Extended Data Fig. 5: Characterization of tumor-infiltrating T cells in Pglyrp1-deficient mice.

(a) Heatmap representing cluster-specific upregulated genes (FDR <0.05, log₂ fold change > log₂(1.5)). If a gene was upregulated in multiple clusters, it is only shown once in the cluster block where it has the biggest fold change. (b) Gene set enrichment analysis of selected Gene Ontology (GO) terms and KEGG and Reactome pathways (top) and published CD8⁺ T cell signatures (bottom) enriched in CD8⁺ T cell-1 (stem-like) cluster vs. CD8⁺ T cell-2 (effector/exhausted) cluster. Only WT cells were included in the analysis. Naïve CD8-1 (Supplementary Table 7); naïve CD8-2 (Supplementary Table 7); terminally exhausted-1⁵⁶; transitory vs. stem-like⁵⁴; terminally exhausted-2⁵³; transitory vs. exhausted⁵⁴; exhausted T cells⁷⁵; effector-like⁵⁶. P-values were computed with the empirical phenotype-based permutation tests (GSEA) and the values shown in the figures were not adjusted for multiple comparisons. (c) RNA velocity analysis was performed on the CD8⁺ T cell clusters (Fig. 3a) using scVelo³¹. The velocity vector field is displayed as streamlines (top) and at single-cell level with each arrow showing the direction and speed (thickness) of movement of an individual cell (bottom). (d) Volcano plot of differentially expressed genes comparing WT vs. Pglyrp1^−/− cells in the Treg cluster (Fig. 3a). Differential genes were computed as FDR < 0.05 and |log₂ fold change| > 0.25. Positive log₂ fold change corresponds to upregulation in Pglyrp1^−/− cells and vice versa. Log₂ fold changes and -log₁₀ p-values were capped within [−1.5, 1.5] and [0, 20] respectively for visualization purposes. P-values were computed with the empirical Bayes quasi-likelihood F-tests in edgeR, then adjusted for multiple comparisons using the Benjamini & Hochberg method (FDR).