Molecular mechanisms underlying regulatory T cell deficiency and potential drugs in COVID-19

Background/Purpose: The 2019 outbreak of coronavirus disease COVID-19 causes immune system disruption. Recent studies reported that the decrease or depletion of regulatory T cell (Treg) may be responsible for overstimulation of the immune system and lung damage in patients with severe COVID-19. This study aims to find the molecular mechanisms and genetic biomarkers associated with Tregs in COVID-19, providing new ideas for the treatment of COVID-19. Method(s): RNA sequencing data of peripheral blood mononuclear cells (PBMC) from 252 COVID-19 infected patients and 69 healthy controls (HC) were obtained from the GEO database. The Tregs composition of COVID-19 samples was quantified using the CIBERSORT deconvolution method. The differential genes (DEGs) were identified by the limma R package. Gene co-expression network analysis (WGCNA) was used to identify the gene. Differentially expressed Tregs-related genes (DETregRGs) were obtained by intersecting DEGs with the highly related modular genes obtained in the previous step. The potential biological functions and pathways of DETregRGs were then explored. Protein-protein interaction (PPI) networks were subsequently constructed to identify hub genes. In addition, the prediction of small molecule drugs for the potential treatment of COVID-19 was made using the CMap database. Result(s): After the weighted gene co-expression network analysis (WGCNA), the turquoise module was highly correlated with Treg expression and a total of 134 DEGs was identified as DETregRGs. These genes were mainly involved in GO biological processes, such as the inflammatory response, and T cell differentiation of thymus. Then, 11 hub genes (including RPS12, RPL21, RPS3A, CD8B, CD3D, TRAT1, RPS6, CD3E, CD28, RPL3, and CD4) were ranked based on Molecular Complex Detection (MCODE) analysis. The TregRG score of COVID-19 patients showed significantly lower than HC, calculated by the 'singscore' algorithms. After the signature query of the CMap database, the KU-0063794, an mTOR inhibitor ranked second in the negative enrichment score, may restore immune system dysregulation caused by increased Th17 differentiation and decreased Treg differentiation during SARS-CoV- 2 infection. Conclusion(s): Our study examined in detail the molecular mechanisms underlying the inadequacy of Tregs in patients with COVID-19 infection. mTOR inhibitors may improve COVID-19 symptoms by expanding Tregs which may be one of the potential therapeutic methods that need further investigation. (Figure Presented).

Novel Immune-Related Genetic Expression for Primary Sjögren's Syndrome.

Objective: To identify novel immune-related genes expressed in primary Sjögren's syndrome (pSS). Methods: Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were screened. The differences in immune cell proportion between normal and diseased tissues were compared, weighted gene co-expression network analysis was conducted to identify key modules, followed by a protein-protein interaction (PPI) network generation and enrichment analysis. The feature genes were screened and verified using the GEO datasets and quantitative real-time PCR (RT-qPCR). Results: A total of 345 DEGs were identified, and the proportions of gamma delta T cells, memory B cells, regulatory T cells (Tregs), and activated dendritic cells differed significantly between the control and pSS groups. The turquoise module indicated the highest correlation with pSS, and 252 key genes were identified. The PPI network of key genes showed that RPL9, RBX1, and RPL31 had a relatively higher degree. In addition, the key genes were mainly enriched in coronavirus disease-COVID-2019, hepatitis C, and influenza A. Fourteen feature genes were obtained using the support vector machine model, and two subtypes were identified. The genes in the two subtypes were mainly enriched in the JAK-STAT, p53, and toll-like receptor signaling pathways. The majority of the feature genes were upregulated in the pSS group, verified using the GEO datasets and RT-qPCR analysis. Conclusions: Memory B cells, gamma delta T cells, Tregs, activated dendritic cells, RPL9, RBX1, RPL31, and the feature genes possible play vital roles in the development of pSS.

Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.

INTRODUCTION: The risk of infection with COVID-19 is high in lung adenocarcinoma (LUAD) patients, and there is a dearth of studies on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape. OBJECTIVES: To fill the research void on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape. METHODS: Herein, we identified genes, specifically the differentially expressed genes (DEGs), correlated with the susceptibility of LUAD patients to COVID-19. These were obtained by calculating standard mean deviation (SMD) values for 49 SARS-CoV-2-infected LUAD samples and 24 non-affected LUAD samples, as well as 3931 LUAD samples and 3027 non-cancer lung samples from 40 pooled RNA-seq and microarray datasets. Hub susceptibility genes significantly related to COVID-19 were further selected by weighted gene co-expression network analysis. Then, the hub genes were further analyzed via an examination of their clinical significance in multiple datasets, a correlation analysis of the immune cell infiltration level, and their interactions with the interactome sets of the A549 cell line. RESULTS: A total of 257 susceptibility genes were identified, and these genes were associated with RNA splicing, mitochondrial functions, and proteasomes. Ten genes, MEA1, MRPL24, PPIH, EBNA1BP2, MRTO4, RABEPK, TRMT112, PFDN2, PFDN6, and NDUFS3, were confirmed to be the hub susceptibility genes for COVID-19 in LUAD patients, and the hub susceptibility genes were significantly correlated with the infiltration of multiple immune cells. CONCLUSION: In conclusion, the susceptibility genes for COVID-19 in LUAD patients discovered in this study may increase our understanding of the high risk of COVID-19 in LUAD patients.

Single-cell RNA sequencing identify SDCBP in ACE2-positive bronchial epithelial cells negatively correlates with COVID-19 severity.

The coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in many deaths throughout the world. It is vital to identify the novel prognostic biomarkers and therapeutic targets to assist with the subsequent diagnosis and treatment plan to mitigate the expansion of COVID-19. Since angiotensin-converting enzyme 2 (ACE2)-positive cells are hosts for COVID-19, we focussed on this cell type to explore the underlying mechanisms of COVID-19. In this study, we identified that ACE2-positive cells from the bronchoalveolar lavage fluid (BALF) of patients with COVID-19 belong to bronchial epithelial cells. Comparing with patients of COVID-19 showing severe symptoms, the antigen processing and presentation pathway was increased and 12 typical genes, HLA-DRB5, HLA-DRB1, CD74, HLA-DRA, HLA-DPA1, HLA-DQA1, HSP90AA1, HSP90AB1, HLA-DPB1, HLA-DQB1, HLA-DQA2, and HLA-DMA, particularly HLA-DPB1, were obviously up-regulated in ACE2-positive bronchial epithelial cells of patients with mild disease. We further discovered SDCBP was positively correlated with above 12 genes particularly with HLA-DPB1 in ACE2-positive bronchial epithelial cells of COVID-19 patients. Moreover, SDCBP may increase the immune infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells in different lung carcinoma. Moreover, we found the expression of SDCBP was positively correlated with the expression of antigen processing and presentation genes in post-mortem lung biopsies tissues, which is consistent with previous discoveries. These results suggest that SDCBP has good potential to be further developed as a novel diagnostic and therapeutic target in the treatment of COVID-19.

The SARS-CoV-2 host cell receptor ACE2 correlates positively with immunotherapy response and is a potential protective factor for cancer progression.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 29 million people and has caused more than 900,000 deaths worldwide as of September 14, 2020. The SARS-CoV-2 human cell receptor ACE2 has recently received extensive attention for its role in SARS-CoV-2 infection. Many studies have also explored the association between ACE2 and cancer. However, a systemic investigation into associations between ACE2 and oncogenic pathways, tumor progression, and clinical outcomes in pan-cancer remains lacking. Using cancer genomics datasets from the Cancer Genome Atlas (TCGA) program, we performed computational analyses of associations between ACE2 expression and antitumor immunity, immunotherapy response, oncogenic pathways, tumor progression phenotypes, and clinical outcomes in 13 cancer cohorts. We found that ACE2 upregulation was associated with increased antitumor immune signatures and PD-L1 expression, and favorable anti-PD-1/PD-L1/CTLA-4 immunotherapy response. ACE2 expression levels inversely correlated with the activity of cell cycle, mismatch repair, TGF-ß, Wnt, VEGF, and Notch signaling pathways. Moreover, ACE2 expression levels had significant inverse correlations with tumor proliferation, stemness, and epithelial-mesenchymal transition. ACE2 upregulation was associated with favorable survival in pan-cancer and in multiple individual cancer types. These results suggest that ACE2 is a potential protective factor for cancer progression. Our data may provide potential clinical implications for treating cancer patients infected with SARS-CoV-2.