In Shakiba et al. (2021), we investigated factors that help define TCR interactions and their effect on the resulting T cell phenotype. We found that tumor-specific T cells' dysfunction program is the composite of affinity-dependent and -independent modules, i.e. TST that encounter tumor antigens with high TCR signal strength rapidly lose effector functions, while TST with low-TCR signal strength for the tumor antigens retain another functional state.
Here, we provide the code details for the bulk RNA-seq and ATAC-seq data from tumor-infiltrating T cells with differing affinities for the tumor antigen. Control cells were naive T cells and normal effector cells.
Raw data can be downloaded from GEO: SuperSeries GSE141818, including GSE141816 (ATAC-seq data) and GSE141817 (RNA-seq data).
Samples were prepared by Mojdeh Shakiba and the sequencing facility at MSKCC. The processing and analyses of the omics data here was performed by Paul Zumbo and Friederike Dündar of the Applied Bioinformtics Core of Weill Cornell Medicine. The code deposited here was primarily written by Paul Zumbo. Don't hesitate to get in touch with questions related to the code.
