Editors' ChoiceCancer

Uncovering metabolic states in cytotoxic T cells, one cell at a time

See allHide authors and affiliations

Science Translational Medicine  30 Sep 2020:
Vol. 12, Issue 563, eabe6027
DOI: 10.1126/scitranslmed.abe6027


Single-cell metabolic state analysis reveals cytotoxic T cell activity patterns that are spatially organized in human colorectal tumors.

Metabolic state regulation in immune cells is critical for activation, differentiation, and effector functions. Recent studies have uncovered the phenotypic and metabolic heterogeneity of immune cell subpopulations in solid tumors, but approaches that comprehensively profile multiple metabolic pathways are needed to enhance our understanding of immunometabolism in tumors and healthy tissue and to uncover new therapeutic targets and predictors of clinical outcomes.

Hartman et al. developed an antibody-based technology that identifies metabolic state, cell type, and immune cell subtypes using mass cytometry and multiplexed ion beam imaging. Analysis of whole blood from human donors revealed distinct cell lineage–specific metabolic states. Given the critical role of CD8+ T cells in killing tumor cells and to further validate their platform, the authors compared resting and activated T cells in vitro. The predictive ability of the glycolytic and tricarboxylic acid profiles generated by their platform was in agreement with conventional extracellular flux analysis.

Integrative metabolic modeling demonstrated that human CD8+ T cells exhibited three phases of metabolic remodeling: early activation of glycolysis and amino acid metabolism, followed by RNA synthesis, and concluding with decreased metabolic protein expression and cell division. Profiling of colorectal tumor–infiltrating CD8+ T cells revealed diverse metabolic phenotypes compared to healthy adjacent tissue and peripheral blood. Using multiplexed ion beam imaging of healthy tissue and colon carcinoma, the authors found that metabolic states were spatially enriched, regardless of the cell type in that region, suggesting the presence of metabolic niches. Last, the authors characterized the tumor-immune boundary, finding that metabolically suppressed CD8+ T cells were located furthest away from the tumor cells, highlighting the critical role of metabolic competition.

This single-cell technology platform uncovered the complexity and heterogeneity of metabolic states in immune cells and the importance of the spatial, tissue-specific, and cell lineage–specific contexts. Future studies that integrate metabolic state measurements with gene expression and functional assays could uncover novel therapeutic targets to reprogram immune cell metabolism depending on the context. Importantly, the applicability of this technology to fixed and formalin-fixed paraffin embedded samples allows for correlation of metabolic state with disease outcomes and therapeutic response.

Highlighted Article

View Abstract

Stay Connected to Science Translational Medicine

Navigate This Article