Methods for reducing the likelihood of and treating graft-versus-host disease

Abstract

The present disclosure provides a method for reducing the likelihood of or treating graft-vs-host disease in a subject by performing assays on GI biopsies from the subject to measure cell numbers and density ratios and by administering to the subject a pharmaceutically effective amount of one or more immunosuppressant agents.

Description

METHODS FOR REDUCING THE LIKELIHOOD OF AND TREATING GRAFT- VERSUS-HOST DISEASEFIELD

[0001] The present disclosure relates to methods for reducing the likelihood of and treating graft- vs-host disease by determining cell type densities and cell density ratios in GI biopsies and administering an immunosuppressant.BACKGROUND

[0002] Hematopoietic cellular transplantation (HCT) is an important treatment for high risk hematologic malignancies (e.g., leukemia, lymphoma, multiple myeloma, acute leukemia, acute myeloid leukemia, dysplastic condition, acute lymphocytic leukemia). Graft-versus- host disease (GVHD) is a major cause of non-relapse mortality post-HCT.

[0003] HCT is also used to treat non-malignant genetic disorders of the blood or immune system (e.g., severe combined immunodeficiency, hemophagocytic lymphohistiocytosis (HLH), hemoglobin disorders such as thalassemia, sickle cell anemia) in which a less severe GVHD effect is beneficial. GVHD is also a major cause of mortality during HCT for these disorders.SUMMARY

[0004] The present invention provides a method for identifying a subject suffering from graft- vs- host disease (GVHD) as a candidate for treatment with one or more immunosuppressant agents, comprising performing an assay on a biopsy from the subject to make: a) at least one group 1 measurement selected from the following group consisting of : % of CD4 conventional T cells in T cells; cell density ratio of regulatory Treg cells:CD8 effector T cells; % of GITR"Ki67" cells in regulatory Treg cells; % of GITR" cells in CD4 conventional-act T cells; % of GITR’ cells in CD8-act T cells; % of regulatory Treg cells in FOXP3+cells; % of GZMB GZMK Ki67’ cells in CD103+cells; % of non-act cells in CD4 conventional T cells: % of GZ'Ki67' cells in CD4 conventional T cells; % of GZ"Ki67" cells in CD8 T cells; % of non-act cells in CD8 T cells; % of GZMB GZMK'Ki67’ cells in CD8 T cells; and % of GZMB'GZMK" Ki67’ cells in CD4 T cells;{02961119.3}b) at least one group 2 measurement selected from the following group consisting of : cell density ratio of CD4 conventional T cells:CD8 T cells; cell density ratio of CD3 cells:CD8 T cells; cell density ratio of epithelial cells:CD8 T cells; cell density ratio of eosinophil cells:CD8 T cells; cell density ratio of neutrophil cells:CD8 T cells; cell density ratio of plasma cells:CD8 T cells; cell density ratio of CD20 T cells:CD8 T cells; cell density ratio of dendritic cells:CD8 T cells; cell density ratio of CD68 cells:CD8 T cells; cell density ratio of NK cells:CD8 T cells; and % of GZ“Ki67+cells in CD8 T cells; c) at least one group 3 measurement selected from the following group consisting of : % of CD8 cells in T cells; % of GITR+Ki67‘ cells in regulatory Treg cells; % of GITR+cells in CD4 conventional-act T cells; % of GITR+Ki67+cells in regulatory Treg cells; % of GZMK+cells in CD8 T cells; % of G1TR+cells in CD9-act T cells; % of FOXP3+CD8 cells in T cells; % of GZMB+cells in CD 103+ cells; % of non-canonical CD8 T cells in FOXP3+cells; % of CD3’ CD8+cells in FOXP3+cells; % of regulatory Treg cells in T cells; % of GZ+Ki67~ cells in CD8 T cells; and % of GZMK+cells in CD4 T cells; and d) at least one group 4 measurement selected from the following group consisting of : % of GZ+Ki67't' cells in CD4 conventional T cells; % of GZ+Ki67+cells in CD8 T cells; % ofcCD3+CD8+ cells in FOXP3+cells; % of act-cells in CD4 conventional T cells; % of GZ^Kib?’ cells in CD4 conventional T cells; % of KI67+cells in CD8 T cells; % of act-cells in CD8 T cells; % of GZMB+ cells in CD8 T cells; % of GZMK+cells in CD103+cells; % of GZ~K167+cells in CD4 conventional T cells; % of KI67+ cells in CD4 T cells; % of GZMB+cells in CD4 T cells; % of KI67+cells in CD103+cells; and % of GITR Ki67+cells in regulatory Treg cells, as determined based on tire performed assay.

[0005] The present invention also provides a method for treating graft-vs-host disease (GVHD) in a subject in need thereof comprising: a) performing or having performed an assay on a biopsy from the subject to make: i) at least one group 1 measurement selected from the following group consisting of : % of CD4 conventional T cells in T cells; cell densi ty ratio of regulatory Treg cells:CD8 effector T cells; % of GITR‘K167‘ cells in regulatory Treg cells; % of GITR~ cells in CD4 conventional-act T cells; % of GITR' cells in CD8-act T cells; % of regulatory Treg cells in FOXP3+cells; % of GZMB GZMK Ki67’ cells in CD103+cells;% of non-act cells in CD4 conventional T cells; % of GZ’Ki67~ cells in CD4 conventional T cells; % of GZ’Ki67" cells in CD8 T cells; % of non-act cells in CD8 T cells; % of GZMB~GZMK"Ki67" cells in CDS T cells; and % of GZMB'GZMK"Ki67" cells in CD4 T cells; ii) at least one group 2 measurement selected from the following group consisting of : cell density ratio of CD4 conventional T cells:CD8 T cells; cell density ratio of CD3 cells:CD8 T cells; cell density ratio of epithelial cells:CD8 T cells; cell density ratio of eosinophil cells:CD8 T cells; cell density ratio of neutrophil cells:CD8 T cells; cell density ratio of plasma cells:CD8 T cells; cell density ratio of CD20 T cells:CD8 T cells; cell density ratio of dendritic cells:CD8 T cells; cell density ratio of CD68 cells:CD8 T cells; cell density ratio of NK cells:CD8 T cells; and % of GZ’Ki67+cells in CD8 T cells; iii) at least one group 3 measurement selected from the following group consisting of : % of CD8 cells in T cells; % of GITR+Ki67' cells in regulatory Treg cells; % of GITR+cells in CD4 conventional-act T cells; % of GITR+Ki67+cells in regulatory Treg cells; % of GZMK+cells in CD8 T cells; % of GITR+cells in CD9-act T cells; % of FOXP3+CD8 cells in T cells; % of GZMB+cells in CD103+ cells; % of non-canonical CD8 T cells in FOXP3+ cells; % of CD3 CD8+cells in FOXP3+ cells; % of regulatory Treg cells in T cells; % of GZ+Ki67‘ cells in CD8 T cells; and % of GZMK+cells in CD4 T cells; and iv) at least one group 4 measurement selected from the following group consisting of : % of GZ+Ki67+cells in CD4 conventional T cells; % of GZ+Ki67+cells in CD8 T cells; % of CD3+CD8+cells in FOXP3+cells; % of act-cells in CD4 conventional T cells; % of GZ+Ki67" cells in CD4 conventional T cells; % of KI67+cells in CD8 T cells; % of act-cells in CD8 T cells; % of GZMB+ cells in CD8 T cells; % of GZMK+cells in CD103+cells; % of GZ’Ki67+cells in CD4 conventional T cells; % of KI67+ cells in CD4 T cells; % of GZMB+cells in CD4 T cells; % of KI67+cells in CD103+cells; and % of GITR Ki67 ' cells in regulatory Treg cells, as determined based on the performed assay; and b) administering to the subject a pharmaceutically effective amount of one or more immunosuppressant agents based on the measurements conducted.

[0006] In one embodiment, each measurement is evaluated for its ability to predict whether the subject will respond to steroid therapy using a receiver operating characteristic (ROC) curve. In a further embodiment, the area under the ROC curve (AUC) or the Fl -score are used for the evaluation.

[0007] In another embodiment, a heatmap of the Pearson correlation coefficient (R) between all measurements is used to predict whether the subject will respond to steroid therapy.

[0008] In another embodiment, at least 2 measurements are made from group 1, group 2, group 3, or group 4.

[0009] In another embodiment, at least 2 measurements are made from each of group 1, group 2, group 3, and group 4.

[0010] In another embodiment, at least 3 measurements are made from group 1, group 2, group 3, or group 4.

[0011] In another embodiment, at least 3 measurements are made from group 1, group 2, group 3, or group 4.

[0012] In another embodiment, at least 4 measurements are made from group 1, group 2, group 3, or group 4.

[0013] In another embodiment, wherein at least 4 measurements are made from group 1, group 2, group 3, or group 4.

[0014] The present disclosure also provides a method for identifying a subject suffering from graft-vs-host disease (GVHD) as a candidate for treatment with one or more immunosuppressant agents, comprising performing an assay on a biopsy from the subject to determine a cell density ratio in the biopsy from the subject, wherein the cell density ratio is the ratio of CD8 effector Tcells:CD4 conventional T cells, CD8 effector T cells:epithelial cells, CD8 effector T cells:CD68 cells, or CD8 effector T cells:regulatory Treg cells, as determined based on the made assay.

[0015] The present disclosure also provides a method for treating GVHD in a subject in need thereof comprising: a) performing or having performed an assay on a biopsy from the subject to determine a cell density ratio in the biopsy from the subject, wherein the cell density ratio is the ratio of CD8 effector T cells :CD4 conventional T cells, CD8 effector T cells:epithelial cells, CD8 effector T cells: CD68 cells, or CD8 effector T cells:Treg cells, as determined based on the performed assay; and b) administering to the subject a pharmaceutically effective amount of one or more immunosuppressant agents based on the cell density ratio.

[0016] In one embodiment, the assay of the present disclosure is an immunohistochemistry assay.

[0017] In another embodiment, the cell density ratio of CD8 effector T cells to CD4 conventional T cells is less than about 1.5 (e.g., 1.4, 1.3, 1.2, 1.1, 1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, or 0.01).

[0018] In yet another embodiment, the cell density ratio of CD8 effector T cells:CD4 conventional T cells is from about 0.01 to about 1.5 (e.g., 0.01 to 1.4, 0.01 to 1.4, 0.01 to 1.3, 0.01 to 1.2, 0.01 to 1.1, 0.01 to 1, 0.01 to 0.9, 0.01 to 0.8, 0.01 to 0.7, 0.01 to 0.5, or 0.01 to 0.4). In another embodiment, the cell density ratio of effector T cells :CD4 conventional T cells is from about 0.1 to about 0.8.

[0019] In a further embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is less than about 0.7 (e.g., 0.65, 0.6, 0.55, 0.5, 0.45, 0.4, 0.3, 0.2, or 0.1).

[0020] In another embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is from about 0.002 to about 0.7 (e.g., 0.002 to 0.65, 0.002 to 0.60, 0.002 to 0.55, 0.002 to 0.5,0.002 to 0.45, 0.002 to 0.4, 0.002 to 0.35, 0.002 to 0.3, 0.002 to 0.25, or 0.002 to 0.2). In a further embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is from about 0.002 to about 0.5.

[0021] In yet another embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is less than about 0.8 (e.g., 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, or 0.05).

[0022] In a further embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is from about 0.01 to about 0.8 (e.g., 0.01 to 0.7, 0.01 to 0.6, 0.01 to 0.5, 0.01 to 0.4, 0.01 to 0.3, 0.01. to 0.2, 0.01 to 0.1, or 0.01 to 0.05). In a further embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is from about 0.1 to about 0.4.

[0023] In yet another embodiment, the cell density ratio of Treg cells: epithelial cells is less than about 32 (e.g., 30, 25, 20, 15, 10, 7, 5, or 4).

[0024] In a further embodiment, the cell density ratio of CD8 effector T cells:Treg cells is from about 0.1 to about 32 (e.g., 0.5 to 32, 1.0 to 32, 2.0 to 32, 5.0 to 32, 7.0 to 32, 8 to 32, 9 to 32, or 1.0 to 32). In another embodiment, the cell density ratio of CD8 effector T cells:Treg cells is from about 1 to about 15.

[0025] In yet another embodiment, the cell density ratio of CD8 effector T cells:CD4 conventional T cells is higher than about 0.3 (e.g., 0.5, 1.0, 1.5, 2.0, or 2.5).

[0026] In a further embodiment, the cell density ratio of CD8 effector T cells:CD4 conventional T cells is from about 0.3 to about 3.0 (e.g., 0.5 to 3.0, 0.7 to 3.0, 0.8 to 3.0, or 1.0 to 3.0). In another embodiment, the cell density ratio of CD8 effector T cells:CD4 conventional T cells is from about 0.5 to about 2.5.

[0027] In yet another embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is more than about 0.008 (e.g., 0.01, 0.05, 0.1, 0.4, 0.6, 0.8, 1.0, 1.1, or 1.2).

[0028] In a further embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is from about 0.008 to about 1.2 (e.g., 0.01 to 1.2, 0.15 to 1.2, 0.2 to 1.2, 0.4 to 1.2 or 0.5 to 1.2). In another embodiment, the cell density ratio of CD8 effector T cells: epithelial cells is from about 0.01 to about 1.2.

[0029] In yet another embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is more than about 0.1 (e.g., 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or 1.0).

[0030] In a further embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is from about 0.1 to about 1.0 (e.g., 0.2 to 1.0, 0.3 to 1.0, 0.4 to 1.0, 0.5 to 1.0. or 0.6 to 1.0). In another embodiment, the cell density ratio of CD8 effector T cells:CD68 cells is from about 0.2 to about 0.8.

[0031] In yet another embodiment, the immunosuppressant agent used in the method of the present disclosure is at least one steroid such as for example a corticosteroid. In a further embodiment, the at least one corticosteroid is prednisone, methylprednisolone, dexamethasone, beclomethasone, or budesonide.

[0032] In a further embodiment, the immunosuppressant agent used in the method of the present disclosure is not a steroid or is not a corticosteroid.

[0033] In a further embodiment, the one or more immunosuppressant agents include but are not limited to cyclosporine, tacrolimus (also known as FK-506 or Fujimycin), methotrexate, mycophenoate mofetil, antithymocyte globulin (ATG), monoclonal antibodies (e.g., anti-CD3, - CD5, and -IL-2 antibodies, anti-CD20 (rituximab), and alemtuzumab (Campath)), anti-TNF drugs (e.g., etanercept (Enbrel®), infliximab, adlimumab), JAK pathway inhibitors (e.g. ruxolitinib and others), lymphocyte immune globulin (Atgam®), sirolimus, ustekinumab, extracorporeal photophoresis (ECP), anti-CD3 drugs (e.g.,Visilizumab and OKT3), anti-CD5 drug and anti-IL-2(CD25) drugs (inolimomab, basiliximab, daclizumab, and denileukin diftitox), anti-CD147 drugs (e.g., Alefacept), anti-ILl R drugs, (e.g., Anakinra), anti-integrin drugs (e.g.,a407 antagonist vedolizumab (Entyvio®), a4 antagonist natalizumab (Tysabri®), and 07 antagonist etrolizumab), mesenchymal stem cells, and regulatory T cells.BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1: Figure 1 shows CD20 cells density (mm2) in gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0035] Figure 2: Figure 2 shows CD3 cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0036] Figure 3: Figure 3 shows CD68 cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0037] Figure 4: Figure 4 shows CD 8 T cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0038] Figure 5: Figure 5 shows CD4 conventional T cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0039] Figure 6: Figure 6 shows regulatory T cells (‘Tregs”) density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density + SEM.

[0040] Figure 7: Figure 7 shows the ratio of CD8 T cells density over Tregs density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density ratio + SEM.

[0041] Figure 8: Figure 8 shows the ratio of CD8 T cells density over CD4 conventional T cells density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density ratio + SEM.

[0042] Figure 9: Figure 9 shows the ratio of CD8 T cells density over CD68 cells density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation, no GI inflammation and GI rare apoptosis as median cell density ratio + SEM.

[0043] Figure 10: Figure 10 shows CD20 cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0044] Figure 11: Figure 11 shows CD3 cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0045] Figure 12: Figure 12 shows CD68 cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0046] Figure 13: Figure 13 shows CD8 T cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0047] Figure 14: Figure 14 shows CD4 conventional T cells density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GIinflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0048] Figure 15: Figure 15 shows Tregs density (mm2) in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density + SEM.

[0049] Figure 16: Figure 16 shows the ratio of CD8 T cells density over Tregs density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density ratio + SEM.

[0050] Figure 17: Figure 17 shows the ratio of CD8 T cells density over CD4 conventional T cells density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density ratio + SEM.

[0051] Figure 18: Figure 18 shows the ratio of CD8 T cells density over CD68 cells density in the gastrointestinal (GI) biopsies taken from hematopoietic stem cell transplant patients with GI inflammation who either responded or not responded to steroid treatment as median cell density ratio + SEM.

[0052] Figure 19: Figure 19 shows the Receiver Operating Characteristics (“ROC”) curve and Area Under Curve (“AUC”) indicating the predictability of steroid treatment of graft-vs-host disease in hematopoietic stem cell transplant patients with GI inflammation using the ratio of CD8 T cells density over Tregs density.

[0053] Figure 20: Figure 20 shows the Receiver Operating Characteristics (“ROC”) curve and Area Under Curve (“AUC”) indicating the predictability of steroid treatment of graft-vs-host disease in hematopoietic stem cell transplant patients with GI inflammation using the ratio of CD8 T cells density over CD4 conventional T cells density.

[0054] Figure 21: Figure 22 shows the Receiver Operating Characteristics (“ROC”) curve and Area Under Curve (“AUC”) indicating the predictability of steroid treatment of graft-vs-host disease in hematopoietic stem cell transplant patients with GI inflammation using the ratio of CD8 T cells density over CD68 cells density.

[0055] Figure 22: Figure 22 shows the Receiver Operating Characteristics (“ROC”) curve and Area Under Curve (“AUC”) indicating the predictability of steroid treatment of graft-vs-host disease in hematopoietic stem cell transplant patients with GI inflammation using the ratio CD8 T cells density over epithelial cells density.

[0056] Figure 23: Figure 23 shows a K-Nearest Neighbors (KNN) based classifier using the following four cell density ratios: CD8 effector T cells:CD4 conventional T cells, CD8 effector T cells: epithelial cells, CD8 effector T cells:CD68 cells, and CD8 effector T cells:regulatory Treg cells.

[0057] Figure 24: Figure 24 shows CD20 cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0058] Figure 25: Figure 25 shows CD3 cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0059] Figure 26: Figure 26 shows CD4 conventional T cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0060] Figure 27: Figure 27 shows CD68 cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0061] Figure 28: Figure 28 shows CD8 T cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0062] Figure 29: Figure 29 shows dendritic cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0063] Figure 30: Figure 30 shows eosinophil cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0064] Figure 31: Figure 31 shows epithelial cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0065] Figure 32: Figure 32 shows neutrophil cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0066] Figure 33: Figure 33 shows NK cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0067] Figure 34: Figure 34 shows plasma cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0068] Figure 35: Figure 35 shows regulatory Treg cells density (mm2) from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0069] Figure 36: Figure 36 shows the ratio of CD20 cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0070] Figure 37: Figure 37 shows the ratio of CD3 cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0071] Figure 38: Figure 38 shows the ratio of CD4 conventional T cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0072] Figure 39: Figure 39 shows the ratio of CD68 cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0073] Figure 40: Figure 40 shows the ratio of dendritic cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0074] Figure 41: Figure 41 shows the ratio of eosinophil cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patientswith rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0075] Figure 42: Figure 42 shows the ratio of epithelial cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0076] Figure 43: Figure 43 shows the ratio of neutrophil cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0077] Figure 44: Figure 44 shows the ratio of NK cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0078] Figure 45: Figure 45 shows the ratio of plasma cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0079] Figure 46: Figure 46 shows the ratio of regulatory Treg cells density over CD8 T cells density with log transformation and normalization across all samples to the range [0,1] from patients with rare apoptosis (‘RA”), no inflammation (“NO-INF”), inflammation with response to steroid therapy (“INF-R”), and inflammation without response to steroid therapy (“INF-NR”).

[0080] Figure 47: Figure 47 shows a heat map of the Pearson correlation coefficient (R) between several features. Each feature corresponds to a row which are from top to bottom as follows: % of CD4 conventional T cells in T cells; cell density ratio of regulatory Treg cells:CD8 effector Tcells; % of GITR K167' cells in regulatory Treg cells; % of GITR" cells in CD4 conventional-act T cells; % of GITR' cells in CD8-act T cells; % of regulatory Treg cells in FOXP3+cells; % of GZMB GZMK Ki67‘ cells in CD103+cells; % of non-act cells in CD4 conventional T cells; % of GZ Ki67‘ cells in CD4 conventional T cells; % of GZ Ki67‘ cells in CD8 T cells; % of non-act cells in CD8 T cells; % of GZMB GZMK Ki67 cells in CD8 T cells; % of GZMB GZMK Ki67 cells in CD4 T cells; cell density ratio of CD4 conventional T cells:CD8 T cells; cell density ratio of CD3 cells:CD8 T cells; cell density ratio of epithelial cells:CD8 T cells; cell density ratio of eosinophil cells:CD8 T cells; cell density ratio of neutrophil cells:CD8 T cells; cell density ratio of plasma cells:CD8 T cells; cell density ratio of CD20 cells:CD8 T cells; cell density ratio of dendritic cells:CD8 T cells; cell density ratio of CD68 cells:CD8 T cells; cell density ratio of NK cells:CD8 T cells; % of GZ Ki67+cells in CD8 T cells; % of CD8 cells in T cells; % of GITR+Ki67‘ cells in regulatory Treg cells; % of GITR+cells in CD4 conventional-act T cells; % of GITR+Ki67+cells in regulatory Treg cells; % of GZMK+cells in CD8 T cells; % of GITR+cells in CD9-act T cells; % of FOXP3+CD8 cells in T cells; % of GZMB+cells in CD103+cells; % of non-canonical CD8 T cells (other) in FOXP3+cells; % of CD3 CD8+cells in FOXP3+cells; % of regulatory Treg cells in T cells; % of GZ+Ki67‘ cells in CD8 T cells; % of GZMK+cells in CD4 T cells; % of GZ+Ki67+cells in CD4 conventional T cells; % of GZ+Ki67+cells in CD8 T cells; % of CD3+CD8+cells in F0XP3+cells; % of act-cells in CD4 conventional T cells; % of GZ+Ki67‘ cells in CD4 conventional T cells; % of KI67+cells in CD8 T cells; % of act-cells in CD8 T cells; % of GZMB+ cells in CD8 T cells; % of GZMK+cells in CD103+cells; % of GZ Ki67+cells in CD4 conventional T cells; % of KI67+ cells in CD4 T cells; % of GZMB+cells in CD4 T cells; % of KI67+cells in CD103+cells; and % of GITR Ki67+cells in regulatory Treg cells.DETAILED DESCRIPTION

[0081] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in the art to which the disclosures belong. All patents, patent applications, published applications and publications, websites and other published materials referred to throughout the entire disclosure herein, unless noted otherwise, are incorporated by reference in their entirety for any purpose. Although any methods andmaterials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, the preferred methods are described.

[0082] While various embodiments and aspects of the present invention are shown and described herein, it will be obvious to those skilled in the art that such embodiments and aspects are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention.

[0083] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described. All documents, or portions of documents, cited in the application including, without limitation, patents, patent applications, articles, books, manuals, and treatises are hereby expressly incorporated by reference in their entirety for any purpose.Definitions

[0084] In this application, the use of the singular includes the plural unless specifically stated otherwise. As used herein, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0085] The term “and / or” refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative ( “or”).

[0086] The term “or” refers to any one member of a particular list and also includes any combination of members of that list.

[0087] The singular forms of the articles “a,” “an” and “the” include plural references unless the context clearly dictates otherwise. For example, the term “a protein” or “at least one protein” can include a plurality of proteins, including mixtures thereof.

[0088] A cell marker indication such as for example “CD8” not followed by a negative sign is equivalent to the cell marker followed by a positive sign “CD8+”. A negative indication after a cell marker is an indication of the absence of the cell marker.

[0089] Unless otherwise indicated, statistically significant means p<0.05.

[0090] As used herein, the term “about” is intended to also include the exact amount. Hence “about 5 percent” means “about 5 percent” and also “5 percent.” “About” means within typical experimental error for the application or purpose intended. Unless otherwise apparent from the context, the term “about” encompasses values within a standard margin of error of measurement (e.g., SEM) of a stated value.

[0091] As used herein, the term “administration” and the like refers to and includes the administration of a composition to a subject or system (e.g., to a cell, organ, tissue, organism, or relevant component or set of components thereof). The skilled artisan will appreciate that route of administration may vary depending, for example, on the subject or system to which the composition is being administered, the nature of the composition, the purpose of the administration, etc. For example, in certain embodiments, administration to an animal subject (e.g., to a human or a rodent) may be bronchial (including by bronchial instillation), buccal, enteral, interdermal, intraarterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, mucosal, intranasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (including by intratracheal instillation), transdermal, vaginal and / or vitreal. In some embodiments, administration may involve intermittent dosing. In some embodiments, administration may involve continuous dosing (e.g., perfusion) for at least a selected period of time. In one embodiment, the term “administration” may refer to providing or giving a subject a therapeutic agent, by any effective route. Exemplary routes of administration are described herein above.

[0092] As used herein, the term “effective” applied to dose or amount refers to that quantity of a compound or pharmaceutical composition that is sufficient to result in a desired activity uponadministration to a subject in need thereof. Note that when a combination of active ingredients is administered, the effective amount of the combination may or may not include amounts of each ingredient that would have been effective if administered individually. The exact amount required will vary from subject to subject, depending on the species, age, and general condition of the subject, the severity of the condition being treated, the particular drug or drugs employed, the mode of administration, and the like.

[0093] As used herein, “locally” or “local administration” means administration at a particular site of the body intended for a local effect and not a systemic effect. Examples of local administration are epicutaneous, inhalational, intra-articular, intrathecal, intravaginal, intravitreal, intrauterine, intra-lesional administration, lymph node administration, intratumoral administration, administration to the inner ear, and administration to a mucous membrane of the subject, wherein the administration is intended to have a local and not a systemic effect.

[0094] As used herein, the term “pharmaceutical composition” refers to a mixture containing a therapeutic agent, optionally in combination with one or more pharmaceutically acceptable excipients, diluents, and / or carriers, to be administered to a subject, such as a mammal, e.g., a human, in order to prevent, treat or control a particular disease or condition affecting or that may affect the subject.

[0095] As used herein, the term “pharmaceutically acceptable” refers to those compounds, materials, compositions and / or dosage forms, which are suitable for contact with the tissues of a subject, such as a mammal (e.g., a human) without excessive toxicity, irritation, allergic response and other problem complications commensurate with a reasonable benefit / risk ratio. Preferably, the term “pharmaceutically acceptable” means approved by a regulatory agency of the Federal or a state government or listed in the U.S. Pharmacopeia or other generally recognized pharmacopeia for use in mammals, and more particularly in humans.

[0096] As used herein, the term “sample” refers to a specimen (e.g., blood, blood component (e.g., serum or plasma), urine, saliva, amniotic fluid, cerebrospinal fluid, tissue (e.g., placental or dermal), pancreatic fluid, chorionic villus sample, and cells) isolated from a subject.

[0097] As used herein, the term “patient” or “subject in need thereof or “subject” refers to a living organism suffering from or prone to a disease (e.g. graft- versus-host disease, cancer, etc.) or condition that can be treated by administration of a compound or pharmaceutical composition or by a method, as provided herein. Non-limiting examples include humans, other mammals, bovines, rats, mice, dogs, monkeys, goat, sheep, cows, deer, and other non-mammalian animals. In embodiments, a patient is human. In embodiments, a subject is human. The terms individual, subject, and patient by themselves do not denote a particular age, sex, race, and the like. Thus, individuals of any age, whether male or female, are intended to be covered by the present disclosure. Likewise, the methods of the present invention can be applied to any race, including, for example, Caucasian (white), African-American (black), Native American, Native Hawaiian, Hispanic, Latino, Asian, and European.

[0098] In certain embodiments, the subject in need thereof is the recipient of a tissue transplant / transfusion. In embodiments, the subject in need thereof is the patient in which the likelihood of graft vs host disease is being reduced. In embodiments, the subject in need thereof is the patient in which graft vs host disease is being treated.

[0099] Diagnosis may be performed by any method or technique known in the art. One skilled in the art will understand that a subject to be treated according to the present disclosure may have been subjected to standard tests or may have been identified, without examination, as one at risk due to the presence of one or more risk factors associated with the disease or condition.

[0100] As used herein, “treatment” and “treating” of a state, disorder or condition can include: (1) preventing, delaying, or reducing the incidence and / or likelihood of the appearance of at least one clinical or sub-clinical symptom of the state, disorder or condition developing in a subject that may be afflicted with or predisposed to the state, disorder or condition, but does not yet experience or display clinical or subclinical symptoms of the state, disorder or condition; or (2) inhibiting the state, disorder or condition, i.e., arresting, reducing or delaying the development of the disease or a relapse thereof or at least one clinical or sub-clinical symptom thereof; or (3) relieving the disease, i.e., causing regression of the state, disorder or condition or at least one ofits clinical or sub-clinical symptoms. The benefit to a subject to be treated is either statistically significant or at least perceptible to the patient or to the physician.Hematopoietic Stem Cell Transplants and Graft- Versus-Host Disease

[0101] For patients with high-risk malignant and non-malignant hematologic diseases, hematopoietic stem cell transplant (HCT) often represents the only option for cure. However, HCT is fraught with complications, leading to high rates of toxicity and patient death. The principal causes of early non-relapse mortality are acute graft-versus-host disease (aGVHD) and infection.

[0102] Graft-versus-host disease or “GVHD” is a significant complication that occurs after an allogeneic bone marrow transplant (transplant from another individual). It happens when the donated bone marrow or peripheral blood stem cells see the recipient's body as foreign, causing the donated cells (graft) to attack the recipient (host).

[0103] The pathophysiology of GVHD includes three phases: 1) activation of APCs (antigen presenting cells); 2) activation, proliferation, differentiation and migration of effector cells; and 3) target tissue destruction. Activation of APC occurs in the first stage of GVHD. Prior to hematopoietic stem cell transplantation, radiation or chemotherapy results in damage of host tissues, especially intestinal mucosa. This allows the microbial products to enter and stimulate pro-inflammatory cytokines such as IL-1 and TNF-a. These pro-inflammatory cytokines increase the expression of MHC and adhesion molecules on APCs, thereby increasing the ability of APC to present antigens. The second phase is characterized by the activation of effector cells.

[0104] Activation of donor T-cells further enhances the expression of MHC and adhesion molecules, chemokines and the expansion of CD 8 + and CD4 + T cells and guest B cells. In the final phase, these effector cells migrate to target organs and mediate tissue damage, resulting in multi-organ failure. Activated cells are indicated herein as “act”.

[0105] Antigen presenting cells or “APC” are a heterogeneous group of immune cells that mediate the cellular immune response by processing and presenting antigens for recognition by certain lymphocytes, for example T cells. The antigens are typically complexed with major histocompatibility complexes (MHCs) on the APC surface for display. APCs include dendritic cells, macrophages, Langerhans cells and B cells. DCs are the most potent professional APCs known to elicit primary T cell responses.

[0106] Dendritic cells or “DCs” are antigen-presenting cells of the immune system. Dendritic cells process antigens and in embodiments present the processed antigen on the cell surface. In embodiments, presentation of processed antigen results in activation and / or proliferation of T cells (e.g. helper T-cells, killer T cells). DCs include conventional dendritic cells (also referred to as myeloid dendritic cells) which typically secrete IL- 12, IL-6, and TNF. DCs include plasmacytoid dendritic cells (pDC) which typically produce high amounts of interferon a. DCs may express certain markers including one or more of CD303, CD141, and CDlc.

[0107] “CD4+ T cells”, “CD4 T cells”, or “helper T cells, are a type of lymphocyte that helps coordinate the immune response against infection and disease. They interact and activate other cells in the immune system. Conventional CD4+ T cells present bacterial antigens to induce cytotoxic and memory CD8+ T cell responses. They also capture and kill bacteria from infected dendritic cells in a process termed transphagocytosis. CD4+ T cells function by further activating memory B cells and cytotoxic T cells, which leads to a larger immune response.

[0108] There are two major types of T cells, “conventional” and “unconventional”, and which operate in fundamentally different ways to mediate and coordinate the immune response. Conventional T cells as those with the capacity for immunologic memory, as opposed to the subsequent elucidation of a phenotypically and functionally distinct set of unconventional T cells. Conventional T cells mediate a highly evolved system that centers on the ability of their collectively diverse T-cell receptors (TCRs), each composed of a heterodimeric a[3 chain, to recognize processed antigenic peptide presented within the grooves of major histocompatibility complex (MHC) molecules on other cells. In contrast to the diverse repertoire of a0 TCR on conventional T cells, unconventional T cells have a more limited TCR repertoire in the form ofcells expressing either an alternative γδ TCR, or a non-diverse α TCR defining a population of so-called invariant natural killer T (iNKT) cells.

[0109] “Treg” or “regulatory T cell” is a subpopulation of T-cells that is capable of suppressing activation of the immune system. Treg cells typically express CD4, CD25, and Foxp3. Treg cells typically express low amounts of or no CD127. Treg cells suppress pro-inflammatory cytokine production and proliferation of T effector cells.

[0110] B cells are lymphocytes, a type of white blood cell (leukocyte), that develops into a plasma cell (a “mature B cell”), which produces antibodies. B cells are antigen-presenting cells, which present processed antigen in that binds to receptors on the B cell surface (e.g. MHC-II molecules). For example, B cells may bind to an antigen by way of a B cell receptor. The antigen may be taken up into the B cell, processed, and the processed antigen may be presented on the surface of the B cell.

[0111] GVHD may be classified as acute or chronic GVHD. Acute GVHD is characterized by selective damage to organs and tissues including, but not limited to, the liver, skin (rash), mucosa, and gastrointestinal (GI) tract. Chronic GVHD also attacks the above organs, but over a long-term course of chronic GVHD can cause damage to the connective tissue and exocrine glands, as well as many other organs and tissues in the body. GI GVHD can result in severe intestinal inflammation, sloughing of the mucosal membrane, severe or high- volume diarrhea, gastrointestinal bleeding, abdominal pain, nausea, anorexia and vomiting. GI GVHD can be diagnosed via intestinal biopsy.

[0112] Acute GVHD (aGVHD) affects 40-60% of hematopoietic stem cell transplant patients and targets the skin, liver, and gastrointestinal (GI) tract. There are 4 stages of severity of disease for each organ affected by a GVHD, from a low grade of 1 to a high grade of 4. A human subject with grade 4 GVHD usually has a poor prognosis. If the GVHD is severe and requires intense immunosuppression involving steroids and additional agents to control the GVHD, then the subject may develop severe infections as a result of the immunosuppression and may die of infection.

[0113] The median onset of acute GVHD is approximately one month after transplant. Acute GVHD (aGVHD) is measured by dysfunction in the three organ systems: the skin, liver and gastrointestinal (GI) tract (Ferrara et al., Lancet 373: 1550-61, 2009). Acute GVHD of the GI tract affects up to 60% of patients receiving allogeneic HCT (Martin et al., Biol. Blood Marrow Transpl. 10: 320-7, 2004). This dysfunction manifests with nausea, vomiting, anorexia, secretory diarrhea and, in more severe cases, abdominal pain and / or hemorrhage.

[0114] Acute GVHD can be clinically indistinguishable from other causes of GI dysfunction such as conditioning regimen toxicity, infection or medication use. Endoscopic biopsy is used to confirm the diagnosis of acute GVHD.

[0115] The principal causes of early non-relapse mortality in HCT patients are acute graft- versus-host disease (aGVHD) and infection. Within aGVHD, the leading cause of death is steroid-refractory (SR) aGVHD. Two issues with SR GI aGVHD predominate, which can significantly impede treatment progress in the field: (1) the mechanisms driving steroid- refractory GI aGVHD are unknown which significantly slows treatment development for SR aGVHD; and (2) there is no accurate test by which to predict SR versus steroid-sensitive (SS) aGVHD at the time of diagnosis. This represents a major barrier, which impedes clinical trial design for up-front therapies to improve outcomes for SR disease, and delays effective treatment for those patients who can be SR, thus increasing the poor prognosis of such patients.

[0116] Lower GI GVHD responds poorly to treatment compared to other target organs, and treatment with high-dose systemic steroid therapy carries significant risks, especially infectious complications in immunosuppressed patients. Thus, developing a test to predict (SS) a GHVD and (SR) aGHVD patients is important to developing up-front therapies for SR patients. Therapies that include for example, non-steroid immunosuppressive agents, can be more effective in treating or reducing the likelihood of developing (SR) aGVHD, if administered early.

[0117] The present disclosure provides a method for identifying SR vs SS GI aGVHD by determining in GI biopsies the density ratio of CD8 effector T cells to at least one cell typeselected from the group consisting of: CD4 conventional T cells, epithelial cells, CD68 cell, and Treg cells. Elevated density ratios as described herein are indicative of SR GI aGVHD and such patients would benefit from treatment using non-steroid immunosuppressive agents.

[0118] The amount of a cell population may be determined in a tissue sample taken from a GI biopsy by flow cytometry, by immunohistochemistry (for example, ELISA) and / or by RNA / DNA analysis using reagents / method known to those skilled in the art.Biopsy and tissue sample

[0119] A tissue sample from a subject (e.g., a tissue sample obtained from a subject, e.g., a subject suffering from GVHD) can be used as a source of cells, a source of RNA, a source of protein, or a source of thin sections for immunohistochemistry (IHC) for measuring the amount of CD8 effector T cells, CD4 conventional T cells, epithelial cells, CD68 cells, regulatory Treg cells, and epithelial cells in the sample. The tissue sample can be obtained by using conventional biopsy instruments and procedures. Endoscopic biopsy, excisional biopsy and incisional biopsy are examples of recognized medical procedures that can be used by one of skill in the art to obtain gastrointestinal tissue samples. In one embodiment, the tissue sample is large enough to provide sufficient cells, RNA, protein, or thin sections for measuring a marker gene (e.g., Pan- CK, DAPI, CD3, CD8, CD20, FoxP3, GITR, CD68, Granzyme B, Granzyme K, CD103, Ki67, ECP, NCR1, BCMA, CD11c, and MPO) expression level or visualizing individual cells by flow cytometry, IHC, or ELISA.

[0120] The tissue sample can be in any form sufficient for cell sorting, RNA extraction, protein extraction, or preparation of thin sections. Accordingly, the tissue sample can be fresh, preserved through suitable cryogenic techniques, or preserved through non-cryogenic techniques. A standard process for handling clinical biopsy specimens is to fix the tissue sample in formalin and then embed it in paraffin. Samples in this form are commonly known as formalin- fixed, paraffin-embedded (FFPE) tissue. Suitable techniques of tissue preparation for subsequent analysis are well-known to those of skill in the art.Immunohistochemistry

[0121] Distinct cell populations may be also determined by immunohistochemistry (IHC). Specifically, the number of CD8 effector T cells, CD4 conventional T cells, epithelial cells, CD68 cells, regulatory Treg cells, and epithelial cells in a given cell population can be determined (e.g., visualized) by IHC. For example, assaying a CD8 T cell population by IHC requires, for example, at least one antibody against a CD8 protein, e.g., at least one anti-CD8 antibody. In exemplary embodiments, the anti-CD8 antibody is labeled with a labels, e.g., a fluorescent label.

[0122] For IHC studies, for example, paraffin-embedded formalin fixed tissues samples can be sliced into sections, e.g., 5 micron sections. Typically, the tissue sections are initially treated in such a way as to retrieve the antigenic structure of proteins that were fixed in the initial process of collecting and preserving the tissue material. Slides are then blocked to prevent non-specific binding by the detection antibodies. The presence of, for example, Pan-CK, DAPI, CD3, CD8, CD20, FoxP3, GITR, CD68, Granzyme B, Granzyme K, CD103, Ki67, ECP, NCR1, BCMA, CD11c, and MPO are then detected by binding their respective antibodies. The detection (primary) antibody is linked to a fluorescent label, either directly or indirectly, e.g., through a secondary antibody or polymer that specifically recognizes the detection (primary) antibody. Typically, the tissue sections are washed and blocked with non-specific protein such as bovine serum albumin between steps. The samples may be counterstained with hematoxylin and / or eosin.Flow Cytometry

[0123] Cell populations may be sorted based on cell surface markers by flow cytometry (e.g., fluorescence activated cell sorting (FACS) analysis). Methods for sorting and counting cells by FACS analysis are well-established and known to those of skill in the art. In general, cells obtained from a blood sample or a tissue sample may be prepared in a single cell suspension. Cells are then labeled with a fluorescent tag (e.g., a fluorescently labeled antibody to a cell surface marker present on the cell population(s) to be identified). The fluorescence can be direct or indirect. For direct fluorescence, a fluorescent tag (e.g., fluorescein, rhodamine, or another fluorochrome) is covalently attached to a primary antibody. For indirect fluorescence, theprimary antibody that binds to a marker present on the cell surface is not labeled with a fluorescent tag. The primary antibody is bound to the cell surface of the targeted cell population. Unbound antibody is removed by a washing step. A fluorescently-tagged secondary antibody that binds the primary antibody is added and any unbound antibody is removed by a washing step.

[0124] FACS analysis can be performed with live or fixed cells. FACS instruments are available to those skilled in the art and include FACScan, FACStar Plus, and FACSCalibur (Becton-Dickinson). FACS analysis software is available to those skilled in the art and includes FlowJo, CellQuest Pro (Becton-Dickinson), and WinMDI (Windows Multiple Document Interface for Flow Cytometry).

[0125] A person skilled in the art will appreciate that FACS analysis can be conducted with a single antibody or multiple antibodies for identifying, counting, and sorting distinct cell populations. For example, a cell population label with a single antibody can be detected and sorted from cells that do not express the specified marker (e.g., CD20 cells can be identified by an antibody specific for CD20).

[0126] A FACS instrument equipped with multiple lasers and fluorescence detectors allows for the use of multiple-antibody labeling and can precisely identify a target cell population. To achieve detection, cells can be labeled with multiple antibodies, each tagged with a different fluorescent label.Data Analysis

[0127] In some embodiments, a method for distinguishing SS from SR aGVHD may include at least one of many methods from machine learning (ML) that are known to persons skilled in the art. Machine learning methods that may be used for data analysis including both prediction and inference. A trained machine-learning classifier can generate an inference of whether the density and density ratio data of the present disclosure is indicative of SS or SR aGVHD. Machine learning methods that may be used by the present disclosure include but are not limited to K-Nearest Neighbors (KNN), Perceptron, Naive Bayes, Decision Tree, Logistic Regression, Artificial Neural Networks / Deep Learning and Support Vector Machine.

[0128] Receiver operating characteristic (ROC) curve is a way to assess the accuracy of model predictions or the ability of a parameter to distinguish between two groups. ROC curves plot sensitivity (the proportion of true positives) versus (1 -specificity) (the proportion of false positives) for different thresholds. The area under the ROC curve (AUC) or the C statistic summarizes the ROC curve and represents the probability that the model or the parameter will correctly rank a random pair of subjects from the two groups.

[0129] K-Nearest-Neighbors (KNN) is an approach to data classification that estimates how likely a data point is to be a member of one group or the other depending on what group the data points nearest to it are in.EXAMPLE 1 - HEMATOPOIETIC CELLULAR TRANSPLANTATION

[0130] Patients underwent hematopoietic stem cell transplantation for both malignant and non- malignant hematologic diseases. These include: acute lymphocytic leukemia, acute myeloid leukemia, myelodysplastic syndrome, bone marrow failure syndromes, metabolic disorders, hemoglobinopathies and other hematologic disorders.EXAMPLE 2 - GASTROINTESTINAL BIOPSIES

[0131] A first analysis of patients (n=122) transplanted who received a first endoscopy for suspected lower GI aGVHD was performed before an assessment of an SR vs SS status was made.

[0132] A second analysis of patients (n=47) transplanted who received a first endoscopy for suspected lower GI aGVHD was performed before an assessment of an SR (n=20) vs SS (n=27) status was made.

[0133] The biopsies were conducted by a gastroenterologist using standard endoscopy techniques as described elsewhere in this application.EXAMPLE 3 - STEROID TREATMENT OF HEMATOPOIETIC CELLULAR TRANSPLANTATION PATIENTS

[0134] Patients who were characterized were treated with steroids based on standards in the field, and per the treating physician’s clinical decision-making.EXAMPLE 4 - FIRST ANALYSIS MEASUREMENTS OF CELL DENSITIY AND PRPORTIONS OF MULTIPLE CELLULAR AND IMMUNE INFILTRATES INTO THE GI TRACT

[0135] Each of the sigmoid colonic biopsies described in Example 2 as part of the first analysis was analyzed with a series of multiplexed IHC panels, capable of tracking both the density and proportions of multiple cellular and immune infiltrates into the GI tract as indicated below. The markers interrogated include: Pan-CK, DAPI, CD3, CD8, CD20, FoxP3, GITR, CD68, Granzyme B, Granzyme K, CD103, Ki67, ECP, NCR1, BCMA, CDllc, and MPO. Sections were stained with multiplex IHC panels to detect the markers. Immune cell subsets were detected using quantitative image analysis. Density and ratio were calculated. Receiver Operator Characteristic (ROC) and K-Nearest Neighbors (KNN) classification were used to identify optimal thresholds to distinguish SS from SR aGVHD.

[0136] Certain cell subtypes were identified based on the following staining patterns as shown in Table 1.Table 1. Cell type staining patterns.Materials and MethodsMultiplex Immunohistochemistry

[0137] A fully automated Multiplex Immunohistochemistry assay was performed on the Ventana Discovery ULTRA platform (Ventana Medical Systems, Tucson, AZ), and as previously described (Marron T et al., The Lancet, 2022).

[0138] The assays were optimized for colon tissue samples. Optimal concentrations of each antibody were determined, and they were applied in the following sequence and detected with the indicated fluorophore.Pan-Immune Panel

[0139] The Pan-Immune Panel contained the following:-Rabbit Anti-CD20 (Clone SP263, Abeam, ab64088) was detected with DISCOVERY - Rhodamine 6G (Roche, Part number: 7988168001).-Rabbit anti-CD3 (Clone SP162, Abeam, ab 135372) was detected with DISCOVERY DCC (Roche, Part number: 7988192001).-Rabbit anti-CD8 (Clone SP239, Abeam, abl78089) was detected with DISCOVERY RED 610 (Roche, Part number: 7988176001).-Rabbit Anti-CD68 (Clone SP251, Abeam, ab 192847) was detected with DISCOVERY Cy5 (Roche, Part number: 7551215001).-Rabbit Anti-FOXP3 (Clone SP97, Abeam, ab99963) was detected with DISCOVERY FAM (Roche, Part number: 7988150001).

[0140] Following staining, the tissue was counter-stained and cover slipped with Invitrogen ProLong Gold Antifade Mountant with NucBlue. Whole slide imaging was performed on the Zeiss Axioscan which was equipped with a Colibri light source and appropriate filters for visualizing these specific fluorophores.

[0141] An additional marker, mouse anti-Pan Keratin (Clone AE1 / AE3 / PCK26, Roche, Part number: 5266840001) was added. Coverslips were removed by immersing the slides overnight in distilled water, staining with the PanCK antibody and detecting with Goat anti-mouse IgG (H+L)-Cy7 (AAT Bioquest, 16856). Slides were re-cover slipped and scanned as described above.Quantitative image analysis

[0142] Quantitative image analysis was preformed using HALO Indica Labs Hyperplex module (IndicaLabs, Albuquerque, NM). For each sample, images from the pan-immune panel and the pan-CK were fused to generate one single image. A first classifier was applied to detect the tissue on each section and an automatic annotation was generated as “whole section”. A second classifier was applied using panCK and DAPI channels to define the epithelium layer (panCK positive) and the lamina propria (panCK negative). Automated annotations were generated as “epithelium” and as “lamina propria”. Immune cells were detected in each area of interest (whole section, epithelium, lamina propria). T cells were defined as CD3+, B cells as CD20+, myeloid cells as CD68+. For each T cell subset, CD8 T cells were defined as CD3+CD8+FOXP3', CD4 as CD3+CD8‘, Tregs as CD3+CD8 FOXP3+and CD4 conventional as CD3+CD8-FOXP3-. Numbers of positive cells for each immune subset were counted and their density measured.Results of first analysis

[0143] Samples taken from 122 biopsies from 122 patients suspected of having lower GI aGVHD were analyzed. 60 samples from 60 patients were found to have histologic evidence of lower GI aGVHD, 12 samples were found to have other reasons for lower GI inflammation (including infections and drug effects, and were not further analyzed), and 15 samples did not have inflammation by histology (termed ‘No Inflammation’ (NI). In an additional 22 biopsies, the histologic findings were characterized as “Rare Apoptosis” (‘RA’), a diagnosis for which there is no national consensus amongst transplant experts about severity or the necessity of treatment and treated as not having aGVHD (with only 3 / 22 of these patients receiving steroids, and all 3 of these being SS). Apoptosis is a process of programmed cell death in which cells undergo self-destruction, typically in response to stress or damage. In the context of gastrointestinal GVHD, it refers to the death of epithelial cells lining the gastrointestinal tract.

[0144] The survival and IHC characteristics for SS, SR, NI and RA was tracked to identify the key clinical and immunologic features distinguishing these 4 groups. The results indicate through 2 years post-HCT (2 -yr), an inferior Overall Survival (OS) of patients with SR vs SS aGVHD (58%, 2-yr OS for SR vs 93% for SS, p <0.0001). The results also indicate that even without steroid treatment, that survival of patients with RA are equivalent to those without GI aGVHD (89% 2-yr OS for no GI aGVHD and 86% 2-yr OS for RA, p = 0.74).Multiplexed IHC analysis was performed on 68 biopsies as indicated above on all biopsies. Cell densities were measured as indicated above in biopsies that were taken from HCT patients prior to steroid treatment and having either no GI inflammation, GI inflammation, or GI rare apoptosis (RA). The cell densities for CD20 T cells, CD3 T cells, CD68 cells, CD8 T cells, CD4 conventional T cells, and regulatory T cells (Tregs) are shown in Figures 1-6, respectively.

[0145] The cell density ratios were measured in the biopsies that were taken from HCT patients prior to steroid treatment and having either no GI inflammation, GI inflammation, or GI rare apoptosis (RA). The cell density ratios of CD8 effector T cells to Tregs, CD4 conventional T cells, and CD68 cells are shown in Figures 7-9, respectively.

[0146] Patients suffering from GI inflammation were treated with steroids as described in Example 3 and patients were sorted as responders or non-responders to treatment. The cell density measurements taken prior to treatment for CD20 cells, CD3 T cells, CD68 cells, CD8 T cells, CD4 conventional T cells, and regulatory T cells (Tregs) are shown in Figures 10-15, respectively and sorted by responders and non-responders.

[0147] The cell density ratios of CD8 effector T cells to Tregs, CD4 conventional T cells, and CD68 cells of responders and non-responders are shown in Figures 16-18, respectively (see also Table 2 and Table 3 below).Table 2 - A list of the density ratios of CD8 effector T cells over CD68 cells, CD4 conventional T cells, CD68 cells, and epithelial cells in aGVHD patients who did not respond to steroid treatment.Table 3- A list of the density ratios of CD8 effector T cells over CD68 cells, CD4 conventional T cells, CD68 cells and epithelial cells in aGVHD patients who responded to steroid treatment.

[0148] The results indicate that rare apoptosis (RA) was associated with fewer immune infiltrates than either the aGVHD or no inflammation (NI) samples. These results suggest the immunologically benign nature of RA, which can be predictive of superior survival in these patients.

[0149] The results further indicate that among patients with histologic inflammation on biopsy, multiplexed IHC was also able to distinguish steroid-sensitive (SR; n=14) vs steroid-resistant (SS; n=14) aGVHD. Thus, while individual cellular infiltrates (including CD20, CD3, CD8, CD4, Tregs, and CD68 cells) could not distinguish these two clinical outcomes, the ratio of CD8 effector cells to multiple other infiltrates could make this classification. This included the density of CD8 / Tregs; CD8 / CD4 conventional T cells; CD8 / CD68 cells; and CD8 / epithelial cells (Figures 16-18 and Tables 1 and 2). A Receiver Operating Characteristic (ROC) analysis was performed to identify thresholds that led to high sensitivity and specificity for classifying SS vs SR based on IHC (Figures 19-22). In addition, a K-Nearest Neighbors (KNN) based classifier was able to identify thresholds that led to high accuracy (81%), specificity (69%), sensitivity (93%) and an overall AUC =0.852 (leave-one-out) for classifying SS vs SR based on the IHC (Figure 23).

[0150] The ability to predict SR vs SS aGVHD allows for tailoring appropriate therapies to the most high-risk aGVHD patients.EXAMPLE 5 - SECOND ANALYSIS MEASUREMENTS OF CELL DENSITIY AND PRPORTIONS OF MULTIPLE CELLULAR AND IMMUNE INFILTRATES INTO THE GI TRACT

[0151] Each of the sigmoid colonic biopsies described in Example 2 as part of the second analysis was analyzed with a series of multiplexed IHC panels, capable of tracking both the density and proportions of multiple cellular and immune infiltrates into the GI tract as indicated in Example 4 above. In addition, the following calculations and assessment were conductedFeature calculation

[0152] Immuno-histochemistry (IHC) was performed to derive estimates of the epithelial cells and density of immune cell types, as well as percentage of immune cell types expressing various markers, in the epithelium and lamina propria of individuals with GvHD. For each density measure, its ratio to the CD8 T cell density was calculated, then normalized across all samples tothe range [0,1]. This was evaluated with and without log transformation of the density values prior to normalization. These features are listed in full in Table 4.Table 4 - List of featuresFeature assessment

[0153] Each feature was evaluated for its ability to predict whether the subject responded to steroid therapy using a receiver operating characteristic (ROC) curve. The area under the ROC curve (AUC) was reported for each feature, along with the Fl -score, which is the harmonic mean of precision and recall. These results are reported in full in Table 5 below.Table 5 - Groups of features, based on clusteringAUC = area under the receiver operating characteristic curve; R = responders, NR = nonrespondersResults of second analysisFrequency of cell types were associated with GvHD inflammation and response to steroids

[0154] Various IHC derived features were generated for individuals with GvHD (Table 4). Many of these features demonstrated visible differences in distributions across patients with rare apoptosis, no inflammation, inflammation with response to steroid therapy, and inflammation without response to steroid therapy (Figures 24-46). Many of these features were also individually predictive of response to steroid therapy (Table 5), as evaluated using the area under the receiver operating characteristic curve (AUC).Hierarchical clustering identifies groups of similar features

[0155] To understand the relationship between the various features that were assessed, Pearson’s correlation coefficients were calculated between each pair of features. This statistical measure helped to quantify the degree of linear relationship between the features. Since the ratio of cell type densities demonstrated better discriminative power than the individual cell type densities, only the ratios were included in this analysis. Hierarchical clustering was then performed on these correlation coefficients, which yielded four groups of highly similar features (Figure 47). Each group included features that were highly predictive (Table 5). The presence of highly predictive features across different groups indicates that these features are not confined to a single cluster. Instead, they span multiple groups, indicating that combinations of features from different clusters could be used to more accurately identify responders, rather than relying on just one group of similar features.

[0156] The present disclosure has been described in detail, including the preferred embodiments thereof. However, it will be appreciated that those skilled in the art, upon consideration of the present disclosure, may make modifications and / or improvements on this disclosure that fall within the scope and spirit of the disclosure.

Claims

CLAIMSWHAT IS CLAIMED IS:

1. A method for identifying a subject suffering from graft- vs-host disease (GVHD) as a candidate for treatment with one or more immunosuppressant agents, comprising performing an assay on a biopsy from the subject to make: a) at least one group 1 measurement selected from the following group consisting of : % of CD4 conventional T cells in T cells; cell density ratio of regulatory Treg cells:CD8 effector T cells; % of GITRKi67‘ cells in regulatory Treg cells; % of GITR" cells in CD4 conventional-act T cells; % of GITR' cells in CD8-act T cells; % of regulatory Treg cells in FOXP3+cells; % of GZMB GZMK Ki67‘ cells in CD103+cells; % of non-act cells in CD4 conventional T cells; % of GZ Ki67‘ cells in CD4 conventional T cells; % of GZ Ki67‘ cells in CD8 T cells; % of non-act cells in CD8 T cells; % of GZMB GZMK Ki67 cells in CD8 T cells; and % of GZMB GZMK Ki67‘ cells in CD4 T cells; b) at least one group 2 measurement selected from the following group consisting of : cell density ratio of CD4 conventional T cells:CD8 T cells; cell density ratio of CD3 cells:CD8 T cells; cell density ratio of epithelial cells:CD8 T cells; cell density ratio of eosinophil cells:CD8 T cells; cell density ratio of neutrophil cells:CD8 T cells; cell density ratio of plasma cells:CD8 T cells; cell density ratio of CD20 T cells:CD8 T cells; cell density ratio of dendritic cells:CD8 T cells; cell density ratio of CD68 cells:CD8 T cells; cell density ratio of NK cells:CD8 T cells; and % of GZ Ki67+cells in CD8 T cells; c) at least one group 3 measurement selected from the following group consisting of : % of CD8 cells in T cells; % of GITR+Ki67‘ cells in regulatory Treg cells; % of GITR+cells in CD4 conventional-act T cells; % of GITR+Ki67+cells in regulatory Treg cells; % of GZMK+cells in CD8 T cells; % of GITR+cells in CD9-act T cells; % of FOXP3+CD8 cells in T cells; % of GZMB+cells in CD 103+ cells; % of non-canonical CD8 T cells in FOXP3+cells; % of CD3' CD8+cells in FOXP3+cells; % of regulatory Treg cells in T cells; % of GZ+Ki67‘ cells in CD8 T cells; and % of GZMK+cells in CD4 T cells; and d) at least one group 4 measurement selected from the following group consisting of : % of GZ+Ki67+cells in CD4 conventional T cells; % of GZ+Ki67+cells in CD8 T cells; % ofCD3+CD8+cells in F0XP3+cells; % of act-cells in CD4 conventional T cells; % of GZ+Ki67‘ cells in CD4 conventional T cells; % of KI67+cells in CD8 T cells; % of act-cells in CD8 T cells; % of GZMB+ cells in CD8 T cells; % of GZMK+cells in CD103+cells; % of GZ Ki67+cells in CD4 conventional T cells; % of KI67+ cells in CD4 T cells; % of GZMB+cells in CD4 T cells; % of KI67+cells in CD103+cells; and % of GITR Ki67+cells in regulatory Treg cells, as determined based on the performed assay.

2. The method of claim 1, wherein at least 2 measurements are made from group 1, group 2, group 3, or group 4.

3. The method of claim 1, wherein at least 2 measurements are made from each of group 1, group 2, group 3, and group 4.

4. The method of claim 1, wherein at least 3 measurements are made from group 1, group 2, group 3, or group 4.

5. The method of claim 1, wherein at least 3 measurements are made from group 1, group 2, group 3, or group 4.

6. The method of claim 1, wherein at least 4 measurements are made from group 1, group 2, group 3, or group 4.

7. The method of claim 1, wherein at least 4 measurements are made from group 1, group 2, group 3, or group 4.

8. The method of any one of claims 1-7, wherein the assay is an immunohistochemistry assay.

9. The method of any one of claims 1-8, wherein the immunosuppressant agent is a steroid.

10. The method of claim 9, wherein the steroid is a corticosteroid.

11. The method of claim 10, wherein the corticosteroid is selected from the group consisting of: a corticosteroid selected from the group consisting of: prednisone, methylprednisolone, dexamethasone, beclomethasone and budesonide.

12. The method of any one of claims 1-8, wherein the immunosuppressant agent is not a steroid.

13. The method of claim 12, wherein the immunosuppressant agent is selected from the group consisting of: cyclosporine, tacrolimus, methotrexate, mycophenoate mofetil, antithymocyte globulin (ATG), monoclonal antibodies (e.g., anti-CD3, -CD5, and -IL-2 antibodies, anti-CD20 (rituximab), and alemtuzumab (Campath)), anti-TNF drugs, JAK pathway inhibitors, lymphocyte immune globulin, sirolimus, ustekinumab, extracorporeal photophoresis, anti-CD3 drugs, anti-CD5 drug and anti-IL-2(CD25) drugs, anti-CD147 drugs, anti-ILl R drugs, anti-integrin drugs, mesenchymal stem cells, and regulatory T cells.

14. A method for treating graft- vs-host disease (GVHD) in a subject in need thereof comprising: a) performing or having performed an assay on a biopsy from the subject to make: i) at least one group 1 measurement selected from the following group consisting of : % of CD4 conventional T cells in T cells; cell density ratio of regulatory Treg cells:CD8 effector T cells; % of GITRKi67‘ cells in regulatory Treg cells; % of GITR' cells in CD4 conventional-act T cells; % of GITR' cells in CD8-act T cells; % of regulatory Treg cells in FOXP3+cells; % of GZMB GZMK Ki67‘ cells in CD103+cells; % of non-act cells in CD4 conventional T cells; % of GZ'Ki67‘ cells in CD4 conventional T cells; % of GZ Ki67‘ cells in CD8 T cells; % of non-act cells in CD8 T cells; % of GZMB GZMKKi67‘ cells in CD8 T cells; and % of GZMB GZMK Ki67‘ cells in CD4 T cells; ii) at least one group 2 measurement selected from the following group consisting of : cell density ratio of CD4 conventional T cells:CD8 T cells; cell density ratio of CD3 cells:CD8 T cells; cell density ratio of epithelial cells:CD8 T cells; cell density ratio of eosinophil cells:CD8 T cells; cell density ratio of neutrophil cells:CD8 T cells; cell density ratio of plasma cells:CD8 T cells; cell density ratio of CD20 T cells:CD8 T cells; cell density ratio of dendritic cells:CD8 T cells; cell density ratio of CD68 cells:CD8 T cells; cell density ratio ofNK cells:CD8 T cells; and % of GZ'Ki67+cells in CD8 T cells; iii) at least one group 3 measurement selected from the following group consisting of : % of CD8 cells in T cells; % of GITR+Ki67‘ cells in regulatory Treg cells; % of GITR+cells in CD4 conventional-act T cells; % of GITR+Ki67+cells in regulatory Treg cells; % of GZMK+cells in CD8 T cells; % of GITR+cells in CD9-act T cells; % of FOXP3+CD8 cells in T cells; % of GZMB+cells in CD 103+ cells; % of non-canonical CD8 T cells in FOXP3+cells; % of CD3' CD8+cells in FOXP3+cells; % of regulatory Treg cells in T cells; % of GZ+Ki67‘ cells in CD8 T cells; and % of GZMK+cells in CD4 T cells; and iv) at least one group 4 measurement selected from the following group consisting of : % of GZ+Ki67+cells in CD4 conventional T cells; % of GZ+Ki67+cells in CD8 T cells; % of CD3+CD8+cells in FOXP3+cells; % of act-cells in CD4 conventional T cells; % of GZ+Ki67‘ cells in CD4 conventional T cells; % of KI67+cells in CD8 T cells; % of act-cells in CD8 T cells; % of GZMB+ cells in CD8 T cells; % of GZMK+cells in CD103+cells; % of GZ Ki67+cells in CD4 conventional T cells; % of KI67+ cells in CD4 T cells; % of GZMB+cells in CD4 T cells; % of KI67+cells in CD103+cells; and % of GITR Ki67+cells in regulatory Treg cells, as determined based on the performed assay; and b) administering to the subject a pharmaceutically effective amount of one or more immunosuppressant agents based on the measurements conducted.

15. The method of claim 14, wherein at least 2 measurements are made from group 1, group 2, group 3, or group 4.

16. The method of claim 14, wherein at least 2 measurements are made from each of group 1, group 2, group 3, and group 4.

17. The method of claim 14, wherein at least 3 measurements are made from group 1, group 2, group 3, or group 4.

18. The method of claim 14, wherein at least 3 measurements are made from group 1, group 2, group 3, or group 4.

19. The method of claim 14, wherein at least 4 measurements are made from group 1, group 2, group 3, or group 4.

20. The method of claim 14, wherein at least 4 measurements are made from group 1, group 2, group 3, or group 4.

21. The method of claim 14, wherein the assay is an immunohistochemistry assay.

22. The method of any one of claims 14-21, wherein the immunosuppressant agent is a steroid.

23. The method of claim 22, wherein the steroid is a corticosteroid.

24. The method of claim 23, wherein the corticosteroid is selected from the group consisting of: a corticosteroid selected from the group consisting of: prednisone, methylprednisolone, dexamethasone, beclomethasone and budesonide.

25. The method of any one of claims 14-21, wherein the immunosuppressant agent is not a steroid.

26. The method of claim 25, wherein the immunosuppressant agent is selected from the group consisting of: cyclosporine, tacrolimus, methotrexate, mycophenoate mofetil, antithymocyte globulin (ATG), monoclonal antibodies (e.g., anti-CD3, -CD5, and -IL-2 antibodies, anti-CD20 (rituximab), and alemtuzumab (Campath)), anti-TNF drugs, JAK pathway inhibitors, lymphocyte immune globulin, sirolimus, ustekinumab, extracorporeal photophoresis, anti-CD3 drugs, anti-CD5 drug and anti-IL-2(CD25) drugs, anti-CD147 drugs, anti-ILl R drugs, anti-integrin drugs, mesenchymal stem cells, and regulatory T cells.

Images