TCF-1 is a key transcription factor in progenitor exhausted CD8 T cells (Tex). Moreover, this Tex cell subset mediates responses to PD-1 checkpoint pathway blockade. However, the role of the transcription factor TCF-1 in early fate decisions and initial generation of Tex cells is unclear. Single-cell RNA sequencing (scRNA-seq) and lineage tracing identified a TCF-1 + Ly108 + PD-1 + CD8 T cell population that seeds development of mature Tex cells early during chronic infection. TCF-1 mediated the bifurcation between divergent fates, repressing development of terminal KLRG1 Hi effectors while fostering KLRG1 Lo Tex precursor cells, and PD-1 stabilized this TCF-1 + Tex precursor cell pool. TCF-1 mediated a T-bet-to-Eomes transcription factor transition in Tex precursors by promoting Eomes expression and drove c-Myb expression that controlled Bcl-2 and survival. These data define a role for TCF-1 in early-fate-bifurcationdriving Tex precursor cells and also identify PD-1 as a protector of this early TCF-1 subset.
When analyzing single-cell RNA-seq data, constructing a pseudo-temporal path to order cells based on the gradual transition of their transcriptomes is a useful way to study gene expression dynamics in a heterogeneous cell population. Currently, a limited number of computational tools are available for this task, and quantitative methods for comparing different tools are lacking. Tools for Single Cell Analysis (TSCAN) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis. TSCAN uses a cluster-based minimum spanning tree (MST) approach to order cells. Cells are first grouped into clusters and an MST is then constructed to connect cluster centers. Pseudo-time is obtained by projecting each cell onto the tree, and the ordered sequence of cells can be used to study dynamic changes of gene expression along the pseudo-time. Clustering cells before MST construction reduces the complexity of the tree space. This often leads to improved cell ordering. It also allows users to conveniently adjust the ordering based on prior knowledge. TSCAN has a graphical user interface (GUI) to support data visualization and user interaction. Furthermore, quantitative measures are developed to objectively evaluate and compare different pseudo-time reconstruction methods. TSCAN is available at https://github.com/zji90/TSCAN and as a Bioconductor package.
PD-1 blockade unleashes CD8 T cells1, including those specific for mutation-associated neoantigens (MANA), but factors in the tumour microenvironment can inhibit these T cell responses. Single-cell transcriptomics have revealed global T cell dysfunction programs in tumour-infiltrating lymphocytes (TIL). However, the majority of TIL do not recognize tumour antigens2, and little is known about transcriptional programs of MANA-specific TIL. Here, we identify MANA-specific T cell clones using the MANA functional expansion of specific T cells assay3 in neoadjuvant anti-PD-1-treated non-small cell lung cancers (NSCLC). We use their T cell receptors as a ‘barcode’ to track and analyse their transcriptional programs in the tumour microenvironment using coupled single-cell RNA sequencing and T cell receptor sequencing. We find both MANA- and virus-specific clones in TIL, regardless of response, and MANA-, influenza- and Epstein–Barr virus-specific TIL each have unique transcriptional programs. Despite exposure to cognate antigen, MANA-specific TIL express an incompletely activated cytolytic program. MANA-specific CD8 T cells have hallmark transcriptional programs of tissue-resident memory (TRM) cells, but low levels of interleukin-7 receptor (IL-7R) and are functionally less responsive to interleukin-7 (IL-7) compared with influenza-specific TRM cells. Compared with those from responding tumours, MANA-specific clones from non-responding tumours express T cell receptors with markedly lower ligand-dependent signalling, are largely confined to HOBIThigh TRM subsets, and coordinately upregulate checkpoints, killer inhibitory receptors and inhibitors of T cell activation. These findings provide important insights for overcoming resistance to PD-1 blockade.
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