Author Correction: Targeting MondoA-TXNIP restores antitumour immunity in lactic-acid-induced immunosuppressive microenvironment.
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Biomedical subjects
Publications and source records attributed to Wenyi Zhao.
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In the tumour microenvironment, accumulated lactic acid (LA) promotes tumour immune evasion by facilitating regulatory T cell (Treg) immunosuppressive function and restraining CD8+ T cell cytotoxicity, but the underlying mechanism remains elusive. Here we report that transcriptional factor MondoA-induced thioredoxin interacting protein (TXNIP) transcription is a common feature of both Treg and CD8+ T cells in response to lactic acid. In contrast to reduction in immunosuppressive capacity in MondoA-deficient Treg cells, loss of MondoA enhanced CD8+ T cell cytotoxic function in the lactic-acid-induced immunosuppressive microenvironment, by restoring glucose uptake and glycolysis. Mechanistically, lactic acid relied on sentrin/SUMO-specific protease 1 (SENP1) to stimulate the MondoA-TXNIP axis, which impaired TCR/CD28-signal-induced CD8+ T cell activation. Importantly, targeting the MondoA-TXNIP axis potentiated antitumour immunity in multiple cancer types and synergized with anti-PD-1 therapy to promote effective T cell responses in colorectal cancer. Our results demonstrate that the MondoA-TXNIP axis is a promising therapeutic target for improving cancer immunotherapy.
Comprehensive and integrated resources on interactions between T-cell receptors (TCRs) and antigens are still lacking for adoptive T-cell-based immunotherapies, highlighting a significant gap that must be addressed to fully understand the mechanisms of antigen recognition by T cells. In this study, we present the T-cell receptor-antigen interaction database (TRAIT), a comprehensive database that profiles the interactions between TCRs and antigens. TRAIT stands out due to its comprehensive description of TCR-antigen interactions by integrating sequences, structures, and affinities. It provides millions of experimentally validated TCR-antigen pairs, resulting in an exhaustive landscape of antigen-specific TCRs. Notably, TRAIT emphasizes single-cell omics as a major reliable data source for TCR-antigen interactions and includes millions of reliable non-interactive TCRs. Additionally, it thoroughly demonstrates the interactions between mutations of TCRs and antigens, thereby benefiting affinity optimization of engineered TCRs as well as vaccine design. TCRs on clinical trials are innovatively provided. With the significant efforts made toward elucidating the complex interactions between TCRs and antigens, TRAIT is expected to ultimately contribute superior algorithms and substantial advancements in the field of T-cell-based immunotherapies. TRAIT is freely accessible at https://pgx.zju.edu.cn/traitdb.