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. Author manuscript; available in PMC: 2026 Oct 25.
Published in final edited form as: Cell Rep. 2026 Sep 9;45(9):117969. doi: 10.1016/j.celrep.2026.117969

B cell-guided inflammatory cascade perpetuates ICI-mediated colitis

Naimah Turner 1,15, Synat Keam 1,15, Noha Abdel-Wahab 2,3,4,5,6,12,15, Jocelynn Colunga-Minutti 1,7, Caroline A Trejo 1, Fernanda G Kugeratski 1,8, Mauro Di Pilato 1,7, Juan M Sevillano Gutierrez 9, Cara Haymaker 7,10, Shabnam Shalapour 11, Adi Diab 3,4,5,13,14, Roza Nurieva 1,7,16,17,*
PMCID: PMC13695358  NIHMSID: NIHMS2212231  PMID: 42721039

SUMMARY

Immune checkpoint inhibitor (ICI) therapy is often accompanied by inflammatory toxicities including ICI-colitis. Therapeutic options are limited because the mechanisms that predict its onset are unclear. We uncover a role for B cells in triggering the intestinal inflammatory cascade following ICIs. An increase in circulating B cells, particularly those with gut-homing markers, antigen-presenting capacity, and proinflammatory cytokine production, is found at the asymptomatic stage in both patients and mice that are susceptible to ICI-colitis. Furthermore, a lack of B cells at the asymptomatic stage abrogates ICI-colitis by reducing the number of pathogenic intestinal T cells in mice. We find that latent microbial dysbiosis may underlie the B cell dysfunction in the asymptomatic stage that predisposes mice to the development of colitis following ICI therapy. Thus, our study examines the immunologic evolution underlying ICI-colitis and proposes B cell dysregulation as a critical initiating factor in this process and a potential biomarker for toxicity risk.

In brief

Turner et al. show that alterations in circulating B cell number and function predict the development of ICI-colitis in mice and patients. Using a murine model of subclinical intestinal inflammation, the authors highlight a unique pathogenic role for B cells in ICI-colitis development preceding the hallmark proinflammatory T cell phenotypes.

Graphical Abstract

graphic file with name nihms-2212231-f0001.webp

INTRODUCTION

Immune checkpoint inhibitors (ICIs) reinvigorate T cell responses through the blockade of inhibitory immune checkpoints such as programmed death-1 (PD-1), its ligand (PD-L1), and/or cytotoxic T lymphocyte-associated protein-4 (CTLA-4).1 ICIs have demonstrated profound therapeutic success in many cancers; however, their use is severely limited by immune-related adverse events (irAEs) affecting approximately 40% of patients.2 ICI-colitis is one of the most common irAEs (8%–27%) that often requires ICI discontinuation and immunosuppressants, such as corticosteroids, as first-line therapy, which may negatively impact anti-tumor responses.3,4 ICI regimens containing CTLA-4 targeting agents, either as monotherapy or in combination with PD-1 or PD-L1 blockade, are associated with a higher incidence and severity of colitis-irAE.4 Common symptoms involved with ICI-colitis include diarrhea (92%–100%), abdominal pain (55%–82%), and hematochezia (55%–64%).1

Patient studies have implicated type 1 and 17 immune responses in driving ICI-colitis. Increased numbers of CD4+ and CD8+ T cells, as well as enhanced levels of interferon gamma (IFN-γ), interleukin (IL)-17A, tumor necrosis factor (TNF), and IL-6 within the colon tissues are reported as a hallmark of ICI-colitis.5–7 Additionally, ICI-colitis is associated with an enrichment of T cells expressing integrin alpha E (ITGAE) and integrin alpha 4 (ITGA4), which encode subunits of intestinal integrins involved in T cell trafficking and retention in the colon.6 ICI-colitis is also marked by myeloid cells with inflammatory gene signatures, such as TNF and IFN-γ-inducible elements, which enhance the recruitment and activation of T cells to the colon.6 Furthermore, patients with irAEs have altered intestinal microbiota, which predicts the development of colitis-irAE.8,9 While clinical studies provide phenotypic characterization of colitis-irAE, limitations in sample collection make it difficult to uncover underlying mechanisms and biomarkers. Therefore, it is imperative to develop preclinical models that closely replicate the clinical setting to improve outcomes.

Recent efforts to develop preclinical models of colitis-irAE focus on replicating the cellular repertoire observed in patients at the time of toxicity but do not account for the immunologic events preceding its onset.10–12 There is a critical need to examine the onset and early stages of disease in order to gain a mechanistic understanding of the cellular and molecular drivers of ICI-colitis and identify patients at risk of toxicity. Here, using unique pre-ICI baseline samples of patients with cancer who did or did not develop colitis following ICIs, we find that dysregulated B cell responses predict the development of colitis-irAE. We utilize a murine model of subclinical intestinal inflammation that only becomes symptomatic following ICIs, which closely replicates the clinical setting and allows for longitudinal study of the immune response. We observe a previously unreported mechanism by which altered B cell activity initiates the inflammatory cascade preceding the hallmark T cell phenotypes observed in ICI-colitis.

RESULTS

Modeling of ICI-related intestinal inflammation in mice

Multiple studies demonstrate that patients with cancer who develop ICI-colitis have subclinical disease that rapidly becomes symptomatic upon ICI treatment.13 Therefore, we implemented a model of subclinical colitis that fully manifests only after ICI therapy. A total of 2.5% dextran sodium sulfate (DSS) was administered to C57BL/6 mice for 3 days to chemically induce latent inflammation that causes epithelial injury and microbiome alterations like those observed in patients with colitis-irAE.4,14–20 On days 3, 5, and 7, mice were intraperitoneally (i.p.) injected with isotype IgG control, anti-PD-1, anti-CTLA-4, or a combination of anti-PD-1 and anti-CTLA-4 (combo ICIs). As a positive control, we employed the classical model of DSS-colitis by administering 4% DSS for 5 days without additional treatment (Figure 1A). Mice treated with isotype IgG control did not develop clinical signs of colitis such as weight loss, shortened colon lengths, diarrhea, or hematochezia. Conversely, mice treated with anti-CTLA-4 or combo ICIs experienced significant loss of body weight, decrease in colon length, severe diarrhea, and hematochezia (Figures 1B–1D; Figure S1A). Furthermore, greater histological damage was observed in mice treated with anti-CTLA-4 or combo ICIs than in other groups, with the highest severity with combo ICIs (Figures 1E and 1F). Symptoms were comparable between the combo ICIs and classic colitis groups, indicating that combo ICIs were sufficient to induce severe colitis in asymptomatic mice primed with a low dose of DSS. Notably, mice treated with anti-PD-1 monotherapy developed milder disease, as is also observed in patient studies.4 These findings collectively demonstrate that our model efficiently induces subclinical colonic inflammation that only becomes symptomatic after ICI administration.

Figure 1. ICI-colitis in mice is associated with expansion of colonic T and B cells.

Figure 1.

(A) C57BL/6 mice were treated with 2.5% DSS dissolved in drinking water for 3 days followed by three injections of ICI(s) or isotype IgG on days 0, 2, and 4, following cessation of DSS (n = 8 per group).

(B) Percent change in baseline body weight.

(C) Colon length in millimeters.

(D) Disease activity index (DAI) score.

(E and F) Histology scoring with representative H&E-stained colon sections. Scale bars: 110 μm.

(G) Relative fraction of colonic immune cell populations as a proportion of CD45.2+ cells.

(H) Frequency of T and B cells as percent of live cells in colons.

(I) Relative fraction of mLN cell populations as a proportion of CD45.2+ cells.

(J) Frequency of T and B cells as a fraction of live cells in mLNs. Experiments were repeated three times with similar results.

Mean ± SEM; one-way ANOVA tests with Bonferroni correction. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

ICI-induced colitis is associated with the expansion of colonic T and B cells

In patients, ICI-colitis is marked by an increase in CD4+ and CD8+ T cells in colonic tissues with type 1 and 17 effector characteristics.6,21 We profiled the immune cell repertoire in the colon and mesenteric lymph nodes (mLNs) of healthy, isotype IgG control, ICI monotherapy, and combo ICI groups and detected a significant expansion of CD4+ T, CD8+ T, and B cells in the colons of the combo ICI-treated mice compared to healthy and isotype IgG control (Figures 1G and 1H; Figures S1B–S1D, S2A, and S2B). The elevated number of colonic T and B cells was comparable between the combo ICI and the classical colitis groups (Figures 1G and 1H). No differences were observed in the frequencies of the analyzed innate cell subsets (natural killer [NK] cells, macrophages [Mϕs], neutrophils, and dendritic cells [DCs]) or Foxp3+ T regulatory (Treg) cells22 with mono and combo ICI therapies (Figure 1G; Figures S1D, S1F, and S2A).

Immune profiling in the mLNs revealed a similar increase in cellularity with combo ICIs (Figure S1C), with no significant alterations in the number of Mϕs (Figure S1E). However, anti-CTLA-4 elicited an expansion of NK cells and DCs compared to IgG isotype control treatment. Furthermore, anti-CTLA-4 monotherapy and combo ICIs induced an expansion of neutrophils in the mLNs compared to healthy, isotype IgG-treated, and anti-PD-1 monotherapy groups (Figure S1E). Although alterations in the composition of the innate compartment were observed in mLNs, the most striking changes occurred in adaptive immunity (Figure 1I). In contrast to the increased colonic CD4+ and CD8+ T cells in ICI-treated mice, there was a corresponding decline in these subsets in the mLNs, suggesting preferential retention of T cells within the colon post-ICI therapy (Figure 1J). Alternatively, like in the colon, we observed a significant increase in the number of B cells and no differences in the number of Treg cells within mLNs of combo ICI-treated mice (Figures 1J and S1F). Additionally, we found that ICI therapy did not significantly alter the expression of PD-1 or CTLA-4 in the colonic or mLN CD4+ T, CD8+ T, or B cells of DSS-treated mice (Figures S1G–S1L). Since the strongest clinical and immunologic phenotypes were observed with combo ICIs, this treatment was employed for subsequent mechanistic studies.

Type 1 and 17 cytokines contribute to ICI-colitis pathogenesis

We next validated if colonic T cells have similar cytokine profiles to those seen in patients with colitis-irAE. To address this, unbiased clustering was performed on colonic CD3+ T cells of combo ICI- or isotype IgG control-treated mice (Figures S3A–S3C). We identified five clusters based on their expression of PD-1 and the cytokines IFN-γ, TNF-α, IL-17A, granzyme B, and granulocyte-macrophage colony-stimulating factor (GM-CSF). Notably, cluster 4, consisting of T cells enriched in PD-1, IFN-γ, TNF-α, IL-17A, and GM-CSF, was overrepresented in the colons of ICI-treated mice (Figures S3A–S3C). Quantitatively, IL-17A+ and IFN-γ+ CD8+ T cells were significantly enriched in the colons and mLNs of ICI-colitis mice compared to healthy or isotype IgG controls (Figures 2A–2D; Figures S3D and S3E). Also, IL-17A+, IFN-γ+, and TNF-α+ CD4+ T cells were enhanced in the colons of ICI-treated mice compared to controls, and these proinflammatory cytokine-producing CD8+ and CD4+ T cells were correlated with increased colitis severity score and decreased colon length by principal component analysis (PCA) (Figures 2A and 2B). These data demonstrate that our model not only recapitulates the clinical phenotype but also the proinflammatory T cell cytokine signatures observed in patients.

Figure 2. ICI-colitis severity is associated with type 1 and 17 cytokines.

Figure 2.

(A) IL-17A, IFN-γ, and TNF-α expression in colonic T cells from healthy mice and DSS-primed mice with or without combo ICIs (n = 5 per group).

(B) Principal component analysis (PCA) biplot of colonic cytokine-expressing T cells correlated with colon length and colitis severity with the ten most contributing loadings as determined by flow cytometry.

(C) IL-17A, IFN-γ, and TNF-α expression by mLN T cells (n = 5 per group).

(D) PCA biplot of mLN cytokine-expressing T cells correlated with colon length and colitis severity with the ten most contributing loadings.

(E) Experimental scheme. Blocking mAbs targeting IL-17A, IFN-γ, and TNF-α were administered on days −1, 1, 3, and 4 after DSS cessation in tandem with combination ICIs on days 0, 2, and 4 (n = 8 per group).

(F) Percent change in baseline body weight.

(G) DAI score.

(H) Colon length in millimeters.

(I) Histological damage scoring (n = 5 per group).Experiments were repeated three times with similar results.

Mean ± SEM; ANOVA tests with Tukey post hoc or Bonferroni correction for multiple comparisons. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Furthermore, blockade of IL-17A, IFN-γ, or TNF-α prior to ICI administration deterred clinical development of colitis compared to untreated mice (Figures 2E–2I; Figure S3F). Additionally, we targeted other cytokines involved in promoting Th17 cell differentiation (IL-6, IL-1β, or IL-23).23 Blockade of IL-6 and IL-1β, but not IL-23, was sufficient to improve body weight and colon length in ICI-treated mice; however, they did not significantly improve the histological score. Interestingly, IL-23 blockade was the only condition to significantly reduce histological damage within the colon (Figures S3G–S3K). Blockade of these proinflammatory cytokines underscores the clinical relevance of this model.

The role of B cells in ICI-colitis development through supporting proinflammatory T cells

While the involvement of T cells in the pathology of ICI-colitis has been extensively studied, the role of B cells is not yet fully understood. B cells express both CTLA-4 and PD-1, and ICIs lead to an increase in the number and function of circulating B cells in patients with irAE.24,25 We observed a pronounced increase in B cells in the colons and mLNs of ICI-colitis mice and profiled their expression of immunoglobulins (Igs) and cytokines. The overall increase in B cell numbers was attributable to the increased total amount of B cells within the colons and mLNs of colitis-irAE mice rather than an expansion of a specific subset (Figures S4A and S2B). While there were no significant differences in IgG1 and IgA expression levels within colonic plasma cells between groups, both colonic and mLN B cells from the combo ICI group had significantly higher levels of IL-17A expression compared to healthy mice (Figures 3A and 3B; Figure S4B). In addition, no significant differences were noted in IL-10, IL-12p40, TNF-α, TGF-β, or IL-35 in mLN and colonic B cells, but there was a slight decrease in IL-6+ B cells in the mLNs of ICI-treated mice compared to healthy mice (Figures 3A and 3B; Figures S4C and S2B).

Figure 3. Cytokine-producing B cells contribute to ICI-colitis by supporting proinflammatory T cells.

Figure 3.

(A) Percent of colonic B cells expressing IL-17A and IL-6, and plasma cells expressing IgG1 and IgA from healthy mice and DSS-primed mice with or without combo ICIs (n = 5 per group).

(B) Percent of mLN B cells expressing IL-17A and IL-6, and plasma cells expressing IgG1 and IgA from healthy mice and DSS-primed mice with or without combo ICIs (n = 5 per group).

(C) Experimental scheme. Blocking mAbs targeting CD19, B220, and CD22 were administered on days −1, 1, 3, and 4 after DSS cessation in tandem with combination ICIs on days 0, 2, and 4 (n = 10 per group).

(D) Percent change in baseline body weight.

(E) DAI score.

(F) Colon length in millimeters.

(G) Histological damage scoring (n = 5 per group).

(H) Representative H&E-stained colon sections of ICI-treated mice with and without B cell depletion. Scale bars: 110 μm.

(I and J) Number of colonic T cells averaged per mm of colon with percent of cells expressing IL-17A, IFN-γ, and TNF-α (n = 5 per group). Experiments were repeated three times with similar results.

Mean ± SEM; ANOVA tests with Tukey post hoc or Bonferroni correction for multiple comparisons. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

We further validated the B cell contribution to ICI-colitis and found that B cell depletion prior to ICI administration significantly decreased all clinical signs of colitis after ICI treatment (Figures 3C–3H). Lack of B cells was associated with a significant reduction of IL-17A, IFN-γ, and TNF-α in CD8+ T cells and a decrease of IFN-γ in colonic CD4+ T cells (Figures 3I and 3J). While B cell depletion did not change the expression of these cytokines in mLN T cells, it significantly enhanced the proportion of CD4+ and CD8+ T cells compared to that in colitis-irAE mice, which is likely a reflection of B cell depletion (Figures S4D–S4F). Furthermore, we found that B cell depletion does not impact colitis development in the non-ICI-mediated classic colitis model (Figures S4G–S4J). Thus, these data highlight a unique pathogenic role for B cells in ICI-colitis development that differs from idiopathic inflammatory bowel disease (IBD), which may be mediated through the regulation of the number and function of T cells.

Reciprocal regulation between B cells and proinflammatory CD8+ T cells

Observing dampened CD8+ T cell responses upon B cell depletion, we sought to determine if there is a reciprocal crosstalk between CD8+ T cells and B cells. We depleted CD8+ T cells and observed a rescue of ICI-colitis development (Figures S5A–S5F). While CD8+ T cell depletion dramatically decreased the number of colonic B cells in ICI-treated mice, there was only a modest decrease in IL-17A and IL-6 and an enhanced IL-12p40 expression in B cells (Figure S5G). Moreover, CD8+ T cell depletion led to a slight decrease in the number of CD4+ T cells as well as reduced IL-17A and TNF-α expression in the colon (Figure S5H). Additionally, there were no differences in the proportion of B cells or their functional status in the mLNs of ICI-colitis mice and those treated with anti-CD8 monoclonal antibodies (mAbs) (Figure S5I). Although there was profound enhancement in the proportion of CD4+ T cells in the mLN of CD8-depleted mice, this is likely a reflection of the loss of the CD8+ T cells (Figures S5J and S5K). Collectively, these data indicate that there is reciprocal regulation between CD8+ T cells and B cells in which B cells contribute to the proinflammatory nature of CD8+ T cells, while those cells influence subsequent B cell recruitment/retention. This process may form a feedback loop to not only encourage but also perpetuate inflammation in ICI-colitis.

Proinflammatory B and T cell responses are consequences of intestinal dysbiosis

Previous studies have demonstrated that ICI-colitis is marked by intestinal microbiota dysbiosis and that baseline microbial composition can be predictive of colitis development.8,9 Thus, to determine if dysbiosis marks and/or is associated with colitis development, we performed 16S rRNA sequencing on fecal samples collected prior to any treatment, after 3 days of DSS, and following two doses of combo ICIs (Figures 4A–4C). While there were no significant differences in alpha diversity, the beta diversities of each group were distinct, suggesting that alterations in the composition of the microbiota occur both prior to and after ICI administration (Figures 4A and 4B). These compositional differences were characterized by a significant decrease in the abundance of Firmicutes in ICI-treated mice with a concomitant increased relative abundance of the Verrucomicrobiota phylum (Figures S6A and S6B). Regardless of ICI administration, colitis-susceptible mice displayed a trend toward decreased Desulfobacterota and Actinobacteriota phyla when compared to untreated mice. Furthermore, LefSe (Linear discriminant analysis Effect Size) analysis identified a cohort of differentially abundant microbes. Of interest, ICI-colitis mice were enriched in Akkermansia, the only constituent of the Verrucomicrobiota phylum in this dataset, and depleted in Negativibaciilus when compared to either control. Further, both colitis-susceptible groups prior to and after ICI displayed a depletion of Prevotellaceae and Roseburia compared to healthy controls (Figure 4C; Figures S6A and S6B). These findings indicate that mice susceptible to colitis have a perturbed microbiota composition, which is further altered by ICI use, as observed in patient studies.

Figure 4. Microbiota dysbiosis instigates proinflammatory T and B cell responses.

Figure 4.

(A–C) (A) Inverse Simpson Index, (B) PCA plot of Bray-Curtis dissimilarity, and (C) LefSe analysis of 16S rRNA sequencing of fecal samples from healthy mice, after 3 days of DSS, and after two doses of combo ICIs (n = 4–5 per group).

(D) Experimental scheme of ICI-colitis and FMT administration (n = 10 per group).

(E) DAI score.

(F) Colon length in millimeters.

(G) Histological damage scoring.

(H–J) Number of colon B and T cells averaged per mm of colon with percent of cells expressing IL-6, IL12p40, IL-17A, IFN-γ, or TNF-α. Experiments were repeated three times with similar results.

Mean ± SEM; ANOVA tests with Tukey post hoc or Bonferroni correction for multiple comparisons. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Next, to assess the impact of dysbiosis at the early (pre-ICI) stage on the onset of ICI-colitis, we administered fecal microbial transplant (FMT) from healthy mice to DSS-primed mice to bolster eubiotic microbiota and subsequently treated the mice with ICIs (Figure 4D). While FMT had no impact on body weight, we observed significant improvement in disease activity scores, colon lengths, and histological scores compared to untreated mice (Figures 4E–4G; Figures S6C and S6D). Clinical improvement was accompanied by reductions in the number of B and T cells within the colon (Figures 4H–4J). Functionally, FMT reduced IL-17A- and IL-6-expressing B cells but did not change IL-12p40 expression (Figure 4H). Additionally, FMT profoundly reduced the expression of IL-17A and IFN-γ in both CD4+ and CD8+ T cells as well as reduced TNF-α expression in CD4+ T cells (Figures 4I and 4J). Although there were no alterations in the functional profile of mLN T and B cells in FMT mice, there was a minor reduction in IL-17A and IL-12p40 expression by B cells as well as IL-17A expression by CD8+ T cells (Figure S6E). Collectively, these data suggest that latent intestinal injury and microbiota perturbations may be initiating factors in ICI-colitis, which instigates expansion of proinflammatory B and T cells, as maintenance of a healthy microbiome deters this pathology.

ICI-driven colonic inflammation is preceded by alterations in B cell number and function

To gain mechanistic insight into the pathogenesis of ICI-colitis, we next assessed how the immune response develops over time in different tissues, including peripheral blood (PB), mLNs, and the colon (Figure 5A). Notably, the proportion of circulating B cells was enhanced pre-ICI (colitis-susceptible mice), prior to any clinical signs of colitis development, and significantly reduced following ICI treatment (Figure 5B). In contrast, the number of colonic and mLN B cells increased only after ICI administration (Figure 5B). In PB, the proportions of both CD8+ and CD4+ T cells significantly increased only after two ICI doses, while mLN proportions were profoundly decreased (Figures 5C and 5D). On the other hand, colonic proportions of CD8+ and CD4+ T cells began to show enhancements in the pre-ICI condition but were not yet significantly enriched following two doses of combo ICIs (Figures 5C and 5D). Importantly, colonic tissues only become enriched with IL-17A and IFN-γ producing CD4+ and CD8+ T cells after ICI administration, which coordinates with a deficit of these cells in the PB (Figure S7A).

Figure 5. Alterations in circulating B cells precede ICI-colitis.

Figure 5.

(A) Experimental scheme on ICI-colitis induction and tissue collection (n = 5 per group).

(B–D) Proportion of B and T cells in PB, mLNs, and colons out of CD45.2+ cells in healthy mice and colitis-susceptible mice prior to and following 2 doses of combo ICIs.

(E–G) Normalized heatmap of number of B cells (as % of live cells) expressing various molecules in mLNs, colons, and PB of colitis-susceptible mice prior to and after 2 or 3 doses of combo ICIs.

(H–K) Proportion of DCs and Mϕs in mLNs and colons out of CD45.2+ cells.

(L) Experimental scheme of ICI-colitis induction in mice pretreated with anti-CD19/anti-B220/anti-CD22 mAbs and tissue collection (n = 5 per group).

(M–O) Frequency of DC subsets as a fraction of live cells in colons and mLNs.

(P) Normalized heatmap of median fluorescent intensity (MFI) of marker expression by mLN DC subsets following combo ICIs with and without B cell blockade.

(Q and R) PCA biplot of markers expressed by T cells from colons and mLNs of mice following combo ICIs with and without B cell blockade with the nine most contributing loadings. Experiments were repeated three times with similar results.

Mean ± SEM; ANOVA tests with Tukey post hoc. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

An enhanced number of circulating B cells was one of the early events that was observed in colitis-susceptible mice (prior to ICIs), and further phenotypic characterization of B cells revealed distinct shifts in their functional status across the PB, mLNs, and the colon with colitis development (Figures 5E–5G). Prior to ICIs, colitis-susceptible mice had a greater number of circulating B cells expressing major histocompatibility complex (MHC) I/II, costimulatory molecules (CD80, CD86, CD40, and ICOSL), and the gut-homing receptor (CCR9), which all decreased with ICIs (Figures 5E–5G). This efflux of activated B cells from PB aligns with an increased number of B cells expressing gut-directing/retention markers (CCR9, LPAM-1, and CD103) and cytokines (IL-17A, IL-12p40, and IL-6) within the colon after ICIs. Additionally, after ICIs, there was an increase in the number of colonic CXCR4+ and CXCR5+ B cells as well as a decrease in the number of B cells expressing T cell immunoglobulin and mucin domain 1 (TIM-1), an immune checkpoint for B cells (Figures 5E–5G).26 Altogether, these data suggest that B cells with antigen-presenting capabilities may mobilize early because of latent colon injury or inflammation and influence the number and function of T cells.

In addition to B cells, DCs and Mϕs are other antigen-presenting cells (APCs) that respond to the gut microbiota, maintain barrier integrity, and can prime adaptive immune responses.27 Disruptions in the homeostatic functions of these cells have been implicated in driving ICI-colitis.12 While we did not see a difference in the number of conventional DCs and Mϕs either pre-ICI, with the exception of DC2 in the colon, or 5 days after combo ICIs (Figures 5H–5K; Figures S1D, S1E, S2, and S7B), the proportions of colonic DC1 and DC2 were significantly enhanced 3 days post-ICIs when compared to untreated mice (Figures 5H and 5I). In addition, we observed a significant increase in the proportion of DCs expressing CCR7, a chemokine involved in the mobilization of DCs to lymphoid tissues, in both the colon and mLNs post-ICIs (Figures 5J and S7B). Conversely, we observed a decrease in the proportion of Mϕs in both the colon and mLNs (Figure 5K). Thus, the DC number and tissue localization are mainly altered post-ICIs.

Dysregulated B cell responses to intestinal injury are key to incite proinflammatory DC and T cell activity

Given the early alterations in the number and function of circulating B cells prior to ICIs, we further examined the mechanism by which B cells contribute to the tissue-specific immune environment pre- and post-ICIs (Figure 5L). With B cell depletion prior to establishing subclinical inflammation, the number of mLN DCs significantly increased both pre- and post-ICIs compared to untreated mice (Figures 5M–5O). Within the colon, there was a significant reduction in CCR7+ DCs and minimal changes in DC1 and DC2 post-ICIs (Figures 5M–5O). Functionally, without B cells, the expanded DCs in the mLNs displayed a more immunoregulatory phenotype after ICIs with enhanced expression of CD83 and CD200 across subsets and a decrease in IL-12p40 in DC2 (Figure 5P).28–33 In contrast, there were no significant alterations in the functional status of colonic DCs except a decrease in IL-6 and IL-12p40 expression in CCR7+ DCs (Figure S7C). Collectively, these findings suggest that DC migratory/retention patterns and activation status during ICI-colitis rely on B cells.

Next, we evaluated the tissue distribution and activity of T cells in ICI-colitis mice lacking B cells over time. While there were no significant alterations in the number or functional status of colonic CD4+ T cells upon B cell depletion, the CD8+ T cells had significant reductions in the expression of IFN-γ, IL-17A, and TNF-α in the absence of B cells (Figures S7D–S7G). Additionally, mLN CD4+ and CD8+ T cell numbers were increased in both pre- and post-ICI conditions upon B cell depletion (Figures S7H and S7I). CD8+ T cells had increased IL-17A, and both CD4+ and CD8+ T cells had decreased TNF-α expression within mLNs (Figures S7J and S7K). On the other hand, there were no differences in Treg numbers in the colons or mLNs with B cell depletion (Figure S7L). Furthermore, after ICIs, we observed an accumulation of CD8+ and CD4+ T cells expressing α4β7 (LPAM-1) integrin and CCR9 in the mLNs of B cell-depleted mice (Figures 5Q and 5R). Both α4β7 (LPAM-1) integrin and CCR9 are essential to the homing of activated lymphocytes to the intestine through interactions with mucosal addressin cell adhesion molecule 1 (MAdCAM-1) expressed on endothelial venules and the chemokine CCL25, respectively.34–36 This finding suggests that, during colitis development, the functional capacity and migratory patterns of DCs and T cells are reliant on B cell activation status and provides insight into the mechanism by which B cell targeting deters the development of ICI-mediated colitis (Figure S7M).

Increase in circulating B cell number is associated with subsequent ICI-colitis development in patients with cancer

Current mechanistic understanding of ICI-colitis has been derived from single-cell RNA analyses with samples collected from patients at or after the onset of toxicity.6,21,37 These samples are often collected after immunosuppressive therapies, which may mask cellular drivers of disease. Thus, baseline samples obtained from patients with cancer prior to the administration of ICIs are imperative to identify candidate cellular and molecular biomarkers of ICI-colitis risk and to inform prophylactic and therapeutic strategies. Here, we analyzed baseline peripheral blood mononuclear cells (PBMCs) from a pilot cohort of 10 patients with melanoma. The median age was 59.5 years (range 41–78), 90% were male, and 90% had stage III/IV cutaneous melanoma (according to the American Joint Committee on Cancer Version 8 staging system). Six patients (60%) subsequently received combination ICIs and four (40%) received single-agent anti-PD-1, with varying intervals between PBMC collection and ICI initiation across patients (Figure 6A; Table S1). Following ICIs, 4 patients (40%) developed grade 3 ICI-colitis per the Common Terminology Criteria for Adverse Events (CTCAE) guidelines (all 4 occurred in the combo-ICI group), whereas six did not develop any irAE through the last available follow-up. Flow cytometric analysis revealed that patients who developed ICI-colitis had a higher proportion of circulating B cells at baseline compared to those who did not develop any irAE (Figures 6B and 6C; Figure S8). Additionally, the circulating B cells between these two groups were phenotypically distinct. In the ICI-colitis group, there was an increased number of B cells expressing the gut-homing molecules CCR9 and LPAM-1, costimulatory molecules such as CD80 and CD86, as well as the cytokines IL-17A, TNF-α, IL-6, and IL-10 when compared to the non-irAE group (Figures 6D and 6E; Figure S8). Notably, these baseline human findings were consistent with the pre-ICI stage of our mouse model, in which colitis-susceptible mice similarly showed expansion of circulating B cells expressing gut-homing features and an activated/APC-like phenotype compared to controls. Collectively, these human data, together with our mechanistic mouse studies, support the hypothesis that the abundance and functional status of circulating B cells prior to ICI exposure are associated with subsequent ICI-colitis risk. Larger prospective cohorts stratified by ICI regimen and by timing of baseline sampling are needed to validate B cell-based biomarkers and to define their predictive performance.

Figure 6. Circulating B cell number predicts ICI-colitis development in patients with cancer.

Figure 6.

(A) Baseline PBMC samples were collected from patients who did (n = 4) or did not (n = 6) develop colitis following ICI administration.

(B) Pie chart representing average relative fraction of each cell type within CD45+ cell population in baseline PBMC samples as determined by flow cytometry.

(C) Representative histogram displaying count of CD19+ cells in baseline PBMC samples.

(D) Heatmap displaying various molecule expression in B cells as a relative fraction of CD45+ cells.

(E) Representative flow cytometry dot plot of LPAM-1 expression in baseline PBMC B cells from indicated patients.

Mean ± SEM; multiple t tests. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

B cells play a role in immune cell homing to the colon during ICI-colitis

Immune cell trafficking to the gut has been shown to be a critical component in ICI-colitis pathogenesis, especially by the α4β7 integrin/MAdCAM-1 mechanism.6,29,38 To validate that α4β7 integrin-mediated trafficking is essential to the development of ICI-colitis in our model, we administered α4β7-blocking mAbs in conjunction with ICIs to impede homing of T and B cells to the colon (Figure S9A). While α4β7 integrin blockade did not deter weight loss, there was significant improvement in all other symptomatic assessments of treated mice (Figures S9B–S9F). These clinical improvements were due to a profound reduction in the number of B and T cells as well as their proinflammatory cytokine signatures (IL-17A, IFN-γ, and TNF-α) within the colon of anti-α4β7-treated mice compared to mice receiving ICIs alone (Figures S9G–S9I). Within the mLN of these mice, there were no alterations in the proportion and function of T or B cells (Figures S9J–S9L). These data collectively implicate α4β7-mediated gut homing of T and B cells as a contributor to colonic inflammation in the ICI setting.

To address the contribution of immune cell trafficking between lymphoid tissues and the colon in ICI-colitis, we adoptively transferred mLN cells from colitis-susceptible mice to naive (untreated) mice followed by isotype IgG control or combo ICI administration (Figure 7A). Unlike isotype IgG controls, treatment of recipient mice with ICIs was sufficient to induce clinical signs of ICI-colitis (Figures 7A–7E). Interestingly, anti-α4β7 treatment prior to cell transfer improved the colon lengths, cellularity, and histological score of ICI-treated mice compared to those who did not receive integrin blockade (Figures 7A–7E). Transferred T and B cells repopulated into the mLNs, with most recovered cells being T cells (Figure S9M). Although transferred cells constituted a small proportion of the overall immune cells within the colons and mLNs of recipient mice, they displayed unique trafficking dynamics based on the therapy administered (Figures 7F and 7G). Only mice receiving combination ICIs had equivalent proportions of transferred cells homing to the colon and mLNs. In contrast, cells transferred to recipient mice, which did not develop colitis, displayed a propensity to traffic to the mLNs. Notably, integrin blockade in conjunction with ICIs enhanced transferred cell trafficking to the heart in recipient mice, which was not observed in any other group (Figures 7F and 7G). Within recipient mice, we observed an increased number of T and B cells in colons of ICI-treated mice compared to the other groups; however, CD8+ T cells were the only subset to show significant elevation (Figure 7H). Further, mLNs of the ICI-treated mice had a significantly larger B cell population compared to other groups, while T cells tended to decrease with significant decreases in the number of CD4+ T cells (Figure 7H). Functionally, compared to the other groups, colon T and B cells of ICI-treated mice were enriched with IFN-γ+ CD4+ T and CD8+ T cells as well as IL-17A+ CD8+ T and B cells (Figure 7I). In addition, the mLNs of these mice were also enriched in IFN-γ+ CD4+ T and CD8+ T cells as well as IL-17A+ CD8+ T cells compared to the other groups (Figure 7I). Furthermore, cell transfer and ICI administration, with or without integrin blockade, led to an enhancement in the number of DCs and Mϕs within the mLN, compared to the transfer-alone and healthy groups (Figure S9N).

Figure 7. B cells play a role in immune cell migration to the colon.

Figure 7.

(A) Experimental scheme of adoptive transfer of fluorescently labeled mLN cells from colitis-susceptible mice to untreated, immunocompetent mice and subsequent ICI treatment (n = 5 per group).

(B) Colon length in millimeters.

(C) Number of live cells in the colon.

(D and E) Histological damage scoring with representative H&E-stained colon sections from indicated groups. Scale bars: 110 μm.

(F) Frequency of transferred cells as a fraction of CD45.2+ cells in colons and mLNs.

(G) Frequency of transferred cells as a fraction of CD45.2+ cells in colons, mLNs, hearts, and lungs.

(H) Frequency of B and T cells as a fraction of live cells in colons and mLNs.

(I) PCA biplot of markers expressed by B and T cells from colons and mLNs with the ten most contributing loadings.

(J) Experimental scheme of adoptive transfer of fluorescently labeled mLN cells from colitis-susceptible mice with or without B cell depletion to untreated, immunocompetent mice and subsequent ICI treatment (n = 5 per group).

(K) Colon length in millimeters.

(L) Number of live cells in the colon.

(M) Histological damage scoring.

(N) Frequency of transferred cells as a fraction of CD45.2+ cells in colons and mLNs of indicated groups.

(O) Percent of B and T cells expressing IFN-γ or IL-17A in colons of ICI-treated mice receiving adoptive transfer of intact or B cell-depleted mLN cells. Experiments were repeated three times with similar results.

Mean ± SEM; ANOVA tests and multiple t tests with Bonferroni correction. ns: no significance, *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

To further understand the role of B cells in the onset of ICI-colitis, we repeated the adoptive transfer with a set of donor mice in which B cells were depleted during DSS administration (Figure 7J). Mice that received B cell-depleted mLN cells and subsequent combo ICI treatment demonstrated longer colon length, decreased colon cellularity, and decreased histological damage compared to recipient mice receiving B cell-containing mLN cells (Figures 7K–7M). Additionally, mice receiving B cell-depleted mLN cell transfer had significantly less cells migrating to the colon after ICIs than recipients of undepleted donors, indicating that B cells may alter the migratory patterns of T cells in the ICI setting (Figure 7N). Furthermore, impediment of colitis was marked by reductions in IFN-γ expression by CD4+ and CD8+ T cells as well as IL-17A expression by CD8+ T and B cells within the colons of ICI-treated mice with B cell-deficient mLN cell transfer (Figure 7O). Overall, the aforementioned data indicate that trafficking of T and B cells is a critical step in colitis development and that lack of B cells impairs this process and reduces the proinflammatory status of T cells in the ICI setting.

DISCUSSION

Effective diagnosis and treatment strategies for ICI-colitis are lacking due to limited knowledge on the mechanisms underlying its onset.4,39,40 Thus, there is an unmet need for robust preclinical models and prospective studies to uncover both predictive biomarkers and mechanism-based therapeutics and prophylaxes.41,42 Here, using samples collected from a pilot cohort of patients susceptible to colitis and mice prior to ICIs, we detected that an increase in circulating B cells, particularly those with gut-homing markers, antigen-presenting capacity, and proinflammatory cytokine production, precedes the cascade of inflammatory immune responses and colitis onset following ICIs.

The role of B cells in both idiopathic IBD and ICI-colitis has been severely understudied. B cells have a myriad of functions such as antigen presentation, cytokine production, antibody secretion, and directing T cell migration, which can possibly contribute to the immune response associated with ICI-colitis.43–47 We find that dysregulated B cell responses are an early event in ICI-colitis development with enhancements in the number of circulating B cells preceding ICIs in both mice and patients with cancer, who develop ICI-colitis. These B cells are marked by gut-homing markers such as CCR9 and α4β7 as well as APC capacity as demonstrated by the expression of MHC I/II, costimulatory factors, and activation markers, which are required for priming T cells observed in the symptomatic stage. In fact, B cell depletion in colitis-susceptible mice leads to a significant reduction in colitis symptoms after ICIs due to a decreased activation state of T cells. Following ICIs, PB, colon, and mLNs are enriched with activated B cells producing proinflammatory cytokines and with reduced expression of the B cell immune checkpoint molecule TIM-1. Unlike ICI-colitis, B cell depletion does not have any effect on models of idiopathic colitis, suggesting distinct pathophysiology between diseases. Collectively, this study suggests a role for B cells in not only directly contributing to the cytotoxicity observed in ICI-colitis but also as a biomarker.

We also find that ICI-colitis in our model is dependent on immune cell migration and that blockade of α4β7 integrins impedes the development of ICI-colitis by impairing extravasation of both T and B cells into gut-associated tissues.48 Additionally, we find temporal shifts in the number of B cells expressing CCR9 with early prevalence in the PB followed by increases within the colon and mLNs after ICIs. This migration axis may be another mechanism by which B cells respond to predisposing insults and accumulate in the colon, which can inhibit mucosal healing and perpetuate proinflammatory cascades.49 In addition to their own migration to the site of inflammation, B cells may influence the trafficking patterns of other immune cells in ICI-colitis through the production of various chemokines and peptides.43,50 In our work, B cell depletion led to the accumulation of T cells expressing gut-homing markers such as CCR9 and α4β7 integrins within the mLN rather than within the colon. Furthermore, the transfer of DSS-primed mLN cells from B cell-depleted mice and subsequent ICI treatment did not induce colitis, while transfer from intact mice did. Collectively, these findings suggest that B cells are involved in the migratory patterns of these cells and consequently contribute to colitis development.

The human gut is a unique environment with constant exposure to dietary and microbial antigens. The intestinal microbiota has been well established in shaping local and systemic immunity, especially in the setting of cancer, ICIs, and irAEs.10,51–53 Immune cells respond to changes in the microbiome, and DCs and B cells are pivotal first responders that coordinate the subsequent immune response.54–56 Many microbes have been shown to lead to a loss of tolerance in B cells and DCs, overstimulate T helper cell responses, and dampen Treg cell function and number.56,57 In our study, colitis-susceptible mice are marked by dysbiosis and simultaneously show alterations in circulating B cell number and activity, suggesting that dysbiosis-induced hyperactivity of B cells drives aberrant T cell responses leading to symptomatic colitis. Manipulation of the microbiota via FMT is being explored for cancer treatment and for mitigation of ICI-mediated diarrhea and colitis, particularly in refractory cases.58,59 In our model, FMT from healthy mouse donors mitigates the development of ICI-colitis and significantly reduces B and T cell numbers as well as their proinflammatory cytokine signatures.

It is critical to pair the mouse study with human biospecimens collected prior to ICI exposure. The early activity of B cells makes them a promising candidate for biomarker or prophylactic exploration. However, contemporary studies of ICI-colitis analyze samples collected at or after the onset of toxicity and are often collected following systemic immunosuppressants.6,60–63 Thus, the activity of B cells may be masked in current studies. To our knowledge, ours is the first study to examine the full baseline PBMC profile of patients susceptible to colitis. We find that patients who go on to develop ICI-colitis have an altered PBMC B cell profile compared to those who do not develop toxicity. These findings provide translational support for the pre-ICI signature observed in our mouse model; however, a larger prospective cohort with standardized baseline sampling and regimen-balanced designs will be required to validate these observations and define predictive performance. To further understand the mechanism of how ICI-colitis arises, it is pertinent to study sequential pre- and post-ICI samples from the same patients who either develop ICI-induced toxicities or tolerate treatment.22 Understanding all players involved, even those that are transient, is critical for the early diagnosis of patients prone to toxicities, as well as the development of effective therapies.

In summary, we uncover a role for B cells in initiating and amplifying ICI-mediated colitis pathology in our mouse model. We observe altered B cell number and activity in mice and a pilot cohort of patients with cancer at the asymptomatic stage, which is associated with colitis development after ICI administration. In mice, we observe altered B cell migration and functionality along with changes in intestinal DCs, which precede the hallmark proinflammatory phenotypes in T cells. Knowledge gained through understanding the kinetic progression of crosstalk between immunity and external factors, such as the microbiome, is instrumental for the development of approaches for diagnosis and treatment of adverse events.

Limitations of the study

This study has potential limitations. Firstly, our findings need to be further validated with expanded patient studies. The human data in this study are exploratory and extremely limited, reflecting a small pilot cohort with clinical heterogeneity, including variability in the interval between baseline PBMC collection and ICI initiation and imbalance in treatment regimen between groups. Therefore, these data should be interpreted as hypothesis-generating rather than establishing biomarker performance. These findings will be further validated in an ongoing investigator-initiated study (NCT04990726) expanding these analyses in larger, regimen-stratified cohorts using paired standardized pre-ICI and early on-treatment post-ICI samples collected prior to colitis onset, with appropriately matched controls. Furthermore, our mouse model findings need to be corroborated using a syngeneic tumor model to understand the contributions of cancer to ICI-colitis development as our preclinical experiments were performed in non-tumor-bearing mice. Lastly, this work primarily utilizes flow cytometry-based methods that can limit the available information, which needs to be further refined using higher throughput methods (e.g., single-cell transcriptomic/proteomic and spatial profiling) to elucidate cellular states and dynamic interactions across various colonic niches.

RESOURCE AVAILABILITY

Lead contact

Requests for further information and resources should be directed to the lead contact, Roza Nurieva (rnurieva@mdanderson.org).

Materials availability

This study did not generate new, unique reagents.

Data and code availability

  • The 16S rRNA-seq data have been deposited at the NCBI Sequence Read Archive (accession number PRJNA1498150) and are publicly available as of the date of publication.

  • This paper does not report original code.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

STAR★METHODS

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Mice

Male C57BL/6 mice (8–10 weeks of age) were purchased from Charles River-Frederick NCI (strain number 556). All mice were housed in specific pathogen free animal facilities, and all animal experiments were performed according to the protocols approved by the Institutional Animal Care and Use Committee of the University of Texas MD Anderson Cancer Center. The influence of sex on experimental outcomes was not evaluated in this study.

Patients and collection of blood samples

This study was approved by the institutional review board at the University of Texas MD Anderson Cancer Center (IRB No: 2019–0390; PA19–0089). Prior to the venipuncture, participants provided written informed consent, allowing collection of peripheral blood (PB) samples. We collected baseline PB samples from 10 patients (9 males and one female) prior to ICI therapy and divided samples into ICI-colitis and ICI-control cohorts based on subsequent development of colitis (N = 4) or not (N = 6), respectively (Table S1). The patients met the Common Terminology Criteria for Adverse Events (CTCAE) diagnostic criteria for colitis with a maximum grade of 3 for all patients.4 For PB samples, the plasma was isolated after centrifugation at 500g for 10 min. Peripheral blood mononuclear cells (PBMCs) were isolated with the FiColl gradient technique (Sigma Aldrich, catalog GE17–1440-02) and cryopreserved in a mixture of 90% heat inactivated Fetal Bovine Serum (FBS) (Gibco, catalog: A52095–01) and 10% dimethyl sulfoxide (Sigma-Aldrich, catalog; D2650).

METHOD DETAILS

ICI-colitis model

Mice were supplied with 2.5% Dextran Sulfate Sodium (DSS; MP Biomedicals, catalog: 160110) dissolved in sterile drinking water for three days and then switched to regular drinking water. Upon supply with water, mice were intraperitoneally injected with 200μg each of anti-PD-1 mAb (clone RMP1–14, Bio X cell and Leinco Technologies), anti-CTLA-4 mAb (clone 9H10, BioXCell and Leinco Technologies), their combination, or isotype IgG (100μg/mouse, polyclonal, BioXcell) every two days, as indicated in Figure 1A. Classic colitis models were supplied with 4% DSS dissolved in sterile drinking water for five days and then switched to regular drinking water with no subsequent treatment. Mice were monitored daily for Disease Activity Index (DAI) scoring on a scale of 0–4 based on the severity of percent weight lost compared to baseline (0: None; 1: 1–10%; 2: 11–15%; 3: 16–19%, 4: 20%), stool consistency (0: Normal; 1: Soft Stool; 2: Loose stool; 3: Diarrhea; 4: Severe Diarrhea), and presence of hematochezia (0: Absence; 4: Presence).64 DAI scores are presented as the mean ± SEM of the sum of these items per individual mouse.

In indicated experiments, mice were intraperitoneally injected with 200μg of each anti-IL-17 mAb (clone 17F3, BioXCell), anti-IFNγ mAb (clone XMG1.2, BioXCell), anti-TNFα mAb (clone XT3.11, BioXCell), anti-IL-6 mAb (clone MP5–20F3, BioXCell), anti-IL-1β mAb (clone B122, BioXCell), anti-IL-23 mAb (clone G23–8, BioXCell), anti-CD19 mAb (clone 1D3, BioXCell and Leinco Technologies), anti-B220 mAb (clone RA3.3A1/6.1 (TIB-146), BioXCell and Leinco Technologies), anti-CD22 mAb, (clone Cy34.1, BioXCell and Leinco Technologies), or anti-α4β7 mAb (clone DATK32, BioXCell) at the indicated schedule.

In fecal microbiome transfer experiments, fecal samples were collected from untreated C57BL/6 mice, suspended in cold phosphate buffered saline (PBS; Cytiva, catalog: SH30256.01) to a concentration of 100 mg/mL and homogenized. Homogenized fecal suspension was centrifuged 2 times at 1000 g for 5 min at 4C to remove bulk debris. Supernatant was extracted and administered to indicated groups of mice (150 μL/per mouse) by oral gavage daily for seven days.

Transfer model of ICI-colitis

mLN cells were harvested from mice which received 2.5% DSS for three days, mashed into single cell suspensions, and resuspended in PBS supplemented with 2% FBS (Gibco, catalog: A52567–01). For cell labeling, Tag-it Violet (Biolegend, catalog: 425101) was diluted to 1 μM concentration directly into cell suspension, incubated for twenty minutes in 37C darkened water bath, then quenched with excess RPMI 1640 medium (Gibco, catalog: 11875–093) including 10% FBS. Labeled cells were washed twice with excess PBS. Five million cells in PBS were injected intravenously into healthy mice. At the end of the experiment, tissues were harvested, processed for flow cytometry, and run on the BD LSR-Fortessa X-20 and analyzed using Flowjo 10.10.0.

Histology

A 5 mm rectal portion of colon was fixed in 10% neutral buffered formalin (Thermo-Fisher, catalog: 5701) for 24–48 h. Formalin-fixed samples were stored in 70% ethyl alcohol (Pharmco, catalog: 111000200). Fixed samples were embedded in paraffin wax, cut in transverse sections, and stained with hematoxylin and eosin. Histological scoring was randomized, blinded, and scored based on the following items: severity of inflammation (0: None; 1: Slight; 2: Moderate; 3: Severe), the spread of inflammation (0: None; 1: Mucosa; 2: Mucosa and Submucosa; 3: Transmural), crypt damage (0: None; 1: Basal 1/3 damaged; 2: Basal 2/3 damaged; 3: Only surface epithelium intact; 4: Entire crypt and epithelium lost), and the percent of circumferential involvement (1: 1–25%; 2: 26–50%; 3: 51–75%; 4: 76–100%).65 Histology scores are presented as the sum of these items per individual mouse.

Cell isolation

On indicated day, colons and mLNs were harvested and stored in cold PBS supplemented with 2% FBS. Colons were measured for length by standard ruler from the cecum to the end of the rectum, flushed with 2 mL cold PBS by syringe, cut longitudinally, minced and digested with collagenase III (Worthington Biomedical, catalog: LS004182) for 30 min in shaker at 37C. Subsequently, colons were mashed against a 70 μm strainer using the plunger of a 3-mL syringe and cells were suspended in complete medium including RPMI 1640 with 10% FBS, 1% pen-strep (Gibco, catalog: 151140–122), 1% L-glutamine (Gibco, catalog: 25030–081), 0.1% 2-mercapethanol (Gibco, catalog: 21985–023), and 0.1% gentamycin (Invitrogen, catalog: 15710–064). mLNs were mashed using the plunger of a 3-mL syringe. Red blood cells were lysed with ACK (Ammonium-Chloride-Potassium) lysing buffer (ThremoFisher Scientific, catalog: A1049201), washed with PBS supplemented with 2% FBS and mLN cells were suspended in complete medium including RPMI 1640 with 10% FBS, 1% pen-strep, 1% L-glutamine, 0.1% 2-mercapethanol, and 0.1% gentamycin. PBMCs were obtained by heart puncture with a 27G needle, subsequent ACK lysis and suspension in in complete medium including RPMI 1640 with 10% FBS, 1% pen-strep, 1% L-glutamine, 0.1% 2-mercapethanol, and 0.1% gentamycin.

Mouse flow cytometry

Cells harvested from mouse tissues were washed twice with staining buffer (PBS including 2% FBS) and centrifuged at 1500 rpm for 5 min 1 × 106 cells per tissue were stained with Live/Dead Fixable Ghost Dye Violet 510 (Cytek, catalog 13–0870-T500) for 10 min at room temperature (RT) followed by Fc receptor blocking using TruStain FcX (anti-mouse CD16/32) antibody (BioLegend, catalog: 101320) for 10 min, at RT. For surface staining, cells were stained with a cocktail of fluorochrome-conjugated antibodies diluted in staining buffer for 20 min at 4C. Fluorochrome-conjugated antibodies to IgA and IgG1 were included in surface staining cocktail. For intracellular stains, cells resuspended in complete RPMI 1640 media (RPMI 1640 with 10% FBS, 1% pen-strep, 1% L-glutamine, 0.1% 2-mercapethanol, and 0.1% gentamycin) were stimulated with phorbol 12-myristate 13-acetate (Sigma Aldrich, catalog: P8139–1MG), ionomycin calcium salt (Sigma-Aldrich, I0634–1MG), and Brefeldin A (Invitrogen, catalog: 00–4506–51) for 4 h at 37C in CO2 incubator prior to staining. Following surface staining, cells were washed with staining buffer (1500 rpm, 5 min), fixed and permeabilized with the IC Fixation Buffer Kit (eBiosciences, catalog: 88–8824–00) for 45 min at 4C for intracellular staining. For nuclear stains, cells were fixed and permeabilized with the Foxp3/Transcription Factor Staining Buffer set (eBiosciences, catalog: 00–5523–00) for 40 min at 4C. After fixation, cells were washed twice with 1X permeabilization buffer (eBiosciences, catalog: 88–8824–00) (1500 rpm, 5 min), and stained with an intracellular or nuclear cocktail of fluorochrome-conjugated antibodies diluted in 1X permeabilization buffer for 45 min at 4C. Stained cells were washed twice with 1X permeabilization buffer (1500 rpm, 5 min) and stored in 2% paraformaldehyde (Thermo-Fisher, catalog: 28908) in PBS prior to acquisition. Fluorescence minus one (FMO) controls were used to determine individual gating following doublet removal and live cell gating. Samples were run on the BD LSRFortessa X-20 (BD Biosciences). 500,000 live events for colon cells and 200,000 live events for mLN cells were collected per sample and analyzed using FlowJo software version 10.10.0.

For the myeloid cell panel, 1 × 106 cells were first stained with CCR7 antibody diluted in complete RPMI 1640 media with 10% FBS, 1% pen-strep, 1% L-glutamine, 0.1% 2-mercapethanol, and 0.1% gentamycin for 1 h at 37C and washed twice with staining buffer (1500 rpm, 5 min). For viability, cells were stained with Live/Dead Fixable Ghost Dye Violet 510 or Zombie Red Fixable Viability dye (Biolegend, catalog 423109) for 10 min at RT followed by Fc receptor blocking using TruStain FcX (anti-mouse CD16/32) antibody for 10 min, at 4C. The staining of surface markers was conducted with antibody mix diluted in staining buffer for 20 min at 4C, followed by two washes in staining buffer (1500 rpm, 5 min). Data were acquired on the same day using BD LSRFortessa X-20 and analyzed using FlowJo software version 10.10.0.

High dimensional flow analyses were performed by concatenating the CD3+ populations of the samples from indicated groups. Prior to concatenation, the CD3+ population of each sample was downsampled to 2,500 events. Data cleaning was performed using FlowAI (v2.3.2) and downsample (v3.3.1) plug-ins via Flowjo 10.10.0. T-stochastic neighbor embedding (t-SNE) was performed using native Flowjo 10.10.0 functionality. Unbiased clustering was performed with FlowSOM (v4.1.0). Cell clusters were explored and annotated using the ClusterExplorer (v1.7.6) plug-in in Flowjo 10.10.0 and projected onto the t-SNE plot.

Cell events per mm of colon were obtained by extracting the gated population counts in Flowjo 10.10.0, as outlined in Figure S2, and normalized to tissue length. The normalization was conducted as follows: for each sample, the entire colon from cecum to rectum, excluding the distal 10 mm, was processed for flow cytometric analysis. 1 × 106 cells were stained per sample. 500,000 live events were collected per sample and used for downstream analysis in Flowjo 10.10.0. Reported values represent the number of events within the respective gate per millimeter of colon (i.e., gated cell count divided by the measured colon length in mm minus 10 mm).

Human flow cytometry

Cryopreserved human PBMCs were thawed, washed in complete culture RPMI 1640 media (5% human AB serum (Sigma-Aldrich, catalog: H4522) 1% L-glutamine, 1% Pen/strep, 0.1% Gentamicin, and 0.1% 2-Mercaptoethanol), and counted using trypan blue (Gibco, catalog: 15250061). A total of 0.5 × 106 cells were aliquoted into individual FACS tubes. Cells were stimulated with phorbol 12-myristate 13-acetate, ionomycin, and brefeldin A for 4 h in complete RPMI media (5% human AB serum, 1% L-glutamin, 1% Pen/strep, 0.01% Gentamicin, 0.01% 2-Mercaptoethanol) at 37C in CO2 incubator. Following stimulation, cells were washed twice with FACS buffer (1% BSA in 1× DPBS without Ca2+/Mg2+) and centrifuged at 1500 rpm for 5 min. Cells were then incubated with Zombie Aqua Flexible Viability dye for 10 min at RT (Biolegend, catalog 423101), washed with FACS buffer followed by Fc receptor blocking with 10% goat serum (Sigma-Aldrich, catalog: G9023). Cells were subsequently stained with surface fluorochrome-conjugated antibodies for 30 min at 4C, followed by washing with FACS buffer (1500 rpm, 5 min). Cells were then fixed using BD Fixation/Permeabilization solution, BD Cytofix/Cytoperm (BD Biosciences, catalog: 51–2090KZ) for 45 min at 4C. After fixation, cells were washed with 1x BD Perm/Wash buffer (BD Biosciences, catalog: 51–2091KZ), permeabilized, and stained with a fluorochrome-conjugated intracellular antibody cocktail diluted in 1x BD Perm/Wash buffer for 45 min at 4C. Following intracellular staining, cells were washed twice with 1x BD Perm/Wash buffer and once with FACS buffer (1500 rpm, 5 min each). Cells were then resuspended in FACS buffer and stored at 4C until acquisition. Data were acquired on the same day using an BD LSRFortessa X-20 (BD Biosciences) and analyzed with FlowJo software (Tree Star, Version 10.10.0). Doublets were removed using FSC and SSC parameters. FMO controls were used to determine gates following dead cell exclusion.

Microbiome sequencing

Individual microbiome samples were collected from co-housed mice and stored at −80C. Genomic DNA was extracted from stool samples using the QIAamp Fast DNA Stool Mini Kit (Qiagen), with an additional bead-beating lysis step. Each tissue sample was supplemented with approximately 150 mg of zirconium beads and lysis buffer. The samples were bead-beaten for 8 min at 3,800 rpm (BioSpec) to ensure bacterial lysis for DNA extraction, followed by the manufacturer’s protocol. Genomic DNA was amplified by PCR using 515F and 806R primer constructs containing sequencing-ready barcodes and adapter sequences. The libraries were assessed using an Agilent 4200 Tapestation system and Qubit fluorometric quantification, then cleaned, pooled, and sequenced on the Illumina MiSeq platform (Illumina, Inc., San Diego, CA) using the 2 × 250 bp paired-end protocol, yielding paired-end reads with near-complete overlap. Sequencing data from paired-end reads was de-multiplexed. Merging of paired-end reads, dereplication, and length filtering was performed using VSEARCH 2.17.1. Following denoising and chimera checking using the UNOISE3 command, unique sequences were taxonomically classified with Mothur using the Silva database version 138. Downstream analyses were performed with R version 4.4.1. The alpha diversity was measured using the Inverse Simpson Index.66 The beta diversity was measured using Bray-Curtis dissimilarity index, which was calculated using the Vegan R package version 2.6–6.1.66 Additionally, MicrobiomeAnalyst 2.0 online software67 was used to perform linear discriminant analysis effect size (LEfSe)68 and heat tree analyses.69

QUANTIFICATION AND STATISTICAL ANALYSIS

Data were graphed in GraphPad Prism 10 or RStudio and analyzed using t-tests, multiple t test, One-way ANOVA, or two-Way ANOVA in GraphPad Prism where applicable (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, ns not significant). Differences were considered significant if p value <0.05. All experiments were performed at least twice, with similar results. All results are expressed as with the mean ± SEM. All N numbers represent biological replicates. A student’s two-tailed unpaired t test was used to determine the significance between means of two groups. One way or two-way ANOVA was used to determine the significance between means of three or more groups. Bonferroni post-hoc tests were used to adjust for pairwise comparisons where applicable. Data distribution was assumed to be normal, with no normality tests performed.

Supplementary Material

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2

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2026.117969.

KEY RESOURCES TABLE.

REAGENT or RESOURCE SOURCE IDENTIFIER

Antibodies

Live/Dead Fixable Ghost DyeTM Violet 510 Cytek Cat#13–0870-T500
TruStain FcX™ (anti-mouse CD16/32) Biolegend Cat#101320; RRID: AB_1574975
Zombie Red™ Fixable Viability dye Biolegend Cat #423109
Zombie AquaTM Flexible Viability dye Biolegend Cat#423101
Anti-mouse F4/80-FITC Biolegend Cat#123108; RRID: AB_893502
Anti-mouse SIRPa-PerCP-Cy5.5 Biolegend Cat#144010; RRID: AB_2563548
Anti-mouse CCR7-BV421 Biolegend Cat#120120; RRID: AB_2561446
Anti-mouse MHCII-BV510 Biolegend Cat#107636; RRID: AB_2734168
Anti-mouse CD86-BV605 Biolegend Cat#105037; RRID: AB_11204429
Anti-mouse Thy1.2-BV650 BD Cat#740442; RRID: AB_2740169
Anti-mouse CD80-BV711 Biolegend Cat#104743; RRID: AB_2810338
Anti-mouse NK1.1-BV785 Biolegend Cat#108749; RRID: AB_2564304
Anti-mouse Ly6G-APC Biolegend Cat#127614; RRID: AB_2227348
Anti-mouse B220-APC Biolegend Cat#103212; RRID: AB_312997
Anti-mouse Ly6C-APC Biolegend Cat#128016; RRID: AB_1732076
Anti-mouse Siglec-F-AF647 BD Cat#562680; RRID: AB_2687570
Anti-mouse CD45-AF700 Biolegend Cat#103128; RRID: AB_493715
Anti-mouse XCR1-APC-Cy7 Biolegend Cat#148224; RRID: AB_2783118
Anti-mouse CD40-PE Invitrogen Cat#12-0401-82; RRID: AB_465649
Anti-mouse PD-L1-PE-Cy5 Biolegend Cat#124344; RRID: AB_2894674
Anti-mouse CD11c-PE-Cy7 BD Cat#558079; RRID: AB_647251
Anti-mouse CD138-BV605 Biolegend Cat#142516; RRID: AB_2562337
Anti-mouse FAS-BV711 BD Cat#740716; RRID: AB_2740397
Live/Dead-Ghost Dye Violet 510 Tonbo Cat#13-0870-T100
Anti-mouse CD45R/B220-BV786 BD Cat#563894
Anti-mouse GL-7-PerCP/Cy5.5 Biolegend Cat#144610; RRID: AB_2562979
Anti-mouse CD3e-Pe-Dazzle594 Biolegend Cat#155620; RRID: AB_2860723
Anti-mouse IgA-APC Invitrogen Cat#17–4204-82; RRID: AB_2848294
Anti-mouse CD45.2 -AF 700 Biolegend Cat#109822; RRID: AB_493731
Anti-mouse IgG1 -APC/Cy7 Biolegend Cat#406620; RRID: AB_2571947
Anti-mouse CD11b-BV605 Biolegend Cat#101237; RRID: AB_11126744
Anti-mouse CD73 BV711 BD Cat#752736; RRID: AB_2917717
Anti-mouse IgD- APC-Cy7 BioLegend Cat#405716; RRID: AB_10662544
Anti-mouse Ly-6G-BV 785 BioLegend Cat#127645; RRID: AB_2566317
Anti-mouse CD45 BV650 BD Cat#563410; RRID: AB_2738189
Anti-mouse B220 PE-CD594 BD Cat#562290; RRID: AB_11151901
Anti-mouse CD19 BV 786 BD Cat#563333; RRID: AB_2738141
Anti-mouse CD138 APC-R700 BD Cat#565176; RRID: AB_2739093
Anti-mouse GL-7 FITC BD Cat#553666; RRID: AB_394981
Anti-mouse FAS BV421 BD Cat#562633; RRID: AB_2737690
Anti-mouse IgG1 BUV-395 BD Cat#743265; RRID: AB_2741388
Anti-mouse IgM PE-Cy7 BD Cat#552867; RRID: AB_394500
Anti-mouse CD38 PerCP Biolegend Cat#102722; RRID: AB_2563333
Anti-mouse CD11b PE-Cy5 Biolegend Cat#101210; RRID: AB_312793
Anti-mouse F4/80 PE Biolegend Cat#123109; RRID: AB_893498
Anti-mouse CD11c PE BIolegend Cat#117307; RRID: AB_313776
Anti-mouse Ly6G PE Biolegend Cat#127607; RRID: AB_1186104
Anti-mouse NK-1.1-PerCP/Cy5.5 BioLegend Cat#108728; RRID: AB_2132705
Anti-mouse F4/80-AF488 BioLegend Cat#123120; RRID: AB_893479
Anti-mouse PD-L1-Pe-Dazzle594 BioLegend Cat#124324; RRID: AB_2565639
Anti-mouse Ly6C-APC BioLegend Cat#128015; RRID: AB_1732087
Anti-mouse CD11c-APC/Cy7 BioLegend Cat#117324; RRID: AB_830649
Anti-mouse LPAM-1-BV650 BD Cat#740493; RRID: AB_2740216
Anti-mouse CD4-BV 711 BD Cat#563050; RRID: AB_2737973
Anti-mouse CD103-BV 421 BioLegend Cat#121422; RRID: AB_2562901
Anti-mouse CD69-PE Biolegend Cat#104507; RRID: AB_313110
Anti-mouse CD45.2-PECF594 BD Cat#565390; RRID: AB_2739214
Anti-mouse CD8a-PE-Cy7 Biolegend Cat#100722; RRID: AB_312761
Anti-mouse CD3e-APC-Cy7 Biolegend Cat#100330; RRID: AB_1877170
Anti-mouse PD-1-BV605 Biolegend Cat#135219; RRID: AB_11125371
Anti-mouse CXCR5-Biotin BD Cat#551960; RRID: AB_394301
Anti-mouse Streptavidin-BV421 Biolegend Cat#405225
Anti-mouse CD8a-PerCP/Cy5.5 Biolegend Cat#100734; RRID: AB_2075238
Anti-mouse CD103-FITC BD Cat#557494; RRID: AB_396731
Anti-mouse CCR9-PE-Cy7 Biolegend Cat#128712; RRID: AB_10933082
Anti-mouse CD4 -APC-Cy7 Biolegend Cat#100413; RRID: AB_312698
Anti-mouse CTLA-4-PerCP-Cy5.5 Biolegend Cat#106316; RRID: AB_2564474
Anti-mouse IL-10-BV421 BD Cat#563276; RRID: AB_2738111
Anti-mouse IL17A-FITC invitrogen Cat#11–7177–81; RRID: AB_763581
Anti-mouse IL6-PE Biolegend Cat#504504; RRID: AB_315338
Anti-mouse IL12/IL23 p40-PE/Cy7 Biolegend Cat#505210; RRID: AB_2565645
Anti-mouse IL-4-BV711 BD Cat#564005; RRID: AB_2738537
Anti-mouse IFNγ-BV786 BD Cat#563773; RRID: AB_2738419
Anti-mouse GMCSF-PerCP-Cy5.5 Biolegend Cat#505410; RRID: AB_2562376
Anti-mouse Granzyme B-AF647 Biolegend Cat#515406; RRID: AB_2566333
Anti-mouse TNFα-AF 700 BD Cat#558000; RRID: AB_396980
Anti-mouse IFNγ-BV711 Biolegend Cat#505835; RRID: AB_11219588
Anti-mouse IL17A-APC Invitrogen Cat#17–7177–81; RRID: AB_763580
Anti-mouse FOXP3-FITC eBioscience Cat#11–5773–82; RRID: AB_465243
Anti-mouse IL17A-PE Invitrogen Cat#17–7177–81; RRID: AB_763580
Anti-mouse TGFb-BV421 Biolegend Cat#141408; RRID: AB_2650898
Anti-mouse IL-35-APC Biotechne Cat#IC2191A; RRID: AB_1964616
Anti-human CD45-APC-Cy7 Biolegend Cat#368518; RRID: AB_2616705
Anti-human CD3-PerCP-Cy5.5 Biolegend Cat#344808; RRID: AB_10640736
Anti-human CTLA-4-PE-Cy7 BioLegend Cat#349913; RRID: AB_2563097
Anti-human CD8 -BV650 Biolegend Cat#344729; RRID: AB_2564509
Anti-human CD19-BV785 Biolegend Cat#302239; RRID: AB_11218596
Anti-human CD4 -BV395 BD Cat#563550; RRID: AB_2738273
Anti-human CXCR5-BV421 Biolegend Cat#356920; RRID: AB_2562303
Anti-human CCR9-PE-DAZZ Biolegend Cat#358918; RRID: AB_2715935
Anti-human IL17-BV711 Biolegend Cat#512327; RRID: AB_11219603
Anti-human IFNg-PE Biolegend Cat#502509; RRID: AB_315234
Anti-human PD1-PE-Cy5 Biolegend Cat#329971; RRID: AB_2910394
Anti-human TNFa-AF700 BD Cat#557996; RRID: AB_396978
Anti-human CD103-BV605 Biolegend Cat#350217; RRID: AB_2564282
Anti-human Foxp3-FITC Biolegend Cat#320106; RRID: AB_439752
Anti-human LPAM-1-APC (AF647) BD Cat#571600; RRID: AB_3686607
Anti-human CD86-PE Biolegend Cat#374206; RRID: AB_2721633
Anti-human CD80-PerCP Biolegend Cat#305232; RRID: AB_2566491
Anti-human HLA-DR-FITC Biolegend Cat#361706; RRID: AB_2563192
Anti-human CD40-AF700 Biolegend Cat#334327; RRID: AB_2563920
Anti-human CTLA-4-BV605 Biolegend Cat#369609; RRID: AB_2632778
Anti-human HLA-A2-BV650 Biolegend Cat#343323
Anti-human PDL1-BV421 Biolegend Cat#329714; RRID: AB_2563852
Anti-human Tim-1-BV711 BD Cat#742543; RRID: AB_2740854
Anti-human IL-10-PE Biolegend Cat#506804; RRID: AB_315454
Anti-human CD27-BUV395 BD Cat#563815; RRID: AB_2744349
Anti-human CD138-AF647 Biolegend Cat#356524;RRID: AB_2564251
Anti-human CD38-PerCP Biolegend Cat#356613; RRID: AB_2562182
Anti-human IgG-AF488 Biolegend Cat#410739; RRID: AB_3083398
Anti-human IL-6-PE-Dazzle Biolegend Cat#501121; RRID: AB_2810621
Anti-human ICOSL-PE-Cy7 Biolegend Cat#309409; RRID: AB_2565670
Anti-human CXCR4-PE-Cy5 Biolegend Cat#306507; RRID: AB_314613
Anti-human CXCL13-AF700 R&D Cat#IC8012N-100UG; RRID: AB_3656648
Anti-human IgD-BV605 Biolegend Cat#348231; RRID: AB_2563336
Anti-human IL-12/23-PB Biolegend Cat#501820;RRID: AB_2124517
Anti-human IgA-BV711 BD Cat#772205; RRID: AB_3693986
Anti-human CD14-AF700 Biolegend Cat#301822; RRID: AB_493747
Anti-human CD16-BUV395 BD Cat#563785; RRID: AB_2744293
Anti-human TCRgdT-BV421 Biolegend Cat#331218; RRID: AB_2562317
Anti-human CD56-BV605 Biolegend Cat#318333;RRID: AB_11142683
Anti-human XCR1-BV711 Biolegend Cat#372633;RRID: AB_3662275
Anti-human CD11c-PE-Cy7 Biolegend Cat#337216; RRID: AB_2129790
Anti-human SIRPa-PE Biolegend Cat#372103; RRID: AB_2650860
Anti-human CD68-PE/Dazzle BD Cat#564944; RRID: AB_2739021
Anti-human CCR7-PE-Cy5 Biolegend Cat#353271;RRID: AB_2904373
Anti-human CD11b-APC Biolegend Cat#340007; RRID: AB_3662236
anti-PD1(RMP1-14) BioXCell Cat#BE0146; RRID: AB_10949053
anti-CTLA-4(9H10) BioXCell Cat#BE0131; RRID: AB_10950184
anti-PD1(RMP1-14) Leinco Technologies Cat#P372; RRID: AB_2749820
anti-CTLA-4(9H10) Leinco Technologies Cat#C2841; RRID: AB_2829599
anti-TNFα(XT3.11) BioXCell Cat#BE0058; RRID: AB_1107764
anti-IL-17A(17F3) BioXCell Cat#BE0173; RRID: AB_10950102
anti-IFNγ(XMG1.2) BioXCell Cat#BE0055; RRID: AB_1107694
anti-IL-6(MP5-20F3) BioXCell Cat#BE0046; RRID: AB_1107709
anti-IL-1β(B122) BioXCell Cat#BE0246; RRID: AB_2687727
anti-IL-23(G23-8) BioXCell Cat#BE0313; RRID: AB_2754551
anti-α4β7 (DATK32) BioXCell Cat#BE0034;RRID: AB_1107713
anti-CD19(1D3) BioXCell Cat#BE0150; RRID: AB_10949187
anti-B220(RA3.3A1/6.1 (TIB-146)) BioXCell Cat#BE0067;RRID: AB_1107651
anti-CD22(Cy34.1) BioXCell Cat#BE0011;RRID: AB_1107613
anti-CD19(1D3) Leinco Technologies Cat#C2117; RRID: AB_2737456
anti-B220(RA3.3A1/6.1 (TIB-146)) Leinco Technologies Cat#C383; RRID: AB_2737486
anti-CD22(Cy34.1) Leinco Technologies Cat#C3358; RRID: AB_2893559
polyclonal Syrian hamster IgG(Polyclonal) BioXCell Cat#BE0087;RRID: AB_1107782

Chemicals, peptides, and recombinant proteins

Dextran Sodium Sulfate (Colitis Grade) MP Biomedicals Cat#160110
Intracellular Fixation & Permeabilization Buffer Set eBioscience Cat#88–8824–00
Foxp3/Transcription Factor Staining Buffer Set eBioscience Cat#00–5523–00
Phosphate Buffered Saline Cytiva Cat# SH30256.01
BD Cytofix/Cytoperm™ BD Biosciences Cat#51-2090KZ
BD Perm/Wash™ buffer BD Biosciences Cat#51-2091KZ
Fetal Bovine Serum Gibco Cat# A52567-01
Human AB serum Sigma-Aldrich Cat# H4522
Trypan Blue Gibco Cat# 15250061
Goat Serum Sigma-Aldrich Cat# G9023
RPMI Gibco Cat#11875–093
Pen-Strep Gibco Cat#15140–122
Genatmicin Gibco Cat#15710–064
2-mercapethanol Gibco Cat#21985–023
L-glutamine Gibco Cat#25030–081
10% Neutral Buffered Formalin Thermo-Fisher Cat#5701
70% Ethyl Alcohol Pharmco Cat#111000200
Collagenase Type III Worthington Biomedical Cat#LS004182
16% Formaldehyde Thermo-Fisher Cat#28908
Cell Culture Grade Water Corning Cat#25–055-CM
0.25% Trypsin-EDTA Gibco Cat#25200–056
ACK (Ammonium-Chloride-Potassium) lysing buffer ThremoFisher Scientific A1049201
Phorbol 12-myristate 13-acetate Sigma-Aldrich Cat#P8139-1MG
Ionomycin calcium salt Sigma-Aldrich Cat#I0634-1MG
Brefeldin A Invitrogen Cat#00–4506–51

Critical commercial assays

Tag-it violet proliferation kit Biolegend Cat#425101

Deposited data

16S rRNA seq data NCBI Sequence Read Archive Accession number PRJNA1498150

Experimental models: Cell lines

B16-ova melanoma Laboratory of Roza Nurieva B16-ova

Experimental models: Organisms/strains

C57BL/6 Charles-River Frederick NCI Cat#556

Software and algorithms

Flowjo v10.10.0 https://www.flowjo.com/ https://www.flowjo.com/
FlowAI v2.3.2 Monaco et al. https://www.flowjo.com/exchange/plugin/flowai
Downsample v3.3.1 https://www.flowjo.com/ https://www.flowjo.com/exchange/plugin/downsample
FlowSOM v4.1.0 Van Gassen et al. https://www.flowjo.com/exchange/plugin/flowsom
Cluster Explorer v1.7.6 https://www.flowjo.com/ https://www.flowjo.com/exchange/plugin/clusterexplorer
R v4.4.1 https://www.r-project.org/ https://www.r-project.org/
Microbiome Analyst v2.0 Dhariwal et al. https://www.microbiomeanalyst.ca/

Highlights.

  • Number and activity of circulating B cell increase in patients and mice susceptible to colitis

  • Latent microbial dysbiosis may underlie the B cell dysfunction in the asymptomatic stage

  • Altered B cell activity at the asymptomatic stage precedes the hallmark T cell phenotypes

  • Dysregulated B cell responses may predict the development of ICI-colitis

ACKNOWLEDGMENTS

We would like to acknowledge Dr. Sang T. Kim’s advice in establishing the mouse model of ICI-colitis. This work was supported by NIH R01 grants (R.N.: CA284684 and AI183604), NIH R03 grant (R.N.: CA286624), Wilkes Melanoma Foundation grant (R.N. and A.D.), NIH/NCI Melanoma and GI SPORE grants (R.N.), Institutional Research Grant (IRG) (R.N.), NIH/NIAID Career Development Award K01AI163412 (N.A.), Kleberg Innovator/Investigator Award (M.D.P.), American Association of Immunologists, Intersect Fellowship (F.G.K.), and Career Development Award from American Assciation for Cancer Research and Breast Cancer Research Foundation (F.G.K). Mauro Di Pilato is a Cancer Prevention and Research Institute of Texas (CPRIT) Scholar in Cancer Research. This work was supported by CPRIT (Recruitment of First-Time Tenure-Track Faculty Members; RR210017; M.D.P.). The Microbiome Facility was supported in part by The University of Texas MD Anderson Cancer Center and P30CA016672. The Research Histology Core Laboratory was supported in part by The University of Texas MD Anderson Cancer Center and NIH P30CA016672 grant. The Flow Cytometry and Cellular Imaging Core Facility was supported in part by The University of Texas MD Anderson Cancer Center and NIH P30CA016672 grant. Illustrations in this manuscript were created in BioRender.com.

Footnotes

DECLARATION OF INTERESTS

All authors declare no competing interests.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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Data Availability Statement

  • The 16S rRNA-seq data have been deposited at the NCBI Sequence Read Archive (accession number PRJNA1498150) and are publicly available as of the date of publication.

  • This paper does not report original code.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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