Downregulation of CD45 Signaling in COVID-19 Patients Is Reversed by C24D, a Novel CD45 Targeting Peptide

TNBC-derived Gal3BP/Gal3 complex induces immunosuppression through CD45 receptor

A preliminary study investigating immunotherapy strategies for aggressive triple negative breast cancer (TNBC) revealed an overexpression of genes involved in the release of extracellular vesicles (EVs). Proteins expressed by EVs play a role in reprogramming the tumor microenvironment and impeding effective responses to immunotherapy. Galectin 3 (Gal3), found in the extracellular space of breast cancer cells, downregulates T-cell receptor expression. Gal3 binds to several receptors, including CD45, which is required for T-cell receptor activation. Previously, we reported a novel tumor escape mechanism, whereby TNBC cells suppress immune cells through CD45 intracellular signals. The objective of this study was to determine the potential association of Gal3 with TNBC-secreted EVs induction of immunosuppression via the CD45 signaling pathway. EVs were isolated from MDA-MB-231 cells and the plasma of patients with TNBC. Mass spectrometry revealed the presence of Gal3 binding protein (Gal3BP) in the isolated small EVs, which interacted with TNBC secreted Gal3. Gal3BP and Gal3 form a complex that induces a significant increase in T-regulatory cells in peripheral blood mononuclear cells (PBMCs). This increase correlates with a significant increase in suppressive interleukins 10 and 35. Blocking the CD45 receptor in PBMCs cultured with tumor-derived EVs impeded the immunosuppression exerted by the Gal3BP/Gal3 complex. This led to an increase in IFN-γ and the activation of CD4, CD8 and CD56 effector cells. This study suggests a tumor escape mechanism that may contribute to the development of a different immunotherapy strategy that complements current therapies used for TNBC.

CD45RA and CD45RO Are Regulated in a Cell-Type Specific Manner in Inflammation and Sepsis

CD45 is a transmembrane glycoprotein that is located on the surface of all leukocytes and modulates both innate and adaptive immune system functions. In a recent study, inflammation modulated the CD45 expression in leukocytes, but the effect on the expression of CD45 subtypes is unknown. In the present study, we therefore investigated the effect of inflammatory conditions in humans (surgery, sepsis) and ex vivo incubation with lipopolysaccharides (LPS) on the expression of the subtypes CD45RA and CD45RO in granulocytes, lymphocytes, and monocytes. Whole blood samples were obtained from healthy volunteers, postoperative patients, and patients with sepsis at day 1 of diagnosis, respectively. Samples were incubated with fluorescent antibodies directed against CD45, CD45RA and CD45RO in the absence and presence of lipopolysaccharide and subjected to flow cytometry. In comparison to volunteers, CD45RA surface expression in postoperative and septic patients was reduced by 89% exclusively on granulocytes, but not on lymphocytes or monocytes. In contrast, CD45RO was exclusively reduced on lymphocytes, by 82%, but not on other cell types. Receiver operating characteristic curve analyses demonstrated that CD45RA (on granulocytes) and CD45RO (on lymphocytes) allow a good differentiation of volunteers and patients with sepsis (AUC = 0.9; p = 0.0001). The addition of LPS to the whole blood samples obtained from volunteers, postoperative patients, and septic patients markedly increased the CD45RO expression in granulocytes, lymphocytes, and monocytes. In contrast, LPS reduced CD45RA exclusively on monocytes. In conclusion, the surface expression of CD45RA and CD45RO is regulated in inflammation in a cell-type- and stimulus-specific manner. Considering that CD45 subtypes are critically involved in immune system signaling, the pathophysiologic and diagnostic implications warrant further investigation.

Methotrexate inhibition of SARS-CoV-2 entry, infection and inflammation revealed by bioinformatics approach and a hamster model

Background

Drug repurposing is a fast and effective way to develop drugs for an emerging disease such as COVID-19. The main challenges of effective drug repurposing are the discoveries of the right therapeutic targets and the right drugs for combating the disease.

Methods

Here, we present a systematic repurposing approach, combining Homopharma and hierarchal systems biology networks (HiSBiN), to predict 327 therapeutic targets and 21,233 drug-target interactions of 1,592 FDA drugs for COVID-19. Among these multi-target drugs, eight candidates (along with pimozide and valsartan) were tested and methotrexate was identified to affect 14 therapeutic targets suppressing SARS-CoV-2 entry, viral replication, and COVID-19 pathologies. Through the use of in vitro (EC₅₀ = 0.4 μM) and in vivo models, we show that methotrexate is able to inhibit COVID-19 via multiple mechanisms.

Results

Our in vitro studies illustrate that methotrexate can suppress SARS-CoV-2 entry and replication by targeting furin and DHFR of the host, respectively. Additionally, methotrexate inhibits all four SARS-CoV-2 variants of concern. In a Syrian hamster model for COVID-19, methotrexate reduced virus replication, inflammation in the infected lungs. By analysis of transcriptomic analysis of collected samples from hamster lung, we uncovered that neutrophil infiltration and the pathways of innate immune response, adaptive immune response and thrombosis are modulated in the treated animals.

Conclusions

We demonstrate that this systematic repurposing approach is potentially useful to identify pharmaceutical targets, multi-target drugs and regulated pathways for a complex disease. Our findings indicate that methotrexate is established as a promising drug against SARS-CoV-2 variants and can be used to treat lung damage and inflammation in COVID-19, warranting future evaluation in clinical trials.

Differential Regulation of CD45 Expression on Granulocytes, Lymphocytes, and Monocytes in COVID-19

CD45 is a transmembrane glycoprotein and protein tyrosine phosphatase expressed on the surface of all nucleated hematopoietic cells. While there is increasing evidence demonstrating the involvement of CD45 in immune system regulation, no information on CD45 expression in inflammation and sepsis is currently available. Therefore, we determined the CD45 surface expression on granulocytes, lymphocytes, and monocytes in patients with COVID-19 and healthy volunteers in both absence and presence of lipopolysaccharide (LPS). Following approval by the local ethics committee, whole blood samples were obtained from patients with COVID-19 infection on day 1 of hospital admission and healthy volunteers. Samples were incubated in absence and presence of LPS and CD45 was measured in granulocytes, lymphocytes, and monocytes using flow cytometry. In comparison with healthy individuals, COVID-19 patients showed an increased CD45 expression on the surface of granulocytes (+35%, p < 0.02) and lymphocytes (+39%, p < 0.0001), but a reduced CD45 expression on monocytes (−35%, p < 0.0001). LPS incubation of whole blood from healthy individuals increased the CD45 expression on granulocytes (+430%, p < 0.0001), lymphocytes (+32%, p = 0.0012), and monocytes (+36%, p = 0.0005), respectively. LPS incubation of whole blood samples from COVID-19 patients increased the CD45 expression on granulocytes and monocytes, and decreased the CD45 expression on lymphocytes. In conclusion, CD45 expression on leucocytes is altered: (1) in COVID-19 patients, and (2) in in vitro endotoxemia in a complex cell-specific way, thus representing a new immunoregulatory mechanism.

Automatic Segmentation of Novel Coronavirus Pneumonia Lesions in CT Images Utilizing Deep-Supervised Ensemble Learning Network

Background: The novel coronavirus disease 2019 (COVID-19) has been spread widely in the world, causing a huge threat to the living environment of people. Objective: Under CT imaging, the structure features of COVID-19 lesions are complicated and varied greatly in different cases. To accurately locate COVID-19 lesions and assist doctors to make the best diagnosis and treatment plan, a deep-supervised ensemble learning network is presented for COVID-19 lesion segmentation in CT images. Methods: Since a large number of COVID-19 CT images and the corresponding lesion annotations are difficult to obtain, a transfer learning strategy is employed to make up for the shortcoming and alleviate the overfitting problem. Based on the reality that traditional single deep learning framework is difficult to extract complicated and varied COVID-19 lesion features effectively that may cause some lesions to be undetected. To overcome the problem, a deep-supervised ensemble learning network is presented to combine with local and global features for COVID-19 lesion segmentation. Results: The performance of the proposed method was validated in experiments with a publicly available dataset. Compared with manual annotations, the proposed method acquired a high intersection over union (IoU) of 0.7279 and a low Hausdorff distance (H) of 92.4604. Conclusion: A deep-supervised ensemble learning network was presented for coronavirus pneumonia lesion segmentation in CT images. The effectiveness of the proposed method was verified by visual inspection and quantitative evaluation. Experimental results indicated that the proposed method has a good performance in COVID-19 lesion segmentation.