Literature DB >> 27683580

Tr1-Like T Cells - An Enigmatic Regulatory T Cell Lineage.

Anna Malgorzata White1, David C Wraith2.   

Abstract

The immune system evolved to respond to foreign invaders and prevent autoimmunity to self-antigens. Several types of regulatory T cells facilitate the latter process. These include a subset of Foxp3(-) CD4(+) T cells able to secrete IL-10 in an antigen-specific manner, type 1 regulatory (Tr1) T cells. Although their suppressive function has been confirmed both in vitro and in vivo, their phenotype remains poorly defined. It has been suggested that the surface markers LAG-3 and CD49b are biomarkers for murine and human Tr1 cells. Here, we discuss these findings in the context of our data regarding the expression pattern of inhibitory receptors (IRs) CD49b, TIM-3, PD-1, TIGIT, LAG-3, and ICOS on Tr1-like human T cells generated in vitro from CD4(+) memory T cells stimulated with αCD3 and αCD28 antibodies. We found that there were no differences in IR expression between IL-10(+) and IL-10(-) T cells. However, CD4(+)IL-10(+) T cells isolated ex vivo, following a short stimulation and cytokine secretion assay, contained significantly higher proportions of TIM-3(+) and PD-1(+) cells. They also expressed significantly higher TIGIT mRNA and showed a trend toward increased TIM-3 mRNA levels. These data led us to conclude that large pools of IRs may be stored intracellularly; hence, they may not represent ideal candidates as cell surface biomarkers for Tr1-like T cells.

Entities:  

Keywords:  CD4+ T cell; IL-10; Tr-1 T cells; inhibitory receptors; peripheral tolerance

Year:  2016        PMID: 27683580      PMCID: PMC5021682          DOI: 10.3389/fimmu.2016.00355

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


CD4+IL-10+ T Cells – A Heterogeneous Population of Cells with a Suppressive Function

In 1997, Groux et al. described a unique population of CD4+ T lymphocytes generated after in vitro stimulation of CD4+ T cells from the T cell receptor (TCR) transgenic DO11-10 mouse with ovalbumin peptide (OVA) and IL-10 or with IL-10 alone. These OVA-specific CD4+ T cells produced high levels of IL-10 and IL-5, moderate levels of IFNγ and TGFβ, low levels of IL-2 and IL-4, and proliferated poorly in response to peptide stimulation (1). High levels of IL-10 suggested a regulatory potential for these cells, since IL-10 is crucial for limiting proinflammatory and autoimmune responses [reviewed in Ref. (2, 3)]. IL-10-deficient mice develop severe colitis, accompanied by tissue damage and excessive inflammation (4). Analysis of this model as well as further studies demonstrated that IL-10 is able to block immune responses at different levels by acting directly and indirectly on both innate and adaptive arms of the immune system [reviewed in Ref. (5)]. As a result, IL-10 can inhibit production of proinflammatory cytokines, antigen presentation, and cell proliferation. In the original paper, the reconstitution of SCID mice with naive CD4+ T cells and OVA-specific CD4+IL-10+ T cell clones resulted in prevention of colitis (1). Later on, several other groups confirmed the antigen-specific suppressive potential of CD4+IL-10+ T cells in vivo using colitis (4), experimental autoimmune encephalomyelitis (EAE) (6–10), collagen-induced arthritis (11), and allergy (12) disease models. Our laboratory has developed an animal model of multiple sclerosis (MS) using a TCR transgenic system. More than 90% of CD4+ T cells in transgenic Tg4 mice express a Vβ8.2 TCR specific for the myelin basic protein (MBP) peptide Ac1–9 presented in the context of MHC I-Au (13). This allowed us to conduct detailed phenotypic analysis of antigen-specific CD4+IL-10+ T cells and identify panel of inhibitory receptors (IRs), which could serve as markers for these cells (7), (see The Need to Discover a Surrogate Marker for Regulatory Tr1-Like T Cells). CD4+IL-10+ T cells can also be generated using human peripheral blood mononuclear cells (PBMC) after stimulation with allogeneic monocytes in the presence of IL-10 (1). They produce high levels of IL-10 and low levels of IL-2 and IL-4, after re-stimulation with αCD3 and αCD28 antibodies, and similar to the murine CD4+IL-10+ T cells can suppress responder CD4+ T cells in vitro (14–17). These results were obtained using several different protocols for the generation of the CD4+IL-10+ T cell population. They involved stimulation with a specific subset of antigen-presenting cells, including plasmacytoid dendritic cells (DCs), immature DCs, or tolerogenic DC (1, 18–20); the presence of cytokines, including IL-10, IL-6, IL-21, or IL-27 (21–24); or using antibodies against various costimulatory molecules, such as CD46, CD2, and CD55 (25, 26), as well as vitamin D3 and immunosuppressive drugs (27). Different laboratories adopted a different set of stimuli, which in their experimental setup worked most efficiently to generate high numbers of CD4+IL-10+ T cells. However, one could question the physiological relevance of such manipulations, because they cannot re-create a complex in vivo environment. Also, different protocols result in the emergence of various subpopulations of CD4+IL-10+ T cells, making characterization of these cells and discovery of specific marker/s of the CD4+IL-10+ T cell population even more challenging. Despite the heterogeneity of the described human CD4+IL-10+ populations, these are generally referred to as T regulatory type 1 cells (Tr1). Nevertheless, it is worth noting that to date, it has not been proven that they represent a unique cell lineage; therefore, we will refer them here as Tr1-like T cells.

The Need to Discover a Surrogate Marker for Regulatory Tr1-Like T Cells

The existence of antigen-specific suppressor Tr1-like T cells makes them an appealing target for designing antigen-specific therapies to treat a wide array of autoimmune diseases and to avoid unnecessary and often burdensome side effects associated with conventional immunosuppressive therapies (28). A constitutively expressed surface marker for Tr1-like T cells would allow us to monitor the emergence, numbers, and functionality of these cells. Many groups have tried to identify such a marker in mouse and man (16, 29–32). In 2013, Gagliani et al. postulated that lymphocyte-activation protein 3 (LAG-3) and CD49b are markers for human Tr1-like T cells (17). LAG-3 belongs to a large family of IRs that are upregulated on activated T cells (33). Here, we discuss the significance of the published findings in the context of other relevant IRs. The in vivo data from our laboratory (7) demonstrated that administration of soluble MBP Ac1–9 peptide, using a dose escalation protocol, resulted in abrogation of EAE, which coincided with appearance of antigen-specific CD4+IL-10+ T cells. A majority of these cells expressed T cell immunoglobulin and mucin domain-3 (TIM-3), T-cell immunoreceptor with Ig and ITIM domains (TIGIT), and 50% of the cells were CD49b+, which is in sharp contrast with the expression pattern observed on the IL-10− T cell subset, where all three markers were present in 6–9% of the cells. Programed cell death protein 1 (PD-1) and LAG-3 were found in the majority of CD4+ T cells, regardless of IL-10 production. These IRs are involved in several mechanisms regulating T cell signaling [reviewed in Ref. (33, 34)]. PD-1 and TIM-3 bind intracellular mediators as SHIP-1/2 (PD-1), Fyn, and PI3K kinase (TIM-3) to deactivate the downstream signaling molecules, and PD-1 can also induce inhibitory genes that inhibit T cell function. TIGIT and LAG-3 prevent optimal signal transduction at the cell membrane by sequestering counter receptors/ligands together with preventing proper formation of the immunological synapse [reviewed in Ref. (33, 34)]. Importantly, these events are dysregulated not only during autoimmune responses (35–37) but also in tumor formation. PD-1, TIM-3, and LAG-3 are found in T cells isolated from melanoma patients (38–40); therefore, their expression on T cells is also relevant for the development of new anticancer therapies. PD-1, belonging to the CD28/CTLA-4 family, provides a negative signal following antigen stimulation [reviewed in Ref. (41)]. Depending on the genetic background, PD-1−/− mice develop a range of autoimmune disorders: lupus-like glomerulonephritis in the C57BL/6 strain, autoimmune dilated cardiomyopathy and gastritis in BALB/C, acute type 1 diabetes mellitus (T1DM) in NOD (42), and myocarditis in MRL, suggesting that other genetic, inherent factors act synergistically with PD-1 in each mouse strain (36). Clearly, PD-1 plays an important role in the maintenance of peripheral tolerance, but due to abundant expression on activated T cells, it is unlikely to be a biomarker for Tr1-like T cells. Apart from PD-1, deficiency in any other of the above-mentioned IRs does not result in the spontaneous development of autoimmune disorders. NOD LAG-3-deficient mice show mild enhancement of T lymphocyte responses, unless crossed with PD-1−/− knockout mice, which causes a lethal myocarditis (36). TIGIT−/− mice are more susceptible to EAE and show only augmented T cell responses when challenged with MOG peptide in vivo (37). CD49b deficiency leads to failure of the establishment of memory T cells in the bone marrow (43), but it does not have any profound effect on peripheral tolerance, while TIM-3−/− mice and mice treated with a TIM-3 Ig fusion protein exhibit moderate defects in induction of antigen-specific tolerance [reviewed in Ref. (44)]. Regarding surface expression, most of the above-mentioned IRs are found in cells with regulatory properties. TIGIT is expressed on human Tr1-like T cells (our observation) but also on human Treg Foxp3+ cells (45). Furthermore, its presence at the cell surface coincides with increased expression of ICOS, TIM-3, and PD-1 on murine Treg cells (37). TIM-3 is upregulated upon activation in vitro in the human Treg subset (46). Recently, it has also been reported that murine CD4+CD49b+ T cells produce high levels of IL-10 and are potent suppressors of arthritis severity when injected in vivo (47). To gain a more detailed understanding of how the expression of PD-1, LAG-3, TIM-3, TIGIT, and ICOS correlates with IL-10 production by human CD4+ T cells, we developed a protocol to generate IL-10+ CD4+ T cells after a different length of stimulation in vitro. The first approach involved isolation of memory and naive T cells and stimulating them with αCD3 and αCD28 antibodies in presence or absence of IL-27, known stimuli for Tr1-like T cell generation (21, 22). IL-27 boosted the percentages of CD4+IL-10+ T cells from 10 to 18% on day 3, which on day 7 decreased to 14% in the presence of IL-27 and 5% in its absence (Figure 1A). However, adding IL-27 did not alter the surface phenotype of Tr1-like T cells (data not shown). Initially, the induction of IL-10 production was accompanied by a slight increase in proportions of cells expressing CD49b and TIM-3 within the IL-10+ T cell subset, but this was not statistically significant. By day 7, CD49b was found in similar percentages on both IL-10+ and IL-10− T cells (Figure 1B). CD49b and TIM-3 were co-expressed by the IL-10+ T cell fraction, but on day 7, CD49b+ cells were mainly TIM-3−. LAG-3 was expressed by 8.6% of IL-10+ T cells on day 7 (Figure 1B), and among these cells, 30% co-expressed TIM-3. The co-expression of LAG-3 and CD49b was observed only on a small proportion of IL-10+ subset (Figure 1B, right panel). The proportion of cells expressing TIGIT was similar between IL-10+ and IL-10− subsets of CD4+ T cells (Figure 1B), and approximately half of them co-expressed TIM-3. Our observations led us to conclude that none of the tested IRs are exclusively expressed on IL-10-producing T cells, and their expression is dynamic, changing over the time course of cell culture.
Figure 1

(A) Naive and memory CD4+ T cells were isolated from PBMC from healthy donors by magnetic selection and stimulated with plate-bound 1 μg/ml αCD3 and 2 μg/ml αCD28 ± 100 ng/ml of IL-27. Intracellular staining for IL-10 was performed on days 3 and 7 after an additional 4-h stimulation with PMA/ionomycin in the presence of Golgi stop. Graphs show the percentages (mean value ± SEM, n = 3 donors) of viable CD4+IL-10+ T cells derived from the naive or memory cell subsets (left panel). A representative dot plot of CD4 and IL-10 staining on memory-derived CD4+ T cells on day 7 is shown in the right panel. (B) Expression of inhibitory receptors (IRs) on CD4+IL-10+/− T cells derived from memory pool after 7 days of cell culture in the presence of 1 μg/ml αCD3 and 2 μg/ml αCD28 examined by flow cytometry. The black bars represent the average percentage of IL-10+ and white bars the IL-10− cell fractions, respectively (mean + SEM, n = 3 donors). Right panel shows a representative dot plot of CD49b and LAG-3 expression on day 7 by memory CD4+IL-10+/− stimulated with αCD3 and αCD28 ± IL-27.

(A) Naive and memory CD4+ T cells were isolated from PBMC from healthy donors by magnetic selection and stimulated with plate-bound 1 μg/ml αCD3 and 2 μg/ml αCD28 ± 100 ng/ml of IL-27. Intracellular staining for IL-10 was performed on days 3 and 7 after an additional 4-h stimulation with PMA/ionomycin in the presence of Golgi stop. Graphs show the percentages (mean value ± SEM, n = 3 donors) of viable CD4+IL-10+ T cells derived from the naive or memory cell subsets (left panel). A representative dot plot of CD4 and IL-10 staining on memory-derived CD4+ T cells on day 7 is shown in the right panel. (B) Expression of inhibitory receptors (IRs) on CD4+IL-10+/− T cells derived from memory pool after 7 days of cell culture in the presence of 1 μg/ml αCD3 and 2 μg/ml αCD28 examined by flow cytometry. The black bars represent the average percentage of IL-10+ and white bars the IL-10− cell fractions, respectively (mean + SEM, n = 3 donors). Right panel shows a representative dot plot of CD49b and LAG-3 expression on day 7 by memory CD4+IL-10+/− stimulated with αCD3 and αCD28 ± IL-27. These results were very different from the data generated in vivo in the tolerance model (7). Therefore, we used a modified version of the protocol previously developed in our laboratory (48), which involved the ex vivo isolation of IL-10+ CD4+ T cells, a short stimulation of unfractionated CD4+ T cells with αCD3 and αCD28 antibodies, followed by IL-10 cytokine secretion assay to allow sorting of IL-10+ cells. This strategy minimized the manipulation of cells in vitro but still allowed us to obtain a sufficient number of CD4+IL-10+ T cells for analysis (3–5% of total CD4+ T cells). The phenotype of highly purified IL-10+ cells differed significantly from the IL-10− subpopulation. TIM-3 expression was significantly higher on IL-10+ T cells as compared to the IL-10− subset (p = 0.0008) and was present in approximately 25% of CD4+ T cells, while 80% of CD4+IL-10+ T cells expressed PD-1 (p = 0.007), which was significantly higher when compared to the IL-10− fraction. Within the PD-1+ T cell population, the percentages of CD49b+ and LAG-3+ cells were lower, both below 10% and although higher than the IL-10+ subset, the differences were not statistically significant (Figure 2A).
Figure 2

(A) The expression of IRs on purified CD4+IL-10+/IL-10− T cells. Magnetically sorted CD4+ T cells were cultured for 16 h in the presence of 1 μg/ml αCD3 and 2 μg/ml of αCD28 antibodies, then harvested, subjected to IL-10 cytokine secretion assay, and sorted by flow cytometry according to their IL-10 expression. Graphs represent the percentages of IL-10+ or IL-10− T cells, expressing each IR determined by flow cytometry (n = 4). Purified CD4+IL-10+/− T cells were rested for 48 h in the presence of 60 U/ml IL-2 and then were restimulated for 4 h with αCD3 and αCD28 antibodies. (B) mRNA levels of IRs on sorted CD4+IL-10+/− T cells. Purified CD4+IL-10+/− T cells were rested for 48 h in the presence of 60 U/ml IL-2 and then were restimulated for 4 h with αCD3 and αCD28 antibodies. Graphs show mean gene expression levels as relative values compared to HPRT-1 (n = 4). (C) Expression of IRs on CD4+IL-10+/− T cell fraction at the point of RNA isolation as evaluated by flow cytometry. Figure shows percentages of viable CD4+IL-10+/− T cells expressing the indicated marker (mean + SEM, n = 4). The significance has been analyzed using t test.

(A) The expression of IRs on purified CD4+IL-10+/IL-10− T cells. Magnetically sorted CD4+ T cells were cultured for 16 h in the presence of 1 μg/ml αCD3 and 2 μg/ml of αCD28 antibodies, then harvested, subjected to IL-10 cytokine secretion assay, and sorted by flow cytometry according to their IL-10 expression. Graphs represent the percentages of IL-10+ or IL-10− T cells, expressing each IR determined by flow cytometry (n = 4). Purified CD4+IL-10+/− T cells were rested for 48 h in the presence of 60 U/ml IL-2 and then were restimulated for 4 h with αCD3 and αCD28 antibodies. (B) mRNA levels of IRs on sorted CD4+IL-10+/− T cells. Purified CD4+IL-10+/− T cells were rested for 48 h in the presence of 60 U/ml IL-2 and then were restimulated for 4 h with αCD3 and αCD28 antibodies. Graphs show mean gene expression levels as relative values compared to HPRT-1 (n = 4). (C) Expression of IRs on CD4+IL-10+/− T cell fraction at the point of RNA isolation as evaluated by flow cytometry. Figure shows percentages of viable CD4+IL-10+/− T cells expressing the indicated marker (mean + SEM, n = 4). The significance has been analyzed using t test. To correlate the surface phenotype with RNA levels, we performed RT-PCR on restimulated IL-10+ and IL-10− cells, which were previously rested for 48 h in the presence of human recombinant IL-2. RT-PCR analysis demonstrated a significant increase in TIGIT expression among IL-10+ T cells (p = 0.03) and a trend toward higher levels of TIM-3 mRNA levels among IL-10+ T cells as compared to the IL-10− T cell subset (Figure 2B), pointing to these two markers as preferential for Tr1-like T cells. However, our flow cytometry analysis of surface IR levels performed at the same time point resulted in a different pattern of expression. There were no statistically significant differences in TIM-3 expression between IL-10+ and IL-10− T cells (approximately 10%), similar to LAG-3+ (5%), much lower as compared to relative RNA levels. By contrast, TIGIT+IL-10+ T cells comprised 25% and PD-1+ 50% of IL-10+ T cells, while their RNA levels were lower than those of TIM-3 and LAG-3. It is also important to note that there were no noticeable differences in the percentages of TIM-3, TIGIT, and PD-1 between IL-10+ and IL-10− T cell subsets at this time point (Figure 2C). This result could be explained by the fact that these IRs are stored intracellularly (49–51) and released to the surface with different kinetics; so although their mRNA is upregulated, this may contribute to intracellular pools rather than cell surface expression of the markers. It has been previously shown that large pools of LAG-3 are stored intracellularly (49), and we were able to detect large proportions of intracellular LAG-3 in both IL-10+ and IL-10− T cells (data not shown). It is possible that the kinetics of LAG-3 release to the cell surface correlates with the suppressive phenotype of the cells. In the same way, surface expression of TIM-3, known to reside in the Golgi apparatus and endoplasmic reticulum (50), could be differentially regulated on the IL-10+ as compared to the CD4+IL-10− subpopulation. There is also evidence for altered regulation of TIM-3 expression in acute myeloid leukemia, where the majority of TIM-3 is expressed on the surface of PMBC as compared to healthy individuals, where TIM-3 is mainly detected intracellularly (51).

Beyond IRs

Due to the lack of any firm evidence demonstrating an exclusive IR marker for Tr1-like T cells, emerging evidence points toward new molecules that might serve as their biomarkers. In 2015, Blumberg’s group published a very elegant study in which they demonstrated that surface expression of TIM-3 is regulated by carcinoembryonic antigen cell adhesion molecule 1 (CEACAM-1), which has the ability to form a heterodimer with TIM-3 in human and murine CD4+ T cells (50). Furthermore, lower proportions of tumor-infiltrating murine CD4+ and CD8+ T cells produced IL-10 after co-blockade of CEACAM-1 and TIM-3 in vivo (50). Equally, one could speculate that CEACAM-1 could also regulate surface expression of TIM-3 on Tr1-like T cells; however, the CEACAM-1 expression on Tr1-like T cells has not yet been studied. It is known that this molecule is expressed on a small population of resting CD4+ T cells in humans and mice (52); hence, it could be a potential candidate for a biomarker for Tr1-like T cells. The second putative candidate is Granzyme B. Previous studies have shown that human and murine CD4+ T cells, which acquire a Tr-1-like phenotype, express Granzyme B (53–55). A recent publication by Schmetterer et al. demonstrates that human CD4+ T cells transduced with the active form of STAT3 produce higher levels of IL-10 and Granzyme B, which was responsible for the suppressive activity of these cells (56). It is worthwhile to point out that the cells did not display elevated levels of CD49b and LAG-3 (56). Interestingly, blocking CEACAM1 increased the cytolytic function of human CD8+ T cells (52); hence, this molecule if expressed on CD4+IL-10+ T cells could influence their cytotoxic function by regulating Granzyme B expression. The third possible candidate to serve as a marker for Tr1-like T cells is class I-restricted T cell-associated molecule (CRTAM) expressed on both CD4+ and CD8+ T cells upon activation. This molecule was upregulated on Tr1-like T cells as a result of tolerance induction after administration of escalating doses of MBP peptide (7). Recently, Saito’s group demonstrated that CRTAM is expressed on a specific subset of CD4+ T cells, which are characterized by high production of IFNγ, expression of Granzyme B, and Eomes after TCR activation, and can develop cytotoxic properties in both mice and humans (57). A comparison of the phenotype of CD4+CRTAM+ T cells with Tr1-like T cells in relation to expression of Granzyme B and CEACAM-1 would provide an insight into the functional differences within a heterogeneous subset of human Tr1-like T cells, especially given that, according to our observations, 50% of these cells expressed IFNγ. In summary, our phenotypic analyses suggest that none of the analyzed IRs can be described as surrogate markers for Tr1-like T cells. Ideally, such a biomarker would be a stable, constitutively expressed cell surface molecule, easily detected on freshly isolated human CD4+ T cells. In the quest to identify it, more detailed analyses using RNA profiling and unbiased proteomics together with studies of epigenetic changes at the IL-10 promoter should be performed. Our laboratory analyzed changes in histone H3 modification at the IL-10 promoter and found similar epigenetic changes in mouse and human CD4+IL-10+ T cells (58). However, Dong et al. found limited epigenetic changes in the status of human IL-10 promoter and a lack of functional memory for IL-10 re-expression in cultured IL-10 secreting cells (59). It is clear that all T cell subsets can secrete IL-10 under certain circumstances (3). Therefore, the question as to whether Tr1 cells constitute a distinct lineage remains open and requires further investigation.

Ethics Statement

NRES Committee North West – Greater Manchester West, Ethical Permission 14/NW/0152. The study did not require consent because it was anonymized study, and we used lymphocyte cones purchased from the NHS blood bank in Bristol, United Kingdom.

Author Contributions

AW performed experimental work and wrote the manuscript. DW coordinated the experimental work and co-wrote the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  58 in total

Review 1.  IL-10-induced anergy in peripheral T cell and reactivation by microenvironmental cytokines: two key steps in specific immunotherapy.

Authors:  C A Akdis; K Blaser
Journal:  FASEB J       Date:  1999-04       Impact factor: 5.191

2.  CEACAM1 regulates TIM-3-mediated tolerance and exhaustion.

Authors:  Yu-Hwa Huang; Chen Zhu; Yasuyuki Kondo; Ana C Anderson; Amit Gandhi; Andrew Russell; Stephanie K Dougan; Britt-Sabina Petersen; Espen Melum; Thomas Pertel; Kiera L Clayton; Monika Raab; Qiang Chen; Nicole Beauchemin; Paul J Yazaki; Michal Pyzik; Mario A Ostrowski; Jonathan N Glickman; Christopher E Rudd; Hidde L Ploegh; Andre Franke; Gregory A Petsko; Vijay K Kuchroo; Richard S Blumberg
Journal:  Nature       Date:  2014-10-26       Impact factor: 49.962

3.  Coexpression of CD49b and LAG-3 identifies human and mouse T regulatory type 1 cells.

Authors:  Nicola Gagliani; Chiara F Magnani; Samuel Huber; Monica E Gianolini; Mauro Pala; Paula Licona-Limon; Binggege Guo; De'Broski R Herbert; Alessandro Bulfone; Filippo Trentini; Clelia Di Serio; Rosa Bacchetta; Marco Andreani; Leonie Brockmann; Silvia Gregori; Richard A Flavell; Maria-Grazia Roncarolo
Journal:  Nat Med       Date:  2013-04-28       Impact factor: 53.440

4.  Cutting edge: TIGIT has T cell-intrinsic inhibitory functions.

Authors:  Nicole Joller; Jason P Hafler; Boel Brynedal; Nasim Kassam; Silvia Spoerl; Steven D Levin; Arlene H Sharpe; Vijay K Kuchroo
Journal:  J Immunol       Date:  2011-01-03       Impact factor: 5.422

Review 5.  Emerging Tim-3 functions in antimicrobial and tumor immunity.

Authors:  Kaori Sakuishi; Pushpa Jayaraman; Samuel M Behar; Ana C Anderson; Vijay K Kuchroo
Journal:  Trends Immunol       Date:  2011-06-21       Impact factor: 16.687

6.  Enhanced frequency of CD18- and CD49b-expressing T cells in peripheral blood of asthmatic patients correlates with disease severity.

Authors:  Massilva Rahmoun; Arnaud Foussat; Hervé Groux; Jérôme Pène; Hans Yssel; Pascal Chanez
Journal:  Int Arch Allergy Immunol       Date:  2006-04-04       Impact factor: 2.749

7.  Interleukin-10-deficient mice develop chronic enterocolitis.

Authors:  R Kühn; J Löhler; D Rennick; K Rajewsky; W Müller
Journal:  Cell       Date:  1993-10-22       Impact factor: 41.582

8.  Differential expression of granzymes A and B in human cytotoxic lymphocyte subsets and T regulatory cells.

Authors:  William J Grossman; James W Verbsky; Benjamin L Tollefsen; Claudia Kemper; John P Atkinson; Timothy J Ley
Journal:  Blood       Date:  2004-07-06       Impact factor: 22.113

9.  Isolation and characterization of human interleukin-10-secreting T cells from peripheral blood.

Authors:  Graziella Mazza; Catherine A Sabatos-Peyton; Rachel E Protheroe; Andrew Herman; John D Campbell; David C Wraith
Journal:  Hum Immunol       Date:  2010-01-07       Impact factor: 2.850

10.  Human tolerogenic DC-10: perspectives for clinical applications.

Authors:  Giada Amodio; Silvia Gregori
Journal:  Transplant Res       Date:  2012-09-28
View more
  30 in total

Review 1.  LAG3 (CD223) as a cancer immunotherapy target.

Authors:  Lawrence P Andrews; Ariel E Marciscano; Charles G Drake; Dario A A Vignali
Journal:  Immunol Rev       Date:  2017-03       Impact factor: 12.988

Review 2.  Neuroinflammation: Extinguishing a blaze of T cells.

Authors:  Nail Benallegue; Hania Kebir; Jorge I Alvarez
Journal:  Immunol Rev       Date:  2022-07-31       Impact factor: 10.983

3.  Smad7 in intestinal CD4+ T cells determines autoimmunity in a spontaneous model of multiple sclerosis.

Authors:  Steffen Haupeltshofer; Teresa Leichsenring; Sarah Berg; Xiomara Pedreiturria; Stephanie C Joachim; Iris Tischoff; Jan-Michel Otte; Tobias Bopp; Massimo C Fantini; Charlotte Esser; Dieter Willbold; Ralf Gold; Simon Faissner; Ingo Kleiter
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-03       Impact factor: 11.205

Review 4.  Tipping the balance: inhibitory checkpoints in intestinal homeostasis.

Authors:  Maria E Joosse; Iris Nederlof; Lucy S K Walker; Janneke N Samsom
Journal:  Mucosal Immunol       Date:  2018-11-29       Impact factor: 7.313

Review 5.  Antigen-specific therapeutic approaches for autoimmunity.

Authors:  Pau Serra; Pere Santamaria
Journal:  Nat Biotechnol       Date:  2019-02-25       Impact factor: 68.164

Review 6.  Understanding LAG-3 Signaling.

Authors:  Luisa Chocarro; Ester Blanco; Miren Zuazo; Hugo Arasanz; Ana Bocanegra; Leticia Fernández-Rubio; Pilar Morente; Gonzalo Fernández-Hinojal; Miriam Echaide; Maider Garnica; Pablo Ramos; Ruth Vera; Grazyna Kochan; David Escors
Journal:  Int J Mol Sci       Date:  2021-05-17       Impact factor: 5.923

7.  hPMSCs inhibit the expression of PD-1 in CD4+IL-10+ T cells and mitigate liver damage in a GVHD mouse model by regulating the crosstalk between Nrf2 and NF-κB signaling pathway.

Authors:  Aiping Zhang; Jiashen Zhang; Xiaohua Li; Hengchao Zhang; Yanlian Xiong; Zhuoya Wang; Nannan Zhao; Feifei Wang; Xiying Luan
Journal:  Stem Cell Res Ther       Date:  2021-06-29       Impact factor: 6.832

Review 8.  Re-Programming Autoreactive T Cells Into T-Regulatory Type 1 Cells for the Treatment of Autoimmunity.

Authors:  Patricia Solé; Pere Santamaria
Journal:  Front Immunol       Date:  2021-07-15       Impact factor: 7.561

9.  Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition).

Authors:  Andrea Cossarizza; Hyun-Dong Chang; Andreas Radbruch; Andreas Acs; Dieter Adam; Sabine Adam-Klages; William W Agace; Nima Aghaeepour; Mübeccel Akdis; Matthieu Allez; Larissa Nogueira Almeida; Giorgia Alvisi; Graham Anderson; Immanuel Andrä; Francesco Annunziato; Achille Anselmo; Petra Bacher; Cosima T Baldari; Sudipto Bari; Vincenzo Barnaba; Joana Barros-Martins; Luca Battistini; Wolfgang Bauer; Sabine Baumgart; Nicole Baumgarth; Dirk Baumjohann; Bianka Baying; Mary Bebawy; Burkhard Becher; Wolfgang Beisker; Vladimir Benes; Rudi Beyaert; Alfonso Blanco; Dominic A Boardman; Christian Bogdan; Jessica G Borger; Giovanna Borsellino; Philip E Boulais; Jolene A Bradford; Dirk Brenner; Ryan R Brinkman; Anna E S Brooks; Dirk H Busch; Martin Büscher; Timothy P Bushnell; Federica Calzetti; Garth Cameron; Ilenia Cammarata; Xuetao Cao; Susanna L Cardell; Stefano Casola; Marco A Cassatella; Andrea Cavani; Antonio Celada; Lucienne Chatenoud; Pratip K Chattopadhyay; Sue Chow; Eleni Christakou; Luka Čičin-Šain; Mario Clerici; Federico S Colombo; Laura Cook; Anne Cooke; Andrea M Cooper; Alexandra J Corbett; Antonio Cosma; Lorenzo Cosmi; Pierre G Coulie; Ana Cumano; Ljiljana Cvetkovic; Van Duc Dang; Chantip Dang-Heine; Martin S Davey; Derek Davies; Sara De Biasi; Genny Del Zotto; Gelo Victoriano Dela Cruz; Michael Delacher; Silvia Della Bella; Paolo Dellabona; Günnur Deniz; Mark Dessing; James P Di Santo; Andreas Diefenbach; Francesco Dieli; Andreas Dolf; Thomas Dörner; Regine J Dress; Diana Dudziak; Michael Dustin; Charles-Antoine Dutertre; Friederike Ebner; Sidonia B G Eckle; Matthias Edinger; Pascale Eede; Götz R A Ehrhardt; Marcus Eich; Pablo Engel; Britta Engelhardt; Anna Erdei; Charlotte Esser; Bart Everts; Maximilien Evrard; Christine S Falk; Todd A Fehniger; Mar Felipo-Benavent; Helen Ferry; Markus Feuerer; Andrew Filby; Kata Filkor; Simon Fillatreau; Marie Follo; Irmgard Förster; John Foster; Gemma A Foulds; Britta Frehse; Paul S Frenette; Stefan Frischbutter; Wolfgang Fritzsche; David W Galbraith; Anastasia Gangaev; Natalio Garbi; Brice Gaudilliere; Ricardo T Gazzinelli; Jens Geginat; Wilhelm Gerner; Nicholas A Gherardin; Kamran Ghoreschi; Lara Gibellini; Florent Ginhoux; Keisuke Goda; Dale I Godfrey; Christoph Goettlinger; Jose M González-Navajas; Carl S Goodyear; Andrea Gori; Jane L Grogan; Daryl Grummitt; Andreas Grützkau; Claudia Haftmann; Jonas Hahn; Hamida Hammad; Günter Hämmerling; Leo Hansmann; Goran Hansson; Christopher M Harpur; Susanne Hartmann; Andrea Hauser; Anja E Hauser; David L Haviland; David Hedley; Daniela C Hernández; Guadalupe Herrera; Martin Herrmann; Christoph Hess; Thomas Höfer; Petra Hoffmann; Kristin Hogquist; Tristan Holland; Thomas Höllt; Rikard Holmdahl; Pleun Hombrink; Jessica P Houston; Bimba F Hoyer; Bo Huang; Fang-Ping Huang; Johanna E Huber; Jochen Huehn; Michael Hundemer; Christopher A Hunter; William Y K Hwang; Anna Iannone; Florian Ingelfinger; Sabine M Ivison; Hans-Martin Jäck; Peter K Jani; Beatriz Jávega; Stipan Jonjic; Toralf Kaiser; Tomas Kalina; Thomas Kamradt; Stefan H E Kaufmann; Baerbel Keller; Steven L C Ketelaars; Ahad Khalilnezhad; Srijit Khan; Jan Kisielow; Paul Klenerman; Jasmin Knopf; Hui-Fern Koay; Katja Kobow; Jay K Kolls; Wan Ting Kong; Manfred Kopf; Thomas Korn; Katharina Kriegsmann; Hendy Kristyanto; Thomas Kroneis; Andreas Krueger; Jenny Kühne; Christian Kukat; Désirée Kunkel; Heike Kunze-Schumacher; Tomohiro Kurosaki; Christian Kurts; Pia Kvistborg; Immanuel Kwok; Jonathan Landry; Olivier Lantz; Paola Lanuti; Francesca LaRosa; Agnès Lehuen; Salomé LeibundGut-Landmann; Michael D Leipold; Leslie Y T Leung; Megan K Levings; Andreia C Lino; Francesco Liotta; Virginia Litwin; Yanling Liu; Hans-Gustaf Ljunggren; Michael Lohoff; Giovanna Lombardi; Lilly Lopez; Miguel López-Botet; Amy E Lovett-Racke; Erik Lubberts; Herve Luche; Burkhard Ludewig; Enrico Lugli; Sebastian Lunemann; Holden T Maecker; Laura Maggi; Orla Maguire; Florian Mair; Kerstin H Mair; Alberto Mantovani; Rudolf A Manz; Aaron J Marshall; Alicia Martínez-Romero; Glòria Martrus; Ivana Marventano; Wlodzimierz Maslinski; Giuseppe Matarese; Anna Vittoria Mattioli; Christian Maueröder; Alessio Mazzoni; James McCluskey; Mairi McGrath; Helen M McGuire; Iain B McInnes; Henrik E Mei; Fritz Melchers; Susanne Melzer; Dirk Mielenz; Stephen D Miller; Kingston H G Mills; Hans Minderman; Jenny Mjösberg; Jonni Moore; Barry Moran; Lorenzo Moretta; Tim R Mosmann; Susann Müller; Gabriele Multhoff; Luis Enrique Muñoz; Christian Münz; Toshinori Nakayama; Milena Nasi; Katrin Neumann; Lai Guan Ng; Antonia Niedobitek; Sussan Nourshargh; Gabriel Núñez; José-Enrique O'Connor; Aaron Ochel; Anna Oja; Diana Ordonez; Alberto Orfao; Eva Orlowski-Oliver; Wenjun Ouyang; Annette Oxenius; Raghavendra Palankar; Isabel Panse; Kovit Pattanapanyasat; Malte Paulsen; Dinko Pavlinic; Livius Penter; Pärt Peterson; Christian Peth; Jordi Petriz; Federica Piancone; Winfried F Pickl; Silvia Piconese; Marcello Pinti; A Graham Pockley; Malgorzata Justyna Podolska; Zhiyong Poon; Katharina Pracht; Immo Prinz; Carlo E M Pucillo; Sally A Quataert; Linda Quatrini; Kylie M Quinn; Helena Radbruch; Tim R D J Radstake; Susann Rahmig; Hans-Peter Rahn; Bartek Rajwa; Gevitha Ravichandran; Yotam Raz; Jonathan A Rebhahn; Diether Recktenwald; Dorothea Reimer; Caetano Reis e Sousa; Ester B M Remmerswaal; Lisa Richter; Laura G Rico; Andy Riddell; Aja M Rieger; J Paul Robinson; Chiara Romagnani; Anna Rubartelli; Jürgen Ruland; Armin Saalmüller; Yvan Saeys; Takashi Saito; Shimon Sakaguchi; Francisco Sala-de-Oyanguren; Yvonne Samstag; Sharon Sanderson; Inga Sandrock; Angela Santoni; Ramon Bellmàs Sanz; Marina Saresella; Catherine Sautes-Fridman; Birgit Sawitzki; Linda Schadt; Alexander Scheffold; Hans U Scherer; Matthias Schiemann; Frank A Schildberg; Esther Schimisky; Andreas Schlitzer; Josephine Schlosser; Stephan Schmid; Steffen Schmitt; Kilian Schober; Daniel Schraivogel; Wolfgang Schuh; Thomas Schüler; Reiner Schulte; Axel Ronald Schulz; Sebastian R Schulz; Cristiano Scottá; Daniel Scott-Algara; David P Sester; T Vincent Shankey; Bruno Silva-Santos; Anna Katharina Simon; Katarzyna M Sitnik; Silvano Sozzani; Daniel E Speiser; Josef Spidlen; Anders Stahlberg; Alan M Stall; Natalie Stanley; Regina Stark; Christina Stehle; Tobit Steinmetz; Hannes Stockinger; Yousuke Takahama; Kiyoshi Takeda; Leonard Tan; Attila Tárnok; Gisa Tiegs; Gergely Toldi; Julia Tornack; Elisabetta Traggiai; Mohamed Trebak; Timothy I M Tree; Joe Trotter; John Trowsdale; Maria Tsoumakidou; Henning Ulrich; Sophia Urbanczyk; Willem van de Veen; Maries van den Broek; Edwin van der Pol; Sofie Van Gassen; Gert Van Isterdael; René A W van Lier; Marc Veldhoen; Salvador Vento-Asturias; Paulo Vieira; David Voehringer; Hans-Dieter Volk; Anouk von Borstel; Konrad von Volkmann; Ari Waisman; Rachael V Walker; Paul K Wallace; Sa A Wang; Xin M Wang; Michael D Ward; Kirsten A Ward-Hartstonge; Klaus Warnatz; Gary Warnes; Sarah Warth; Claudia Waskow; James V Watson; Carsten Watzl; Leonie Wegener; Thomas Weisenburger; Annika Wiedemann; Jürgen Wienands; Anneke Wilharm; Robert John Wilkinson; Gerald Willimsky; James B Wing; Rieke Winkelmann; Thomas H Winkler; Oliver F Wirz; Alicia Wong; Peter Wurst; Jennie H M Yang; Juhao Yang; Maria Yazdanbakhsh; Liping Yu; Alice Yue; Hanlin Zhang; Yi Zhao; Susanne Maria Ziegler; Christina Zielinski; Jakob Zimmermann; Arturo Zychlinsky
Journal:  Eur J Immunol       Date:  2019-10       Impact factor: 6.688

Review 10.  Harnessing Mechanisms of Immune Tolerance to Improve Outcomes in Solid Organ Transplantation: A Review.

Authors:  Priscila Ferreira Slepicka; Mahboubeh Yazdanifar; Alice Bertaina
Journal:  Front Immunol       Date:  2021-06-10       Impact factor: 7.561

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.