Wnt/β-catenin activation epigenetically reprograms Regulatory T cells in IBD and progression to dysplasia.

doi:10.21203/rs.3.rs-110212/v1

Download PDF

Article

Wnt/β-catenin activation epigenetically reprograms Regulatory T cells in IBD and progression to dysplasia.

https://doi.org/10.21203/rs.3.rs-110212/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

The molecular and functional diversity of regulatory T-cells (T_regs) in health and in disease remains unclear. We previously described in colorectal cancer (CRC) patients a subpopulation of RORγt⁺ T_regs with elevated expression of β-catenin and pro-inflammatory properties. Here we observed progressive expansion of RORγt⁺ T_regs in inflammatory bowel disease (IBD) patients during inflammation and early dysplasia. Activating Wnt/β-catenin signaling in human and murine T_regs was sufficient to recapitulate the disease-associated increase in frequencies of RORγt⁺ T_regs expressing IL-17, IFN-γ, and TNFa. We found that binding of the β-catenin interacting partner, TCF-1, to DNA overlapped with Foxp3 binding at enhancer sites of pro-inflammatory pathway genes. Sustained Wnt/β-catenin activation induced newly accessible chromatin sites in these genes and upregulated their expression. These findings indicate that TCF-1 and Foxp3 together limit the expression of pro-inflammatory genes in T_regs. Activation of ꞵ-catenin signaling interferes with this function and promotes the disease-associated RORγt⁺ T_reg phenotype.

Gastroenterology & Hepatology

Immunology

Epigenetics & Genomics

Allergy & Immune Disorders

Regulatory T cells

IBD

Regulatory T cells (T_regs) are essential to sustain peripheral tolerance and prevent autoimmune pathology. A growing body of evidence suggests that T_regs adapt phenotypically and functionally to their anatomic location and in response to the inflammatory millieu^{1, 2}. Multiple T_reg sub-populations have been described that express additional T helper (T_H) cell lineage transcription factors³ including T-bet⁴, GATA-3⁵, and RORγt^{6, 7}. Adopting these programs equips T_regs with the ability to specifically regulate different T_H responses. The intestine comprises a highly diverse T_reg compartment. Specifically, RORγt-expressing T_regs are found in the colon, small intestine (SI), and at lower frequencies in the peripheral lymphoid organs of healthy mice^{6, 7, 8}. These cells are necessary to maintain the balance of intestinal inflammatory responses. In humans, however, it remains unclear whether RORγt⁺/Foxp3⁺ T_regs have physiological regulatory functions.

T_regs are defined by a core regulatory program established during late T_reg differentiation by Foxp3 binding to gene enhancers made accessible by Foxo1⁹. Moreover, Foxp3 acts together with other factors forming multi-molecular complexes with different modes of action^{10, 11}; functioning as an activator in complex with RelA, Ikzf2 (Helios), Ep300, and Kat5, and a repressor with EZH2, YY1, and Ikzf3¹². This seminal work^{9, 10, 11, 12}, however, suggests that Foxp3 has a complex interactome, which requires further study. Recently, it was suggested that overlap of Foxp3 binding with the transcription factor TCF-1 may affect the maintenance of T_reg function¹³. We further showed that TCF-1 binding also overlaps with multiple other factors including Ikaros, Runx, Ets, and HEB in double positive thymocytes. In particular, it cooperates with HEB to initiate T cell-specific programs through active enhancer (AE) binding and regulation of chromatin accessibility ¹⁴. Furthermore, TCF-1 plays critical roles in the differentiation of T_H lineages¹⁵, memory formation¹⁶, and counteracting exhaustion¹⁷. In T cells, TCF-1 is the bona fide DNA-binding partner of β-catenin, the central effector of the Wnt-signaling cascade. The classical Wnt-signaling dogma defines TCF-1 as a DNA-bound repressor until Wnt signals stabilize β-catenin, which translocates to the nucleus and binds TCF-1 to initiate transcription¹⁸. β-catenin is also stabilized upon T cell receptor (TCR) engagement in T cells¹⁹. Excessive Wnt/β-catenin activation in T_regs may impact T_reg function²⁰ and is linked to autoimmunity in the context of multiple sclerosis²¹. Foxp3 binding to DNA has been suggested to overlap with β-catenin in human T_regs, which parallels the overlap between TCF-1 and Foxp3 DNA occupancy in mice¹³.

Immune suppression through recruitment of T_regs is a major immune escape mechanism in cancer²² and increased tumor-infiltrating and/or circulating T_regs are correlated with detrimental outcomes²³. Their role in colorectal cancer (CRC) remains unclear^{24, 25, 26, 27}, as T_regs also suppress chronic inflammation, which is a cancer-promoting factor in inflammatory bowel disease (IBD)-associated CRC^{28, 29}. We described a sub-population of RORγt⁺ T_regs that expands in the tumor and peripheral blood (PB) of CRC patients throughout disease progression³⁰. While these cells still suppress T cell proliferation, they are also pro-inflammatory, as they express IL-17 and promote mast cell degranulation. In murine polyposis models, we causatively linked the pro-inflammatory skewing of T cells to activation of Wnt/β-catenin-signaling during thymic development³¹.

Here, we show that RORγt⁺ T_regs expressing the pro-inflammatory cytokines IL-17, IFNg, and TNFa expand progressivelly in both IBD and IBD/CRC patients and in mouse models of colitis and colitis/dysplasia. We establish that enhanced Wnt/β-catenin signaling is responsible for the induction of pro-inflammatory RORγt⁺ T_regs. Moreover, we provide a molecular mechanism that explains this disease-associated phenomenon. We found that TCF-1 and Foxp3 co-bind regulatory elements, most importantly active enhancers, of genes that are involved in pro-inflammatory processes and limit their expression. Upon Wnt/β-catenin activation, these genes gain newly accessible chromatin sites and become transcriptionally upregulated. Hence, the upregulation of β-catenin imposes a pro-inflammatory phenotype onto T_regs by interfering with TCF-1/Foxp3-mediated gene suppression.

Frequencies of β-catenin^high RORγt⁺ T_regs increase in the PB and colonic mucosa of IBD patients during inflammation and malignant disease progression. We previously established that RORγt⁺ T_regs expand in sporadic CRC patients³⁰. To understand the etiology of this expansion, we investigated IBD, which represents a unique platform to study the mechanisms underlying the emergence and distribution of RORγt⁺ T_regs during inflammation and progression to CRC. We analyzed colonic tissue and/or PB samples from 65 IBD patients, with or without dysplasia (IBD/Dys), and compared them to a group of 20 healthy donors (HD; Table S1).

We first determined the frequencies of circulating fractions (Fr.) of naïve T_regs (Fr.I=CD45RA⁺Foxp3^int), activated T_regs (Fr.II=CD45RA^-Foxp3^high), and activated conventional T cells (Fr.III= CD45RA^-Foxp3^int) within CD4⁺ T cells as suggested by Sakaguchi and colleagues (Fig. 1a-e)³²^, ²⁷. Previously, we reported that Fr.II of activated T_regs selectively increased in sporadic CRC compared to HDs³⁰. Likewise, here we show a progressive enrichment of Fr.II T_reg frequencies from HDs to IBD and IBD/Dys (Fig. 1c). We also observed a progressive increase of non-T_reg Fr.III T cells, which were suggested to be prognostic for CRC clinical outcomes (Fig. 1c)²⁷. We previously defined proinflammatory T_regs in patients by their expression of RORγt. We therefore assessed the proportions of RORγt-expressing cells within the Sakaguchi T_reg fractions (Fig. 1b-d) as well as in the classically defined CD25⁺Foxp3⁺CD127^-T_reg population (Fig. S1a-c). In accordance with our previous work, RORγt⁺ cells were enriched within Fr.II of activated T_regs in IBD/Dys patients (Fig. 1d). Similarly, frequencies of RORγt⁺ within CD25^hiFoxp3⁺CD127^-T_regs also increased in IBD and IBD/Dys patients compared to HDs (Fig. S1b, c). Conclusively, PB RORγt⁺ T_reg frequencies were elevated in IBD and IBD/Dys patients.

Previously, we causatively linked the skewing of CD4⁺ conventional T cells towards a Th17/pro-inflammatory phenotype to the activation of the Wnt/β-catenin pathway³¹. Hence, we assessed the expression of β-catenin in RORγt⁺ and RORγt^- Fr.II T_regs and in CD25^hiFoxp3⁺CD127^- T_regcells. Indeed, RORγt expression in T_regs uniformly correlated with enhanced β-catenin protein levels (Fig. 1b, e and Fig. S1d-e). Specifically, β-catenin expression was significantly higher in RORγt⁺ compared to RORγt^- Fr.II T_regs in patients and HDs (Fig. 1e). Further validating previous findings by our group and others^{21, 30}, the RORγt⁺but not the RORγt^- CD25⁺Foxp3⁺CD127^- PB T_regs produced proinflammatory cytokines upon stimulation with PMA/Ionomycin (Fig. 1f-i and Fig S1d-g). More precisely, RORγt⁺ PB T_regs intracellularly accumulated IL-17, IFNg, and TNFa (Fig. 1 f-h) and a fraction of them were even found to be double producers for TNFa and IL-17 (Fig. 1i). Importantly, a significantly higher percentage of RORgt⁺ PB T_regs produced IFNg in IBD and IBD/Dys patients compared to HDs (Fig. 1g-h). Furthermore, compared to RORgt^-, co-expression of IL-17 and TNFa was significantly more frequent in RORgt⁺ PB T_regs of IBD and IBD/Dys patients but not of HDs (Fig. 1i). These findings show that chronic inflammation in IBD and IBD/Dys conincides with the increase in frequencies of the previously described RORgt⁺T_reg population in the PB which produces multiple pro-inflammatory cytokines.

Next, we determined the frequencies of tissue-resident RORγt⁺ T_regs in IBD patients by purifying mononuclear cells (MNCs) from inflamed (INF) and less inflamed (‘margin’, M) colonic mucosa samples. We found substantially higher frequencies of total Foxp3⁺ T cells (~30%) within tissue-resident CD4⁺ T cells compared to the PB. Moreover, tissue-resident total Foxp3⁺ T cells were significantly increased in IBD/Dys compared to IBD patients (Fig. 1j) for both M and INF areas. We also found that frequencies of RORγt⁺ T_regs increased from the margin to the inflamed mucosa (Fig. 1k-l). Like their circulating counterparts, tissue-resident RORγt⁺ T_regs expressed significantly higher levels of β-catenin compared to RORγt^- T_regs (Fig. 1m-n) and produced IL-17 upon stimulation (Fig. S1h, Fig. 1o). Thus, circulating RORγt⁺ T_regs in IBD/Dys patients share major similarities with tissue-resident RORγt⁺ T_regs and are likely tissue/tumor derived.

To explore possible RORγt⁺ T_reg tumor infiltration we analyzed datasets from The Cancer Genome Atlas (TCGA, Research Network: https://www.cancer.gov/tcga) and determined how expression changes of Wnt/β-catenin, T_reg, and Th17 pathway genes were connected. To do this, we calculated the average z-scores over all genes in the ‘human WNT signature’ (KEGG_human_WNT)^{33, 34} and signatures containing genes that are transcriptionally up-regulated in Th17 cells (TH17_UP) and T_regs (T_reg_UP) that were kindly provided to us by Dr. Benoist and colleagues¹⁰. The TH17_UP positively correlated with the KEGG_human_WNT signature (p<0.001, Spearman-score r=0.5604, red dots Fig. 1p) and mirrored the equally strong positive correlation between the T_reg_UP and the KEGG_human_WNT (p<0.001, Spearman-score r=0.6161, blue dots Fig. 1p) signatures. Also, the TH17_UP and T_reg_UP signatures showed a strong positive correlation (p<0.001, Spearman-score r=0.7836, Fig. S1i). This suggests that the T_reg infiltrate in CRC tumors with an activated Wnt signature may possess Th17-like traits.

We further assessed whether the enhanced expression of T_reg/Th17 signature genes could be correlated with adverse survival in the TCGA cohort, as the expression of Th17 associated genes was previously linked to detrimental outcome in CRC³⁵. The effect on survival was tested with a machine learning approach. Coefficient values were derived from the machine learning approach for each gene in the TH17_UP, Treg_UP, and the combined TH17_UP/Treg_UP signatures via Cox proportional-hazards regression (example for the TH17_UP signature is shown in Fig. S1k,l) (Table S2). The genes whose enhanced expression predicted decreased survival included, amongst others, LEF-1 and MAF. We then divided patients, based on the median score of the TH17_UP, Treg_UP and combined TH17_UP/Treg_UP signature (TH17_UP signature shown as example in Fig. S1i). We interogated the survival outcomes of groups with above versus below the median score of the weighted signatures. These analyses indicated that above-median signature scores for the TH17_UP (Fig. 1q, p<0.0001, log-rank test, n=188 – below and above median) T_reg_UP (Fig. 1r, p<0.0001) and most importantly for the combined TH17_UP/T_reg_UP genes (Fig. 1s, p<0.0001) correlated with reduced overall survival. The significant detriment in survival for the combined weighted signature (TH17_UP/Treg_UP) further supports the suggestion from the unweighted Spearman correlations that a T_reg tumor infiltrate with Th17-traits might results in adverse survival.

Ex vivo stabilization of β-catenin in human T_regs is sufficient to induce the pro-inflammatory phenotype. Given our finding that RORγt expression in T_regs correlates with increased β-catenin levels in IBD(/Dys) patients, we investigated whether β-catenin stabilization was sufficient to induce RORγt and pro-inflammatory cytokine expression in HD T_regs. Therefore, we treated HD PBMCs ex vivo with the GSK-3β inhibitor Chiron (CHIR99021) to stabilize β-catenin protein. Levels of β-catenin (Fig. 2a) and RORγt (Fig. 2c) were assessed in CD4⁺CD25⁺Foxp3⁺ T_regs after 4 (d4) and 7 (d7) days of culture with Chiron. Intracellular β-catenin (Fig. 2b) as well as RORγt (Fig. 2d) levels were significantly elevated in T_regs after Chiron treatment at both time points. While β-catenin expression plateaued on d4, RORγt expression in Chiron-treated T_regs increased significantly between d4 and d7 (Fig. 2d).

In addition to β-catenin regulation, GSK-3β phosphorylates STAT proteins in T cells^{36, 37}, which promote the expression of pro-inflammatory cytokines IL-17 (STAT3)^{38, 39} and IFN-γ (STAT1)^{40, 41}. Hence, GSK-3β inhibition cannot be used to assess downstream cytokine production in these ex vivo cultures. Alternatively, in human primary T cell cultures¹⁹ and in murine thymocytes⁴² it was shown that TCR engagement stabilizes β-catenin. To determine the physiological effect of β-catenin activation, we cultured HD PBMCs for 4d in the presence of its natural activator, Wnt3a, in combination with CD3/CD28-beads, CD3/CD28-beads alone, or vehicle control (Fig. 2e). CD3/CD28-beads were removed from cultures on d4 and Fr.II T_reg cells (Fig. 2f) were analyzed for β-catenin and RORγt expression (Fig. 2g,h) as well as cytokine production (Fig. 2i,j) on d6. Intracellular levels of β-catenin and RORgt directly correlated (Fig 2g) and increased significantly in Wnt3a/CD3/CD28 and CD3/CD28 compared to vehicle control treated Fr.II T_regs (Fig. 2h). Similarly, a significantly higher frequency of Wnt3a/CD3/CD28 and CD3/CD28 treated Fr.II T_regs expressed the proinflammatory cytokines IL-17, IFNγ, and TNFa (Fig. 2j) after PMA/Ionomycin stimulation. As observed in IBD(/Dys) patients, expression of IL-17 and TNFα (Fig. 2i,k) coincided and a smaller proportion of Fr.II T_regs even co-expressed IL-17 and IFNγ. Interestingly, gut homing receptor CCR9 became strongly upregulated (Fig. 2l) in Fr.II T_regs upon Wnt/ꞵ-catenin-activating stimulation. Conclusively, TCR stimulation in combination with activating Wnt-signals induced a pro-inflammatory phenotype in Fr.II T_regs that is indentical with that observed in IBD(/Dys) patients (Fig. 1). Hence, these observations imply that β-catenin stabilization in primary human PBMCs is sufficient to drive the proinflammatory phenotype of T_regs observed in IBD and CRC patients.

Activated RORγt⁺ sub-populations of T_regs expressing gut homing receptors peripherally expand during disease progression in a murine IBD/CRC model. To recapitulate our findings in patients and further analyze IBD/CRC-associated RORγt⁺ T_regs, we used our previously established murine APC^Δ468(APC^Δ) polyposis model⁴³. In this model, translation of the adenomatous polyposis coli (APC) protein prematurely terminates due to ablation of exons 11 and 12, resulting in a truncated, nonfunctional 468 aa protein. The pathology of APC^Δ resembles APC^Min/+ mice. They develop intestinal polyposis that spreads to the colon over time, and succumb to disease between 6-8 month of age⁴⁴^, ⁴⁵. In previous work we used this model to demonstrate that T_reg-specific ablation of Rorc reduced polyp burden in APC^Δ mice³⁰. Treatment of APC^Min/+ mice with dextran sodium sulfate (DSS), which causes colitis in mice⁴⁶, leads to the development of invasive CRC^{47, 48}. We established invasive colonic lesions (Fig. 3b), by treating 3-4-month-old APC^Δmice with 3 rounds of 2% DSS in the drinking water for 7 days followed by 2 weeks recovery (Fig. 3a). This regimen led to colon shortening and a highly significant increase in colonic adenomas compared to untreated APC^Δ mice (Fig. 3c).

Next, we assessed the frequencies of total colonic T_regs (Fig. 3d) and RORγt⁺ T_regs (Fig. 3e). Each of the three pathologic conditions colitis (WT+DSS), polyposis (APC^Δ-DSS), and IBD/CRC (APC^Δ+DSS) displayed increased colonic CD25⁺Foxp3⁺ T_reg (Fig. 3d) and RORγt⁺ T_reg (Fig. 3e) frequencies compared to naïve mice (WT-DSS). As observed in IBD patients, β-catenin expression was significantly higher in RORγt⁺ T_regs than in RORγt^- T_regs for all treatment groups, (Fig. 3f). However, total T_regs (Fig. 3d) and RORγt⁺ T_regs (Fig. 3e) trended towards even higher frequencies in IBD/CRC compared to colitis or polyposis alone. We speculated that specific sub-populations of RORγt⁺ T_regs increased under IBD/CRC conditions, but the effect was masked by the overall increase of T_regs. Therefore, we designed two flow cytometric panels comprising CD4, Foxp3, CD25, RORγt, and β-catenin to distinguish distinct RORγt⁺ and RORγt^- T_reg subsets. The first panel assessed tissue and inflammation homing markers; gut-homing receptor CCR9, inflammation-homing receptor CCR6, and tissue-residency marker CD103. The second panel focused on proliferation and activation markers Ki67, CD44, CD69, and CD62L (Fig. 3g). We gated on CD4⁺CD25⁺Foxp3⁺ T_regs from spleen (SPL) and colon MNCs, concatenated the populations from all experimental groups, and performed tSNE analysis. RORγt⁺ T_reg gates were then superimposed onto the respective tSNE landscape revealing unique populations (Fig. S2a,b). These landscapes show that the complexity of RORγt⁺ T_reg populations in the colon is greater than in the spleen (tissue and inflammation homing panel: colon=8, SPL=2 populations, activation panel: colon=8, SPL=3 populations, Fig 3g). To trace the origin of these cells, we focused on populations that expressed the same markers between the spleen and colon (red arrows, Fig. 3g). Analysis of expression profiles (Fig. S2a,b) revealed that RORγt⁺ T_reg populations shared between the colon and spleen expressed CCR9/CD103, and Ki67/CD44 (Fig. 3g). Cumulative analysis confirmed that CCR9⁺CD103⁺ (Fig. 3h) and CD44⁺Ki67⁺ (Fig. 3i) RORγt⁺ T_reg frequencies in the IBD/CRC group (APC^Δ+DSS) increased compared to the untreated WT, colitis (WT+DSS), and polyposis (APC^Δ-DSS) groups for colonic and splenic samples. Moreover, polyposis (APC^Δ-DSS) or colitis (WT+DSS) alone also showed elevated frequencies of the shared T_reg populations in the colon, compared to the untreated group. This suggested that during IBD/CRC carcinogenesis a sub-population of highly activated and proliferative RORγt⁺ T_regs with gut-homing properties expanded in the colon and the periphery (SPL). It further indicated diversity within the RORγt⁺ T_reg subset, particularly in the colon.

T_reg-specific β-catenin stabilization in mice results in a pro-inflammatory T_reg phenotype in mice. Ex vivo Wnt/β-catenin pathway activation in primary human HD T_regs recapitulated the phenotype of RORγt⁺ T_regs observed in patients (Fig. 2). Accordingly, we examined in mice whether T_reg-specific activation of the Wnt/β-catenin pathway was sufficient to induce RORγt⁺ T_regs. We introduced the ctnnb1^fl(ex3) allele⁴⁹ into the Foxp3^YFP-Cre mice established by Rudensky and colleagues⁵⁰. Cre-excision of exon 3 encoding the β-catenin degradation domain leads to intracellular accumulation of β-catenin protein.

As the Foxp3 gene resides on the X-chromosome, male mice are hemizygous. Male Foxp3^YFP-Cre Ctnnb1^fl(ex3) (CAT) mice showed severe X-linked, scurfy-like^{51, 52} immune-pathology, (Fig. S3b) they were smaller than Foxp3^YFP-Cre WT (Cre) littermates and died ~3-4 weeks after birth (Fig. S3a). They further presented enlarged secondary lymphoid organs, particularly peripheral lymph nodes (pLN), and splenomegaly (Fig. S3c). Histological assessment via H&E staining of paraffin-embedded tissue sections revealed a reduced thymic cortex and severe immune infiltrates in lungs and liver (Fig. S3d, blue arrows). These observations mirrored those of a recent study using a different Foxp3Cre⁵³ with the same floxed β-catenin allele²¹.

The observed pathology in CAT mice implied a lymphoproliferative disorder. Hence, we next assessed the activation status of conventional T cells in the peripheral lymphoid organs and thymi of 21-day-old mice. Compared to Cre-only, CAT mice had increased frequencies of total CD3⁺ cells in the spleen and pLNs; with a decrease of CD4⁺ T helper (T_H) cells in the pLNs and mLNs and an increase of CD8⁺ cytotoxic T cells (CTLs) in the spleen (Fig. S3e), indicating imbalanced T cell proliferation. This was further supported by the increase of Ki67⁺T_Hcells and CTLs in CAT compared to WT mice (Fig S4a-b). Moreover, CD25^-Foxp3^-CD4⁺ T_H cells and CTLs were strongly activated in CAT mice. The frequencies of T_Hcells and CTLs expressing the activation markers CD44, CD69, and CD25 were significantly increased in all peripheral lymphoid organs whereas the fractions of T cells expressing the naïve T cell marker CD62L was reduced. (Fig. S4a-b).

The highly activated effector T cell compartment in CAT mice suggested that β-catenin stabilization altered T_reg function. T_reg frequencies strongly decrease within mLNs and spleens of CAT mice, however thymic T_reg generation was unaltered (Fig. 4a, Fig. S4c). In peripheral T_regs, Foxp3 expression mildly increased (Fig. 4b), whereas expression of the T_reg marker Neuropilin (Fig. S4d) did not change. Similar to the human ex vivo cultures, β-catenin stabilization (Fig. 4c) was sufficient to uniformely upregulate RORγt (Fig. 4d) levels in CAT (β-catenin^high) compared to Cre T_regs. Moreover, β-catenin^high T_regs were highly activated, as evidenced by increased frequencies of CD44⁺ (Fig. 4e) and CD69⁺ (Fig. 4f) T_regs and decreased CD62L⁺ T_regs (Fig. 4g) in CAT mice. Likewise, T_regs in CAT mice were more proliferative, demonstrated by Ki67 staining (Fig. 4h). Lastly, we tested the ability of β-catenin^high T_regs to suppress proliferation of polyclonally activated, CFSE-labeled CD4⁺CD25^- T effector cells (T_eff) in vitro. Compared to control Cre T_regs, β-catenin^high T_regs had significantly reduced suppressive function for all T_reg:T_eff ratios tested (Fig. 4i).

Conclusively, β-catenin stabilization in murine T_regs was sufficient to up-regulate RORγt and induce an activated, pro-inflammatory phenotype that mirrored the systemically expanding RORγt⁺ T_reg sub-population observed in the APC^Δ/DSS model (Fig. 3i). The lymphoproliferative disease in CAT mice could thus be attributed to a combination of the activated phenotype and the reduced suppressive function of β-catenin^high T_regs.

β-catenin^high T_regs are competitively disadvantaged in a chimeric setting and spontaneously express proinflammatory cytokines. Foxp3^YFP-Cre heterozygous females represent natural chimeras of β-catenin^high/YFP⁺ versus WT/YFP^- T_regs due to random X-chromosome inactivation. These mice provide the opportunity to test the pathogenic potential of β-catenin^high/RORγt^high T_regs in a competitive chimeric setting. Interestingly, compared to hemizygous males, heterozygous Foxp3^Cre(+/-)females that carry the Ctnnb1^fl(ex3) allele are healthy.

When comparing Cre (Foxp3^YFP-Cre(+/-) WT) and CAT (Foxp3^YFP-Cre(+/-) Ctnnb1^fl(ex3)) female mice, total T_reg numbers in the spleen and thymus were identical between genotypes (Fig. 5a). The frequency of YFP⁺ T_regs, however, was drastically reduced in CAT compared to Cre females (Fig. 5b). Cumulative analysis of YFP⁺ and YFP^- T_reg fractions showed that YFP⁺ T_regs only accounted for 1-3% of total T_regs in all peripheral lymphoid organs of female CAT mice (Fig. 5c). The thymic output of YFP⁺ T_regs was also reduced to 20 % in CAT females. In Cre females the ratio of YFP⁺/YFP^- T_regs was also slightly reduced to 40%/60% (Fig. 5b,c). This could be attributed to the YFP-Cre transgene rendering Foxp3 expression in YFP⁺ T_regs mildly hypomorphic compared to T_regs with an unaltered Foxp3 locus⁵⁴. The persisting YFP⁺/β-catenin^high T_regs had elevated RORγt expression (Fig. 5d) and an activated phenotype, as evidenced by increased CD44 expression (Fig. 5e) compared to CAT YFP^- T_regs but also compared to Cre YFP⁺/YFP^- T_reg populations. In accordance to our findings in patients’ RORgt⁺ T_regs, CAT YFP⁺/β-catenin^high compared to YFP^- and to Cre YFP⁺/YFP^- T_reg populations spontaneously expressed proinflammatory cytokines IL-17, IFNg, and TNFa. Further mirroring our finding in patients (Fig. 1), a significant proportion of these YFP⁺/β-catenin^high T_regs co-expressed IL-17 and IFNg or IL-17 and TNFa (Fig. 5f-i). In accordance to findings in human samples, the gut-homing receptor CCR9 was upregulated (Fig. S5a) as shown for wnt3a/anti-CD3/28-treated human T_regs (Fig. 2l). Conclusively, in a non-inflammed setting, β-catenin^high/RORγt^high T_regs have a competitive disadvantage in chimeric mice. Although they do not spontaneously cause disease, they are poly-functional in producing proinflammatory cytokines.

The DNA-binding partner of β-catenin, TCF-1, and Foxp3 co-bind accessible chromatin at gene loci that are crucial for T_reg function. Previous work indicated that β-catenin²⁰/TCF-1¹³ occupy DNA together with Foxp3. Thus, we anticipated that precise mapping of TCF-1 and Foxp3 co-binding in T_regs, could provide a molecular explanation for the change in the phenotype of T_regs that overexpress β-catenin. To address this, we analyzed TCF-1 DNA binding in T_regs through chromatin immunoprecipitation and deep sequencing (ChIPseq) in Foxp3^YFP-Cre WT T_regs. Furthermore, we assessed regions of accessible chromatin in T_regs via transposase-accessible chromatin approach and deep sequencing (ATAC-seq). We also utilized available data⁵⁵ for Foxp3-binding (Foxp3-ChIPseq), histone marks including; monomethylated histone 3 at Lys4 (H3K4me1), tri-methylated H3 Lys4 (H3K4me3), acetylated H3 at Lys27 (K3K27Ac), trimethylated H3 at Lys27 (H3K27me3), and Methyl-CpG binding domain-based capture and sequencing (MBD-seq).

We assigned TCF-1 (Fig. S6a-c) and Foxp3 (Fig. S7a-c) ChIPseq-peaks to specific gene regulatory regions by performing K-means clustering guided by the surrounding chromatin modifications. 14.6% of TCF-1 (Fig. S6a) and 24.0% of Foxp3 (Fig. S7a) binding sites, were assigned to active enhancers (AE, enriched for H3K4me1, H3K27Ac), 41.6% and 39.3% of transcription factor binding sites to poised enhancers (PE, enriched for H3K4me1, lacking H3K27Ac), and 44.0% and 36.7% to promoters (Pr, enriched for H3K4me3, H3K27ac, and accessible chromatin (ATAC-seq signal)). Both TCF-1 and Foxp3 preferentially bound open and poised chromatin as their binding sites rarely overlapped with the repressive histone mark H3K27me3 (Fig. S6b-c, Fig. S7b-c). We next performed motif analysis for TCF-1- and Foxp3-bound sites. TCF-1-bound enhancer sites were enriched for the TCF-1 consensus motif, while both promoter and enhancer Foxp3-bound sites were enriched for the Foxp3 motif (Fig S6d, Fig. S7d). The high enrichment for motifs of other factors like Ets, RUNX and YY family members agreed with previous evidence that TCF-1¹⁴ and Foxp3¹² act in multi-molecular complexes. Pathway enrichment analysis (http://www.metascape.org) revealed that TCF-1 (Fig. S6e) and Foxp3 (Fig. S7e) binding to promoter and enhancer sites marked genes involved in T cell activation and other T cell processes, as well as in general DNA and RNA metabolism processes.

We further analyzed directly overlapping TCF-1 and Foxp3 co-bound sites (Fig. 6), which included 504 AE, 389 PE, and 1101 Pr (Fig. 6a). Examples for TCF-1 and Foxp3 co-bound gene loci at AE (Tcf7), PE (Ccr7), and Pr (Stat1) sites are visualized as IGB tracks (Fig. 6f). The TCF-1 consensus motif, but not the Foxp3 binding motif, was highly enriched in the overlapping AE and Pr sites (Fig. 6d). Pathway enrichment analysis revealed that co-binding of TCF-1 and Foxp3, particularly at AE sites, marked genes involved in Th17 differentiation, T cell activation, and cytokine production pathways (Fig. 6e). Thus, in T_regs TCF-1 and Foxp3 together occupied genes whose upregulation could explain the phenotype of RORγt⁺ T_regs observed in IBD/CRC patients and mouse models.

β-catenin stabilization drives the proinflammatory phenotype of RORγt⁺ T_regs through epigenetic and transcriptional regulation of critical Foxp3 and TCF-1 co-bound genes. The classical Wnt signaling model posits that TCF-1 acts as a transcriptional repressor that becomes an activator once β-catenin binds and mediates epigenetic changes. Hence, one could speculate that, in a Wnt-off state, TCF-1 is part of Foxp3 repressor complexes¹², which act together to limit the expression of genes that should not be permanently expressed in bona fide T_regs. Thus, we postulated that β-catenin stabilization specifically affects the transcription and epigenetic states of these TCF-1/Foxp3 co-bound genes.

To explore this possibility, we performed ATAC-seq analysis of YFP⁺CD25⁺ β-catenin^high T_regs FACS sorted from CAT (Foxp3^YFP-Cre Ctnnb1^fl(ex3)) and WT (Foxp3^YFP-Cre) mice (Fig. 7a). β-catenin^high T_regs (23,084 peaks) had fewer accessible sites than Cre T_regs (29,566 peaks). However, the sites that lost accessibility from Cre to β-catenin^high (Cre unique sites, 9831 peaks), already had low accessibility in Cre T_regs and yet were not fully closed in β-catenin^high T_regs. The majority of sites remained consistently open for both genotypes (common, 19735 peaks) and 3349 sites gained de novo accessibility in β-catenin^high T_regs. We specifically analyzed the newly accessible sites for transcription factor binding motifs (Fig. 7b). One of the most strongly enriched motifs was that of TCF-1 (Tcf7), indicating that β-catenin together with TCF-1 may directly alter the accessibility of corresponding genes. Additionally, motifs of transcription factors that are involved in Th17 differentiation (Maf, RARg) and T cell activation (JunB) were highly enriched. The 3349 newly accessible sites corresponded to 2582 genes (Fig. 7a) of which 370 were co-bound by TCF-1 and Foxp3 (Fig. 7c). Pathway enrichment analysis of these 370 genes revealed that T cell activation, cytokine production, and Th17 differentiation pathways were most significantly enriched (Fig. 7d).

We next performed RNA-seq expression profiling to investigate how the changes in chromatin accessibility impacted transcription in β-catenin^high T_regs. Differential expression testing yielded 3190 up- and 2795 down-regulated (q-value≤0.05) genes in β-catenin^high compared to Cre T_regs. The upregulated list comprised genes that are essential for T_reg function, including CTLA-4 and Il2ra (CD25, Fig. 7e). Pathway enrichment analysis for significantly up-regulated genes that were co-bound by TCF-1 and Foxp3 (Fig. 7f-g) revealed an enrichment for the very same pathways identified by the newly accessible chromatin sites, namely, T cell activation and Th17 differentiation (Fig. S8).

We next assessed the dynamic chromatin accessibility changes following β-catenin stabilization of genes co-bound by TCF-1/Foxp3 in different regulatory regions. Therefore, we compared the log₂-fold accessibility changes in β-catenin^high T_regs over Cre T_regs for promoter, PE, and AE co-bound to that of all differentially accessible genes (Fig. 8a). Although, genes co-bound by TCF-1/Foxp3 always gained accessibility, the AE-bound genes showed the strongest increase in accessibility in β-catenin^high T_regs (Fig. 8a). As AE-bound genes are most affected by β-catenin stabilization, we specifically searched for those that were up-regulated, gained accessibility, and were TCF-1/Foxp3 co-bound at AE sites in T_regs (Fig. 8b). This yielded in 49 genes, that were identified to belong to T cell activation and Th17 differentiation pathways (Fig. 8b). We further validated these findings via an inverse, non-supervised approach. We retrieved gene lists for the Th17 differentiation (102 genes) pathway (GSEA/MSigDB database), and used the same T_{reg_}UP signature (195 genes) used for TCGA screening. The leukocyte migration (242 genes) pathway (GSEA/MSigDB database) was also assessed due to the observed increase in CCR9 expression in RORγt⁺ T_regs in humans (Fig. 2l) and mice (Fig. 3, Fig. S5d) suggesting their migration from the colon to the periphery. Comparing accessibility of genes in these pathways showed strong de novo accessible sites that arise after β-catenin activation in T_regs (red lines) compared to common (black lines) and WT sites (green lines, Fig. 8c). Moreover, gene set enrichment analysis (GSEA⁵⁶) showed a significant positive upregulation for Th17 differentiation and leukocyte migration pathways (Fig. 8d, Fig. S8). The T_{reg_}UP signature, however, was not consistently changed between WT and β-catenin^high T_regs (Fig. 8d). This indicated that the core T_reg program was not drastically altered, but non-T_reg/effector T cell functions were acquired upon β-catenin activation. For instance, activation of β-catenin led to the acquisition of a newly accessible site in the IFNγ locus (Fig. 5e, black arrow), which may account for the ability of β-catenin^high T_regs to express IFNγ. Similarly, the IL-17 locus gained accessibility (Fig. 8e), which may account for spontaneous IL-17 production in β-catenin^high T_regs (Fig 5h,i).

Overall, our findings indicated that β-catenin activation caused epigenetic and transcriptional changes of crucial Foxp3/TCF-1 co-regulated genes. This resulted in the induction of transcriptional programs responsible for Th17 differentiation/T cell activation that were super-imposed onto the T_reg program and potentially conferred the observed pro-inflammatory phenotype to β-catenin^high T_regs.

Diverse T_reg populations that express transcriptional programs in addition to the core T_reg signature as functional adaptation to the tissue microenvironment and inflammatory milieu have been described ^{1, 2, 3, 4, 5, 6, 7}. Here we address mechanisms that potentially underlie T_reg functional changes in chronic inflammation and cancer, focusing on a population of RORγt⁺ T_regs in the context of IBD and CRC. Our results show that during IBD and progression to dysplasia, RORγt-expressing T_regs that produce proinflammatory cytokines selectively expand in the colon and PB of patients. We linked this RORγt⁺ T_regphenotype to enhanced Wnt/β-catenin signaling in both humans and animal models. Our molecular analyses provide evidence that TCF-1, the DNA-binding partner of β-catenin, together with Foxp3, controls the expression of genes involved in T cell activation and Th17-proinflammatory processes. The stabilization of β-catenin upregulates the expression of these genes by promoting chromatin accessibility and thereby superimposes pro-inflammatory traits onto the core T_reg program.

In healthy mice, a specific consortium of bacteria induces RORγt⁺ T_regs mainly in the colon, where they regulate local inflammatory responses ^{6, 7}. During IBD and progression to cancer, antigens from bacteria and from the chronically-inflamed, damaged mucosal tissue mediate persistent TCR-stimulation⁵⁷. Furthermore, CRC tumors and the inflamed mucosa were shown to secrete enhanced levels of activating Wnt proteins^{58, 59}. This persistent TCR- stimulation^{19, 42} in a Wnt rich environment has the potential to strongly activate Wnt/β-catenin in T cells. Furthermore, mucosal barrier dysfunction in IBD and IBD/Dys likely enables the PB dissemination of the RORγt⁺ T_regs in an antigen-driven manner leading to their systemic occurance. Indeed, our ex vivo experiments in human PBMCs indicate that TCR-stimulation and activating Wnt signals stabilize β-catenin in T_regs and increase the frequencies of RORγt⁺ T_regs, which express the pro-inflammatory cytokines IL-17, IFNγ, and TNFa. A certain proportion of these RORγt⁺ T_regs showed a poly-functional cytokine profile by co-expressing IL-17 and IFNg or IL-17 and TNFa simultaneously. Furthermore, genetic β-catenin stabilization in our Foxp3^Cre-driven mouse model induces T_regs that are homogenously RORγt^high and spontaneously produce IL-17, IFNγ, and TNFa even in the absence of overt inflammation in a competitive chimeric setting. These findings suggest that constitutive Wnt/β-catenin signaling in human as well as murine T_regs is sufficient to promote the pro-inflammatory RORγt⁺ T_reg-phenotype.

We previously showed increased frequencies of circulating RORγt⁺ T_regs in patients with sporadic CRC³⁰. Here we found that in IBD RORγt⁺ T_regs also expand systemically and have proinflammatory properties, promoting the notion that colonic and circulating RORγt⁺ T_regs may be related. This is supported by several findings. First the observation that β-catenin stabilization both in human PBMCs and in the chimeric mouse model upregulates gut-homing receptor CCR9. Second, the finding that the expanding RORγt⁺ T_regs in the IBD/CRC mouse model express CCR9 as well as tissue-residency marker CD103 undeline their colonic/tissue origin. Finally, the observation that β-catenin stabilization transcriptionally upregulates leukocyte migration genes including CCR7, which promotes cell entry to lymphoid tissues⁶⁰, suggests altered migration. As mentioned above, mucosal barrier dysfunction^{61, 62} can cause systemic microbial and tissue-specific antigen-spread during IBD/CRC and contribute to systemic immune dysregulation⁵⁷. It was previously reported that T_reg migration in breast cancer can be Ag-specific^{63, 64}. Similarly, the above conditions may facilitate migration of gut-tissue-resident RORγt⁺ T_regs and/or support their maintenance in the periphery, thereby increasing their frequencies in IBD and CRC.

The epigenetic and transcriptional studies presented here focus on determining the mechanisms by which T_reg-specific β-catenin-activation promotes the disease-associated RORγt⁺ T_reg phenotype. In line with previous evidence that TCF-1 interacted with the signature T_reg transcription factor Foxp3²⁰, here we show that the genome-wide TCF-1-DNA binding in T_regs substantially overlaps with that of Foxp3¹³. Importantly, we find that TCF-1 and Foxp3 co-bind active enhancer regions of genes responsible for Th17 differentiation, T cell activation, and leukocyte migration. Recent studies have shown that Foxp3 binding to active enhancers⁹ can activate or suppress expression of the associated genes depending on local interactions with other specific cofactors. In particular, Foxp3 likely acts as a repressor in complexes with YY1, EZH2, and Ikzf3¹². Based on current evidence²⁰^,¹³ and our own results, TCF-1 possibly participates in repressive regulatory complexes with Foxp3. The finding that the conserved YY1 binding motif is strongly enriched in the Foxp3/TCF-1 co-bound DNA-sites further supports this suggestion. Moreover, our findings that β-catenin stabilization enhances chromatin accessibility and the expression of certain TCF-1/Foxp3 co-bound genes indicates that the TCF-1/Foxp3-mediated regulation of these genes depends on β-catenin expression levels. Enhanced β-catenin binding to TCF-1 may alter the TCF-1/Foxp3 regulation of these gene loci by displacing co-repressors to promote transcription. Indeed, the regions that gain de novo accessibility with β-catenin stabilization are enriched for the TCF-1 binding motif, suggesting that the β-catenin-mediated epigenetic changes involve TCF-1. These molecular changes mediated by β-catenin promote a duality in the phenotype of RORγt⁺ T_regs by enhancing pro-inflammatory Th17 differentiation and leukocyte migration pathways without abrogating the regulatory core T_reg signature.

In conclusion, our study establishes the progressive and systemic expansion of RORγt⁺ T_regs during IBD and progression to dysplasia and highlights activation of β-catenin as a major underlying molecular process. We show that TCF-1 and Foxp3 function together to control the expression of a pro-inflammatory program through binding to active enhancer regions of the associated genes. We further define that this regulation is driven by β-catenin stabilization, which promotes chromatin accessibility and enhances transcription of the TCF-1/Foxp3 co-regulated genes. β-catenin mediates upregulation of T cell activation and Th17 signature genes and superimposes this activated proinflammatory phenotype onto the core T_reg program. Future studies should establish the ontology and TCR specificities of the disease-associated RORγt⁺ T_regs, as well as their roles in perpetuating inflammation. It is curcial to understand the exact contributions of RORγt⁺ T_regs to chronic intestinal inflammation and malignancies, which first and foremost should address the effects of pro-inflammatory cytokine production by these cells on disease progression.

The present data connects to our previous report that frequencies of pro-inflammatory T_regs increase in the blood of CRC patients³⁰ and expands it to a pre-malignant setting of chronic inflammation. The step wise increase in the frequencies of RORγt⁺ T_regs expressing IL-17, IFN-γ, and TNFa from IBD to early dysplasia and CRC emphasizes the involvement of these cells in pro-inflammatory immune dysregulation fostering chronic inflammation and therewith acting cancer-promoting. Early intervention in cancer treatment is greatly needed. In this context frequencies of circulating RORγt⁺ T_regs could serve as a biomarker in IBD and CRC. Furthermore, our detailed molecular analysis of genes and processes affected by ꞵ-catenin stabilization in T_regs could help identify targets to limit the systemic expansion of potentially disease-promoting pro-inflammatory T_regs during CRC.

Patients and Healthy Donors. 43 patients undergoing major surgery for Crohn’s disease (CD)/ulcerative colitis (UC) treatment (proctocolectomy, colectomy, partial ileectomy, or combinations of the aforementioned procedures) were consented to donate 45ml of peripheral blood either directly preop or directly postop. Up to 4g of fresh intestinal mucosal tissue was collected from inflamed, margin (in most cases less inflamed), and dysplastic areas from the surgical specimens (if made available for research purposes by pathology) from the same patients. Additionally, 22 IBD patients undergoing routine colonoscopy check-up visits and 20 healthy individuals participated to the study by donating up to 45ml of peripheral blood. Informed consent was obtained from all patients and healthy donors. The protocol was approved by the University of Chicago Division of the Biological Sciences Institutional Review Board (BSD IRB) and was performed in accordance to Federal Law.

Isolation and flow cytometric analysis of PBMCs and MNCs from patient and healthy donor samples. PBMCs were isolated from peripheral blood samples using LymphoprepTM (Serumwerk Bernburg AG for Alere Technologies AS, via Stemcell 7851) density gradient centrifugation. MNCs were isolated from mucosal tissue samples using the Tumor Dissociation Kit, human (Miltenyi 130-059-929) and gentleMACS C Tubes (Miltenyi 130-093-237) following the instructions from the Lamina Propria Dissociation Kit, mouse (Miltenyi 130-097-410). MNCs isolated from blood and intestinal mucosa were either first re-stimulated with Cell Stimulation Cocktail plus protein transport inhibitors 500x (eBioscience 00-4975-93) for three hours in X-Vivo-20 media (LONZA 04-448-Q) or used directly for flow cytometric staining. Cells were stained for viability using the LIVE/DEAD Aqua fluorescent reactive dye (Molecular Probes – life technologies L34963), followed by surface staining with varying combinations of the following antibodies: CD3 (clone OKT3, BioLegend; UCHT1, ThermoFisher), CD4 (clone RPA-T4, BD), CD8 (RPA-T8, eBioscience/ThermoFisher Scientific/BD), CD25 (clone M-A251, BD), CD45RA (clone HI100, BD/BioLegend), CD127 (clone HIL-7R-M21, BD), CD279/PD-1 (clone EH12.1.H7, BioLegend), CD152/CTLA-4 (clone 14D3, eBioscience/ThermoFisher Scientific), CCR9 (L053E8, BioLegend (V27-580, BD) and respective manufacturer isotype controls. Following surface staining, cells were fixed and permeabilized using Foxp3/Transcription Factor Fixation/Permeabilization Concentrate and Diluent (Affymetrix/eBioscience/ThermoFisher Scientific, 00-5521) and intracellular staining was performed for Foxp3 (clone 236A/E7, eBioscience/Thermo Fisher Scientific), RORγt (clone Q21-559, BD), β-Catenin (clone 14/Beta-Catenin, BD) IL-17 (clone BL 168, BioLegend), IFNγ (clone 4S.B3, eBioscience/Thermo Fisher Scientific), TNFα (Mab11, BioLegend), Ki67 (Ki-67, BioLegend), and respective manufacturer isotype control antibodies. Samples were then acquired using a 4 laser/15 detector LSR-Fortessa instrument (BD) or an 5-Laser Aurora (Cytek^TM) instrument. For the spectral flow stainings Brilliant Stain Buffer Plus (BD) was added to the staining mixes according to manufacturer’s insctructions. Isolated PBMCs were either analyzed directly ex vivo or frozen (10 % DMSO (SIGMA D2650), 90% human AB Serum (Gemini 100-512)) and analyzed in batch directly after thawing.

Analysis of TCGA data. Spearman Correlations; The results are based on data generated by the TCGA Research Network: https://www.cancer.gov/tcga. Average z-scores for each individual gene in each of the signatures and for the tumors of each individual patient in the TCGA database were downloaded. Average z-scores are calculated as relative mRNA expression value of an individual gene and tumor, normalized to the gene’s expression distribution in a reference population (defined as all samples that are haploid for the respective gene). Then, the z-scores of all genes in each individual signature were averaged over the number of genes in the respective signature, yielding average z-scores for the Th17_UP, Treg_UP, and KEGG_human_WNT signatures for each patient. Regularized Regression of TCGA Gene Expression; In order to determine the ability of the TH17 gene signature to inform patient-level survival, we deployed Cox proportional-hazards regression on colorectal cancer clinical data extracted from TCGA. We used Ridge regression regularization ⁶⁵ and chose an optimal penalty coefficient λ using 10–fold cross validation optimized for partial likelihood deviance. The TH17 gene-based score for each patient was generated by multiplying the coefficient vector by the patient-level gene expression. Patient scores were dichotomized at the median and Kaplan-Meier curves were plotted. Statistical coding was performed using R version 3.1.2, and packages survival ⁶⁶, glmnet ⁶⁷, and survminer ⁶⁸.

In vitro Wnt/β-catenin pathway activation in HD PBMCs. PBMCs were isolated via density gradient centrifugation under sterile conditions. Cells were adjusted to 1 x 10⁷ cells in X-Vivo^TM20 media (LONZA, 04-448Q) supplemented with 10% AB-Serum (Gemini, 100-512), 100 U/ml recombinant human (rh)-IL-2 (PreproTech, 200-02), 60 U/ml IL-4 (PreproTech, 200-04), and 1 ng/ml TGF-β1 (PreproTech, 100-21) and seeded in 12-well plates at 2 x 10⁶ cells/well. For the GSK3-β inhibition, cells were treated with 6 μM Chiron (CHIR99021, Sigma, SML1046) or DMSO vehicle control for 6 days total, supplemented with 3 μM of fresh Chiron daily. Samples were analyzed via flow cytometry on day 4 and 7 for expression of CD4, CD25, CD3, β-catenin, Foxp3 and RORγt. For the TCR/wnt3a stimulation 4 x 10⁶ cells were seeded in 6-well plates. They were stimulated with human T-activator CD3/CD28 Dynabeads (Thermo Fisher, 11161D) at a 1:1 bead-to-cell ratio and rh-wnt3a (R&D Systems, 5036-WN-010) was added at 100 ng/ml dilution. Cells were supplemented with 50 ng/ml rh-Wnt3a daily. On day 4, the T-activator beads were removed, while wnt3a treatment continued until day 6. On day 6, cells were split, and one half was re-stimulated with Cell Stimulation Cocktail for 3 hours. All samples were analyzed by flow cytometry using the same panel as for the patient sample analysis and spectral flow cytomerty.

Mice. Foxp3^YFP-Cre Ctnnb1^fl(ex3)⁴⁹, Foxp3^YFP-Cre⁵⁰, APC^Δ468⁴³, CD45.1 and WT mice were used in all experiments described. All mice were maintained on the C57BL/6 background. Mice were housed under specific pathogen-free (SPF) conditions in the animal facilities at the University of Chicago in accordance with protocol #71880, approved by the University of Chicago Institutional Animal Care and Use Committee.

Mouse model for IBD-associated colon cancer. 3-4 months old APC^Δ468 (male and female) and aged-matched WT mice were treated with 3 rounds of 2% dextran sulfate sodium salt (colitis grade, 160110, MP) in the drinking water ad libitum over 7 days with a 2-week recovery period on normal drinking water between each round (see experimental treatment scheme Fig. 3a). Weight loss was monitored every other day.

Histological assessment of inflamed tissues. Peripheral lymphoid organs and vital organs were resected from mice and directly ex vivo formalin fixed (HT5014, Sigma-Aldrich). Colons were harvested from mice, flushed free of feces with ice-cold HBBS, formalin fixed, and Swiss rolled. All fixed organs were paraffin embedded and 4mm sections were used for H&E staining. Embedding, sectioning and H&E staining service was provided by the University of Chicago Human Tissue Resource Center (HTRC).

Isolation of lymphocytes from thymi, peripheral lymphoid organs, and the intestinal mucosa of mice. Thymi, peripheral lymph nodes, mesenteric lymph nodes, and spleens were resected. Single cell suspensions were generated by mashing the organs through 40-100 μm cells strainers while flushing the strainers with ice-cold 1 x PBS. Erythrocytes in the spleen single cell suspensions were lysed by resuspending the cell pellets in 2 ml ACK buffer (150 mM NH₄Cl, 10 mM KHCO₃, 0,1 mM EDTA, pH = 7,2-74), each, for 1 min on ice. The reaction was stopped by adding 15 ml of PBS + 2% FCS, cells were spun down immediately after and washed in 10 ml ice cold PBS. Dead cells were removed by filtering the lysed cells suspensions through 40 μm cell strainers. Intestinal lamina propria lymphocytes were isolated according to the protocol published by Atarashi and colleagues⁶⁹.

T_reg Proliferation Inhibition Assay. Untouched CD4⁺CD25^- T cells were isolated from peripheral lymph nodes and spleens of 10-week old CD45.1 mice using the CD4⁺ T cell isolation kit, mouse (130-104-454, Miltenyi). The protocol was modified by adding 1 μl biotin rat anti-mouse CD25 (553070, BD) antibody per 100 μl of the Labeling Cocktails to remove T_regs. Purified CD4⁺CD25^- CD45.1⁺ T cells were CFSE labeled using Cell Trace CFSE (C34554, Invitrogen/Fisher) and stimulated using Dynabeads Mouse T-Activation CD3/CD28 (11456-D, Gibco/Life Technologies/Fisher) in a 1:1 ratio. 50,000 CFSE-labeled T cells and 50,000 beads were seeded in 96-well round-bottom plates in 200 μl culture media (DMEM (D6429, Sigma) supplemented with 0.4 % Gentamycin (G1397, Sigma), 1% HEPES, and 10%FCS per well. After 48h, CD4⁺CD25⁺ T_regs from Foxp3^YFP-Cre Ctnnb1^fl(ex3) and Foxp3^YFP-Cre mice were added, respectively. T_regs were purified from peripheral lymph nodes and spleens using the CD4+CD25+ Regulatory T cell Isolation Kit II (130-091-041, Miltenyi). The assay was performed in triplicates with T_reg to T effector ratios of 1:1, 1:2, and 1:4. Samples were incubated for another 48h and then collected for flow cytometric read out. Cells were stained for viability and then surface stained with CD45.1 (clone A20, BD), CD45.2 (clone 104, BD), CD25 (clone PC61, BD) and CD4 (clone GK1.5, BD) antibodies. Stained samples were acquired using a 4 laser/15 detector LSR-Fortessa instrument (BD).

Flow cytometry and FACS of murine lymphocytes. Cells isolated from peripheral lymphoid organs, thymi, and intestinal mucosa were either first re-stimulated with Cell Stimulation Cocktail (plus protein inhibitors, 500 x, eBioscience, 00-4975-93) for three hours in X-Vivo-20 (LONZA, 04-448-Q) or used directly for flow cytometric staining. Cells were stained for viability using the LIVE/DEAD Aqua fluorescent reactive dye (Molecular Probes – life technologies, L34963), followed by surface staining with varying combinations the following antibodies in FACS buffer (1x PBS + 2% v/v FCS): CD3 (clone 145-2C11, BD), CD4 (clone GK1.5, BD), CD8 (clone 53-6.7, BD), CD25 (clone PC61, BD), CD44 (clone IM7, BD), CD62L (clone MEL-14, BD), CD69 (clone H1.2F3, BD), CD103 (clone M290, BD), CD196/CCR6 (clone 29-2L17, BioLegend), CD199/CCR9 (clone CW-1.2, BioLegend), CD304/Neuropilin-1 (clone 3E12, BioLegend), CTLA-4 (UC10-4B9, BioLegend), GITR (DTA-1, BD). Following surface staining, cells were fixed and permeabilized using Foxp3/Transcription Factor Fixation/Permeabilization Concentrate and Diluent (Affymetrix/eBioscience/Thermo Fisher Scientific, 00-5521). Intracellular flow cytometric staining was performed with anti-β-catenin (clone 14/Beta-Catenin, BD), RORγt (clone Q31-378, BD), Foxp3 (clone FJK-16s, eBiosience/Fisher), Helios (clone 22F6, BioLegend), anti-GFP (clone FM264C, BioLegend), IFNγ (clone XMG1.2, BD), IL-17A (clone TC11-18H10, BD), TNFα (MP6-XT22, BioLegend), Ki67 (B56, BD), and respective manufacturer isotype control antibodies. Stained samples were acquired using a 5 laser/18 detector LSR-Fortessa X20 (BD) instrument, an 5-Laser Aurora (Cytek^TM) instrument, or sorted using 4 laser/15 detector AriaII/IIIu (BD) FACS sorters. For the spectral flow stainings, Brilliant Stain Buffer Plus (BD) was added to the staining mixes according to manufacturer’s insctructions. Flow data was analyzed using FlowJo Version 10 software (FlowJo LLC, BD).

Chromatin immunoprecipitation and sequencing (ChIP-seq). 1×10⁷ CD25⁺YFP⁺ T_regs were FACS sorted from LN and SPL isolated CD4⁺ T cells (CD4⁺ T Cell Isolation Kit, mouse, 130-104-454, Miltenyi) of 10-12-week-old Foxp3^YFP-Cre WT mice. Chromatin immunoprecipitation and library generation performed as previously described^{14, 70}. Libraries were sequenced on a HiSeq 4000 sequencer at the University of Chicago Genomics Facility.

Isolation and preparation of samples for RNA-seq. 1.5-4.0x10⁵ CD25⁺YFP⁺ T_regs were FACS sorted from MACS-pre-purified CD4⁺ T cells (CD4⁺ T Cell Isolation Kit, mouse, 130-104-454, Miltenyi) isolated from LNs of 21 day old Foxp3^YFP-Cre Ctnnb1^fl(ex3) and Foxp3^YFP-Cre WT mice. Total RNA was isolated using the PicoPure^TM RNA Isolation Kit (KIT0202, Arcturus) following the manufacturer’s instructions. Libraries were generated and sequenced by the University of Chicago Genomics Facility.

Assay for transposase accessible chromatin and sequencing (ATAC-seq). For ATAC–seq, 5-10x10⁴ YFP⁺CD25⁺ T_regs were FACS sorted from MACS-pre-purified CD4⁺ T cells (CD4+ T Cell Isolation Kit, mouse, 130-104-454, Miltenyi) isolated from LNs of 21 day old Foxp3^YFP-Cre Ctnnb1^fl(ex3) and Foxp3^YFP-Cre WT mice. Cells were centrifuged at 500g at 4°C for 5 min, washed with 1 x PBS, and centrifuged again. Cells were resuspended in lysis buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl₂, and 0.1% IGEPAL CA-630) and immediately centrifuged at 500 g at 4 °C for 10 min. Pellets were resuspended in transposition reaction buffer (25 μl 2× Tagment Buffer (FC-121-1030, Illumina), 2.5 μl Tagment DNA Enzyme, and 22.5 μl nuclease-free H₂O) for 30 min at 37 °C. DNA was purified with a Qiagen MinElute Kit and amplified with Nextera PCR primers (Illumina Nextera Index Kit) and NEBNext PCR Master Mix (M0541, New England BioLabs). Amplified DNA was purified with a Qiagen PCR cleanup kit. Libraries were sequenced on a HiSeq 4000 sequencer at the University of Chicago Genomics Facility.

Genome mapping and data analysis. Sequenced ChIP and ATAC datasets were mapped with the Galaxy (https://usegalaxy.org/) suite of tools. Data were groomed and aligned to the mouse mm10 genome with Bowtie, allowing up to one mismatch and retaining only uniquely mapped reads, and unmapped reads were filtered. For transcription factors (TCF-1, Foxp3) peak calling was performed with MACS via HOMER⁷¹. Transcription factor peak calling was performed relative to input controls with the requirement that peaks be at a minimum 5-fold enriched over input and meet a p-value cutoff of 1 x 10^–5. Open-chromatin (ATAC-seq) peaks were called with Macs2⁷² with --nomodel set and no background provided. Differential accessibility testing of ATACseq data was performed using the edgeR Bioconductor package⁷³. Sequenced RNA datasets were aligned to the mouse mm10 genome like the ChIP–seq datasets. Differential gene expression analysis was performed with Cuffdiff2⁷⁴. Genes with transcript abundance differences below q<0.05 were considered to be significantly differentially expressed. Heat maps of normalized reads for gene subsets were generated with using Genepattern⁷⁵. Motif analysis was performed with the HOMER motif-discovery algorithm, and transcription-factor overlap analysis was conducted with the HOMER mergePeaks command, considering only peaks that directly overlapped. Peaks were annotated to the mm10 genome with annotatePeaks.pl in HOMER. Histograms for transcription factors and histone modifications were generated with ngs.plot software⁷⁶. K-means clustering of ChIP–seq datasets and heat maps were also generated with ngs.plot. Transcription factor binding was visualized with the Integrated Genome Browser software⁷⁷. Pathway enrichment analysis for genes identified by ChIP–seq and RNA-seq analysis was performed via Metascape (http://metascape.org)⁷⁸.

Statistical analysis. Results from biologically distinct experiments were combined and analyzed with the indicated statistical tests in Prism 7 (GraphPad). The statistical significance of RNA-seq data was determined with Cuffdiff and for ATACseq data with edgeR. ChIP–seq (factor enrichment) and ATAC–seq (chromatin accessibility) p-value cutoffs were determined with MACS2. Gene pathway enrichment p-values were determined with Metascape. Data are presented as mean ± SEM.

Kuswanto, W. et al. Poor Repair of Skeletal Muscle in Aging Mice Reflects a Defect in Local, Interleukin-33-Dependent Accumulation of Regulatory T Cells. Immunity 44, 355-367 (2016).
Ito, M. et al. Brain regulatory T cells suppress astrogliosis and potentiate neurological recovery. Nature 565, 246-250 (2019).
Zhu, J., Yamane, H. & Paul, W.E. Differentiation of effector CD4 T cell populations (*). Annual review of immunology 28, 445-489 (2010).
Levine, A.G. et al. Stability and function of regulatory T cells expressing the transcription factor T-bet. Nature 546, 421-425 (2017).
Yu, F., Sharma, S., Edwards, J., Feigenbaum, L. & Zhu, J. Dynamic expression of transcription factors T-bet and GATA-3 by regulatory T cells maintains immunotolerance. Nature immunology 16, 197-206 (2015).
Ohnmacht, C. et al. MUCOSAL IMMUNOLOGY. The microbiota regulates type 2 immunity through RORgammat(+) T cells. Science 349, 989-993 (2015).
Sefik, E. et al. MUCOSAL IMMUNOLOGY. Individual intestinal symbionts induce a distinct population of RORgamma(+) regulatory T cells. Science 349, 993-997 (2015).
Yang, B.H. et al. Foxp3(+) T cells expressing RORgammat represent a stable regulatory T-cell effector lineage with enhanced suppressive capacity during intestinal inflammation. Mucosal Immunol 9, 444-457 (2016).
Samstein, R.M. et al. Foxp3 exploits a pre-existent enhancer landscape for regulatory T cell lineage specification. Cell 151, 153-166 (2012).
Fu, W. et al. A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells. Nature immunology 13, 972-980 (2012).
Delacher, M. et al. Genome-wide DNA-methylation landscape defines specialization of regulatory T cells in tissues. Nature immunology 18, 1160-1172 (2017).
Kwon, H.K., Chen, H.M., Mathis, D. & Benoist, C. Different molecular complexes that mediate transcriptional induction and repression by FoxP3. Nature immunology 18, 1238-1248 (2017).
Xing, S. et al. Tcf1 and Lef1 are required for the immunosuppressive function of regulatory T cells. The Journal of experimental medicine 216, 847-866 (2019).
Emmanuel, A.O. et al. TCF-1 and HEB cooperate to establish the epigenetic and transcription profiles of CD4(+)CD8(+) thymocytes. Nature immunology 19, 1366-1378 (2018).
Choi, Y.S. et al. LEF-1 and TCF-1 orchestrate T(FH) differentiation by regulating differentiation circuits upstream of the transcriptional repressor Bcl6. Nature immunology 16, 980-990 (2015).
Zhou, X. et al. Differentiation and persistence of memory CD8(+) T cells depend on T cell factor 1. Immunity 33, 229-240 (2010).
Scott, A.C. et al. TOX is a critical regulator of tumour-specific T cell differentiation. Nature 571, 270-274 (2019).
MacDonald, B.T., Tamai, K. & He, X. Wnt/beta-catenin signaling: components, mechanisms, and diseases. Dev Cell 17, 9-26 (2009).
Lovatt, M. & Bijlmakers, M.J. Stabilisation of beta-catenin downstream of T cell receptor signalling. PloS one 5 (2010).
van Loosdregt, J. et al. Canonical Wnt signaling negatively modulates regulatory T cell function. Immunity 39, 298-310 (2013).
Sumida, T. et al. Activated beta-catenin in Foxp3(+) regulatory T cells links inflammatory environments to autoimmunity. Nature immunology 19, 1391-1402 (2018).
Mittal, D., Gubin, M.M., Schreiber, R.D. & Smyth, M.J. New insights into cancer immunoediting and its three component phases--elimination, equilibrium and escape. Current opinion in immunology 27, 16-25 (2014).
Wing, J.B., Tanaka, A. & Sakaguchi, S. Human FOXP3(+) Regulatory T Cell Heterogeneity and Function in Autoimmunity and Cancer. Immunity 50, 302-316 (2019).
Salama, P. et al. Tumor-infiltrating FOXP3+ T regulatory cells show strong prognostic significance in colorectal cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 27, 186-192 (2009).
deLeeuw, R.J., Kost, S.E., Kakal, J.A. & Nelson, B.H. The prognostic value of FoxP3+ tumor-infiltrating lymphocytes in cancer: a critical review of the literature. Clinical cancer research : an official journal of the American Association for Cancer Research 18, 3022-3029 (2012).
Sinicrope, F.A. et al. Intraepithelial effector (CD3+)/regulatory (FoxP3+) T-cell ratio predicts a clinical outcome of human colon carcinoma. Gastroenterology 137, 1270-1279 (2009).
Saito, T. et al. Two FOXP3(+)CD4(+) T cell subpopulations distinctly control the prognosis of colorectal cancers. Nature medicine 22, 679-684 (2016).
Feagins, L.A., Souza, R.F. & Spechler, S.J. Carcinogenesis in IBD: potential targets for the prevention of colorectal cancer. Nat Rev Gastroenterol Hepatol 6, 297-305 (2009).
Terzic, J., Grivennikov, S., Karin, E. & Karin, M. Inflammation and colon cancer. Gastroenterology 138, 2101-2114 e2105 (2010).
Blatner, N.R. et al. Expression of RORgammat marks a pathogenic regulatory T cell subset in human colon cancer. Science translational medicine 4, 164ra159 (2012).
Keerthivasan, S. et al. beta-Catenin promotes colitis and colon cancer through imprinting of proinflammatory properties in T cells. Science translational medicine 6, 225ra228 (2014).
Miyara, M. et al. Functional delineation and differentiation dynamics of human CD4+ T cells expressing the FoxP3 transcription factor. Immunity 30, 899-911 (2009).
Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic acids research 28, 27-30 (2000).
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic acids research 45, D353-D361 (2017).
Tosolini, M. et al. Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, th2, treg, th17) in patients with colorectal cancer. Cancer research 71, 1263-1271 (2011).
Beurel, E. & Jope, R.S. Differential regulation of STAT family members by glycogen synthase kinase-3. The Journal of biological chemistry 283, 21934-21944 (2008).
Beurel, E., Michalek, S.M. & Jope, R.S. Innate and adaptive immune responses regulated by glycogen synthase kinase-3 (GSK3). Trends Immunol 31, 24-31 (2010).
Beurel, E., Yeh, W.I., Michalek, S.M., Harrington, L.E. & Jope, R.S. Glycogen synthase kinase-3 is an early determinant in the differentiation of pathogenic Th17 cells. Journal of immunology 186, 1391-1398 (2011).
Wei, L., Laurence, A., Elias, K.M. & O'Shea, J.J. IL-21 is produced by Th17 cells and drives IL-17 production in a STAT3-dependent manner. The Journal of biological chemistry 282, 34605-34610 (2007).
Beurel, E. et al. Regulation of Th1 cells and experimental autoimmune encephalomyelitis by glycogen synthase kinase-3. Journal of immunology 190, 5000-5011 (2013).
O'Shea, J.J. & Paul, W.E. Mechanisms underlying lineage commitment and plasticity of helper CD4+ T cells. Science 327, 1098-1102 (2010).
Kovalovsky, D. et al. Beta-catenin/Tcf determines the outcome of thymic selection in response to alphabetaTCR signaling. Journal of immunology 183, 3873-3884 (2009).
Gounari, F. et al. Loss of adenomatous polyposis coli gene function disrupts thymic development. Nature immunology 6, 800-809 (2005).
Moser, A.R. et al. ApcMin: a mouse model for intestinal and mammary tumorigenesis. Eur J Cancer 31A, 1061-1064 (1995).
You, S. et al. Developmental abnormalities in multiple proliferative tissues of Apc(Min/+) mice. Int J Exp Pathol 87, 227-236 (2006).
Chassaing, B., Aitken, J.D., Malleshappa, M. & Vijay-Kumar, M. Dextran sulfate sodium (DSS)-induced colitis in mice. Curr Protoc Immunol 104, Unit 15 25 (2014).
Cooper, H.S. et al. The role of mutant Apc in the development of dysplasia and cancer in the mouse model of dextran sulfate sodium-induced colitis. Gastroenterology 121, 1407-1416 (2001).
Tanaka, T. et al. Dextran sodium sulfate strongly promotes colorectal carcinogenesis in Apc(Min/+) mice: inflammatory stimuli by dextran sodium sulfate results in development of multiple colonic neoplasms. International journal of cancer. Journal international du cancer 118, 25-34 (2006).
Harada, N. et al. Intestinal polyposis in mice with a dominant stable mutation of the beta-catenin gene. Embo J 18, 5931-5942 (1999).
Rubtsov, Y.P. et al. Regulatory T cell-derived interleukin-10 limits inflammation at environmental interfaces. Immunity 28, 546-558 (2008).
Godfrey, V.L., Wilkinson, J.E. & Russell, L.B. X-linked lymphoreticular disease in the scurfy (sf) mutant mouse. Am J Pathol 138, 1379-1387 (1991).
Brunkow, M.E. et al. Disruption of a new forkhead/winged-helix protein, scurfin, results in the fatal lymphoproliferative disorder of the scurfy mouse. Nature genetics 27, 68-73 (2001).
Wing, K. et al. CTLA-4 control over Foxp3+ regulatory T cell function. Science 322, 271-275 (2008).
Franckaert, D. et al. Promiscuous Foxp3-cre activity reveals a differential requirement for CD28 in Foxp3(+) and Foxp3(-) T cells. Immunology and cell biology 93, 417-423 (2015).
Kitagawa, Y. et al. Guidance of regulatory T cell development by Satb1-dependent super-enhancer establishment. Nature immunology 18, 173-183 (2017).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America 102, 15545-15550 (2005).
Zitvogel, L., Ayyoub, M., Routy, B. & Kroemer, G. Microbiome and Anticancer Immunosurveillance. Cell 165, 276-287 (2016).
Voloshanenko, O. et al. Wnt secretion is required to maintain high levels of Wnt activity in colon cancer cells. Nat Commun 4, 2610 (2013).
Moparthi, L. & Koch, S. Wnt signaling in intestinal inflammation. Differentiation (2019).
Pham, T.H., Okada, T., Matloubian, M., Lo, C.G. & Cyster, J.G. S1P1 receptor signaling overrides retention mediated by G alpha i-coupled receptors to promote T cell egress. Immunity 28, 122-133 (2008).
Turner, J.R. Intestinal mucosal barrier function in health and disease. Nature reviews. Immunology 9, 799-809 (2009).
Konig, J. et al. Human Intestinal Barrier Function in Health and Disease. Clin Transl Gastroenterol 7, e196 (2016).
Schmidt, H.H. et al. HLA Class II tetramers reveal tissue-specific regulatory T cells that suppress T-cell responses in breast carcinoma patients. Oncoimmunology 2, e24962 (2013).
Rathinasamy, A. et al. Tumor specific regulatory T cells in the bone marrow of breast cancer patients selectively upregulate the emigration receptor S1P1. Cancer immunology, immunotherapy : CII 66, 593-603 (2017).
Hoerl, A.E. & Kennard, R.W. Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics 12, 55-67 (1970).
Therneau, T.M. A Package for Survival Analysis in S. 2.38 ed. CRAN.R-project.org; 2015.
Friedman, J.H., Hastie, T. & Tibshirani, R. Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of statistical software 33, 22 (2010).
Kassambara, A., Kosinski, M., Biecek, P. & Fabian, S. Package ‘survminer’. 2017.
Atarashi, K. et al. Th17 Cell Induction by Adhesion of Microbes to Intestinal Epithelial Cells. Cell 163, 367-380 (2015).
Dose, M. et al. beta-Catenin induces T-cell transformation by promoting genomic instability. Proceedings of the National Academy of Sciences of the United States of America 111, 391-396 (2014).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Molecular cell 38, 576-589 (2010).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol 9, R137 (2008).
Robinson, M.D., McCarthy, D.J. & Smyth, G.K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140 (2010).
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7, 562-578 (2012).
Reich, M. et al. GenePattern 2.0. Nature genetics 38, 500-501 (2006).
Shen, L., Shao, N., Liu, X. & Nestler, E. ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases. BMC Genomics 15, 284 (2014).
Freese, N.H., Norris, D.C. & Loraine, A.E. Integrated genome browser: visual analytics platform for genomics. Bioinformatics 32, 2089-2095 (2016).
Tripathi, S. et al. Meta- and Orthogonal Integration of Influenza "OMICs" Data Defines a Role for UBR4 in Virus Budding. Cell Host Microbe 18, 723-735 (2015).

There is NO Competing Interest.

Download PDF

Version 1

posted

You are reading this latest preprint version

Wnt/β-catenin activation epigenetically reprograms Regulatory T cells in IBD and progression to dysplasia.

Status:

Version 1

Abstract

Figures

Introduction

Results

Discussion

Materials And Methods

References

Additional Declarations

Supplementary Files

Status:

Version 1