A multiomic workflow to study CPI colitis

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 (figure 1A, online supplemental table S1). Viably cryopreserved intestinal biopsies were thawed in a single batch and digested into single-cell suspensions, which minimally impacts gene expression and cell representation in biopsies compared with fresh processing.5 In a separate experiment, cryopreserved PBMCs from the same patients were also thawed in a single batch. For both workflows, biopsies or PBMCs were pooled in a single tube prior to processing for single-cell sequencing. After sequencing, single cells from specific patients were computationally deconvoluted by matching donor-specific single-nucleotide polymorphisms obtained from bulk RNA sequencing.6 In a distinct workflow, a sample of thawed and digested biopsy cells was taken for separate single-cell proteomic analysis via mass cytometry (CyTOF, panel in online supplemental table S2). In total, the donors included nine patients with cancer and histoendoscopically confirmed colitis from CPI therapy: six received anti-PD-1 (αPD-1) therapy alone and three received combination αPD-1 + anti-CTLA-4 (αCTLA-4). These were compared to three healthy controls (HC) undergoing colonoscopy and three patients with UC (online supplemental table S1). One UC patient (HS6) did not yield viable single cells from biopsy after processing, but contributed to the blood data. Cells from CPI colitis patient HS11 were present in the biopsy data, but not in the blood data. Of note, most CPI colitis patients had previously received corticosteroids before biopsy, with three patients receiving TNF blockade (all had been treated with αPD-1). One individual (HS10) received vedolizumab in addition to TNF blockade for their αPD-1 colitis. While most patients had a suboptimal initial response to corticosteroids and required further immunosuppression (TNF blockade and/or vedolizumab) and were therefore steroid-refractory, three of the patients (HS7, HS8, and HS13) did eventually respond to increased corticosteroids alone (online supplemental table S1).

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Figure 1

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.

scRNA-seq identifies key conserved populations in CPI colitis samples

After quality control and unbiased clustering, 50,845 and 43,791 sequenced biopsy and blood cells passed filter, respectively. Using Leiden clustering followed by semi-supervised annotation (Methods, marker genes/proteins in online supplemental table S3), we identified conserved coarse immune populations in both biopsies and blood, as well as additional coarse non-immune populations in biopsies (figure 1B,C). Cells were well distributed by disease state, and prior CPI and immunosuppression (figure 1B and online supplemental figure S1). We were able to further subcluster several coarse populations (B and plasma cells, CD4⁺ and CD8⁺ T cells, myeloid cells, cycling populations, epithelial cells, endothelial cells, and stromal cells) into fine subpopulations in biopsies (figure 1D and online supplemental figure S2A,B) and blood (figure 1E and online supplemental figure S2C). Importantly, in colonic biopsies, this includes a cytotoxic CD8⁺ T-cell subset expressing GZMB, PRF1, and IFNG (“CD8T GZMB”), a separate cytotoxic subset expressing GZMK, DUSP2, and EOMES (“CD8T GZMK”), as well as a distinct tissue-RM population expressing CD69, ITGAE, and ITGA1 (“CD8T RM”). For CD4⁺ T cells, in addition to FOXP3⁺ regulatory T cells (“CD4T reg”), CXCR5⁺ follicular helper T cells (“CD4T fh-like”), and S100A4, VIM, and IL7R expressing memory cells, there was similarly an RM population expressing CD69, ITGAE, and ITGA1 (“CD4T RM”). Both CD8⁺ and CD4⁺ T cells include a naïve KLF2⁺ SELL⁺ subset. Hence, canonical immune and non-immune populations are identified in CPI colitis patients, including both cytotoxic and resident memory T-cell subpopulations in inflamed colitis tissues.

CPI colitis is associated with cytotoxic T-cell activity and myeloid dysregulation, distinct from ulcerative colitis

Cell abundance analysis of scRNA-seq data revealed significant enrichment of cytotoxic CD8⁺ T cells in CPI colitis biopsies compared with HC, while group 3 innate lymphoid cells (ILC3s) were depleted (figure 2A, left). Notably, these significant changes were not seen in UC with varying endoscopic severity, compared with either CPI colitis or HC. CyTOF analysis based on manual gating of canonical cell type markers shows a similar, but not significant, trend of increased CD8⁺ T cells in CPI colitis (figure 2A, right). In the blood, general immune subtypes did not show significant changes across disease conditions, indicating a lack of remodeling of peripheral immune responses (online supplemental figure S3C,D).

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Figure 2

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 log₂(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 |log₂(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.

Differentially expressed gene (DEG) testing in biopsies between disease conditions further revealed large gene expression shifts (|log₂(fold change)| >1) that were specific to CPI colitis tissues over both HC and UC, and occurred across multiple immune and non-immune populations (figure 2B, DEG lists by disease in online supplemental tables S4 and S5). Within the T-cell compartment, CD8⁺ T cells upregulated numerous genes indicating an activated state, including immune checkpoints CTLA4 and LAG3, ectoenzymes ENTPD1 and CD38, T-cell activation marker HLA-DRA, and transcription factor BATF, which is essential for effector CD8⁺ T-cell differentiation7 (figure 2C). CD8⁺ T cells also overexpressed effector molecules including IFNG and cytolytic genes PRF1, GZMB, GZMA, and GZMH, suggesting mechanisms for colon damage mediated by these effector cells. Upregulation of cell trafficking-related genes including integrin ITGAE, chemokine receptor CXCR6, chemokines CCL4 and CCL5, and ITK (which is required for gut homing8 supports their role in T-cell recruitment to inflamed tissues. Anti-inflammatory ANXA1 was downregulated, which has been shown to exacerbate T cell-dependent inflammation.9 Interestingly, TNF was also downregulated, implying that CD8⁺-derived TNF may not underlie inflammation in these cases of CPI colitis. Gene Set Enrichment Analysis (GSEA) confirms CD8⁺ T-cell upregulation of pathways associated with chemokine signaling and TCR signaling including ITK, as well as global interferon signaling seen across cell populations (see below) (online supplemental figures S4A and S5A, online supplemental tables S6 and S7). While CD4⁺ T cells in CPI colitis showed similar downregulation of ANXA1 and upregulation of CCL4 and to a lesser extent IFNG (log₂(FC)=0.68), their differential expression of other genes in CPI colitis was minimal. γδ T cells also overexpressed a similar suite of genes including LAG3, GZMB, and chemokine/receptors CCL3L3 and CX3CR1. They additionally overexpressed SOCS3, which may provide negative feedback for interferon (IFN)-γ signaling. T cell-intrinsic gene expression changes were robust across individual patients despite distinct primary tumor types (online supplemental figure S6), arguing for a conserved adaptive immune signature in this primarily steroid-experienced CPI colitis cohort.

The cycling population is a heterogeneous population, which forms a joint cluster driven by shared overexpression of proliferative genes such as STMN1 and MKI67. Because of this, we found DEGs in cycling cells in CPI colitis (over healthy) to be highly impacted by marker genes of specific constituent cell populations (figure 2C). Specifically, CPI colitis cycling populations had higher expression of cytotoxic T-cell genes including CD3D, CD3G, CD3E, TRAC, CD7, CD8A, CD8B, GZMB, GZMA, and IFNG, as well as T-cell activation markers CTLA4, BATF, ENTPD1, TIGIT, and LAG3, suggesting a propensity for cytotoxic CD8⁺ T-cell subsets to proliferate in this disease state. Conversely, plasma cell-associated marker genes CD79A, JCHAIN, IGHA1, IGHA2, IGKC, IGLL5, TNFRSF17, and MZB1 were downregulated in the CPI colitis cycling population, suggesting quantitative depletion of cycling plasma cells. Additionally, non-cycling plasma cells had similar downregulation of JCHAIN, IGHA2 and IGLL5, but also survival factors TNFRSF13B and CD4410 and gut-homing integrins ITGA4 and ITGB7, pointing to the possible impairment of homing, activation, and survival of plasma cells in the CPI colitis state.

Overall myeloid gene expression changes were also similarly related to the heterogeneous composition of this population. The upregulation of lineage markers for inflammatory macrophages (CD14, CD68, C1QA, C1QB, C1QC), and downregulation of dendritic cell marker genes (CD1C, CLEC9A, CLEC10A, and CD83) (figure 2C) may be related to quantitative chances in their abundance (see below). In addition to this, upregulation of pro-inflammatory molecules (CD38, CD40, IL32; chemokines CCL3/4/18, CXCL9/10; cathepsins; and inflammatory potentiators S100A8/9), and downregulation of the anti-inflammatory molecule ANXA1, collectively reflect the contribution of pro-inflammatory macrophages to CPI colitis pathology.

Across the immune compartment, the changes in cell type abundance seen in CPI colitis were generally not seen in UC, arguing for distinct immunopathology. This is also supported by a comparison of gene expression changes in these two pathogenic states. Most genes that are differentially expressed in CPI colitis versus HC (|log₂(FC)| >1) were not differentially expressed when UC and HC are compared (figure 2D). This is exemplified by the cytotoxic CD8⁺ T-cell population, which generally does not co-regulate genes in common in the healthy comparisons with either CPI colitis or UC (figure 2E, left). This is also shown by direct DE testing between CPI colitis and UC, which confirms that many of the same genes in the CPI colitis comparison with HC, are distinctly upregulated in CPI colitis as distinct effector molecules from UC. These include IFN signaling molecules IFNG, STAT1, and JAK3; cytotoxic genes PRF1, GZMB, GZMA, and GZMH; immune checkpoints LAG3, CTLA4, and TIGIT; activation molecules CD38, TNFRSF9, BATF, and HLA-DRA; and trafficking-related genes CXCR6, ITGAE, and CCL4 (figure 2E, right). The immune checkpoints TIGIT and TNFRSF9 are uniquely upregulated in the direct CPI colitis versus UC comparison (and not vs HC), pointing to unique overexpression of these regulatory mechanisms in the CPI colitis disease state. Although the UC sample size was small (n=2 with multiplexed biopsy data), and heterogenous with regard to endoscopic activity (Discussion), a separate dedicated analysis of UC patients compared with HC5 confirmed the unique immunopathology of CPI colitis highlighted here.

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

Subclustering of immune populations from biopsies reveals key contributions for myeloid and T-cell subtypes. Myeloid subclustering (online supplemental figure S2A) demonstrated significant macrophage enrichment, accompanied by depletion of conventional type 1 dendritic cells (cDC1s) (figure 3A). At the level of gene expression, cDC1 cells do not show significant DEG (data not shown), but cDC2s show distinct upregulation of major histocompatibility complex (MHC) class I antigen presentation (HLA-A, HLA-C, TAP1), IFN induced chemokine signaling (CXCL10), and DC licensing/activation (CD40) (figure 3B, DEG lists in online supplemental table S8). They also downregulate IL1B which may be compensatory (figure 3B). DE programs in cDC2 were conserved across individual patients regardless of primary tumor type (figure 3C). Macrophages upregulate cathepsin C (CTSC) which may contribute to inflammatory pathogenesis (data not shown). Other myeloid subpopulations did not demonstrate significant DEG (data not shown). Myeloid subpopulations in the blood (classical and non-classical monocytes, and cDCs, online supplemental figure S2C) are not detectably different in frequency in CPI colitis (online supplemental figure S3D, right).

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Figure 3

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 log₂(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.

For the T-cell subcompartment, RM precursors and cytotoxic effector populations were strongly implicated in CPI colitis. Specifically, both CD4⁺ RM and CD8⁺ RM populations, as well as CD8⁺ GZMB⁺ cells, were all significantly enriched in CPI colitis versus HC (figure 3D). CD8⁺ GZMB⁺ cells in particular were more than 10-fold more abundant. Cycling T cells also trended towards enrichment in CPI colitis, supporting findings from coarse DE testing of the cycling population, although this was not significant (online supplemental figure S3A, left). In addition, the CD8⁺ RM population demonstrated dynamic regulation of gene modules in CPI colitis that may contribute to pathogenesis, including downregulation of anti-inflammatory genes ANXA1, ANXA2, SOCS1, and TGFB1 as well as an upregulation of homing and trafficking molecules ITGAE and CXCR6; immune checkpoints CTLA4, LAG3, and ENTPD1; activation molecules TNFRSF9, CD38, BATF, JAK3, STAT1, and STAT3; and signaling and effector molecules such as ITK, CRTAM, PRF1, GZMB, and IFNG (figure 3E). These findings were consistent across individual patients (figure 3F). GSEA for CD8⁺ RM underscores the upregulation of adaptive immune signaling via ITK, CTLA4, LAG3; cytokine signaling via JAK3 and STAT1; and downregulation of interleukin signaling supported by ANXA1, TGFB1, TNF, and SOCS1 (online supplemental figure S4C and S5C, online supplemental tables S6 and S7). CD4⁺ RM and CD8⁺ GZMB populations demonstrated few to no DEGs in CPI colitis. However, cytotoxic CD8⁺ GZMB cells compared with their RM counterparts express higher levels of cytolytic genes (GZMB, NKG7, PRF1, GNLY, GZMA, GZMH), effector molecules (IFNG), and chemokines (CCL3, CCL4), which would be consistent with their role as effector cells causing terminal epithelial damage (data not shown). Generally significant changes by frequency were not seen in other immune subpopulations (cycling, B, plasma cells) in biopsies (online supplemental figure S3A), or T-cell subpopulations in the periphery (online supplemental figure S3D, right).

Clonal analysis of these specific T-cell phenotypes implicates developmental relationships between both RM populations and terminal GZMB⁺ effectors. We obtained paired TCR data from single cells with transcriptome data (biopsies: 15,394 cells with TCRβ and 12,810 cells with TCRαβ paired with RNA data; blood: 17,694 cells with TCRβ and 12,714 cells with TCRαβ paired with RNA data). We used the NAIR analytic approach11 to identify expanded clusters of single cells where >1 cell shared the same TCRαβ heterodimer. This revealed that biopsies from CPI colitis patients had significantly higher numbers of expanded clusters (normalized to the total number of cells per sample) compared with both HC and UC (online supplemental figure S7A). Consistent with this finding, total T cells from CPI colitis biopsies had a significantly higher Gini coefficient (0.18) than HC (0.07, p=0.013), which was also numerically higher than UC although not significant (0.14, p=0.099), consistent with clonal expansion in the CPI colitis state (online supplemental figure S7B). T cells from the blood of these patients did not demonstrate significant changes in the numbers of expanded clusters or Gini coefficient in CPI colitis, consistent with minimal remodeling of the overall peripheral T-cell repertoire (online supplemental figure S7A,B). Moreover, network analysis indicates increased TCRαβ clonotype sharing between RM and cytotoxic phenotypes in CPI colitis. Looking at expanded clusters in biopsies, although HC tissue has low-level pairwise sharing between CD4⁺ RM, CD8⁺ RM, or CD8⁺ GZMB populations (range: 1.3–2.5% of expanded clusters), all of these frequencies are increased in CPI colitis (range: 8.8–22% of expanded clusters). In addition, individual clusters in CPI colitis biopsies exhibit three-way sharing between all three populations (7.2% of expanded clusters), which is never seen in HC (single patient network plots in figure 3G, quantitation in online supplemental figure S7C,D). The clonotype sharing, which is the result of irreversible somatic rearrangement of the CDR3 locus, indicates a direct developmental relationship between these populations. Furthermore, given the known role of RM cells in rapid tissue responses to previously encountered antigens, and the higher cytolytic effector program of the GZMB⁺ cells, this supports a model where both CD4⁺ RM and CD8⁺ RM cells act as directly related tissue precursors, which on recognition of tissue antigens give rise to CD8⁺ GZMB progeny responsible for tissue damage in CPI colitis.

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

In the non-immune compartment in CPI colitis biopsies, epithelial, endothelial, stromal and enteric neural cells do not demonstrate significant changes in abundance this disease state (figure 4A, left), which is corroborated by orthogonal CyTOF (figure 4A, right), However, significant gene expression changes are seen in all these populations in CPI colitis, relative to either UC or HC (figure 4B, DEG lists by disease in online supplemental tables S4 and S8). Specifically, the stromal and enteric neural populations share upregulation of neutrophil chemokines (CXCL1/7/8/9/10), proinflammatory IL32, as well as possible compensatory mechanisms such as IL18BP (which inhibits IL18 signaling) and metallothioneins that scavenge reactive oxygen species (figure 4C). While generally these changes are conserved across the majority of individual CPI colitis patients, several patients (HS8, HS10, HS13) represent a subset that upregulate these programs to a lesser degree (online supplemental figure S6). This may be related to their lower endoscopic severity score (0–1), or for patients HS8 and HS13, the fact that they responded to increased corticosteroids alone (online supplemental table S1), but this will require further study and validation.

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Figure 4

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 log₂(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 |log₂(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.

Interestingly, GSEA analysis for stromal cells in CPI colitis versus HC not only supports upregulation of proinflammatory cytokine signaling and metallothioneins, but also identifies changes in metabolism, specifically a common focus on increased NAD⁺ catabolism (NAMPT, NNMT), as well as tryptophan metabolism (WARS, IDO1) (online supplemental figures S4B and S5B and online supplemental tables S6 and S7 for GSEA, figure 4C for volcano plots of individual genes). These same metabolic genes are also significantly upregulated in enteric neural cells from CPI colitis versus HC (figure 4C). While these pathways have been implicated in UC pathogenesis,12 13 they also distinctly characterize stromal cells in CPI colitis. Most DE genes between CPI colitis versus HC are distinct from genes from UC comparisons to healthy (figure 4D,E, left), and in direct comparisons between UC and CPI colitis, NAD⁺ catabolism, tryptophan metabolism, and metallothionein genes are again uniquely upregulated in CPI colitis stroma (figure 4E, right). Stromal handling of NAD⁺/tryptophan may therefore be unique to CPI colitis over other colitis states, via diminished epithelial survival via NAD⁺ depletion, increased toll-like receptor 2 and 4 activation by WARS,14 15 or compensatory inhibition of inflammation via IDO-mediated tryptophan depletion.

We also observe CPI colitis-specific dysregulation of the BMP pathway in stromal cells, which is a known contributor to colitis models as it modulates intestine morphogenesis, homeostasis, and inflammation.16 Specifically, we see downregulation of the Wnt regulator BMP4, which is anti-inflammatory and protective in DSS-induced colitis models through stem cell maintenance and epithelial proliferation, along with its downstream targets ID/1/2/3.16–18 Furthermore, we also see downregulation of Wnt antagonist FRZB, and BMP4 antagonists HIPK2 and HITRA319–21 (figure 4C,E). Despite some heterogeneity in upregulated gene modules in stromal cells across patients, the downregulation of BMP and Wnt signaling is highly conserved across individuals (online supplemental figure S6). GSEA analysis points to possible effects of BMP4 downregulation on IGF transport and elastic fiber formation as well (online supplemental figure S5B and online supplemental tables S6 and S7). Together, these results suggest decreased BMP activity in CPI colitis, which could further exacerbate colonic damage and inflammation.

While epithelial cells also have substantial gene expression changes in CPI colitis (figure 4B,D), these may represent a shared program of epithelial loss of homeostasis across colitis states. Specifically, epithelial cells in CPI colitis (over healthy) showed downregulation of many homeostatic genes (GUCA2A, GUCA2B, CHP2, ANPEP), small molecule transporters (AQP8, SLC25A5, SLC26A2, SLC26A3, SLC9A3R1, CLCA4, FXYD3, FABP1, CA1, CA2, CA4), and protective molecules (TFF3, PRAP1, and LYPD8) (figure 4C). Epithelial cells also downregulated genes related to structure (EPCAM, KRT8/18/19/20, CLDN3/4), and antibody transport function (PIGR, FCGRT). These downregulated genes are highly conserved across individual patients (online supplemental figure S6). Of note, almost half the DEGs between HC versus CPI colitis, and nearly all DEGs between HC versus UC, consisted of shared dysregulated genes (figure 4F, left), while there were almost no DEGs between CPI colitis and UC (figure 4F, right). Shared genes downregulated in both UC and CPI colitis were many of the aforementioned genes also downregulated compared with healthy that are involved in homeostasis, transport, and structure (figure 4F, left). Together these results indicate that although UC and CPI colitis may have distinct immune mechanisms, both pathologic states converge on loss of intestinal homeostasis modules.

Endothelial cells in CPI colitis upregulate MAdCAM-1, the ligand of integrin α4β7, particularly after TNF blockade and αCTLA-4

Endothelial cells in CPI colitis contribute to pathogenesis in several respects. In addition to their overexpression of chemokines promoting inflammation (eg, CCL14, CXCL11), and downregulation of KLF2 which inhibits T-cell rolling and adhesion to endothelium22 (figure 4C, DEG lists by disease in online supplemental table S4), the CPI colitis endothelial cells significantly upregulated MADCAM1, the ligand for integrin α4β7. α4β7 binding to MADCAM1 facilitates T-cell recruitment to the gut.23 24 Vedolizumab is a monoclonal antibody against α4β7, that is, Food and Drug Administration approved for both Crohn’s disease and UC, and it is frequently used off-label for CPI colitis.25 However, the specific CPI colitis disease states that may be more responsive to this therapy are unknown. In an exploratory analysis, MADCAM1 was particularly upregulated in patients who received prior TNF blockade, as well as those who received a combination of αCTLA-4 with αPD-1 CPI (figure 4G, DEG lists by suppression in online supplemental table S9). While this analysis is limited by sample size and heterogeneity, these findings suggest that patients with αCTLA-4-induced colitis, or those who do not respond to steroids or anti-TNF therapy, may benefit from vedolizumab.

CPI colitis features global IFN-γ response including enhanced antigen presentation

To gain a broader look at other pathways in CPI colitis, we looked at genes that were commonly overexpressed across multiple coarse populations compared with HC. Interestingly, of the top fifteen genes that were upregulated in the greatest number of populations, 12 emerged as downstream of IFN signaling (figure 5A, DEG by disease in online supplemental table S4). This included IFN-γ signaling molecule STAT1, early IFN-γ response genes GBP1, GBP2, GBP4, GBP5, ISG20, and IRF1, and, interestingly, antigen presentation-related genes HLA-DRA, CD74, TAP1, and immunoproteasome subunits PSMB8 and PSMB9. Of note, the most frequently overexpressed gene was FKBP5, which associates with and regulates the steroid receptor complex and trafficking26 and may be compensatory in this predominantly steroid-experienced setting. Looking closer at each population, we found many immune and non-immune cell types upregulating molecules in CPI colitis related to IFN-γ-JAK-STAT signaling (IFNGR2, JAK2, STAT1/3) and gene modules expressed in response to IFN-γ (GBP*, IFITM*, IRF*) (GSEA results in figure 5B and online supplemental tables S6 and S7, DE genes in online supplemental figure S8A). Overexpression of IFNG only in CD8⁺ (eightfold enriched), cycling, and CD4⁺ populations implicates T cells as the primary source for IFN-mediated effects.

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Figure 5

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 log₂(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.

Additionally, antigen presentation modules were also upregulated globally, in both professional and non-professional antigen-presenting immune and non-immune cells, which may occur in response to IFN-γ signaling (GSEA results in figure 5B and online supplemental tables S6 and S7). These include both HLA class I and II genes, TAP1, CD74, CIITA, as well as proteasome subunit genes and immunoproteasome subunits (PSMB8/9/10) (DE genes in online supplemental figure S8B).

Interestingly, among the epithelial subpopulations, the absorptive colonocyte may specifically integrate homeostasis and IFN-mediated inflammation. This is because this population appears to be a target for tissue damage—absorptive colonocytes were significantly depleted in CPI colitis (online supplemental figure S3B, left), even when the total epithelial population was not (figure 4A). In addition, these absorptive colonocytes downregulated many of the previously mentioned homeostatic genes (figure 5C) seen in coarse epithelial comparisons (figure 4C), but distinct from coarse epithelial cells, these colonocytes exhibited unique overexpression of IFN-γ signaling (STAT1/3, IFITM1/3, ISG20), downstream antigen presentation (HLA-DRA/B1, CD74, PSMA4, PSMB9, PSME2), as well as inflammatory genes (S100P, S100A11/14/16) and POMP, a chaperone protein required for assembly of both the proteasome and immunoproteasome (figure 5C, DEG lists by disease in online supplemental table S8). Colonocyte gene expression changes were highly conserved across individuals (figure 5D). Pathway analysis supports upregulation of inflammatory pathways, as well as downregulation of metabolic and small molecule transport pathways as indicated by decreased SLC*, AQP*, and ATP transcript expression (online supplemental figure S4C and S5C). Together, these signatures additionally implicated absorptive colonocytes as the epithelial convergence point of IFN-γ-induced signaling, antigen presentation, and inflammation.

We confirmed this trend of increased antigen presentation by looking at HLA-DR expression in non-professional antigen-presenting cells by CyTOF (figure 5E). Epithelial, endothelial, CD8⁺ and CD4⁺ T cells, CD4⁺ T regulatory (Treg) cells, and natural killer T (NKT) cells all significantly upregulated HLA-DR in CPI colitis. The effect was especially striking in both epithelial cells and CD8⁺ T cells, going from almost no HLA-DR expression in both populations in HC tissue to an average of 60% and 20% HLA-DR⁺ epithelial and CD8⁺ T cells, respectively. While HLA-DR can be an activation marker in human T cells, its upregulation (along with IFN-inducible proteasome subunits) across cell types suggests that IFN signaling in inflamed CPI colitis tissues may establish a feedback loop leading to upregulated antigen presentation, including a possible presentation by non-professional antigen presenting cells (APCs). This enhanced antigen presentation, including altered peptide isoforms generated by immunoproteasome subunits, may potentially drive CPI colitis pathogenesis.

Unbiased CyTOF clustering reveals activated HLA-DR⁺ CD38⁺ cytotoxic CD8⁺ and CD4⁺ RM populations

Because our transcriptomic data suggested that CD8⁺ T-cell activation was pivotal to CPI colitis pathology, we looked at activation markers expressed by CD8⁺ T cells via CyTOF for proteomic confirmation. CPI colitis CD8⁺ T expressed significantly more CD38⁺ cells and less CD27⁺ compared with HC (figure 6A). Additionally, we observed trends (not significant) of increased CTLA-4⁺ and T cell immunoreceptor with immunoglobulin and ITIM domains (TIGIT)⁺ populations. Of note, we saw no trends in PD-1 expression by both RNA and protein.

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Figure 6

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.

Separately, we additionally performed unbiased clustering and visualized our CyTOF data via Uniform Manifold Approximation and Projection (UMAP) (Cyclone27) to investigate unanticipated cell populations. This identified several populations that clustered based on HLA-DR expression (figure 6B,C). Several epithelial cellular adhesion molecule (EpCAM)⁺ epithelial clusters emerged, that also expressed HLA-DR. Interestingly, CD3⁺ T cells (CD4⁺, CD8⁺, and CD4⁻CD8⁻ T (dnT)) were split into respective clusters that either co-expressed HLA-DR⁺CD38⁺ or did not (HLA-DR⁻CD38⁻). Both surface markers have been shown to mark activated T cells, in particular, HLA-DR, and their co-expression identified a distinct activated T-cell subset in the CPI colitis microenvironment using unsupervised analysis.

Looking at cell population frequencies in the unbiased CyTOF clusters, we found a significant increase in HLA-DR⁺ accompanied by a significant decrease in HLA-DR⁻ epithelial cell frequencies in CPI colitis compared with healthy (figure 6D). Additionally, all three (CD4⁺, CD8⁺, dnT) HLA-DR⁺CD38⁺ T-cell clusters showed a trend towards increased frequency which was not statistically significant. Because our unbiased clustering revealed a strong correlation between HLA-DR and CD38 expression in T cells, we also manually applied this co-expression gate to our CyTOF T-cell populations. In CD8⁺ T CD4⁺ T, dnT, and CD4⁺ Treg cells, there was a significant increase in manually gated HLA-DR⁺CD38⁺ populations, accompanied by a significant decrease in HLA-DR⁻CD38⁻ cells in CPI colitis (figure 6E).

Lastly, we also looked at HLA-DR and CD38 expression in our scRNA-seq object, on the transcript and protein (CITE-seq) level to understand what T-cell subpopulation are marked by co-expression of these markers. By both RNA and protein, two of the populations that are quantitively enriched in CPI colitis (CD8⁺ GZMB and CD4⁺ RM cells, figure 3D) were positive for both HLA-DR and CD38, indicating that their specific activation is linked to the CPI colitis state (figure 6F). The third T-cell population that was enriched in CPI colitis (CD8⁺ RM cells) was strongly positive for HLA-DRA transcript but not CD38. Overall, HLA-DR and CD38 co-expression may mark the pathologically relevant, activated T cells in CPI colitis, which includes CD4⁺ RM precursors as well as CD8⁺ cytotoxic effectors, narrowing the target cells for potential therapeutic strategies.

CPI colitis from αPD-1 and combination αPD-1/αCTLA-4 have distinct immunopathological features

We also investigated the distinct mechanisms of colitis induced by αPD-1 versus combination αPD-1/αCTLA-4 treatment. Exploratory comparisons were restricted to the two patients with αPD-1 colitis who received only steroids (HS8 and HS9), versus the three patients with αPD-1/αCTLA-4 colitis who also received only steroids (HS13, HS14, HS15), to ensure consistent immunosuppression for comparability. The myeloid population demonstrates more gene expression changes with combination blockade (figure 7A, top; online supplemental table S10). Many combination-upregulated genes related to monocytes/macrophages (CD14, S100A8/9), chemotaxis and trafficking (integrin ITGB2, CCL4, CXCL2/3, complement receptors C3AR1/C5AR1), inflammatory signaling (IL1R2, IFNGR2, TLR2), and compensatory anti-inflammatory signaling (metallothioneins). Conversely, αPD-1 colitis demonstrated upregulation of ITGB7 and CLEC10A (figure 7B, top left). Many of the inflammatory/myeloid genes upregulated in combination colitis were also upregulated in αPD-1 colitis but to a lesser extent compared with healthy (figure 7B, top right). However, overall myeloid composition was not significantly different between CPI (figure 7C, top).

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Figure 7

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 log₂(FC)>1 or <−1) between healthy, αPD-1 colitis, and αPD-1 + αCTLA-4 (combo) colitis. (B) DE genes (p<0.05 and log₂(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.

Distinct differences were also seen in the CD8T compartment, where both αPD-1 and combination colitis induced robust differential expression versus HC (figure 7A, bottom; online supplemental table S10). While combination colitis showed a propensity for integrin ITGB2 and granzyme K (GZMK), as previously described,3 these patients also upregulated co-stimulation (ICOS) and other immune checkpoints including ENTPD1 and CD27. αPD-1 colitis involved a distinct program with upregulation of cytotoxic genes (NKG7, GNLY, GZMM, CRTAM), distinct integrins (ITGAE, ITGB7), and multiple MHC class II isoforms indicative of T-cell activation (figure 7B, bottom left). This αPD-1 associated cytotoxic program was also upregulated in combination colitis versus healthy, although to a lesser extent (figure 7B, bottom right). T-cell subset frequency was not significantly different by CPI (figure 7C, bottom).

Other modules of genes were co-regulated across cell types in each form of CPI colitis. In general, IFN target genes including IFNGR1 and IFNGR2 were more upregulated in αCTLA-4 colitis, although unexpectedly IFNG upregulation itself was seen in αPD-1 colitis in cycling and enteric neural cells (figure 7D, left). MHC class I expression in plasma cells and MHC class II expression in enteric neural cells were highest in αCTLA-4 colitis, while MHC class II upregulation in CD8T and cycling populations (likely from cycling T cells) were more pronounced in αPD-1 colitis (figure 7D, right). Overall, these findings point to distinct modules of myeloid-related inflammation, co-stimulation and antigen presentation from αPD-1/αCTLA-4 colitis, versus cytotoxic signaling and T-cell activation that drives αPD-1 colitis.

External validation underscores a conserved role for activated CD4 RM T cells and cDC dysregulation in CPI colitis across the steroid exposure spectrum

To understand what features of the CPI colitis tissue microenvironment are conserved regardless of steroid exposure, we validated our findings in a recently published scRNA-seq data set of CD45-sorted immune cells from patients with steroid-naïve melanoma with endoscopically confirmed CPI colitis on biopsies, or who received CPI but had no colitis on endoscopy.2 We adopted similar filtering and analytic workflows including annotation as we had applied to our own data (Methods, marker gene annotation online supplemental table S3). This reveals similar canonical immune types (figure 8A,B). Similar to our primarily steroid-experienced work, there was quantitative enrichment of cytotoxic CD8 T cells and macrophages, as well as depletion of cDC1, cDC2, and ILC3 cells which was not described in the original report (figure 8C). These changes in cell type frequency were only seen in CPI colitis and not merely with CPI treatment, suggesting these are shared features specific to the CPI colitis state (and not a treatment effect of CPI exposure alone), and are conserved regardless of cancer type or steroid exposure. The steroid-naïve data set does indicate more robust increases in cycling cells and depletion of plasma cells compared with our predominantly steroid-experienced samples. While CPI treatment alone does modulate many similar genes to CPI colitis, there is still a distinct gene expression program associated with the colitis state with a larger number of genes specifically upregulated in CPI colitis over CPI-treated patients without colitis (figure 8D,E, DEG lists in online supplemental table S11). Some of this program is driven by IFN signaling; as previously reported and as in our own data, the most frequently upregulated genes across populations are mostly IFN-related (figure 8F, also online supplemental figure S9A), although of note, FKBP5 is not frequently upregulated in this validation data set, consistent with its lack of induction in these steroid-naïve patients. Strikingly, many of the other co-regulated genes in both CPI treatment and CPI colitis are similar in this steroid-naïve versus our mostly steroid-experienced data (figure 8G). These include: in CD8⁺ T cells, immune checkpoints such as CTLA4, LAG3, HAVCR2 (as described) plus ENTPD1 and the activation markers HLA-DRA and CD38; and in myeloid cells, inflammatory pathways such as the chemokines CXCL9 and CXCL10, IL1B, and S100A8 and S100A9 (also as described). Intriguingly, CD8⁺ T cells also downregulate TNF and anti-inflammatory ANXA1 as in the steroid-experienced data. In cDCs, WARS and IDO are again upregulated as in our data, validating a role for tryptophan metabolism across steroid exposure states. Altogether, this external validation argues for conserved cytotoxic and myeloid inflammatory states driven by IFN signaling between steroid-naïve and our predominantly steroid-experienced CPI colitis across cancer patients (many of whom are steroid-refractory), and also validates cDC/ILC3 depletion and altered tryptophan metabolism from our data as additional conserved CPI colitis hallmarks.

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Figure 8

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 |log₂(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 log₂(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 log₂(FC)>1) in both healthy versus CPI colitis and CPI only versus CPI colitis. (G) Overlapping DE genes (p<0.05 and log₂(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.

Identification of T-cell subsets based on subclustering (marker genes for annotation in online supplemental table S3) identifies similar tissue populations including cytotoxic, cycling, gd, and MAIT cells (figure 8H,I). Separate subclustering of CD8⁺ T cells further identifies an RM population that is CD69⁺ ITGAE⁺ ITGA1⁺, and within the CD4⁺ population further identifies a predominant RM population (“CD4T RM act”) that co-expresses the activation markers CD38 and HLA-DRA as in our data, with a separate population that does not express these markers and has mixed features of RM and memory cells (“CD4T RM-mem”) (figure 8I). Importantly, in addition to enrichment of GZMB⁺ CD8⁺ and cycling T cells, CPI colitis tissue also demonstrates a significant enrichment of the activated CD38⁺ HLA-DRA⁺ CD4⁺ RMs that is not an effect of CPI treatment alone (figure 8J). This is despite a lack of enrichment of CD8⁺ RMs, and a significant depletion in the non-activated CD4⁺ RM-memory population, as previously described. This argues that activated CD38⁺ HLA-DR⁺ CD4⁺ RMs, which we first described in the primarily steroid-experienced CPI colitis state, may be mobilized at a low level in CPI colitis prior to steroid exposure as well. As the disease spectrum shifts to steroid-experienced or refractory colitis, further activation of this subset may result in a quantitative enrichment and further generation of cytotoxic effectors as seen in our data.

A closer examination of co-regulated genes in prominent T-cell subpopulations reveals common versus distinct regulation of activated CD4⁺ RMs. Again, T-cell subpopulations demonstrate modules of genes that are co-regulated in CPI treatment and CPI colitis, as well as distinct genes specific to the CPI colitis state that are not seen with CPI exposure without colitis (figure 8K,L, online supplemental table S12). Comparing activated CD4⁺ RMs versus their CD8⁺ RM and cytotoxic CD8⁺ GZMB⁺ counterparts, common features upregulated in both CPI treatment and CPI colitis include marked overexpression of CD38 (in contrast to its less pronounced overexpression in our mostly steroid-experienced data), as well as chemokines such as CXCR6, immune checkpoints such as CTLA4 and ENTPD1, and activation markers such as MHC class II (figure 8M). At the same time, the activated CD4⁺ RMs are distinct in being less cytotoxic than their CD8⁺ counterparts, but also in their upregulation of PDCD1 (vs LAG3/HAVCR2 in CD8⁺), the distinct integrin ITGA2 (vs ITGB2 in CD8⁺ RM), and the distinct immune checkpoint TNFRSF25 (death receptor 3). These findings require validation but point to largely conserved cell-intrinsic functional programs in the T-cell compartment in steroid-naïve and steroid-experienced states, but also separate regulatory mechanisms of activated CD4⁺ RMs that may be useful for their identification and targeted treatment.