TDO2+ myofibroblasts mediate immune suppression in malignant transformation of squamous cell carcinoma
Simeng Hu, … , Fan Bai, Zhi Wang
Simeng Hu, … , Fan Bai, Zhi Wang
Published August 16, 2022
Citation Information: J Clin Invest. 2022;132(19):e157649. https://doi.org/10.1172/JCI157649.
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Research Article Immunology Oncology Article has an altmetric score of 10

TDO2+ myofibroblasts mediate immune suppression in malignant transformation of squamous cell carcinoma

Abstract

Characterization of the dynamic change in the immunological landscape during malignant transformation from precancerous lesions to cancerous lesions in squamous cell carcinoma (SCC) is critical for the application of immunotherapy. Here, we performed single-cell RNA-Seq (scRNA-Seq) of 131,702 cells from 13 cancerous tissues of oral squamous cell carcinoma (OSCC), 3 samples of precancerous oral leukoplakia, and 8 adjacent normal samples. We found that tumor-infiltrating CD4+ and CD8+ T cells were functionally inhibited by immunosuppressive ligands expressed on various types of myeloid cells or neutrophils in the process of oral carcinogenesis. Notably, we identified a subset of myofibroblasts that exclusively expressed tryptophan 2,3-dioxygenase (TDO2). These TDO2+ myofibroblasts were located distally from tumor nests, and both CD4+ and CD8+ T cells were enriched around them. Functional experiments revealed that TDO2+ myofibroblasts were more likely to possess the ability for chemotaxis toward T cells but induced the transformation of CD4+ T cells into Tregs and caused CD8+ T cell dysfunction. We further showed that use of the TDO2 inhibitor LM10 attenuated the inhibitory states of T cells, restored the T cell antitumor response, and prevented the progression of OSCC malignant transformation in murine models. Our study reveals a multistep transcriptomic landscape of OSCC and demonstrates that TDO2+ myofibroblasts are potential targets for immunotherapy.

Authors

Simeng Hu, Huanzi Lu, Wenqiang Xie, Dikan Wang, Zhongyan Shan, Xudong Xing, Xiang-Ming Wang, Juan Fang, Wei Dong, Wenxiao Dai, Junyi Guo, Yanshu Zhang, Shuqiong Wen, Xin-Yu Guo, Qianming Chen, Fan Bai, Zhi Wang

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Figure 2

T cell dysfunction and cell state transitions in OSCC.

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T cell dysfunction and cell state transitions in OSCC. (A) UMAP plot sho...
(A) UMAP plot showing the distribution of CD4+ T cell subsets. Each color represents a CD4+ T cell subset. (B) Bar plots showing the percentage of CD4+ T cell subsets among total CD4+ T cells in adjacent normal, OLK, and OSCC tissues. Each color represents a tissue type. (C) Bar plots showing the percentages of TCR-expanded clonotypes in the CD4+ T cell subsets. The colors indicate different expanded clonotypes. (D) The RNA velocity of CD4+ T cells was visualized on the UMAP plot based on the stochastic model in the scVelo algorithm, suggesting a putative differentiation direction for CD4+ T cells. The arrows indicate the putative differentiation direction. (E) UMAP plot showing the distribution of CD8+ T cell subsets. Each color represents a CD8+ T cell subset. (F) Bar plots showing the percentages of 3 subsets of CD8+ T cells among total CD8+ T cells in adjacent normal, OLK, and OSCC tissues. (G) Violin plots showing the expression levels of effector molecules and immune-inhibitory receptors in 3 subsets of CD8+ T cells. (H) The RNA velocity of CD8+ T cell subsets was visualized on the UMAP plot based on the stochastic model in the scVelo algorithm, suggesting a putative differentiation direction for CD8+ T cell subsets. Arrows represent the putative differentiation direction. *P < 0.05, **P < 0.01, and ****P < 0.0001, by Kruskal-Wallis test followed by Bonferroni’s multiple-comparison test (B and F).