Single-cell RNA-seq of T cells in B-ALL patients reveals an exhausted subset with remarkably heterogeneity

Characterization of functional T cell clusters is key to developing strategies for immunotherapy and predicting clinical responses in leukemia. Here, we performed single-cell RNA sequencing (scRNA-seq) with T cells sorted from the peripheral blood of healthy individuals and patients with B cell-acute lymphoblastic leukemia (B-ALL). Unbiased bioinformatics analysis enabled us to identify 13 T cell clusters in the patients based on their molecular properties. All 11 major T cells subsets in healthy individuals were found in the patients with B-ALL, with the counterparts in the patients universally showing more activated characteristics. Two exhausted T cell populations, characterized by up-regulation of TIGIT, PDCD1, HLADRA, LAG3, and CTLA4 were specifically discovered in B-ALL patients. Of note, these exhausted T cells possessed remarkable heterogeneity, and ten sub-clusters were further identified, which were characterized by different cell cycle phase, naïve states, and GNLY (coding granulysin) expression. Coupled with single-cell T cell receptor repertoire profiling, we suggested diverse originations of the exhausted T cells in B-ALL, and clonally expanded exhausted T cells were likely to originate from CD8+ effector memory/terminal effector cells. Together, these data provide for the first-time valuable insights for understanding exhausted T cell populations in leukemia. Overall design: Single cell RNA-seq with 28,812 T cells sorted from the peripheral blood of healthy individuals and patients with B cell-acute lymphoblastic leukemia, as well as T-cell receptor repertoire sequencing from one of the healthy individuals and the same patients.