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HTLV-1 infection promotes excessive T cell activation and transformation into adult T cell leukemia/lymphoma
Benjy J.Y. Tan, … , Masahiro Ono, Yorifumi Satou
Benjy J.Y. Tan, … , Masahiro Ono, Yorifumi Satou
Published December 15, 2021
Citation Information: J Clin Invest. 2021;131(24):e150472. https://doi.org/10.1172/JCI150472.
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Research Article Infectious disease Virology

HTLV-1 infection promotes excessive T cell activation and transformation into adult T cell leukemia/lymphoma

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Abstract

Human T cell leukemia virus type 1 (HTLV-1) mainly infects CD4+ T cells and induces chronic, persistent infection in infected individuals, with some developing adult T cell leukemia/lymphoma (ATL). HTLV-1 alters cellular differentiation, activation, and survival; however, it is unknown whether and how these changes contribute to the malignant transformation of infected cells. In this study, we used single-cell RNA-sequencing and T cell receptor–sequencing to investigate the differentiation and HTLV-1–mediated transformation of T cells. We analyzed 87,742 PBMCs from 12 infected and 3 uninfected individuals. Using multiple independent bioinformatics methods, we demonstrated the seamless transition of naive T cells into activated T cells, whereby HTLV-1–infected cells in an activated state further transformed into ATL cells, which are characterized as clonally expanded, highly activated T cells. Notably, the greater the activation state of ATL cells, the more they acquire Treg signatures. Intriguingly, the expression of HLA class II genes in HTLV-1–infected cells was uniquely induced by the viral protein Tax and further upregulated in ATL cells. Functional assays revealed that HTLV-1–infected cells upregulated HLA class II molecules and acted as tolerogenic antigen-presenting cells to induce anergy of antigen-specific T cells. In conclusion, our study revealed the in vivo mechanisms of HTLV-1–mediated transformation and immune escape at the single-cell level.

Authors

Benjy J.Y. Tan, Kenji Sugata, Omnia Reda, Misaki Matsuo, Kyosuke Uchiyama, Paola Miyazato, Vincent Hahaut, Makoto Yamagishi, Kaoru Uchimaru, Yutaka Suzuki, Takamasa Ueno, Hitoshi Suzushima, Hiroo Katsuya, Masahito Tokunaga, Yoshikazu Uchiyama, Hideaki Nakamura, Eisaburo Sueoka, Atae Utsunomiya, Masahiro Ono, Yorifumi Satou

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Figure 3

CCA analysis shows that ATL cells acquire the Treg phenotype and are highly activated.

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CCA analysis shows that ATL cells acquire the Treg phenotype and are hig...
(A) Violin plots show the 1D CCA scores for T cell activation and the Treg phenotype, grouped by clinical diagnosis. Box plots in each violin summarize the median (midline) and IQRs. (B) Scatter plot shows the correlation between the 1D CCA score for T cell activation and the Treg phenotype. Blue line shows the regression model of the CCA scores for all cells. (C) Plot shows the pseudotime trajectory for the entire CD4+ T cell population colored by pseudotime. (D) Plot shows the distribution of uninfected helper cells, infected non-ATL cells, and infected ATL cells along the pseudotime axis. (E) Plot shows the distribution of 1D CCA scores for T cell activation and the Treg phenotype in the pseudotime space (for cells from C). (F) Expression of T cell–related marker genes along the pseudotime axis from C. (G) Split heatmap shows the expression profile of genes that vary as a function of pseudotime and are branch dependent. The pseudotime trajectory begins from the middle of the heatmap (gray box) and moves to the left for the bottom branch and to the right for the top branch. The start of the arrow indicates the bifurcation point for the trajectory shown in C. Hierarchical clustering grouped the genes into 4 clusters, indicated by outlined colored boxes on the right, along with the top 3 enriched pathways. ****P < 0.0001, by 1-way ANOVA with post hoc Tukey’s test (A).

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ISSN: 0021-9738 (print), 1558-8238 (online)

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