Tumor-migrating peripheral Foxp3-high regulatory T cells drive poor prognosis in hepatocellular carcinoma
CD4+ regulatory T cells (Tregs) are pivotal in HCC progression. However, systemic depletion of all Tregs risks autoimmunity. Existing subgroup classifications highlight Tregs' phenotypic and functional heterogeneity but lack coherent consensus. This study aimed to classify Treg subtypes using s...
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| Vydáno v: | Hepatology (Baltimore, Md.) |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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01.07.2025
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| ISSN: | 1527-3350, 1527-3350 |
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| Abstract | CD4+ regulatory T cells (Tregs) are pivotal in HCC progression. However, systemic depletion of all Tregs risks autoimmunity. Existing subgroup classifications highlight Tregs' phenotypic and functional heterogeneity but lack coherent consensus. This study aimed to classify Treg subtypes using single-cell CITE-seq, integrating data from tumor, non-tumor, and blood samples in HCC patients. We also validated the clinical relevance and prognostic value of this classification.BACKGROUND AND AIMSCD4+ regulatory T cells (Tregs) are pivotal in HCC progression. However, systemic depletion of all Tregs risks autoimmunity. Existing subgroup classifications highlight Tregs' phenotypic and functional heterogeneity but lack coherent consensus. This study aimed to classify Treg subtypes using single-cell CITE-seq, integrating data from tumor, non-tumor, and blood samples in HCC patients. We also validated the clinical relevance and prognostic value of this classification.CITE-seq analysis was performed on 51,067 CD4+ T cells from eight HCC patients. Validation involved 96 HCC patients and 53 healthy donors using flow cytometry, functional assays, and clinical data.METHODSCITE-seq analysis was performed on 51,067 CD4+ T cells from eight HCC patients. Validation involved 96 HCC patients and 53 healthy donors using flow cytometry, functional assays, and clinical data.Trajectory and TCR analyses identified a peripheral Foxp3high Treg subset that preferentially migrate to tumor sites, acquiring a terminally differentiated, activated phenotype. These tumor-infiltrating Foxp3high Tregs exhibit elevated LAYN and TRM signatures and further increase their Foxp3 expression and immunosuppressive functions by pro-inflammatory cytokines in tumor tissue. The CCL5/CCR5 axis is crucial for recruiting Foxp3high Tregs from peripheral blood into the tumor microenvironment. A strong correlation was observed between the percentage of Foxp3high Tregs in peripheral blood and their counterparts in tumor regions, suggesting their potential as peripheral biomarker. Notably, a peripheral Foxp3high Tregs/CD4+ T cells percentage>3.5% predicted overall survival and early recurrence, with AUROCs exceeding 0.75.RESULTSTrajectory and TCR analyses identified a peripheral Foxp3high Treg subset that preferentially migrate to tumor sites, acquiring a terminally differentiated, activated phenotype. These tumor-infiltrating Foxp3high Tregs exhibit elevated LAYN and TRM signatures and further increase their Foxp3 expression and immunosuppressive functions by pro-inflammatory cytokines in tumor tissue. The CCL5/CCR5 axis is crucial for recruiting Foxp3high Tregs from peripheral blood into the tumor microenvironment. A strong correlation was observed between the percentage of Foxp3high Tregs in peripheral blood and their counterparts in tumor regions, suggesting their potential as peripheral biomarker. Notably, a peripheral Foxp3high Tregs/CD4+ T cells percentage>3.5% predicted overall survival and early recurrence, with AUROCs exceeding 0.75.Peripheral Foxp3high Tregs migrate to tumor sites via the CCR5-CCL5 axis and mature in response to pro-inflammatory cytokines. The proportion of these Tregs in peripheral blood correlates with their presence in tumors, making them a potential biomarker for predicting HCC outcomes.CONCLUSIONPeripheral Foxp3high Tregs migrate to tumor sites via the CCR5-CCL5 axis and mature in response to pro-inflammatory cytokines. The proportion of these Tregs in peripheral blood correlates with their presence in tumors, making them a potential biomarker for predicting HCC outcomes. |
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| AbstractList | CD4+ regulatory T cells (Tregs) are pivotal in HCC progression. However, systemic depletion of all Tregs risks autoimmunity. Existing subgroup classifications highlight Tregs' phenotypic and functional heterogeneity but lack coherent consensus. This study aimed to classify Treg subtypes using single-cell CITE-seq, integrating data from tumor, non-tumor, and blood samples in HCC patients. We also validated the clinical relevance and prognostic value of this classification.BACKGROUND AND AIMSCD4+ regulatory T cells (Tregs) are pivotal in HCC progression. However, systemic depletion of all Tregs risks autoimmunity. Existing subgroup classifications highlight Tregs' phenotypic and functional heterogeneity but lack coherent consensus. This study aimed to classify Treg subtypes using single-cell CITE-seq, integrating data from tumor, non-tumor, and blood samples in HCC patients. We also validated the clinical relevance and prognostic value of this classification.CITE-seq analysis was performed on 51,067 CD4+ T cells from eight HCC patients. Validation involved 96 HCC patients and 53 healthy donors using flow cytometry, functional assays, and clinical data.METHODSCITE-seq analysis was performed on 51,067 CD4+ T cells from eight HCC patients. Validation involved 96 HCC patients and 53 healthy donors using flow cytometry, functional assays, and clinical data.Trajectory and TCR analyses identified a peripheral Foxp3high Treg subset that preferentially migrate to tumor sites, acquiring a terminally differentiated, activated phenotype. These tumor-infiltrating Foxp3high Tregs exhibit elevated LAYN and TRM signatures and further increase their Foxp3 expression and immunosuppressive functions by pro-inflammatory cytokines in tumor tissue. The CCL5/CCR5 axis is crucial for recruiting Foxp3high Tregs from peripheral blood into the tumor microenvironment. A strong correlation was observed between the percentage of Foxp3high Tregs in peripheral blood and their counterparts in tumor regions, suggesting their potential as peripheral biomarker. Notably, a peripheral Foxp3high Tregs/CD4+ T cells percentage>3.5% predicted overall survival and early recurrence, with AUROCs exceeding 0.75.RESULTSTrajectory and TCR analyses identified a peripheral Foxp3high Treg subset that preferentially migrate to tumor sites, acquiring a terminally differentiated, activated phenotype. These tumor-infiltrating Foxp3high Tregs exhibit elevated LAYN and TRM signatures and further increase their Foxp3 expression and immunosuppressive functions by pro-inflammatory cytokines in tumor tissue. The CCL5/CCR5 axis is crucial for recruiting Foxp3high Tregs from peripheral blood into the tumor microenvironment. A strong correlation was observed between the percentage of Foxp3high Tregs in peripheral blood and their counterparts in tumor regions, suggesting their potential as peripheral biomarker. Notably, a peripheral Foxp3high Tregs/CD4+ T cells percentage>3.5% predicted overall survival and early recurrence, with AUROCs exceeding 0.75.Peripheral Foxp3high Tregs migrate to tumor sites via the CCR5-CCL5 axis and mature in response to pro-inflammatory cytokines. The proportion of these Tregs in peripheral blood correlates with their presence in tumors, making them a potential biomarker for predicting HCC outcomes.CONCLUSIONPeripheral Foxp3high Tregs migrate to tumor sites via the CCR5-CCL5 axis and mature in response to pro-inflammatory cytokines. The proportion of these Tregs in peripheral blood correlates with their presence in tumors, making them a potential biomarker for predicting HCC outcomes. |
| Author | Lin, Yung-Chang Fan, Jian-He Jeng, Wen-Juei Teng, Wei Lin, Chun-Yen Mahalingam, Jayashri Wu, Cheng-Heng Ku, Wei-Ting Lin, Po-Ting Lin, Chen-Chun Lin, Shi-Ming Wu, Tsung-Han Su, Chung-Wei Peng, Chien-Wei Chen, Wei-Ting Huang, Chien-Hao Yang, Chan-Keng Sheen, I-Shyan |
| Author_xml | – sequence: 1 givenname: Chien-Hao surname: Huang fullname: Huang, Chien-Hao – sequence: 2 givenname: Wei-Ting surname: Ku fullname: Ku, Wei-Ting – sequence: 3 givenname: Jayashri surname: Mahalingam fullname: Mahalingam, Jayashri – sequence: 4 givenname: Cheng-Heng surname: Wu fullname: Wu, Cheng-Heng – sequence: 5 givenname: Tsung-Han surname: Wu fullname: Wu, Tsung-Han – sequence: 6 givenname: Jian-He surname: Fan fullname: Fan, Jian-He – sequence: 7 givenname: Chung-Wei surname: Su fullname: Su, Chung-Wei – sequence: 8 givenname: Po-Ting surname: Lin fullname: Lin, Po-Ting – sequence: 9 givenname: Chien-Wei surname: Peng fullname: Peng, Chien-Wei – sequence: 10 givenname: Chan-Keng surname: Yang fullname: Yang, Chan-Keng – sequence: 11 givenname: Wei surname: Teng fullname: Teng, Wei – sequence: 12 givenname: Wen-Juei surname: Jeng fullname: Jeng, Wen-Juei – sequence: 13 givenname: Wei-Ting surname: Chen fullname: Chen, Wei-Ting – sequence: 14 givenname: Chen-Chun surname: Lin fullname: Lin, Chen-Chun – sequence: 15 givenname: Shi-Ming surname: Lin fullname: Lin, Shi-Ming – sequence: 16 givenname: I-Shyan surname: Sheen fullname: Sheen, I-Shyan – sequence: 17 givenname: Yung-Chang surname: Lin fullname: Lin, Yung-Chang – sequence: 18 givenname: Chun-Yen surname: Lin fullname: Lin, Chun-Yen |
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| Copyright | Copyright © 2025 American Association for the Study of Liver Diseases. |
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