USE OF CD26 AND CD39 AS NEW PHENOTYPIC MARKERS FOR ASSESSING MATURATION OF FOXP3+ T CELLS AND USES THEREOF FOR DIAGNOSTIC PURPOSES

Abstract

Among regulatory T cells, natural regulatory T cells (nTregs) ensure the control of self-tolerance and are currently tested in clinical trials in autoimmune diseases and allogeneic hematopoietic stem cell transplantation. Here the inventors show that based on CD39/CD26 markers, the human nTreg population is comprised of 5 major cell subsets each representing a distinct state of maturation. Phenotypic and genetic characteristics of the subsets illustrate the structural parental maturation between subsets which further correlates with expression of regulatory factors. Importantly, the inventors also show that blood nTreg CD39/CD26 profile, remaining constant over a 2year period in healthy persons but varying between individuals, represents a novel biomarker for monitoring chronic diseases, as illustrated in their preliminary study on AI (dermatomyositis, rheumatoid arthritis and leukemias). Accordingly, the present invention relates to the use of CD26 and CD39 as phenotypic markers for assessing maturation of natural Treg cells.

Claims

1. A population of Foxp3+ T cells selected from the group consisting of: the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26+CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26−CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26+CD39+, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26−CD39+, and the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26+CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26−CD39−, the population of Foxp3+ T cells (M3) having the following phenotype: CD45RA-CD26+CD39+, and the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26−CD39+.

2. The population of Foxp3+ T cells of claim 1 which is CD4.sup.+ or CD8.sup.+.

3. The population of Foxp3+ T cells of claim 1 which is CD25.sup.+ or CD25.sup.−.

4. The population of Foxp3+ T cells of claim 1 which is selected from the group consisting of: the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N1) having the following phenotype: CD25.sup.+CD45RA.sup.+CD26.sup.+CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N2) having the following phenotype: CD25.sup.+CD45RA.sup.+CD26.sup.−CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N3) having the following phenotype: CD25.sup.+CD45RA.sup.+CD26.sup.+CD39.sup.+, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N4) having the following phenotype: CD25.sup.+CD45RA.sup.+CD26.sup.−CD39.sup.+, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M1) having the following phenotype: CD25.sup.+CD45RA.sup.−CD26.sup.+CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M2) having the following phenotype: CD25.sup.+CD45RA.sup.−CD26.sup.−CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M3) having the following phenotype: CD25.sup.+CD45RA.sup.−CD26.sup.+CD39.sup.+, and the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M4) having the following phenotype: CD25.sup.+CD45RA.sup.−CD26.sup.−CD39.sup.+.

5. The population of Foxp3+ T cells of claim 1 which is selected from the group consisting of: the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N1′) having the following phenotype: CD25.sup.−CD45RA.sup.+CD26.sup.+CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N2′) having the following phenotype: CD25.sup.−CD45RA.sup.+CD26.sup.−CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N3′) having the following phenotype: CD25.sup.−CD45RA.sup.+CD26.sup.+CD39.sup.+, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (N4′) having the following phenotype: CD25.sup.−CD45RA.sup.+CD26.sup.−CD39.sup.+, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M1′) having the following phenotype: CD25.sup.−CD45RA.sup.−CD26.sup.+CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells (M2′) having the following phenotype: CD25.sup.−CD45RA.sup.−CD26.sup.−CD39.sup.−, the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells having (M3′) the following phenotype: CD25.sup.−CD45RA.sup.−CD26.sup.+CD39.sup.+, and the population of CD4.sup.+ Foxp3.sup.+ regulatory T cells having (M4′) the following phenotype: CD25.sup.−CD45RA.sup.−CD26.sup.−CD39.sup.+.

6. (canceled)

7. A method of assessing the maturation stage of a population of Foxp3+ T cells comprising i) detecting the expression of the phenotypic markers CD45RA, CD25, CD26 and CD39 in said population of Foxp3+ T cells and ii) determining a category of maturation stage to which said population of Foxp3+ T cells belongs.

8. (canceled)

9. A method of determining whether a subject suffers from an impaired immune response and/or immunosenescence comprising i) quantifying the amount of at least one population of Foxp3+ T cells according to claim 1 in a sample obtained from the subject, and ii) comparing the amount quantified at step i) with a predetermined reference value wherein detecting a differential between said amount and said predetermined reference value indicates whether the subject suffers from an impaired immune response and/or immunosenescence.

10. A method of determining whether a subject has or is at risk of having a disease that is an autoimmune inflammatory disease, an infectious disease or a cancer and treating the disease comprising i) quantifying the amount of at least one population of Foxp3+ T cells according to claim 1 in a sample obtained from the subject, and ii) treating the disease when there is a difference between the amount quantified in step i) and a corresponding reference value based on healthy controls.

11. A method of determining whether a patient suffering from an autoimmune inflammatory disease, an infectious disease or a cancer will achieve a therapeutic response with a treatment comprising i) quantifying the amount of at least one population of Foxp3+ T cells according to claim 1 in a sample obtained from the patient and ii) and comparing the amount quantified at step i) with a predetermined reference value wherein detecting a differential between said amount and said predetermined reference value indicates whether the patient achieves or does not achieve a therapeutic response with the treatment.

12. A method of determining whether a patient suffering from an autoimmune inflammatory disease, an infectious disease or a cancer is at risk of relapse comprising i) quantifying the amount of at least one population of Foxp3+ T cells according to claim 1 in a sample obtained from the patient, and ii) comparing the amount quantified at step i) with a predetermined reference value wherein detecting a differential between said amount and said predetermined reference value indicates whether the patient is or is not at risk of relapse.

13. A method for predicting the survival time of a subject suffering from a cancer comprising i) quantifying the amount of at least one population of Foxp3+ T cells according to claim 1 in a sample obtained from the subject, and ii) comparing the amount quantified at step i) with a predetermined reference value wherein detecting a differential between said amount and said predetermined reference value indicates whether the patient will have a short or long survival time.

14. The method according to claim 9, wherein at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 populations of Foxp3+ T cells are quantified.

15. The method according to claim 9, wherein the quantification is absolute or relative.

16. The method according to claim 9, wherein the quantification is relative to a population of Foxp3+ T according to claim 1.

17. The method according to claim 9, wherein a ratio between at least 2 populations of cells is calculated and compared to a predetermined reference value, and wherein detecting a differential between said amount and said predetermined reference value indicates respectively: whether the subject suffers from an impaired immune response and/or immunosenescence, or whether the subject has or is at risk of having an autoimmune inflammatory disease, an infectious disease or a cancer, or whether the patient will achieve or will not achieve a therapeutic response treatment with a CD39 inhibitor, or whether the patient is or is not at risk of relapse, or whether the subject has a short or long survival time.

18. The method of claim 17 wherein the ratio between the population (M4) and (M1) is determined, and wherein the higher the M4/M1 ratio, the higher is the probability that the subject has or is at risk of having an autoimmune inflammatory disease.

19. The method of claim 17 wherein the ratio between the population (N4) and (N1) is determined, and wherein the higher the N4/N1 ratio, the higher is the probability that the subject has or is at risk of having a cancer.

20. A method of determining whether a patient suffering from cancer is eligible for treatment with a CD39 inhibitor and if so, treating the patient with the CD39 inhibitor comprising i) quantifying the amount of a population of CD39+ cells selected from the group consisting of selected from the group consisting of: the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26+CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26−CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26+CD39+, the population of Foxp3+ T cells having the following phenotype: CD45RA+CD26−CD39+, and the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26+CD39−, the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26−CD39−, the population of Foxp3+ T cells (M3) having the following phenotype: CD45RA−CD26+CD39+, and the population of Foxp3+ T cells having the following phenotype: CD45RA−CD26−CD39+, and ii) treating the patient with the CD39 inhibitor when a difference between the amount and a predetermined reference value is detected.

21. A kit comprising a panel of antibodies specific for CD3, CD4, CD8, Foxp3, CD25, CD45RA, CD26 and CD39.

22. The method of claim 7, wherein the category is N1, N2, N3, N4, M1, M2, M3 or M4.

23. The method of claim 10, wherein the disease is cancer, the at least one population of Foxp3+ T cells includes the N1, N2, N3 and N4 naïve populations of Foxp3+ T cells, and the step of treating is performed when an increase of the N2, N3 and N4 naive populations and/or a decrease of the N1 naive population is detected, compared to the corresponding reference value.

24. The method of claim 10, wherein the disease is an autoimmune inflammatory disease, the at least one population of Foxp3+ T cells includes the CD25+, CD25−, CD127+ and CD127− populations of Foxp3+ T cells, and the step of treating is performed when a ratio of CD25+/CD25− cells is decreased and a ratio of CD127+/CD127− is increased, compared to the corresponding reference value.

Description

[0158] FIGURES

[0159] FIG. 1. FOXP3 nTreg heterogeneity in healthy human PBMCs analysis. (A1-A2) Boxplots showing the distribution of the 4 nTreg subsets based on their expression of CD39 and CD26 in naive and memory CD25.sup.−nTreg variants. Longitudinal analysis of nTreg subsets frequency in 3 individuals for over a 2-year period. (B) Facs sorted nTreg subsets phenotypic, epigenetic and physiologic characteristic s. (B1) Summary plot of MFI ratio of FOXP3 expression on Treg subsets to Tconv cells. Scatterplot indicating FOXP3−TSDR (B2) and CpG site 1 in the IL-2 region promoter (B3) demethylation status of both the 5 major FACS sorted nTreg subsets (N1, M1-4) and the 2 conventional T cells (C, naive and memory) as assessed by bisulfate pyrosequencing. CFSE-labelled nTreg subsets (N1, M1, M4) and Tconv (4×10.sup.4 per well) were stimulated with 0.5 ug/ml of pbaCD3 in presence of irradiated ΔCD3 feeder. (B4) Measure of IL-2 secretion in culture supernatant from 40h-stimulated T cells by ELISA. (B5) T cell activation status and T cell proliferation were evaluated by the median fluorescence intensity of CD25 expression and the CFSE dilution assay respectively. Data shown are expressed as mean±SEM.

[0160] FIG. 2. Microenvironmental context of TCR stimulation governs nTreg subset parental maturation. (A) N1 cells convert into M1 cells after stimulation in vitro. Histogram indicating the percentage of CD45RI expressed by stimulated N1 cells (n=3). (B) M4 cells convert into M1 cells in vitro when stimulated as above in presence of IL-2, TGF-β and PGE2Histograms indicating both the percentage of CD26 and CD39 exhibited by stimulated M1 cells and their MFI (n=3). (C) M4 cells represent a no return differentiation stage. CFSE-labeled nTreg subsets were stimulated as indicated above. (C1) Histogram indicating the percentage of proliferating cells in stimulated cell culture (n=4). (C2) Histogram showing the percentage of 7-AAD positive stimulated nTreg subsets (D) Graphs showing CD27 and CD28 frequency in the 3 nTreg subsets N1, M1 and M4 expressing either CCR7.sup.+ or CCRT (n=3). (E) Schema of parental maturation process of the nTreg population. Data shown are expressed as mean±SEM.

[0161] FIG. 3: RNA sequencing analysis confirmed both nTreg subsets heterogeneity and parental maturation. N1, Ml and M4 nTreg populations present distinct transcriptomic profiles. (A-B) Principal component analysis performed on whole transcriptome data of 10 nTregs samples obtained by RNA sequencing experiments including 25313 genes in transcripts per kilobase million (TPM).

[0162] FIG. 4. FOXP3+ regulatory blood sub-population's distribution is modified in auto-immunity and cancer. (A, B, C) Data are presented as median with interquartile range in HD compared to DM, RhA and AML. (A) Histogram of CD25+/CD25− (A1) and CD127.sup.−/CD127.sup.− (A2) frequency ratio among CD4.sup.−FOXP3.sup.+ T cells. (B) Scatter plot depict the frequency of N2 population (B1) and N3 population (B2) among nTreg RA.sup.+. (C) Histograms depict the frequency ratio of N4/N1 and M4/M1 among nTreg CD45RA.sup.+ and nTreg CD45RA.sup.− respectively, defined by FOXP3.sup.+CD127.sup.−CD25.sup.+ (C1). Histograms depict the frequency ratio of N4/N1 and M4/M1 among nTreg variant CD45RA.sup.+ and nTreg variant CD45RA.sup.− respectively, defined by FOXP3.sup.+CD127.sup.−CD25− (C2). (D1-2) Kaplan-Meier survival curve representing the survival percentage of relapsing AML patients after HSCT treated by Azacytidine and donor lymphocytes infusion after inclusion. Patients were divided into 2 groups either with low (upper curve) or high (lower curve) ratio. N4/N1 ratio; a 0.2 cut-off was used between high and low ratio (p=0.1) (El). M4/M1 ratio; a 4-cut-off ratio was used between high and low ratio (p=0.01) (E2).

[0163] FIG. 5. Evolution of Treg subpopulations after treatment during dermatomyositis. Data are presented as median with interquartile range in HD compared to DM before and after treatment. (A) Histogram of CD25+/CD25− frequency ratio among CD4.sup.+FOXP3.sup.+ T cells. (B) Histograms depict the frequency ratio of N4/N1 and M4/M1 among nTreg CD45RA.sup.+ and nTreg CD45RA.sup.− respectively, defined by FOXP3.sup.+CD127.sup.−CD25.sup.+.

EXAMPLE

[0164] I—CD39 CD26 Markers Help Delineate Structural Phenotypic and Genetic Heterogeneity of nTregs in Human Blood.

[0165] At a resting stage, nTregs developed in the thymus, are currently characterized by their expression of high levels of CD25, low levels of CD127, expression of the master transcript

[0166] FOXP3 (16), a demethylated TSDR (26) and are not able to synthesize IL-2 thereby being functionally anergic (27). In the present study, nTregs identification in healthy human blood was performed using intracellular FOXP3. The cells were then analyzed for the expression of CD25, CD127, CD45RA in combination with the two functional markers CD26 and CD39. The Visne analysis illustrates that CD4.sup.+ FOXP3.sup.+ CD127.sup.−/low exhibit various expression of CD45RA, CD25, CD39 and CD26 markers supporting nTregs heterogeneity (Data not shown). Furthermore, based on CD39 and CD26 expression, the FOXP3.sup.+ CD127.sup.−/low CD25+ nTreg population and the FOXP3.sup.+ CD127.sup.−/low CD25.sup.−nTreg variant population are respectively comprised of 5 major subsets, i.e., naive CD45RA.sup.+ CD26.sup.+ CD39.sup.−(N1), memory CD45RA−CD26.sup.+ CD39− (M1), CD45RA.sup.−CD26.sup.−CD39.sup.− (M2), CD45RA.sup.−CD26.sup.+ CD39.sup.+ (M3) and CD45RA.sup.−CD26.sup.−CD39.sup.+ (M4) (FIG. 1A1). All the subsets display high FOXP3 expression (FIG. 1B1), associated with a very high demethylation level of TSDR (FIG. 1B2), and, in contrast to memory Tconv cells, they exhibit a relatively low demethylation level of CpG site 1 in the IL-2 promoter, essential for inducing IL-2 production upon TCR activation (FIG. 1B3) (25). Moreover, nTreg subset cells were functionally in an anergic state, given that, following CD3 stimulation, they were unable to synthesize IL-2 (FIG. 1B4), lost their CD25 activating marker and did not proliferate (FIG. 1B5). These characteristics include these subsets in the nTreg lineage definition. Importantly, whereas nTreg subset distribution is stable in each adult individual for over a two-year period (FIG. 1A2), it varies interindividualy (FIG. 1A1). Also, the nTreg subsets distribution is not gender dependent (Data not shown) but does not vary according to age as illustrated in newborn cord blood (Data not shown) and elderly individuals (Data not shown). The use of intracellular FOXP3.sup.+ to identify nTregs population in human PBMCs enabled us to highlight other FOXP3.sup.+ subsets. A subset of CD4.sup.+ bearing CD8 are present at very low frequencies (1.33% in CD4.sup.+ FOXP3.sup.+) (Data not shown). As this discrete population has a similar expression of FOXP3 (Data not shown) and relatively high levels of demethylated TSDR (75%) (Data not shown) as those exhibited by nTregs, they may represent a CD4.sup.+ CD8.sup.+ DP nTreg variant. A memory subset of FOXP3.sup.+ cells with low CD25 expression (19.75%) was also observed (Data not shown). Among this subset, only cells exhibiting CD39.sup.+ expressed a high demethylation level TSDR associated with a partial demethylation of the CpG site 1 in the IL-2 promoter (Data not shown) and a relatively high expression of FOXP3 (Data not shown). We considered these cells as atypical CD25.sup.−nTreg variants. Furthermore, the use of FOXP3 as a marker to identify regulatory T cell subtypes enabled us to characterize an activated CD4.sup.+ FOXP3.sup.+ CD127.sup.+ population in resting PBMCs. This cell population represents 7.55% of the FOXP3.sup.+ CD4.sup.+ T cells, and were CD39−CD26.sup.+ (Data not shown) with a low demethylated levels of TSDR (Data not shown) associated with a lower level of FOXP3 expression than that found in nTregs (Data not shown). This was anticipated given that FOXP3 is a regulatory transcript known to be produced in activated memory conventional T cells following their TCR stimulation (17). Interestingly, by using the regulatory marker CD15S (27), we isolated a small subset of cells (13.2%) in this FOXP3+ CD127.sup.+ population, which express the regulatory protein FOXP3 at a lower MFI level (Data not shown) than that found in nTregs associated with a partially demethylated TSDR (50%) (Data not shown) and other regulatory markers including CD25, CTLA-4, TIGIT, HLA-DR and FCRL3 (Data not shown). It is noteworthy that these cells exhibit, as conventional memory CD4.sup.+ T cells, a high demethylation level of CpG site 1 in the IL-2 promoter region (Data not shown). These data strongly suggest that the very low percentage of CD127.sup.+ CD25.sup.+ FOXP3.sup.+ present in resting blood cells originate from activated memory conventional CD4.sup.+ T cells trans-differentiated to expressing regulatory T cells but did not develop from the thymus as the true nTregs are (1).

[0167] In summary: 1) based on CD39 / CD26 markers human blood nTreg population can be subdivided into 5 major subsets in which expression of FOXP3 is a necessary but not sufficient characteristic to define nTregs. 2) FOXP3 regulatory transcripts expressed by activated T cells (17) may also be expressed by conventional memory CD4.sup.+ CD127.sup.+, though at low levels in healthy human blood.

[0168] II—The Microenvironmental Context of TCR Stimulation Governs nTreg Subset Parental Maturation.

[0169] nTreg subsets from PBMCs were sorted and cultured separately under various different conditioned media. Naive N1 cells, cultured in the presence of different doses of IL-2, express the CD25 marker, loose their anergic state, and convert to memory cells exhibiting a CD26.sup.+CD39.sup.−60 M1 profile (FIG. 2A). Memory M1 cells, when TCR stimulated and cultured with IL-2, convert into M4 cells in the presence of TGF-β plus PGE2 (Data not shown). While TGF-β favors the loss of cell surface CD26 marker (72% to 30%), PGE2 enhances the CD39 marker (25% to 67%) (FIG. 2B). The M1 subset cells, when TCR stimulated, in the presence of IL-2, reached a no return stage to CD39.sup.− M3 or M4 subsets. FIG. 2C shows that, following TCR stimulation in the presence of IL-2, M4 cells, being at an advanced stage of differentiation, proliferate less (FIG. 2C1) and are more susceptible to apoptosis (FIG. 2C2) than N1 and M1 cells after a 4 day-culture. It is noteworthy that the CCR7 CD27 CD28 based naive/CM/EM/TEMRA cell cycle nomenclature currently acknowledged for CD4.sup.+ and CD8.sup.+ T cells (29) does not fit with the nTregs maturation given that CD27 and CD28 markers are maintained all along the nTreg cell cycle (FIG. 2D). FIG. 2.E briefly schematizes the parental maturation process of the nTreg population in healthy individuals: naive precursor (N1) subset cells progress through immature memory (M1) and then to mature memory (M4) via either transient CD26.sup.− (M2) or CD39.sup.+ (M3) subsets.

[0170] III—RNA Sequencing Analysis Confirmed Both nTreg Subsets Heterogeneity and Parental Maturation.

[0171] A—Heterogeneity of nTreg Populations

[0172] In order to characterize the N1, M1 and M4 nTreg populations at a transcriptomic level, RNA sequencing experiments were performed on ten nTregs total RNA samples (4 N1, 3 M1 and 30 3 M4) and generated RNA expression data of 25313 genes in transcripts per kilobase million (TPM). Principal component analysis performed on these data revealed a first component (PC1) explaining 60.15% of the total variance of the transcriptome among the samples which is sufficient to separate them in their three respective groups, i.e. N1, M1 and M4 (FIGS. 3A and 3B). These results were confirmed by unsupervised hierarchical clustering analysis of RNA sequencing data which showed the clustering of the samples in three distinct groups corresponding to N1, M1 and M4, where M1 and M4 samples present transcriptomic profiles closer to each other than those of N1 samples (Data not shown). Further differential expression analysis among the three groups revealed 1886, 2998 and 592 differentially expressed genes with more than twofold change (adjusted (BH) P-value <0.05) between N1 and M1, N1 and M4, and M1 and M4 respectively, including 215 differentially expressed genes between the three groups (Data not shown). Thus the RNA sequencing results demonstrated the transcriptomic heterogeneity of nTregs.

[0173] B—Parental Maturation of nTreg Subsets.

[0174] The RNA sequencing supervised analysis confirms that each nTreg subset tested represents a maturation stage in nTreg life, even though, in resting nTreg cells, expression levels of mRNA and corresponding protein do not systematically parallel. The analysis focused on the mRNA expression of markers characterizing each a different phase of a T cell life. N1 to M1 to M4 maturation is reflected in mRNA expression levels of markers corresponding to cell 1) activation, 2) proliferation, 3) functional regulatory differentiation and 4) senescence (Table 1). Interestingly in this table of 40 relevant markers 1) KI-67 associated with cell cycle phases G1, S, G2, M but blocked in phase GO has been included in the activation but not in the IL-2 dependent proliferation phase, given the nTreg intrinsic inability to produce IL-2 required for proliferation. 2) Due to the low number of tested individuals (3 per subset), a trend but not a significant difference in the mRNA expression level of markers was most often observed. However individuals of each subset most often exhibited the same mRNA maturation profile, though each at a variable magnitude (Table 1).

[0175] IV—Medical Implications

[0176] 1-NTreg CD39/CD26 Profile Provides a Novel Blood Biomarker for Monitoring Chronic Inflammatory Diseases and Post Irradiation Leukemias.

[0177] To investigate alteration of blood FOXP3 subpopulations in chronic inflammatory diseases, cryopreserved PBMCs of 12 untreated dermatomyositis (DM), 18 rheumatoid arthritis (RhA) both treated with immunosuppressive agents (representing auto-immune diseases associated with auto-antibodies and T cell activation) and 10 relapsing acute myeloid leukemia (AML) after hematopoietic stem cell transplantation (HSCT) were compared to 20 healthy adults (Table 2). The data are summarized in FIG. 4.

[0178] Auto-immunity: Whereas there was no difference in the CD4/CD8 ratio and in the frequency of CD4.sup.+ T cells and FOXP3.sup.+ cells within CD4.sup.+ T cells (data not shown), we observed great changes within the FOXP3.sup.+ population. In the FOXP3.sup.+ population, analysis of the flow cytometry profile in auto-immunity revealed a decrease of CD25.sup.+/25.sup.− ratio (FIG. 4A1) and significant increase of CD127.sup.+/CD127.sup.− ratio (FIG. 4A2). The same tendency was observed in SLE. FOXP3 MFI within subpopulations was higher in CD127.sup.−CD25.sup.−CD45RA.sup.− compared to CD127.sup.−CD25.sup.−CD45RA.sup.+ and CD127.sup.+ (Data not shown) suggesting the accumulation of both activated CD127.sup.+ T helper cells expressing low levels of FOXP3 (outbound black disk, Data not shown) and nTregs loosing CD25.sup.+, as a marker of intense activation, expressing high levels of FOXP3 (outbound disk, Data not shown), consistent with previous findings (30). We next questioned whether the CD39/CD26 subset distribution of blood nTreg represents a novel pathogenic biomarker to monitor patients suffering from chronic inflammatory diseases. It revealed an elevation of the M4/M1 ratio (FIG. 4C1-2) in DM both in the CD25.sup.+ nTreg and the CD25.sup.−nTreg variant subsets in relation to an accumulation of the M4 terminal differentiated nTreg population. RhA was associated with marked increase of the N2 subpopulation above in healthy controls.

[0179] Moreover, abnormalities observed at diagnosis during DM reversed at least partially but significantly after treatment arguing for the use of CD39/CD26 subset distribution of blood nTreg as a biomarker of treatment response.

[0180] Acute myeloid leukemia: We observed a significant decrease of CD4+ T cells, as well as a decrease of the CD4.sup.+/CD8.sup.+ ratio and of CD45RA.sup.+ cells both in Tconv and nTregs (Data not shown) after HSCT as described (31). Patients suffering from AML after HSCT exhibited a highly decreased CD25.sup.+/CD25.sup.− ratio (FIG. 4A1), indicating an elevation of a CD25.sup.− abnormal variant. Concerning the CD39/CD26 subset distribution, the M4/M1 was highly elevated (FIG. 4C2) and the nTreg CD45RA.sup.+ distribution was skewed towards an accumulation of the N2, N3, N4 subsets (FIG. 4B1-2) and a decrease of the N1 as shown by the N4/N1 ratio (FIG. 4C1-2). The blood biomarkers study illustrates that within the blood FOXP3 T cell population, chronic inflammatory diseases are associated with an abnormal accumulation of FOXP3.sup.+CD25.sup.− cells and FOXP3.sup.+CD127.sup.+ cells. Also the CD39/CD26 profile of FOXP3 memory cells skewed to a high expression of CD39.sup.+ marker (mainly subset M4), in DM and AML. AML and RhA were, moreover, associated with elevation of respectively both N1, N2 and N3 and N2 populations. Moreover, interestingly both high M4/M1 and N4/N1 ratio were associated with mortality during AML in relapse after HSCT (FIG. 4D1-2).

[0181] FIG. 5 depicts the evolution of Treg subpopulations after treatment during dermatomyositis. In particular, FIG. 5A shows the CD25+/CD25− frequency ratio among CD4.sup.+FOXP3.sup.+ T cells and FIG. 5B depict the frequency ratio of N4/N1 and M4/M1 among nTreg CD45RA.sup.+ and nTreg CD45RA.sup.− respectively, defined by FOXP3.sup.+CD127.sup.−CD25.sup.+.

[0182] Discussion:

[0183] Although there have been over 50,000 publications on nTregs since their discovery in 1994 (1), our basic knowledge of these cells is still ill-defined and even confusing. Given their medical implication in autoimmune diseases (32) and their administration by adoptive transfer to treat these diseases or GVHD (24, 33), it is urgent that we obtain better understanding of these cells. The present study attempts to clarify some critical aspects on nTregs. The first question high lightened concerns as to which subsets of regulatory T cells belong to the nTregs lineage. These cells initially defined by their CD4.sup.+CD25.sup.+ phenotype (1), their natural thymic developmental origin, their necessary but not sufficient FOXP3 transcript expression, were further structurally well identified at a resting stage in human PBMCs, by their demethylated FOXP3-TSDR region (26), and lack of IL-2 production (27). These typic nTregs are distinguished from activated memory T cells originating from different CD4+ or CD8+ subtypes, which, under a tolerogenic microenvironment, transdifferentiate to express the regulatory FOXP3 transcript (17).

[0184] We further found in this study that human blood FOXP3 nTregs exhibit a CD39/CD26− based heterogeneous phenotypic profile comprised of 5 major subsets (FIG. 1). These subsets represent different stages of FOXP3 Treg maturation, as revealed by in vitro experiments carried out on separate subsets under different culture conditions critically including IL 2 and/or PGE2 and/or TGF β (FIG. 2). The supervised analysis of mRNA expression levels of markers implicated in the different phases of nTreg life (cell activation, proliferation, functional regulatory differentiation and senescence) confirm the subsets parental maturation (FIGS. 3A and 3B).

[0185] Most importantly, the present basic studies have relevant medical implications both for clinical diagnostics and therapy. At the clinical level, the finding that the CD39/CD26 profile was stable in healthy individuals over time but variable inter-individually prompted us to evaluate whether this profile represents a novel biomarker to be used for monitoring nTreg dysfunction in chronic inflammatory diseases. Initial phenotypic analysis carried out on PBMCs from AI patients suffering from DM, PAR and SLE as well as from AML patients after HSCT, not only showed disease-specific CD39/CD26 profiles but also abnormal expression of minor nTreg subsets including CD25-M4 variant, N2-4 subsets and FOXP3.sup.+ 127.sup.+ expressing M4 as illustrated in FIG. 4.

REFERENCES

[0186] Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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