Predicting recognition between T cell receptors and epitopes with TCRGP
Fig 5
Analysis of HBV-specific T cells in HCC patients.
(A) Schematics for the analysis of single-cell RNA and TCRαβ sequencing data using TCRGP and multimer-sorted data. (B) Numbers of cells predicted to recognize different epitopes by TCRGP with probability of at least 85%. HBV-reactivity was assessed by four different TCRGP classifiers trained against four different HBV-epitopes (HBVcore169, HBVcore195, HBVpol282, HBVpol387). Other predictions were made using the models trained with the VDJdb data. (C) Dimensionality reduced representation (UMAP) of the 1189 CD8+ T cells from HBV+ HCC-patients from peripheral blood, normal adjacent tissue and tumour tissue. Encircled dots represent the T cells predicted to be HBV-reactive by TCRGP. (D) The frequencies of T cells predicted to recognize different HBV-epitopes in each cluster. (E) Z-score normalized mean expressions of known canonical markers to assess CD8+ cell phenotypes (naïve, cytotoxic, costimulatory inhibitory, and effector memory markers) in the three different exhausted cell clusters. Exhausted 3 was predicted to be enriched for HBV-targeting T cells (p = 3e-06, p.adj = 0.001).