CAR+ and CAR- T cells share a differentiation trajectory into an NK-like subset after CD19 CAR T cell infusion in patients with B cell malignancies.

Chimeric antigen receptor (CAR) T cell therapy is effective in treating B cell malignancies, but factors influencing the persistence of functional CAR+ T cells, such as product composition, patients' lymphodepletion, and immune reconstitution, are not well understood. To shed light on this issue, here we conduct a single-cell multi-omics analysis of transcriptional, clonal, and phenotypic profiles from pre- to 1-month post-infusion of CAR+ and CAR- T cells from patients from a CARTELL study (ACTRN12617001579381) who received a donor-derived 4-1BB CAR product targeting CD19. Following infusion, CAR+ T cells and CAR- T cells shows similar differentiation profiles with clonally expanded populations across heterogeneous phenotypes, demonstrating clonal lineages and phenotypic plasticity. We validate these findings in 31 patients with large B cell lymphoma treated with CD19 CAR T therapy. For these patients, we identify using longitudinal mass-cytometry data an association between NK-like subsets and clinical outcomes at 6 months with both CAR+ and CAR- T cells. These results suggest that non-CAR-derived signals can provide information about patients' immune recovery and be used as correlate of clinically relevant parameters.

Identification of human progenitors of exhausted CD8+ T cells associated with elevated IFN-γ response in early phase of viral infection.

T cell exhaustion is a hallmark of hepatitis C virus (HCV) infection and limits protective immunity in chronic viral infections and cancer. Limited knowledge exists of the initial viral and immune dynamics that characterise exhaustion in humans. We studied longitudinal blood samples from a unique cohort of individuals with primary infection using single-cell multi-omics to identify the functions and phenotypes of HCV-specific CD8+ T cells. Early elevated IFN-γ response against the transmitted virus is associated with the rate of immune escape, larger clonal expansion, and early onset of exhaustion. Irrespective of disease outcome, we find heterogeneous subsets of progenitors of exhaustion, based on the level of PD-1 expression and loss of AP-1 transcription factors. Intra-clonal analysis shows distinct trajectories with multiple fates and evolutionary plasticity of precursor cells. These findings challenge the current paradigm on the contribution of CD8+ T cells to HCV disease outcome and provide data for future studies on T cell differentiation in human infections.

Human CD8 T-stem cell memory subsets phenotypic and functional characterization are defined by expression of CD122 or CXCR3.

Long-lived T-memory stem cells (TSCM ) are key to both naturally occurring and vaccine-conferred protection against infection. These cells are characterized by the CD45RA+ CCR7+ CD95+ phenotype. Significant heterogeneity within the TSCM population is recognized, but distinguishing surface markers and functional characterization of potential subsets are lacking. Human CD8 TSCM subsets were identified in healthy subjects who had been previously exposed to CMV or Influenza (Flu) virus in flow cytometry by expression of CD122 or CXCR3, and then characterized in proliferation, multipotency, self-renewal, and intracellular cytokine production (TNF-α, IL-2, IFN-γ), together with transcriptomic profiles. The TSCM CD122hi -expressing subset (versus CD122lo ) demonstrated greater proliferation, greater multipotency, and enhanced polyfunctionality with higher frequencies of triple positive (TNF-α, IL-2, IFN-γ) cytokine-producing cells upon exposure to recall antigen. The TSCM CXCR3lo subpopulation also had increased proliferation and polyfunctional cytokine production. Transcriptomic analysis further showed that the TSCM CD122hi population had increased expression of activation and homing molecules, such as Ccr6, Cxcr6, Il12rb, and Il18rap, and downregulated cell proliferation inhibitors, S100A8 and S100A9. These data reveal that the TSCM CD122hi phenotype is associated with increased proliferation, enhanced multipotency and polyfunctionality with an activated memory-cell like transcriptional profile, and hence, may be favored for induction by immunization and for adoptive immunotherapy.

Exploring and analysing single cell multi-omics data with VDJView.

BACKGROUND: Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information. RESULTS: We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians. CONCLUSIONS: VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview.