This data forms the key input files for the analysis of single cell data as outlined in the publication titled: Immune Checkpoint Blockade sensitivity and Progression-Free Survival associates with baseline CD8+ T cell clone size and cytotoxicity. This is currently available as a pre-print on BioRXiv (DOI: https://doi.org/10.1101/2020.11.15.383786) and at the time of deposition is undergoing peer review. The abstract for this work is as follows: Immune checkpoint blockers (ICB) exert their anti-cancer effects via CD8+ T cells, although how responses vary over sub-populations and across clones is incompletely understood. We performed single-cell RNA-sequencing of CD8+ T cells and their receptors pre- and post-ICB across eight patients, integrating results with bulk-sequencing data (n=209). We identify seven subsets with divergent responses to ICB, finding the effector cluster demonstrates the most pronounced changes. Likewise, transcriptomic response to ICB relates to clone size, with large clones demonstrating increased numbers of regulated genes of higher immunological pertinence. Cytotoxic effector clones were more likely to persist long-term following ICB and overlapped with public tumour-infiltrating lymphocyte clonotypes. Notably, pre-treatment CD8+ cytotoxicity associated with progression-free survival, highlighting the importance of the baseline CD8+ immune landscape in long-term response. This work further advances understanding of the molecular determinants of ICB response and assists in the search for peripheral prognostic biomarkers. The data consists of three files: 1. Gene expression matrix of CD8 T cells pre- and post-treatment. Each cell barcode is prefixed with an alpha-numeric which specifies the timepoint (A=pre-treatment, B=post-treatment) and the individual donor. 2. Seurat object containing gene expression data and metadata for CD8 T cells (pre- and post-treatment) 3. Seurat object contianing just CD8 T cells which have co-comitant V(D)J sequencing data available. The cells contained within the expression matrices and Seurat objects have undergone full pre-processing and QC steps and are used for the analysis and figures in the linked manuscript. For raw data, please refer to the FASTQ files which have been deposited in the European Genome–phenome Archive, which is hosted by the European Bioinformatics Institute and the Centre for Genomic Regulation (accession no. EGAS00001005507). Scripts used in the analysis of this data can be found on the Fairfax Lab bitbucket account (https://bitbucket.org/bpfairfax/immune-checkpoint-blockade-sensitivity-and-progression-free/src/master/)