Single-Cell RNA-Seq of T Cells in B-ALL Patients Reveals an Exhausted Subset with Remarkable Heterogeneity

Abstract

Characterization of functional T cell clusters is key to developing strategies for immunotherapy and predicting clinical responses in leukemia. Here, single-cell RNA sequencing is performed 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 the authors to identify 13 T cell clusters in the patients based on their molecular properties. All 11 major T cell subsets in healthy individuals are 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 are specifically discovered in B-ALL patients. Of note, these exhausted T cells possess remarkable heterogeneity, and ten sub-clusters are further identified, which are characterized by different cell cycle phases, naïve states, and GNLY (coding granulysin) expression. Coupled with single-cell T cell receptor repertoire profiling, diverse originations of the exhausted T cells in B-ALL are suggested, and clonally expanded exhausted T cells are 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.

Keywords: B cell-acute lymphoblastic leukemia; T cells; heterogeneity; single-cell RNA sequencing.