bioRxivCancer BiologyPreprint
High-dimensional single-cell definition of CLL T cells identifies Galectin-9 as novel immunotherapy target
L. L. Cid, J. K. Leong, I. F. Botana, Y. Paul, M. Wierz, A. Floerchinger, S. Gonder, G. Pagano, M. Chazotte, K. Bestak, C. Schifflers, M. Iskar, T. Roider, F. Czernilofsky, P.-M. Bruch, J.-P. Mallm, A. Cosma, D. E. Campton, E. Gerhard-Hartmann, A. Rosenwald, D. Colomer, E. Campo, D. Shapiro, S. Dietrich, P. Lichter, , M. Seiffert
Abstract
Failure of cancer immunotherapy is linked to T cell exhaustion. To decipher the underlying mechanisms, we explored the T cell landscape in blood, bone marrow and lymph node samples of patients with chronic lymphocytic leukemia (CLL), and spleen samples of a CLL mouse model. By single-cell RNA-sequencing, mass cytometry (CyTOF), and multiplex image analysis of tissue microarrays, we identified a disease-specific accumulation of distinct regulatory T cell subsets and T cell exhaustion stages and their trajectories in CLL lymph nodes. Integration of T cell receptor sequencing data revealed a clonal expansion of CD8+ precursor exhausted T cells (TPEX), suggesting their CLL reactivity. Interactome analyses identified the TIM3 ligand Galectin-9 as a novel immunoregulatory molecule in CLL. Blocking of Galectin-9 in CLL-bearing mice slowed down disease development and reduced the number of TIM3-expressing T cells. Galectin-9 expression correlated with shorter survival of patients with CLL, renal cell carcinoma or glioma. Statement of significanceOur findings for the first time define the T cell landscape in CLL lymph nodes and reshape the current understanding of T cell exhaustion in this malignancy. They further introduce Galectin-9 as novel immune checkpoint with a high potential to overcome resistance to PD1 targeting drugs in CLL and beyond.
- organism: human
- assay: scRNA-seq
- assay: CITE-seq
- assay: spatial transcriptomics
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Leukemic cell-secreted interleukin-9 suppresses cytotoxic T cell-mediated killing in chronic lymphocytic leukemia
G. Boncompagni, V. Tatangelo, … C. T. Baldari·bioRxiv·Oct 23, 2023
- Interleukin-10 suppression enhances T-cell antitumor immunity and responses to checkpoint blockade in chronic lymphocytic leukemia
J. R. Rivas, Y. Liu, … S. Bondada·bioRxiv·Jul 15, 2020
- CAR-T cells targeting CCR9 and CD1a for the treatment of T cell acute lymphoblastic leukemia
Néstor Tirado, Klaudyna Fidyt, … Pablo R. Menéndez·Journal of Hematology & OncologyPeer-reviewed·Jul 1, 2025
- Single-cell transcriptome analysis reveals TOX as a promoting factor for T-cell exhaustion and a predictor for anti-PD1 responses in human cancer
- Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy
Pavan Bachireddy, Elham Azizi, … Catherine J Wu·Cell ReportsPeer-reviewed·Nov 1, 2021
- High CD44 expression identifies rare chemoresistant leukemic cells endowed with enhanced E-Selectin binding in T-ALL
J. Calvo, I. Naguibneva, … F. Pflumio·bioRxiv·Dec 20, 2023