Fig. 4: Assessing the functional states of tumor-infiltrating T cells in PPLELC.

(a) Subclustering of tumor-infiltrating T cells on the UMAP plots of the scRNA-seq datasets. (b) Expression and distribution of canonical T cell marker genes among cells. Red to gray: high to low expression. (c) Average expression of T cell-specific markers across different clusters. The dot size is proportional to the relative expression level of each gene. (d) T cell distribution from tumors and normal tissues. (e, f) Violin plots showing the signature scores of cytotoxic and exhaustion gene sets for each tumor-infiltrating T cell cluster in the snRNA-seq. Signature scores for each cell were calculated by the VISION method. (g, h) Violin plots showing the signature scores of progenitors and terminal exhaustion gene sets for each tumor-infiltrating T cell cluster in the scRNA-seq. Signature scores for each cell were calculated by the VISION method. (i, j) GSEA of significantly enriched pathways for DEGs of cytotoxic (left) and exhausted (right) T cell cluster in the snRNA-seq data. Top significant results ranked by their NES are illustrated. (k) Representative images of multiplex IHC staining in PPLELC tumor tissues. Proteins detected using respective antibodies in the assays are indicated on top. The green, yellow, and red arrows indicated the representative cells positive for LMP1, FOXP3 and CD8 proteins in PPLELC tissue, respectively. Scale bars are 200 μm. Data are presented as means ± standard deviation from three independent experiments; *P  <  0.05, **P  <  0.01, ***P  <  0.001.