Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: scRNAseq identifies key conserved populations in CPI colitis samples. (A) Schematic of study design. Peripheral blood or colon biopsies from all patients were, respectively, pooled, stained for CITE-seq, underwent scRNA-seq and TCR-seq workflows, and were later deconvoluted by patient single-nucleotide polymorphisms (SNPs) via demuxlet. A separate split of biopsy samples was barcoded, pooled, and analyzed via mass cytometry (CyTOF). (B–C) Uniform Manifold Approximation and Projection (UMAP) plots of total cells from biopsy (B) or blood (C) data. Coarse annotations are shown by color at left. Biopsy data is also separately shown by disease state and checkpoint inhibitor received. (D) Dot plots showing landmark genes for coarse annotations (top), CD4 + T-cell subsets (bottom left), and CD8+T cell subsets (bottom middle) in biopsy samples. Expression of immunotherapy targets are additionally shown in CD8 + T-cell subsets (bottom right). (E) Dot plots showing landmark genes for coarse annotations (left), CD4 + T-cell subsets (top right), and CD8+T cell subsets (bottom right) in blood samples. CITE-seq, cellular indexing of transcriptomes and epitopes by sequencing; CPI, checkpoint inhibitors; CyTOF, cytometry by time-of-flight; HC, healthy controls; PD-1, programmed cell death protein 1; scRNA-seq, single-cell RNA sequencing; SNP, single-nucleotide polymorphisms; TCR-seq, T cell receptor sequencing; UC, ulcerative colitis.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Staining, Mass Cytometry, Expressing, Sequencing, Cytometry, RNA Sequencing

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: CPI colitis is associated with cytotoxic T-cell activity and myeloid dysregulation, distinct from ulcerative colitis. (A) Cell frequency of coarse annotated total immune cells by scRNA-seq (left) or CyTOF (right) in biopsies, stratified by disease (mean+SD; each dot represents one patient; *p<0.05 and q<0.1). (B) Number of scRNA-seq differentially-expressed (DE) genes (p<0.05 and log 2 (FC)>1 or <−1) between disease states, for each coarse immune population. (C) scRNA-seq DE genes in healthy versus CPI colitis biopsies by immune populations, with DE genes of interest labeled and color coded by category. (D) Number of DE genes (p<0.05 and |log 2 (FC)| >1) that are found uniquely in only healthy versus CPI colitis, only healthy versus ulcerative colitis (UC), or in both comparisons in biopsy samples, for each coarse immune population. (E) Overlapping DE genes (left) in both healthy versus CPI colitis (x axis) and healthy versus UC (y axis) as well as DE genes between UC and CPI colitis (right) with genes of interest labeled, for CD8 + T cells. CPI, checkpoint inhibitors; CyTOF, cytometry by time-of-flight; HC, healthy controls; scRNA-seq, single-cell RNA sequencing.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Activity Assay, Labeling, Cytometry, RNA Sequencing

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: The CPI colitis microenvironment is characterized by dendritic cell and macrophage dysregulation, and expanded CD4 + RM precursors that are clonally related to CD8 + RM and pathogenic cytotoxic T cells. (A) scRNA-seq-defined myeloid subpopulation frequencies in biopsies across disease states (mean+SD; each dot represents one patient; *p<0.05 and q<0.1). (B) scRNA-seq DE genes (p<0.05 and log 2 (FC)>1 or <−1) in cDC2 between healthy and CPI colitis, with select genes of interest labeled. (C) Heatmap showing DE genes from (B) for cDC2 as z-scores across individual patients (columns). (D) scRNA-seq-defined T-cell subtype frequencies in biopsies across disease states (mean+SD; formatted as in A). (E) DE genes in CD8 + RM cells between healthy and CPI colitis, with select genes of interest labeled. (F) Heatmap of DE genes from (E) for CD8 + RM across individual patients. (G) TCR network plots for two patients with CPI colitis (HS11, HS13). Single cells with RNA and TCR data are denoted by nodes with symbols encoding their functional annotation, and cells with a common TCRαβ CDR3 sequence are grouped together in a single cluster (shaded gray circles). Nodes from biopsy data are shown. cDC1, conventional type 1 dendritic cells; LAMP, lysosomal associated membrane protein; pDC, plasmacytoid DC; myeloid NOS, myeloid not otherwise specified; CPI, checkpoint inhibitors; DC, dendritic cell; DE, differential expressed; HC, healthy controls; RM, resident memory; scRNA-seq, single-cell RNA sequencing; TCR, T cell receptor; UC, ulcerative colitis.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Labeling, Functional Assay, Sequencing, Membrane, RNA Sequencing

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: Stromal and endothelial cells in CPI colitis uniquely dysregulate NAD + and tryptophan metabolism, while both CPI colitis and UC converge on loss of epithelial homeostasis. (A) Cell frequency of coarse-annotated total non-immune cells by scRNA-seq (left) or CyTOF (right) in biopsies, stratified by disease states (mean+SD; each dot represents one patient; *q<0.1). (B) Number of scRNA-seq differentially-expressed (DE) genes (p<0.05 and log 2 (FC)>1 or <−1) between disease states, for each non-immune population. (C) DE genes in healthy versus CPI colitis biopsies by non-immune populations, with DE genes of interest labeled. (D) Number of DE genes (p<0.05 and |log 2 (FC)| >1) that are found uniquely in either healthy versus CPI colitis, healthy versus ulcerative colitis (UC), or both comparisons in biopsy samples, for each non-immune population. (E–F) Overlapping DE genes (left) in both healthy versus CPI colitis (x axis) and healthy versus UC (y axis) as well as DE genes between UC and CPI colitis (right) with genes of interest labeled, for stromal cells (E) and epithelial cells (F). (G) Heatmap showing relative expression (z-score) of MADCAM1 in endothelial cells for individual patients (healthy controls, or patients with CPI colitis with distinct CPI exposure and immunosuppression). Fold change reported for comparisons with significant changes (p<0.05) relative to healthy controls (HS1-3). CPI, checkpoint inhibitors; CyTOF, cytometry by time-of-flight; HC, healthy controls; scRNA-seq, single-cell RNA sequencing.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Labeling, Expressing, Cytometry, RNA Sequencing

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: CPI colitis features global IFN-γ response including enhanced antigen presentation. (A) Single-cell RNA sequencing genes upregulated across the greatest number of coarse populations (p<0.05 and log 2 (FC)>1) in healthy versus CPI colitis. (B) Gene Set Enrichment Analysis showing significantly upregulated pathways (rows) across coarse cell populations (columns) relating to either interferon signaling (top rows) or antigen presentation (bottom rows). (C) DE genes between healthy and CPI colitis biopsies in epithelial absorptive colonocytes. Genes of interest are labeled. (D) Heatmap showing DE genes from (C) across individual patients. (E) Protein expression of HLA-DR by CyTOF in non-professional antigen-presenting populations (mean+SD; each dot represents one patient; *p<0.05 and q<0.1). CPI, checkpoint inhibitors; CyTOF, cytometry by time-of-flight; DE, differentially expressed; HC, healthy controls; IFN, interferon; MHC, major histocompatibility complex; UC, ulcerative colitis.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Immunopeptidomics, RNA Sequencing, Labeling, Expressing, Cytometry

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: Unbiased discovery reveals activated HLA-DR + CD38 + cytotoxic CD8 + and CD4 + RM populations. (A) Protein expression by unbiased CyTOF analysis of T-cell checkpoint/activation markers in CPI colitis biopsies, stratified by disease states (mean+SD; each dot represents one patient; *p<0.05 and q<0.1). (B) CyTOF UMAP plots of all live-cell events, color-coded by annotated unbiased clusters. Data is also shown separately in the inset below by disease state. (C) Feature plots of select marker expression projected on the UMAP space from (B) specifically CD4, CD8a, CD3 for T cells; EpCAM for epithelial cells; HLA-DR for class II antigen presentation and activated T cells; CD38 for activated T cells. (D) Non-immune (left) and immune (right) population frequencies based on unbiased clustering of CyTOF data, by disease state (formatted as in A). (E) CyTOF expression of manually gated HLA-DR and CD38 in T-cell subsets, by disease state. (Bar graph: formatted as in A); pie chart: per cent of each population shown). (F) scRNA-seq (RNA) and CITE-seq (protein) expression of CD38 and HLA-DR(A) in scRNA-seq defined T subpopulations. CITE-seq, cellular indexing of transcriptomes and epitopes by sequencing; CPI, checkpoint inhibitors; CTLA-4, cytotoxic T-lymphocyte-associated antigen 4; CyTOF, cytometry by time-of-flight; EpCAM, epithelial cell adhesion molecule; HC, healthy controls; PD-1, programmed cell death protein 1; RM, resident memory; scRNA-seq, single-cell RNA sequencing; UC, ulcerative colitis; UMAP, Uniform Manifold Approximation and Projection; TIM3, T-cell immunoglobulin and mucin-domain containing 3; TIGIT, T cell immunoreceptor with immunoglobulin and ITIM domains; ICOS, inducible T cell costimulator.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Expressing, Activation Assay, Marker, Immunopeptidomics, Sequencing, Cytometry, RNA Sequencing

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: Checkpoint inhibitors colitis from αPD-1 and combination αPD-1/αCTLA-4 have distinct immunopathological features. (A–C) Single-cell RNA sequencing biopsy results for myeloid cells (top row), and CD8 + T cells (bottom row). (A) Number of DE genes (p<0.05 and log 2 (FC)>1 or <−1) between healthy, αPD-1 colitis, and αPD-1 + αCTLA-4 (combo) colitis. (B) DE genes (p<0.05 and log 2 (FC)>1 or <−1) between αPD-1 and combo (left) and overlapping DE genes (right) in both healthy versus αPD-1 (x axis) and healthy versus combo (y axis), with genes of interest labeled. (C) Subpopulation cell frequencies in αPD-1 and combo colitis patients. (mean+SD; each dot represents one patient). (D) DE genes between αPD-1 and combo, with genes related to IFN-γ signaling (left) or antigen presentation (right) labeled. cDC1, conventional type 1 dendritic cells; CTLA-4, cytotoxic T-lymphocyte-associated antigen 4; DC, dendritic cell; DE, differentially expressed; IFN, interferon; LAMP, lysosomal associated membrane protein; NOS, not otherwise specified; PD-1, programmed cell death protein 1; pDC, plasmacytoid dendritic cell.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: RNA Sequencing, Labeling, Immunopeptidomics, Membrane

Journal: Journal for Immunotherapy of Cancer

Article Title: Dysregulation of CD4 + and CD8 + resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

doi: 10.1136/jitc-2023-008628

Figure Lengend Snippet: External validation underscores a conserved role for activated CD4 RM T cells and cDC dysregulation in CPI colitis across the steroid exposure spectrum. (A) Uniform Manifold Approximation and Projection (UMAP) plots generated from a data set of CD45 + -sorted colon biopsy cells, color coded by coarse annotations (right), and separately plotted by disease state in the inset at left. (B) Dot plots showing marker genes for coarse annotations. (C) Cell frequency of coarse-annotated cells by single-cell RNA sequencing in biopsies, stratified by disease states (mean+SD; each dot represents one patient; *p<0.05 and q<0.1). (D) Number of DE genes (p<0.05 and |log 2 (FC)| >1) that are found uniquely in either healthy versus CPI colitis, CPI only (no colitis) versus CPI colitis, or both comparisons, for each coarse population. (E) Number of DE genes (p<0.05 and log 2 (FC)>1 or <−1) between disease states, for each coarse population. (F) DE genes upregulated across the greatest number of coarse populations (p<0.05 and log 2 (FC)>1) in both healthy versus CPI colitis and CPI only versus CPI colitis. (G) Overlapping DE genes (p<0.05 and log 2 (FC)>1 or <−1) in both healthy versus CPI colitis (x axis) and CPI only versus CPI colitis (y axis) in select coarse populations, with genes of interest labeled. (H) UMAP plots generated from a data set of CD3 + -sorted colon biopsy cells, color coded by coarse annotations (right), and separately plotted by disease state in the inset at left. (I) Dot plots showing landmark genes for coarse T-cell annotations (top left), CD4 + T-cell subpopulations (top right), and CD8 + T-cell subpopulations (bottom left). Expression of immunotherapy targets additionally shown in CD8 + T-cell subsets (bottom right). (J) Cell frequency of T-cell subpopulations out of all annotated T cells, stratified by disease states (formatted as in C). (K) Number of DE genes that are found uniquely in either healthy versus CPI colitis, CPI only (no colitis) versus CPI colitis, or both comparisons, for each T-cell subpopulation. (L) Number of DE genes between disease states, for each T-cell subpopulation. (M) Overlapping DE genes in both healthy versus CPI colitis (x axis) and CPI only versus CPI colitis (y axis) in select T-cell subpopulations, with genes of interest labeled. cDC1, conventional type 1 dendritic cells; CPI, checkpoint inhibitors; DE, differentially-expressed; ILC3, type 3 innate lymphoid cells; NK, natural killer; NOS, not otherwise specified; pDC, plasmacytoid dendritic cell; RM, resident memory; GD, gamma delta.

Article Snippet: To study checkpoint inhibitor-induced colitis (CPI colitis) through an unbiased, multiomic lens, we performed multiplexed single-cell RNA sequencing (scRNA-seq) and T cell receptor (TCR) sequencing (TCR-seq) (10x Genomics), with barcoded antibody staining for protein features (TotalSeq-C, BioLegend), on patient colon biopsies and peripheral blood mononuclear cells (PBMCs) from healthy controls, patients with UC, and patients with CPI colitis ( , ).

Techniques: Biomarker Discovery, Generated, Marker, RNA Sequencing, Labeling, Expressing

Journal: Frontiers in Immunology

Article Title: Single-cell transcriptomic analysis in two patients with rare systemic autoinflammatory diseases treated with anti-TNF therapy

doi: 10.3389/fimmu.2023.1091336

Figure Lengend Snippet: Single Cell Profiling of PBMCs and PMNs in SAID Patients. (A) Study design, comparing transcriptomics of PBMCs and PMNs from pre-treatment (CAPS_NT, TRAPS_NT) and Etanercept treated (CAPS_TNFi, TRAPS_TNFi) blood samples of both patients and one healthy donor (HD). (B, C) UMAP plot, colored by 17 subtypes (B) identified by unsupervised clustering or 5 sample origins (C) . Batch effect removed by Harmony algorithm. (D) Expression of representative markers of each cell type (y-axis) in 17 clusters (x-axis). Dot size represents the percentage of cells in which the gene is detected. Color indicates the centered mean expression. (E) Fraction of 5 sample origins in 17 cell types. Total cell count of each sample was normalized to 100. (F) Boxplot displaying the detected gene number (nFeature_RNA) and percentage of mitochondria genes (percent.mt) in each cell type.

Article Snippet: The processing of blood samples, including PBMC and neutrophil isolation, library preparation, and single-cell RNA sequencing were done by CapitalBio Technology, Beijing.

Techniques: Expressing, Cell Counting