Targeting of the CD161 Inhibitory Receptor Enhances T cell-mediated Immunity Against Hematological Malignancies.
Francesca Alvarez CalderonByong Ha KangOleksandr KyrysyukShiwei ZhengHao WangNathan D MathewsonAdrienne M LuomaXiaohan NingJason PyrdolXuan CaoMario L SuvàGuo-Cheng YuanKarl Dane WittrupKai W WucherpfennigPublished in: Blood (2023)
The CD161 inhibitory receptor is highly upregulated by tumor-infiltrating T-cells in multiple human solid tumor types, and its ligand CLEC2D is expressed by both tumor cells and infiltrating myeloid cells. Here we assessed the role of the CD161 receptor in hematological malignancies. Systematic analysis of CLEC2D expression using the Cancer Cell Line Encyclopedia (CCLE) revealed that CLEC2D mRNA was most abundant in hematological malignancies, including B-cell and T-cell lymphomas as well as lymphocytic and myelogenous leukemias. CLEC2D protein was detected by flow cytometry on a panel of cell lines representing a diverse set of hematological malignancies. We therefore used yeast display to generate a panel of high-affinity, fully human CD161 monoclonal antibodies (mAbs) that blocked CLEC2D binding. These mAbs were specific for CD161 and had a similar affinity for human and non-human primate CD161, a property relevant for clinical translation. A high-affinity CD161 mAb enhanced key aspects of T-cell function, including cytotoxicity, cytokine production and proliferation, against B-cell lines originating from patients with ALL, DLBCL and Burkitt lymphoma. In humanized mouse models, this CD161 mAb enhanced T-cell-mediated immunity, resulting in a significant survival benefit. ScRNA-seq data demonstrated that CD161 mAb treatment enhanced expression of cytotoxicity genes by CD4 T-cells as well as a tissue-residency program by CD4 and CD8 T-cells that is associated with favorable survival outcomes in multiple human cancer types. These fully human monoclonal antibodies thus represent potential immunotherapy agents for hematological malignancies.
Keyphrases
- endothelial cells
- nk cells
- pluripotent stem cells
- oxidative stress
- induced apoptosis
- signaling pathway
- squamous cell carcinoma
- immune response
- cell death
- machine learning
- electronic health record
- single cell
- big data
- papillary thyroid
- mouse model
- deep learning
- artificial intelligence
- cell proliferation
- quality improvement
- climate change
- cancer therapy
- endoplasmic reticulum stress
- saccharomyces cerevisiae
- rna seq
- replacement therapy