Despite being first described 45 years ago, the existence of a distinct diabetic cardiomyopathy remains controversial. Nonetheless, it is widely accepted that the diabetic heart undergoes characteristic structural and functional changes in the absence of ischaemia and hypertension, which are independently linked to heart failure progression and are likely to underlie enhanced susceptibility to stress. A prominent feature is marked collagen accumulation linked with inflammation and extensive extracellular matrix changes, which appears to be the main factor underlying cardiac stiffness and subclinical diastolic dysfunction, estimated to occur in as many as 75% of optimally controlled diabetics. Whether this characteristic remodelling phenotype is primarily driven by microvascular dysfunction or alterations in cardiomyocyte metabolism remains unclear. Although hyperglycaemia regulates multiple pathways in the diabetic heart, increased reactive oxygen species (ROS) generation is thought to represent a central mechanism underlying associated adverse remodelling. Indeed, experimental and clinical diabetes are linked with oxidative stress which plays a key role in cardiomyopathy, while key processes underlying diabetic cardiac remodelling, such as inflammation, angiogenesis, cardiomyocyte hypertrophy and apoptosis, fibrosis and contractile dysfunction, are redox sensitive. This review will explore the relative contributions of the major ROS sources (dysfunctional nitric oxide synthase, mitochondria, xanthine oxidase, nicotinamide adenine dinucleotide phosphate oxidases) in the diabetic heart and the potential for therapeutic targeting of ROS signalling using novel pharmacological and non-pharmacological approaches to modify specific aspects of the remodelling phenotype in order to prevent and/or delay heart failure development and progression.

CTLA-4 is a member of the costimulatory family, has homology to CD28, and binds the B7 family of ligands. Unlike CD28, CTLA-4 ligation transmits a negative signal in T cells. CTLA-4 expression, while inducible in most T cells, is expressed constitutively on T cells with a regulatory phenotype. The mechanism controlling CTLA-4 expression in human T cells is poorly characterized, thus we sought to better understand the mechanism of activation of the CTLA-4 gene. By cloning the 5′ upstream promoter and creating promoter-deletion reporter constructs, we show that the proximal promoter is critical for activating the CTLA-4 gene. Within this region, we identify a NFAT consensus sequence that binds NFAT with high affinity that differs from other NFAT sequences and does not recruit AP-1. Analysis of the chromatin proteins in the native CTLA-4 gene shows that this promoter region becomes associated with acetylated histones by chromatin immunoprecipitation assays. In addition, NFAT1 binds to the promoter of the CTLA-4 gene after stimulation by chromatin immunoprecipitation. The functional requirement of the NFAT site for CTLA-4 transcription was demonstrated by mutations in the NFAT site that abolished the activity of the promoter. Furthermore, inhibitors of NFAT suppressed CTLA-4 gene expression, indicating that NFAT plays a critical role in regulating the induction of the CTLA-4 gene in lymphocytes. The identification of NFAT as a critical regulator of the CTLA-4 gene suggests that targeting NFAT function may lead to novel approaches to modulate the CTLA-4 gene to control the immune response.

Purpose: Mycosis fungoides (MF) is a cutaneous T-cell lymphoma (CTCL) characterized by neoplastic skin-homing T cells. To better understand the immunopathogenesis of MF, we analyzed the functional ability of peripheral blood mononuclear cells (PBMC) from early and late MF/CTCL patients to express cytokine genes. In late stage MF/CTCL, patients were separated into those with blood involvement (+B) and without blood involvement (−B). Experimental Design: We analyzed TH1 (interleukin 2 (IL-2), IFN-γ), TH2 (IL-4, IL-5, IL-10, IL-13), and TH17 (IL-17) cytokine gene expression from activated PBMCs from normal (n = 12), psoriasis (n = 6), early MF/CTCL (n = 11), and late MF/CTCL+B (n = 4) and MF/CTCL−B (n = 3) by quantitative real-time PCR. Results: PBMCs from early MF/CTCL and psoriasis showed higher induction of IL-2, IL-4, and IFN-γ genes than those from normal and late MF/CTCL−B and MF/CTCL+B (P < 0.05) in descending order. PBMCs from late MF/CTCL−B exhibited generally the highest level of IL-5, IL-10, IL-13, and IL-17 expression compared with the other groups. PBMCs from early MF/CTCL and late MF/CTCL−B had similarly elevated IL-13 and IL-17. Of all groups, PBMCs from late MF/CTCL+B had the lowest levels of IL-2 (P < 0.05), IL-4, IFN-γ, IL-13, and IL-17. Conclusions: The different pattern of cytokine gene expression suggests a change in immune function in MF/CTCL from early MF/CTCL to late MF/CTCL−B to late MF/CTCL+B. These stages are consistent with localized disease associated with an anti-tumor immune response and late MF/CTCL associated with a loss of immune function mediated by malignant T cells that share regulatory T cell–like properties.

CTLA-4 is a costimulatory molecule that negatively regulates T cell activation. Originally identified in murine CD8+ T cells, it has been found to be rapidly induced on human T cells. Furthermore, CTLA-4 is expressed on regulatory T cells (Tregs). Clinically, targeting CTLA-4 has clinical utility in the treatment of melanoma. Whether the expression of CTLA-4 is differentially regulated in CD8+ vs. CD4+ human T cells is unclear. Here we analyzed CTLA-4 in normal human CD4+ and CD8+ T cell subsets and show for the first time that CTLA-4 is expressed significantly higher in the CD4+ T cells than in CD8+ T cells. CTLA-4 is higher at the protein and the transcriptional level in CD4+ T cells. This increase is due to activation of the CTLA-4 promoter, which undergoes acetylation at the proximal promoter. Furthermore, we show that blocking CTLA-4 on CD4+ T cells permits greater proliferation in CD4+ vs. CD8+ cells. These findings demonstrate a differential regulation of CTLA-4 on CD4+ and CD8+ T cell subsets, which is likely important to the clinical efficacy for anti-CTLA-4 therapies. The findings hint to strategies to modulate CTLA-4 expression by targeting epigenetic transcription to alter the immune response.

Mycosis fungoides (MF) is a low-grade lymphoma of cluster of differentiation (CD)4+, CD45RO+, cutaneous leukocyte antigen (CLA)+ T cells that homes to the skin. To understand the functional abnormalities in this disease, we study the regulation of cytotoxic T-lymphocyte antigen (CTLA)-4 in peripheral blood mononuclear cells (PBMCs) from patients with MF. CTLA-4 is a costimulatory molecule for T cells that functions in immunoregulation. Unlike the expression of CD28, which is expressed constitutively on T cells, CTLA-4 expression is highly regulated. In the analysis of PBMCs in MF, we found that CTLA-4 is stimulated by phorbol myristate acetate/A23187 to a greater level when compared to normals. This defect was seen in the dominant clones of T cells. The increased CTLA-4 expression was significant between normal and MF, with a correlation between higher expression of CTLA-4 and a higher grade of MF. In a patient whose disease progressed, the CTLA-4 level increased. The abnormal level of CTLA-4 was confirmed at both the transcription and translation levels. Although MF is associated with a Th2 bias, Th1 cytokines IL-2 and IFN-gamma enhanced CTLA-4 expression, while IL-4 did not. These findings reveal an abnormal regulation of CTLA-4 expression in MF and show that PBMCs from patients with MF have properties that are divergent from those of normal T cells.

Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch® arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, Gβψ, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch® methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.

Background Dysfunctions in memory T cells contribute to various inflammatory autoimmune diseases and neoplasms. We hypothesize that investigating the differences of genetic profiles between resting and activated naïve and memory T cells may provide insight into the characterization of abnormal memory T cells in diseases, such as Sézary syndrome (SS), a neoplasm composed of CD4+ CD45RO+ cells. Objective We determined genes distinctively expressed between resting and activated naive and memory cells. Levels of up-regulated genes in resting and activated memory cells were measured in SS PBMCs, which were largely comprised of CD4+ CD45RO+ cells, to quantitatively assess how different Sézary cells were from memory cells. Methods We compared gene expression profiles using high density oligo-microarrays between resting and activated naïve and memory CD4+ T cells. Differentially expressed genes were confirmed by qRT-PCR and immunoblotting. Levels of genes up-regulated in activated and resting memory T cells were determined in SS PBMCs by qRT-PCR. Results Activated memory cells expressed greater numbers of immune-mediated genes involved in effector function compared to naïve cells in our microarray analysis and qRT-PCR. Nine out of 14 genes with enhanced levels in activated memory cells had reduced levels in SS PBMCs (p<0.05). Conclusions Activation of memory and naïve CD4+ T cells revealed a diverging gap in gene expression between these subsets, with memory cells expressing immune-related genes important for effector function. Many of these genes were markedly depressed in SS patients, implying Sézary cells are markedly impaired in mounting immune responses compared to memory cells.

Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICI) remain limited to a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetics and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveals a highly prevalent patient molecular profiles predictive of response to PD-(L)1 immune checkpoint inhibitors. A clinical blood test based on the set of 8 3D genomic biomarkers has been developed and validated on several independent cancer patient cohorts to predict response to PD-(L)1 immune checkpoint inhibition. The predictive 8 biomarker set is derived from prospective observational clinical trials, representing 229 treatments with Pembrolizumab, Atezolizumab, Durvalumab, in diverse indications: melanoma, non-small cell lung, urethral, hepatocellular, bladder, prostate cancer, head and neck, vulvar, colon, breast, bone, brain, lymphoma, larynx cancer, and cervix cancers. The 3D genomic 8 biomarker panel for response to immune checkpoint therapy achieved high accuracy up to 85%, sensitivity of 93% and specificity of 82%. This study demonstrates that a 3D genomic approach could be used to develop a predictive clinical assay for response to PD-(L)1 checkpoint inhibition in cancer patients.