Abstract
CD8 T cells are key mediators of anti-tumor immunity, yet their differentiation states and clonal architecture within the acute myeloid leukemia (AML) bone marrow microenvironment remain incompletely defined. We performed high dimensional immune profiling of bone marrow samples from 46 newly diagnosed AML patients using mass cytometry to probe the microenvironment and T cell states. We used single-cell RNA and T cell receptor (TCR) sequencing to define CD8 T cell phenotypes, transcriptional states, and clonal architecture. AML-associated CD8 T cells were skewed toward terminally differentiated effector memory cells re-expressing CD45RA (TEMRAs), while canonically exhausted T cell populations were rare. Functional studies revealed that TEMRA CD8 T cells robustly produced IFNγ and TNFα upon in vitro stimulation. Clonal expansion was concentrated within the TEMRA compartment. Comparison of TCR sequences with known viral epitopes identified a small subset of expanded viral-specific clonotypes, while the majority of highly expanded clonotypes had unknown specificity and may include AML-specific T cells. Differential gene expression analysis revealed shared cytotoxic effector programs during clonal expansion but diverging activation signatures: viral-specific clones upregulated canonical T cell receptor signaling genes, whereas expanded clones of unknown specificity exhibited enrichment of natural killer (NK) receptor-associated genes. These genes comprised the leukemia-associated NK-immune (LaNKi) score which was elevated in an independent AML dataset compared to pan cancer tumor infiltrating lymphocytes. These findings define the CD8 T cell differentiation landscape and clonal architecture in AML marrow at diagnosis and suggest that T cell dysfunction in AML diverges from classical activation and exhaustion paradigms.
Key points
CD8 T cells in AML are enriched for terminally differentiated states not defined by traditional checkpoint-inhibitor expression.
The LaNKi score marks clonally expanded CD8 T cells of unknown specificity and is validated across independent AML and pan-cancer datasets.
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