scholarly journals COVID-19 and Cancer: Discovery of Difference in Clinical Immune Indexes

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiaojiao Zeng ◽  
Xianghu Jiang ◽  
Liu Yang ◽  
Yunbao Pan ◽  
Yirong Li
Keyword(s):  
T Cells ◽  
B Cells ◽  
Nk Cells ◽  
Cancer Patients ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Roc Curves ◽  
Immune Disorder ◽  
Respiratory Cancer ◽  
Tnf Α

Objective. This study explored the consistency and differences in the immune cells and cytokines between patients with COVID-19 or cancer. We further analyzed the correlations between the acute inflammation and cancer-related immune disorder. Methods. This retrospective study involved 167 COVID-19 patients and 218 cancer patients. COVID-19 and cancer were each further divided into two subgroups. Quantitative and qualitative variables were measured by one-way ANOVA and chi-square test, respectively. Herein, we carried out a correlation analysis between immune cells and cytokines and used receiver operating characteristic (ROC) curves to discover the optimal diagnostic index. Results. COVID-19 and cancers were associated with lymphopenia and high levels of monocytes, neutrophils, IL-6, and IL-10. IL-2 was the optimal indicator to differentiate the two diseases. Compared with respiratory cancer patients, COVID-19 patients had lower levels of IL-2 and higher levels of CD3+CD4+ T cells and CD19+ B cells. In the subgroup analysis, IL-6 was the optimal differential diagnostic parameter that had the ability to identify if COVID-19 patients would be severely affected, and severe COVID-19 patients had lower levels of lymphocyte subsets (CD3+ T cells, CD3+CD4+ T cells, CD3+CD8+T cells, and CD19+ B cells) and CD16+CD56+ NK cells and higher level of neutrophils. There were significant differences in the levels of CD3+CD4+ T cells and CD19+ B cells between T1-2 and T3-4 stages as well as IL-2 and CD19+ B cells between N0-1 and N2-3 stages while no significant differences between the metastatic and nonmetastatic cancer patients. Additionally, there were higher correlations between IL-2 and IL-4, TNF-α and IL-2, TNF-α and IL-4, TNF-α and IFN-γ, and CD16+CD56+NK cells and various subsets of T cells in COVID-19 patients. There was a higher correlation between CD3+CD4+ T cells and CD19+ B cells in cancer patients. Conclusion. Inflammation associated with COVID-19 or cancer had effects on patients’ outcomes. Accompanied by changes in immune cells and cytokines, there were consistencies, differences, and satisfactory correlations between patients with COVID-19 and those with cancers.

scholarly journals Circulating cytokines and lymphocyte subsets in patients who have recovered from COVID-19

2020 ◽  
Author(s):  
Hasi Chaolu ◽  
Xinri Zhang ◽  
Xin Li ◽  
Xin Li ◽  
Dongyan Li
Keyword(s):  
T Cells ◽  
B Cells ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Cd4 T Cells ◽  
Lymphocyte Subsets ◽  
Healthy Controls ◽  
Tnf Α ◽  
Ifn Γ ◽  
Circulating Cytokines

To investigate the immune status of people who previously had COVID-19 infections, we recruited patients 2 weeks post-recovery and analyzed circulating cytokines and lymphocyte subsets. We measured levels of total lymphocytes, CD4+ T cells, CD8+ T cells, CD19+ B cells, CD56+ NK cells, and the serum concentrations of interleukin (IL)-1, IL-4, IL-6, IL-8, IL-10, transforming growth factor beta (TGF-β), tumor necrosis factor alpha (TNF-α), and interferon gamma (IFN-γ) by flow cytometry. We found that in most post-recovery patients, levels of total lymphocytes (66.67%), CD3+ T cells (54.55%), CD4+ T cells (54.55%), CD8 + T cells (81.82%), CD19+ B cells (69.70%), and CD56+ NK cells(51.52%) remained lower than normal, whereas most patients showed normal levels of IL-2 (100%), IL-4 (80.88%), IL-6 (79.41%), IL-10 (98.53%), TNF-α (89.71%), IFN-γ (100%) and IL-17 (97.06%). Compared to healthy controls, 2-week post-recovery patients had significantly lower absolute numbers of total lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD56+ NK cells, along with significantly higher levels of IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ and IL-17. Among post-recovery patients, T cells, particularly CD4+ T cells, were positively correlated with CD19+ B cell counts. Additionally, CD8+ T cells positively correlated with CD4+ T cells and IL-2 levels, and IL-6 positively correlated with TNF-α and IFN-γ. These correlations were not observed in healthy controls. By ROC curve analysis, post-recovery decreases in lymphocyte subsets and increases in cytokines were identified as independent predictors of rehabilitation efficacy. These findings indicate that the immune system has gradually recovered following COVID-19 infection; however, the sustained hyper-inflammatory response for more than 14 days suggests a need to continue medical observation following discharge from the hospital. Longitudinal studies of a larger cohort of recovered patients are needed to fully understand the consequences of the infection.

scholarly journals Circulating Cytokines and Lymphocyte Subsets in Patients Who Have Recovered from COVID-19

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Hasichaolu ◽  
Xinri Zhang ◽  
Xin Li ◽  
Xin Li ◽  
Dongyan Li
Keyword(s):  
T Cells ◽  
B Cells ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Cd4 T Cells ◽  
Lymphocyte Subsets ◽  
Healthy Controls ◽  
Cell Counts ◽  
Tnf Α ◽  
Ifn Γ

To investigate the immune status of people who previously had COVID-19 infections, we recruited two-week postrecovery patients and analyzed circulating cytokine and lymphocyte subsets. We measured levels of total lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD56+ NK cells and the serum concentrations of interleukin- (IL-) 1, IL-4, IL-6, IL-8, IL-10, transforming growth factor beta (TGF-β), tumor necrosis factor alpha (TNF-α), and interferon gamma (IFN-γ) by flow cytometry. We found that in most postrecovery patients, levels of total lymphocytes (66.67%), CD3+ T cells (54.55%), CD4+ T cells (54.55%), CD8+ T cells (81.82%), CD19+ B cells (69.70%), and CD56+ NK cells (51.52%) remained lower than normal, whereas most patients showed normal levels of IL-2 (100%), IL-4 (80.88%), IL-6 (79.41%), IL-10 (98.53%), TNF-α (89.71%), IFN-γ (100%), and IL-17 (97.06%). Compared to healthy controls, two-week postrecovery patients had significantly lower absolute numbers of total lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD56+ NK cells, along with significantly higher levels of IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ, and IL-17. Among postrecovery patients, T cells, particularly CD4+ T cells, were positively correlated with CD19+ B cell counts. Additionally, CD8+ T cells were positively correlated with CD4+ T cells and IL-2 levels, and IL-6 positively correlated with TNF-α and IFN-γ. These correlations were not observed in healthy controls. By ROC curve analysis, postrecovery decreases in lymphocyte subsets and increases in cytokines were identified as independent predictors of rehabilitation efficacy. These findings indicate that the immune system gradually recovers following COVID-19 infection; however, the sustained hyperinflammatory response for more than 14 days suggests a need to continue medical observation following discharge from the hospital. Longitudinal studies of a larger cohort of recovered patients are needed to fully understand the consequences of the infection.

scholarly journals Immune dysfunction in ankylosing spondylitis (AS) and the potential of tumor necrosis factor-α (TNF-α) inhibitor Anbainuo as an effective treatment

2020 ◽  
Author(s):  
Mingcan Yang ◽  
Qing Lv ◽  
Qiujing Wei ◽  
Yutong Jiang ◽  
Jun Qi ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Immune Function ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Helper T Cells ◽  
Effector Memory ◽  
Regulatory B Cells ◽  
Tnf Α

Abstract Background Studies into ankylosing spondylitis (AS) and its relationship with immune function are controversial, and the correlation between the efficacy of TNF-α inhibitor and changes in immune function is unclear. Methods A total of 40 immune cells were tested with flow cytometry, and the results of 105 HC (healthy control) subjects, 177 active-stage AS patients, and 23 AS cases before and after 12 weeks of Anbainuo therapy were analyzed. Results Compared with the HC group, the proportion of immune cells, such as naïve and central memory CD4+T cells, in AS increased (p<0.0001), but effector memory and terminally differentiated CD4+T cells were decreased (p<0.01 and 0.0001, respectively). Naïve, central memory, and effector memory CD8+T cells were increased (p<0.0001, 0.001, and 0.01, respectively), but terminally differentiated CD8+T cells were decreased (p<0.0001). Th1 cells (helper T cells-1), Tfh1 cells (follicular helper T cells-1), Tc1 cells (cytotoxic T cells-1), and Tregs (regulatory T cells) were lower (p<0.01, 0.05, 0.0001, and 0.001, respectively), but Th17 cells, Tfh17 cells, and Tc cells were higher (p<0.001, 0.0001 and 0.001, respectively). The proportions of total B cells and class-switched B cells were increased (p<0.05), but non-switched B cells, plasma cells, memory B cells, and immature Bregs (regulatory B cells) were lower (p<0.01, 0.0001, 0.0001, and 0.0001, respectively). After Anbainuo therapy, the percentage of Tregs and B10 cells (IL-10-producing regulatory B cells) had increased (p<0.01and 0.05, respectively), and the increase in Tregs was positively correlated with the decrease in CRP (C-reactive protein) (r= 0.489, p=0.018). Conclusions We found that, in terms of both innate and acquired immunity, active-stage AS patients have an immunity imbalance involving multiple types of immune cells, including CD4+T cells, CD8+T cells, Th cells, Tfh cells, Tc cells, Tregs, Bregs, and B cells. Anbainuo can not only help to inhibit disease activity and partial immune function imbalance in AS but can also increase the number of negative regulatory cells in inflammation.

scholarly journals Effect of Autoimmune Cell Therapy on Immune Cell Content in Patients with COPD: A Randomized Controlled Trial

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Wen Li ◽  
Guanhong Li ◽  
Wei Zhou ◽  
Hui Wang ◽  
Yuqiong Zheng
Keyword(s):  
T Cells ◽  
B Cells ◽  
Treatment Group ◽  
Cell Therapy ◽  
Nk Cells ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Conventional Treatment ◽  
Control Group ◽  
Cd8 Cells

Objective. To explore the effect of autoimmune cell therapy on immune cells in patients with chronic obstructive pulmonary disease (COPD) and to provide a reference for clinical treatment of COPD. Methods. Sixty patients with stable COPD were randomly divided into control group and treatment group ( n = 30 ). The control group was given conventional treatment, and the treatment group was given one autoimmune cell therapy on the basis of conventional treatment. The serum levels of CD3+ T cells, CD4+ T cells, CD8+ cells, B cells, and NK cells in the peripheral blood were detected by flow cytometry. Possible adverse reactions were detected at any time during treatment. Results. There were no significant differences in the contents of CD3+ T cells, CD4+ T cells, CD8+ cells, B cells, and NK cells in the serum of the control group ( P > 0.05 ). Compared with before treatment, the contents of CD3+ T cells, CD4+ T cells, CD8+ cells, B cells, and NK cells in the serum of the treatment group were significantly increased ( P < 0.05 ). The ratio of CD 4 + / CD 8 + T cells in both control and treatment groups did not change significantly during treatment ( P > 0.05 ). There were no significant differences in serum CD3+ T cells, CD4+ T cells, CD8+ cells, B cells, and NK cells in the treatment group at 30 days and 90 days after treatment ( P > 0.05 ), but they were significantly higher than those in the control group ( P < 0.05 ). Conclusion. Autoimmune cell therapy can significantly increase the level of immune cells in the body and can be maintained for a long period of time, which has certain clinical benefits for recurrent respiratory tract infections and acute exacerbation in patients with COPD.

scholarly journals TNF-α inhibitor therapy can improve the immune imbalance of CD4+ T cells and negative regulatory cells but not CD8+ T cells in ankylosing spondylitis

2020 ◽  
Author(s):  
Mingcan Yang ◽  
Qing Lv ◽  
Qiujing Wei ◽  
Yutong Jiang ◽  
Jun Qi ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Cd4 T Cells ◽  
Effector Memory ◽  
Regulatory Cells ◽  
Regulatory B Cells ◽  
Tnf Α ◽  
Immune Imbalance

Abstract Background: Studies into ankylosing spondylitis (AS) and its relationship with immune function are controversial, and the correlation between the efficacy of TNF-α inhibitor and changes in immune function is unclear.Methods: A total of 40 immune cells were tested with flow cytometry, and the results of 105 HC (healthy control) subjects, 177 active-stage AS patients, and 23 AS cases before and after 12 weeks of TNF-α inhibitor therapy (Anbainuo) were analyzed.Results: Compared with the HC group, the proportion of immune cells, such as naïve and central memory CD4+T cells, in AS increased (p<0.0001), but effector memory and terminally differentiated CD4+T cells were decreased (p<0.01 and 0.0001, respectively). Naïve, central memory, and effector memory CD8+T cells were increased (p<0.0001, 0.001, and 0.01, respectively), but terminally differentiated CD8+T cells were decreased (p<0.0001). Th1 cells (helper T cells-1), Tfh1 cells (follicular helper T cells-1), Tc1 cells (cytotoxic T cells-1), and Tregs (regulatory T cells) were lower (p<0.01, 0.05, 0.0001, and 0.001, respectively), but Th17 cells, Tfh17 cells, and Tc cells were higher (p<0.001, 0.0001 and 0.001, respectively). The proportions of total B cells and class-switched B cells were increased (p<0.05), but non-switched B cells, plasma cells, memory B cells, and immature Bregs (regulatory B cells) were lower (p<0.01, 0.0001, 0.0001, and 0.0001, respectively). After Anbainuo therapy, the percentage of naïve CD4+ T cells had decreased (p<0.05) but Tregs and B10 cells (IL-10-producing regulatory B cells) had increased (p<0.01and 0.05, respectively), and the increase in Tregs was positively correlated with the decrease in CRP (C-reactive protein) (r= 0.489, p=0.018). Conclusions: We found that active-stage AS patients have an immunity imbalance involving multiple types of immune cells, including CD4+T cells, CD8+T cells, Th cells, Tfh cells, Tc cells, Tregs, Bregs, and B cells. TNF-α inhibitor Anbainuo can not only help to inhibit disease activity but can also improve the immune imbalance of CD4+ T cells and negative regulatory cells. But CD8 + T cells have not been rescued.

Engineered immunostimulatory cells can convert PBMCs from chronic lymphocytic leukemia (CLL) patients into potent tumor killing immune cells.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 7517-7517
Author(s):  
Joshua W. Keegan ◽  
Frank Borriello ◽  
Stacey M. Fernandes ◽  
Jennifer R. Brown ◽  
James A. Lederer
Keyword(s):  
T Cells ◽  
B Cells ◽  
Tumor Cell ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Immune Cells ◽  
Killing Activity ◽  
Tumor Killing ◽  
Tumor Cell Killing ◽  
Potent Tumor

7517 Background: Alloplex Biotherapeutics has developed a cellular therapeutic that uses ENgineered Leukocyte ImmunoSTimulatory cell lines called ENLIST cells to activate and expand populations of tumor killing effector cells from human peripheral blood mononuclear cells (PBMCs). This process leads to a 300-fold expansion of NK cells, CD8+ T cells, NKT cells, and TCRγδ T cells that are called SUPLEXA cells, which will be cryopreserved and transferred back into patients as an autologous immune cell therapy for cancer. In this study, PBMCs from CLL patients were used to generate SUPLEXA cells as a first approach to comparatively profile SUPLEXA cells from cancer patients and normal healthy volunteers (NHVs). Methods: ENLIST cell lines were engineered by expressing curated immunomodulatory proteins in the SK-MEL-2 melanoma cell line. Two million (M) PBMCs from 10 CLL patients or 2 NHVs were incubated with 0.4 M freeze/thaw killed ENLIST cells for 5 days in XVIVO-15 medium with 2% heat-inactivated human AB serum (XAB2) and then split 1:15 in XAB2 containing IL-7 and IL-15 to expand. After 9 days, SUPLEXA cells were harvested and cryopreserved. Results: Original PBMCs and matched SUPLEXA cells from each donor were thawed and characterized by mass cytometry (CyTOF) using a 47-marker antibody panel. CyTOF staining results of PBMCs from CLL patients demonstrated approximately 95% leukemia cells and few T cells, NK cells, B cells, and monocytes. CyTOF staining of SUPLEXA cells from all 10 CLL patients showed expansion of NK cells (17%), CD8 T cells (11%), and CD4 T cells (7.5%) that were similar in phenotype to SUPLEXA cells from NHVs showing high expression of granzymes and perforin that are indicative of potent tumor cell killing activity. Cancer cells in the original CLL PBMC samples were reduced to 0.78%. However, a population of non-T/non-B cells (60% ± 9.5%) was detected in SUPLEXA cells from all CLL patients that require further characterization. Next, SUPLEXA cells from CLL and NHV patients were comparatively tested for tumor cell killing activity at 2:1, 1:1, and 1:2 effector to target cell (MEL-14 melanoma cells expressing RFP) ratios. Percent killing of tumor cells by SUPLEXA cells prepared from CLL patients (77.8% ± 2.6% at 2:1) and NHVs (81.5% ± 0.3% at 2:1) were nearly identical at all effector to target ratios. Conclusions: We demonstrate for the first time that PBMCs from CLL patients can be converted into SUPLEXA cells despite low numbers of normal immune cells at baseline and the known immunologic impairment present in CLL patients. Importantly, SUPLEXA cells derived from CLL patients acquire potent tumor killing activity that is indistinguishable from SUPLEXA cells prepared from NHVs. Taken together, these findings support the feasibility of converting PBMCs from CLL patients with low percentages of NK and T cells into an autologous cellular therapy for cancer.

scholarly journals Prognostic significance of natural killer cell-associated markers in gastric cancer: quantitative analysis using multiplex immunohistochemistry

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hee Young Na ◽  
Yujun Park ◽  
Soo Kyung Nam ◽  
Jiwon Koh ◽  
Yoonjin Kwak ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
B Cells ◽  
Nk Cells ◽  
Natural Killer ◽  
Immune Cells ◽  
Nk Cell ◽  
Critical Role ◽  
Killer Cell ◽  
Prognostic Significance

Abstract Background Natural killer (NK) cells mediate the anti-tumoral immune response as an important component of innate immunity. The aim of this study was to investigate the prognostic significance and functional implication of NK cell-associated surface receptors in gastric cancer (GC) by using multiplex immunohistochemistry (mIHC). Methods We performed an mIHC on tissue microarray slides, including 55 GC tissue samples. A total of 11 antibodies including CD57, NKG2A, CD16, HLA-E, CD3, CD20, CD45, CD68, CK, SMA, and ki-67 were used. CD45 + CD3-CD57 + cells were considered as CD57 + NK cells. Results Among CD45 + immune cells, the proportion of CD57 + NK cell was the lowest (3.8%), whereas that of CD57 + and CD57- T cells (65.5%) was the highest, followed by macrophages (25.4%), and B cells (5.3%). CD57 + NK cells constituted 20% of CD45 + CD57 + immune cells while the remaining 80% were CD57 + T cells. The expression of HLA-E in tumor cells correlated with that in tumoral T cells, B cells, and macrophages, but not CD57 + NK cells. The higher density of tumoral CD57 + NK cells and tumoral CD57 + NKG2A + NK cells was associated with inferior survival. Conclusions Although the number of CD57 + NK cells was lower than that of other immune cells, CD57 + NK cells and CD57 + NKG2A + NK cells were significantly associated with poor outcomes, suggesting that NK cell subsets play a critical role in GC progression. NK cells and their inhibitory receptor, NKG2A, may be potential targets in GC.

scholarly journals The Complexity of Microglial Interactions With Innate and Adaptive Immune Cells in Alzheimer’s Disease

2020 ◽  
Vol 12 ◽  
Author(s):  
Season K. Wyatt-Johnson ◽  
Randy R. Brutkiewicz
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
T Cells ◽  
B Cells ◽  
Nk Cells ◽  
Immune Cells ◽  
Reactive Microglia ◽  
Adaptive Immune Cells ◽  
Affected Relative ◽  
Peripheral Immune Cells

In the naïve mouse brain, microglia and astrocytes are the most abundant immune cells; however, there is a complexity of other immune cells present including monocytes, neutrophils, and lymphocytic cells, such as natural killer (NK) cells, T cells, and B cells. In Alzheimer’s disease (AD), there is high inflammation, reactive microglia, and astrocytes, leaky blood–brain barrier, the buildup of amyloid-beta (Aβ) plaques, and neurofibrillary tangles which attract infiltrating peripheral immune cells that are interacting with the resident microglia. Limited studies have analyzed how these infiltrating immune cells contribute to the neuropathology of AD and even fewer have analyzed their interactions with the resident microglia. Understanding the complexity and dynamics of how these immune cells interact in AD will be important for identifying new and novel therapeutic targets. Thus, this review will focus on discussing our current understanding of how macrophages, neutrophils, NK cells, T cells, and B cells, alongside astrocytes, are altered in AD and what this means for the disorder, as well as how these cells are affected relative to the resident microglia.

Increased Expression of PD-1 on CD4+ T Cells from Patients with Chronic Lymphocytic Leukemia

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4154-4154
Author(s):  
Mary M Sartor ◽  
David J Gottlieb
Keyword(s):  
T Cells ◽  
B Cells ◽  
Chronic Lymphocytic Leukemia ◽  
Nk Cells ◽  
Cd4 T Cells ◽  
Mononuclear Cells ◽  
Lymphocytic Leukemia ◽  
Effector Memory ◽  
Cd4 Cells ◽  
Normal Peripheral Blood

Abstract Although the predominant finding in patients with chronic lymphocytic leukemia (CLL) is an expansion of monoclonal B lymphocytes, a polyclonal expansion of T cells co-exists in CLL patients. Allogenic stem cell transplants for CLL suggest that a significant graft versus leukaemia effect mediated through recognition of minor MHC or leukaemia specific antigens can be achieved. Since it appears that the immune system and probably T cells recognise CLL cells, it is possible that one or more T cell defects might contribute to the initiation or maintenance of a clone of CLL lymphocytes. PD-1 is a coinhibitory molecule that is expressed on T cells in patients with chronic viral infections. It has been suggested that PD-1 expression might be a marker of cell exhaustion due to antigenic overstimulation. We examined the expression of PD-1 and its naturally occurring ligands PD-L1 and PD-L2 on both B and T cells in patients with CLL and compared this with expression on normal peripheral blood mononuclear cells. We found that PD-1 was expressed on over 10% of CD4+ T cells in 7 of 9 cases of CLL (mean 22±16%) but not on CD4+ T cells in any of 9 normal donors (mean 0±0%), p=0.0009. There was no difference in PD-1 expression on CD8+ or CD14+ PBMCs from CLL patients and normal donors (for CD8+ 24±21% and 19±16% for CLL and normals; for CD14+ 58±16% and 71±31% for CLL and normals). More than 10% of CD5+/19+ CLL cells expressed PD-1 in 7 of 10 cases (mean 18±18%) while more than 10% of normal B cells from 6 of 7 donors also expressed PD-1 (mean 49±30%). We examined the expression of PD-1 on naïve, central memory, effector memory and terminally differentiated subsets of CD4+ cells (CD62L+CD45RA+, CD62L+CD45RA−, CD62L−CD45RA− and CD62L−CD45RA+ respectively) from CLL patients and normal donors. The expression of PD-1 was higher on CD4+ cells from CLL patients in all subsets. The effect was most prominent in the effector memory subset (mean 54±4% for CLL patients versus 26±17% for normal donors, p=0.02). We looked for expression of PD-L1 and PD-L2 on T cells, B cells, monocytes and NK cells from CLL patients and normal donors. PD-L1 was only expressed on monocytes (mean 30±23%) and NK cells (mean 14±19%) from CLL patients and on monocytes from normal donors (mean 35±26%). There was no expression of PD-L2 on any cell type in either CLL patients or normal donors. We conclude that there is increased expression of the co-inhibitory molecule PD-1 on CD4+ T cells in patients with CLL. Ligation of PD-1 by PD-L1 expressed on monocytes or NK cells could inhibit immune responses to tumor and infectious antigens leading to persistence of clonally expanded cells and predisposition to opportunistic pathogens.

Anti-GvHD Effect of Antithymocyte Globulin Is Mediated by Antibodies Binding to T Cells and Regulatory NK Cells, and Less So or Not at All by Antibodies Binding to Other Mononuclear Cell Subsets

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2346-2346
Author(s):  
Mette Hoegh-Petersen ◽  
Minaa Amin ◽  
Yiping Liu ◽  
Alejandra Ugarte-Torres ◽  
Tyler S Williamson ◽  
...  
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
B Cells ◽  
Nk Cells ◽  
Cd8 T Cells ◽  
Cd4 T Cells ◽  
Antithymocyte Globulin ◽  
Chronic Gvhd ◽  
Wilcoxon Test ◽  
Effector Memory

Abstract Abstract 2346 Introduction: Polyclonal rabbit-anti-human T cell globulin may decrease the likelihood of graft-vs-host disease (GVHD) without increasing the likelihood of relapse. We have recently shown that high levels of antithymocyte globulin (ATG) capable of binding to total lymphocytes are associated with a low likelihood of acute GVHD grade 2–4 (aGVHD) as well as chronic GVHD needing systemic therapy (cGVHD) but not increased likelihood of relapse (Podgorny PJ et al, BBMT 16:915, 2010). ATG is polyclonal, composed of antibodies for antigens expressed on multiple cell subsets, including T cells, B cells, NK cells, monocytes and dendritic cells. These cell subsets may play a role in the pathogenesis of GVHD. The anti-GVHD effect of ATG may be mediated through killing/inhibition of one or several of these cell subsets (eg, T cells) or their subsets (eg, naïve T cells as based on mouse experiments naïve T cells are thought to play a major role in the pathogenesis of GVHD). To better understand the mechanism of action of ATG on GVHD, we set out to determine levels of which ATG fraction (capable of binding to which cell subset) are associated with subsequent development of GVHD. Patients and Methods: A total of 121 patients were studied, whose myeloablative conditioning included 4.5 mg/kg ATG (Thymoglobulin). Serum was collected on day 7. Using flow cytometry, levels of the following ATG fractions were determined: capable of binding to 1. naïve B cells, 2. memory B cells, 3. naïve CD4 T cells, 4. central memory (CM) CD4 T cells, 5. effector memory (EM) CD4 T cells, 6. naïve CD8 T cells, 7. CM CD8 T cells, 8. EM CD8 T cells not expressing CD45RA (EMRA-), 9. EM CD8 T cells expressing CD45RA (EMRA+), 10. cytolytic (CD16+CD56+) NK cells, 11. regulatory (CD16-CD56high) NK cells, 12. CD16+CD56− NK cells, 13. monocytes and 14. dendritic cells/dendritic cell precursors (DCs). For each ATG fraction, levels in patients with versus without aGVHD or cGVHD were compared using Mann-Whitney-Wilcoxon test. For each fraction for which the levels appeared to be significantly different (p<0.05), we determined whether patients with high fraction level had a significantly lower likelihood of aGVHD or cGVHD than patients with low fraction level (high/low cutoff level was determined from ROC curve, using the point with maximum sum of sensitivity and specificity). This was done using log-binomial regression models, ie, multivariate analysis adjusting for recipient age (continuous), stem cell source (marrow or cord blood versus blood stem cells), donor type (HLA-matched sibling versus other), donor/recipient sex (M/M versus other) and days of follow up (continuous). Results: In univariate analyses, patients developing aGVHD had significantly lower levels of the following ATG fractions: binding to naïve CD4 T cells, EM CD4 T cells, naïve CD8 T cells and regulatory NK cells. Patients developing cGVHD had significantly lower levels of the following ATG fractions: capable of binding to naïve CD4 T cells, CM CD4 T cells, EM CD4 T cells, naïve CD8 T cells and regulatory NK cells. Patients who did vs did not develop relapse had similar levels of all ATG fractions. In multivariate analyses, high levels of the following ATG fractions were significantly associated with a low likelihood of aGVHD: capable of binding to naïve CD4 T cells (relative risk=.33, p=.001), EM CD4 T cells (RR=.30, p<.001), naïve CD8 T cells (RR=.33, p=.002) and regulatory NK cells (RR=.36, p=.001). High levels of the following ATG fractions were significantly associated with a low likelihood of cGVHD: capable of binding to naïve CD4 T cells (RR=.59, p=.028), CM CD4 T cells (RR=.49, p=.009), EM CD4 T cells (RR=.51, p=.006), naïve CD8 T cells (RR=.46, p=.005) and regulatory NK cells (RR=.55, p=.036). Conclusion: For both aGVHD and cGVHD, the anti-GVHD effect with relapse-neutral effect of ATG appears to be mediated by antibodies to antigens expressed on naïve T cells (both CD4 and CD8), EM CD4 T cells and regulatory NK cells, and to a lesser degree or not at all by antibodies binding to antigens expressed on B cells, cytolytic NK cells, monocytes or DCs. This is the first step towards identifying the antibody(ies) within ATG important for the anti-GVHD effect without impacting relapse. If such antibody(ies) is (are) found in the future, it should be explored whether such antibody(ies) alone or ATG enriched for such antibody(ies) could further decrease GVHD without impacting relapse. Disclosures: No relevant conflicts of interest to declare.

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