Molecular Targets for 17α-Ethynyl-5-Androstene-3β,7β,17β-Triol, an Anti-Inflammatory Agent Derived from the Human Metabolome

HE3286, 17α-ethynyl-5-androstene-3β, 7β, 17β-triol, is a novel synthetic compound related to the endogenous sterol 5-androstene-3β, 7β, 17β-triol (β-AET), a metabolite of the abundant adrenal steroid dehydroepiandrosterone (DHEA). HE3286 has shown efficacy in clinical studies in impaired glucose tolerance and type 2 diabetes, and in vivo models of types 1 and 2 diabetes, autoimmunity, and inflammation. Proteomic analysis of solid-phase HE3286-bound bead affinity experiments, using extracts from RAW 264.7 mouse macrophage cells, identified 26 binding partners. Network analysis revealed associations of these HE3286 target proteins with nodes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for type 2 diabetes, insulin, adipokine, and adipocyte signaling. Binding partners included low density lipoprotein receptor-related protein (Lrp1), an endocytic receptor; mitogen activated protein kinases 1 and 3 (Mapk1, Mapk3), protein kinases involved in inflammation signaling pathways; ribosomal protein S6 kinase alpha-3 (Rsp6ka3), an intracellular regulatory protein; sirtuin-2 (Sirt2); and 17β-hydroxysteroid dehydrogenase 1 (Hsd17β4), a sterol metabolizing enzyme

Image based machine learning for identification of macrophage subsets

Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplified by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at the two ends of the spectrum. Characterisation of M1 and M2 subsets is usually carried out by quantification of multiple cell surface markers, transcription factors and cytokine profiles. These approaches are time consuming, require large numbers of cells and are resource intensive. In this study, we used machine learning algorithms to develop a simple and fast imaging-based approach that enables automated identification of different macrophage functional phenotypes using their cell size and morphology. Fluorescent microscopy was used to assess cell morphology of different cell types which were stained for nucleus and actin distribution using DAPI and phalloidin respectively. By only analysing their morphology we were able to identify M1 and M2 phenotypes effectively and could distinguish them from naïve macrophages and monocytes with an average accuracy of 90%. Thus we suggest high-content and automated image analysis can be used for fast phenotyping of functionally diverse cell populations with reasonable accuracy and without the need for using multiple markers

T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection.

The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence. Here we show that a transcriptional signature reflecting CD8 T-cell exhaustion is associated with poor clearance of chronic viral infection, but conversely predicts better prognosis in multiple autoimmune diseases. The development of CD8 T-cell exhaustion during chronic infection is driven both by persistence of antigen and by a lack of accessory 'help' signals. In autoimmunity, we find that where evidence of CD4 T-cell co-stimulation is pronounced, that of CD8 T-cell exhaustion is reduced. We can reproduce the exhaustion signature by modifying the balance of persistent stimulation of T-cell antigen receptors and specific CD2-induced co-stimulation provided to human CD8 T cells in vitro, suggesting that each process plays a role in dictating outcome in autoimmune disease. The 'non-exhausted' T-cell state driven by CD2-induced co-stimulation is reduced by signals through the exhaustion-associated inhibitory receptor PD-1, suggesting that induction of exhaustion may be a therapeutic strategy in autoimmune and inflammatory disease. Using expression of optimal surrogate markers of co-stimulation/exhaustion signatures in independent data sets, we confirm an association with good clinical outcome or response to therapy in infection (hepatitis C virus) and vaccination (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (type 1 diabetes, anti-neutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, idiopathic pulmonary fibrosis and dengue haemorrhagic fever). Thus, T-cell exhaustion plays a central role in determining outcome in autoimmune disease and targeted manipulation of this process could lead to new therapeutic opportunities

The three main stumbling blocks for anticancer T cells.

Memory and effector T cells have the potential to counteract cancer progression, but often fail to control the disease, essentially because of three main stumbling blocks. First, clonal deletion leads to relatively low numbers or low-to-intermediate T cell receptor (TCR) affinity of self/tumor-specific T cells. Second, the poor innate immune stimulation by solid tumors is responsible for inefficient priming and boosting. Third, T cells are suppressed in the tumor microenvironment by inhibitory signals from other immune cells, stroma and tumor cells, which induces T cell exhaustion, as demonstrated in metastases of melanoma patients. State-of-the-art adoptive cell transfer and active immunotherapy can partially overcome the three stumbling blocks. The reversibility of T cell exhaustion and novel molecular insights provide the basis for further improvements of clinical immunotherapy

Tumor antigen-specific FOXP3+ CD4 T cells identified in human metastatic melanoma: peptide vaccination results in selective expansion of Th1-like counterparts.

We have previously shown that vaccination of HLA-A2 metastatic melanoma patients with the analogue Melan-A(26-35(A27L)) peptide emulsified in a mineral oil induces ex vivo detectable specific CD8 T cells. These are further enhanced when a TLR9 agonist is codelivered in the same vaccine formulation. Interestingly, the same peptide can be efficiently recognized by HLA-DQ6-restricted CD4 T cells. We used HLA-DQ6 multimers to assess the specific CD4 T-cell response in both healthy individuals and melanoma patients. We report that the majority of melanoma patients carry high frequencies of naturally circulating HLA-DQ6-restricted Melan-A-specific CD4 T cells, a high proportion of which express FOXP3 and proliferate poorly in response to the cognate peptide. Upon vaccination, the relative frequency of multimer+ CD4 T cells did not change significantly. In contrast, we found a marked shift to FOXP3-negative CD4 T cells, accompanied by robust CD4 T-cell proliferation upon in vitro stimulation with cognate peptide. A concomitant reduction in TCR diversity was also observed. This is the first report on direct ex vivo identification of antigen-specific FOXP3+ T cells by multimer labeling in cancer patients and on the direct assessment of the impact of peptide vaccination on immunoregulatory T cells