoma Center, Department of Hematology, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical UniversityAbstract Angioimmunoblastic T-cell lymphoma (AITL) is a kind of aggressive T-cell lymphoma with significant enrichment of non-malignant tumor microenvironment (TME) cells. However, the complexity of TME in AITL progression is poorly understood. We performed single-cell RNA-Seq (scRNA-seq) and imaging mass cytometry (IMC) analysis to compare the cellular composition and spatial architecture between relapsed/refractory AITL (RR-AITL) and newly diagnosed AITL (ND-AITL). Our results showed that the malignant T follicular helper (Tfh) cells showed significantly increased proliferation driven by transcriptional activation of YY1 in RR-AITL, which is markedly associated with the poor prognosis of AITL patients. The CD8+ T cell proportion and cytotoxicity decreased in RR-AITL TME, resulting from elevated expression of the inhibitory checkpoints such as PD-1, TIGIT, and CTLA4. Notably, the transcriptional pattern of B cells in RR-AITL showed an intermediate state of malignant transformation to B-cell-lymphoma, and contributed to immune evasion by highly expressing CD47 and PD-L1. Besides, compared to ND-AITL samples, myeloid-cells-centered spatial communities were more prevalent but showed reduced phagocytic activity and impaired antigen processing and presentation in RR-AITL TME. Furthermore, specific inhibitory ligand-receptor interactions, such as CLEC2D-KLRB1, CTLA4-CD86, and MIF-CD74, were exclusively identified in the RR-AITL TME. Our study provides a high-resolution characterization of the immunosuppression ecosystem and reveals the potential therapeutic targets for RR-AITL patients.https://doi.org/10.1038/s41408-024-01199-0 |
| spellingShingle | Mengyan Zhu Ning Li Lei Fan Rongrong Wu Lei Cao Yimin Ren Chuanyang Lu Lishen Zhang Yun Cai Yuzhu Shi Zihan Lin Xueying Lu Jiayan Leng Shiyang Zhong Xingfei Hu Bin Huang Runheng Huang Wanting Zhou Diru Yao Lingxiang Wu Wei Wu Quanzhong Liu Peng Xia Ruize Chen Wenyu Shi Ruohan Zhang Sali Lv Chunling Wang Liang Yu Jianyong Li Qianghu Wang Kening Li Hui Jin Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma Blood Cancer Journal |
| title | Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma |
| title_full | Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma |
| title_fullStr | Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma |
| title_full_unstemmed | Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma |
| title_short | Single-cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed/refractory angioimmunoblastic T-cell lymphoma |
| title_sort | single cell transcriptomic and spatial analysis reveal the immunosuppressive microenvironment in relapsed refractory angioimmunoblastic t cell lymphoma |
| url | https://doi.org/10.1038/s41408-024-01199-0 |
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