Tetraspanin CD53: an overlooked regulator of immune cell function

Exploring the crosstalk molecular mechanisms between IgA nephropathy and Sjögren's syndrome based on comprehensive bioinformatics and immunohistochemical analyses

IgA nephropathy (IgAN) and Sjogren's syndrome (SS) are two autoimmune diseases with undetermined etiology and related to abnormal activation of lymphocytes. This study aims to explore the crucial genes, pathways and immune cells between IgAN and SS. Gene expression profiles of IgAN and SS were obtained from the Gene Expression Omnibus and Nephroseq data. Differentially expressed gene (DEG) and weighted gene co-expression network analyses (WGCNA) were done to identify common genes. Enrichment analysis and protein-protein interaction network were used to explore potential molecular pathways and crosstalk genes between IgAN and SS. The results were further verified by external validation and immunohistochemistry (IHC) analysis. Additionally, immune cell analysis and transcription factor prediction were also conducted. The DEG analysis revealed 28 commonly up-regulated genes, while WGCNA identified 98 interactively positive-correlated module genes between IgAN and SS. The enrichment analysis suggested that these genes were mainly involved in the biological processes of response to virus and antigen processing and presentation. The external validation and IHC analysis identified 5 hub genes (PSMB8, PSMB9, IFI44, ISG15, and CD53). In the immune cell analysis, the effector memory CD8 T and T follicular helper cells were significantly activated, and the corresponding proportions showed positively correlations with the expressions of the 5 hub genes in the two autoimmune diseases. Together, our data identified the crosstalk genes, molecular pathways, and immune cells underlying the IgAN and SS, which provides valuable insights into the intricate mechanisms of these diseases and offers potential intervention targets.

N-Glycosylation-dependent regulation of immune-specific tetraspanins CD37 and CD53

Tetraspanin proteins play an important role in many cellular processes as they are key organizers of different receptors on the plasma membrane. Most tetraspanins are highly glycosylated at their large extracellular loop; however, little is known about the function of tetraspanin glycosylation in immune cells. In this study we investigated the effects of glycosylation of CD37 and CD53, two tetraspanins important for cellular and humoral immunity. Broad and cell-specific repertoires of N-glycosylated CD37 and CD53 were observed in human B cells. We generated different glycosylation mutants of CD37 and CD53 and analyzed their localization, nanoscale plasma membrane organization, and partner protein interaction capacity. Abrogation of glycosylation in CD37 revealed the importance of this modification for CD37 surface expression, whereas surface expression of CD53 was unaffected by its glycosylation. Single-molecule dSTORM microscopy revealed that the nanoscale organization of CD53 was not dependent on glycosylation. CD37 interaction with its partner proteins CD53 and CD20 was affected by glycosylation in a localization-dependent way, whereas its interaction with IL-6Rα was independent of glycosylation. Surprisingly, glycosylation was found to inhibit the interaction between CD53 and its partner proteins CD45, CD20, and, to a lesser extent CD37. Together, our data show that glycosylation affects the interaction capacity of immune-specific tetraspanins CD37 and CD53, which adds another layer of regulation to immune membrane organization.

GS-TCGA: Gene Set-Based Analysis of The Cancer Genome Atlas

Most tools for analyzing large gene expression datasets, including The Cancer Genome Atlas (TCGA), have focused on analyzing the expression of individual genes or inference of the abundance of specific cell types from whole transcriptome information. While these methods provide useful insights, they can overlook crucial process-based information that may enhance our understanding of cancer biology. In this study, we describe three novel tools incorporated into an online resource; gene set-based analysis of The Cancer Genome Atlas (GS-TCGA). GS-TCGA is designed to enable user-friendly exploration of TCGA data using gene set-based analysis, leveraging gene sets from the Molecular Signatures Database. GS-TCGA includes three unique tools: GS-Surv determines the association between the expression of gene sets and survival in human cancers. Co-correlative gene set enrichment analysis (CC-GSEA) utilizes interpatient heterogeneity in cancer gene expression to infer functions of specific genes based on GSEA of coregulated genes in TCGA. GS-Corr utilizes interpatient heterogeneity in cancer gene expression profiles to identify genes coregulated with the expression of specific gene sets in TCGA. Users are also able to upload custom gene sets for analysis with each tool. These tools empower researchers to perform survival analysis linked to gene set expression, explore the functional implications of gene coexpression, and identify potential gene regulatory mechanisms.

Tetraspanin CD53 regulates peripheral blood leucocytes vitality and pathogen infection in turbot (Scophthalmus maximus)

Cluster of differentiation 53 (CD53) also known as OX44 or tetraspanin 25 (TSPAN25) is a glycoprotein belonging to the tetraspanin family. Members of the tetraspanin family are characterized by four transmembrane domains, including intracellular N- and C-termini, and small and large extracellular domains. Currently, the function of CD53 in teleost is not well understood. In this study, we identified a CD53 (named SmCD53) from turbot (Scophthalmus maximus) and examined its expression and biological activity. SmCD53 contained 231 amino acid residues and was predicted to be a tetraspanin with small and large extracellular domains. SmCD53 expression was observed in different tissues, particularly in immune-related organs. Experimental infection with bacterial or viral pathogen significantly up-regulated SmCD53 expression in a time-dependent manner. Immunofluorescence microscopy analysis showed that SmCD53 was localized on the surface of PBL and was recognized by antibody against its large extracellular domain. Ligation of SmCD53 onto PBLs with antibodies suppressed the respiratory burst activity, inflammatory reaction, and enhanced cell viability. SmCD53 knockdown significantly enhanced bacterial dissemination and proliferation in turbot. Overall, these results underscore the importance of CD53 in the maintenance of the function and homeostasis of the immune system.

Identification of hub genes and transcription factors in patients with primary gout complicated with atherosclerosis

Evidence shows that primary gout is prone to develop to atherosclerosis, but the mechanism of its occurrence is still not fully clarified. The aim of this study was to explore the molecular mechanism of the occurrence of this complication in gout. The gene expression profiles of primary gout and atherosclerosis were downloaded from the gene expression omnibus database. Overlapping differentially expressed genes (DEGs) between gout and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analyses. Hub genes were identified using protein-protein interaction networks. The immune infiltrations of 28 types of immune cells in gout and control samples from GSE160170 were evaluated by the ssGSEA method. Transcription factors (TFs) were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. A total of 168 overlapping DEGs were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in chemokine signaling pathway, regulation of actin cytoskeleton, and TNF signaling pathway. CytoScape demonstrated 11 hub genes and two gene cluster modules. The immune infiltration analysis showed that the expression of DEGs in gout was significantly upregulated in activated CD4 T cells, gamma delta T cells, T follicular helper cell, CD56dim natural killer cells, and eosinophil. TRRUST predicted one TF, RUNX family transcription factor 1. Our study explored the pathogenesis of gout with atherosclerosis and discovered the immune infiltration of gout. These results may guide future experimental research and clinical transformation.

Spatial Transcriptomic Profiling of Tetraspanins in Stage 4 Colon Cancer from Primary Tumor and Liver Metastasis

Stage 4 colon cancer (CC) presents a significant global health challenge due to its poor prognosis and limited treatment options. Tetraspanins, the transmembrane proteins involved in crucial cancer processes, have recently gained attention as diagnostic markers and therapeutic targets. However, their spatial expression and potential roles in stage 4 CC tissues remain unknown. Using the GeoMx digital spatial profiler, we profiled all 33 human tetraspanin genes in 48 areas within stage 4 CC tissues, segmented into immune, fibroblast, and tumor compartments. Our results unveiled diverse gene expression patterns across different primary tumor sub-regions. CD53 exhibited distinct overexpression in the immune compartment, hinting at a potential role in immune modulation. TSPAN9 was specifically overexpressed in the fibroblast compartment, suggesting involvement in tumor invasion and metastasis. CD9, CD151, TSPAN1, TSPAN3, TSPAN8, and TSPAN13 displayed specific overexpression in the tumor compartment, indicating potential roles in tumor growth. Furthermore, our differential analysis revealed significant spatial changes in tetraspanin expression between patient-matched stage 4 primary CC and metastatic liver tissues. These findings provide spatially resolved insights into the expression and potential roles of tetraspanins in stage 4 CC progression, proposing their utility as diagnostic markers and therapeutic targets. Understanding this landscape is beneficial for tailoring therapeutic strategies to specific sub-tumor regions in the context of stage 4 CC and liver metastasis.

Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning

Background

Lupus nephritis (LN) is a common and severe glomerulonephritis that often occurs as an organ manifestation of systemic lupus erythematosus (SLE). However, the complex pathological mechanisms associated with LN have hindered the progress of targeted therapies.

Methods

We analyzed glomerular tissues from 133 patients with LN and 51 normal controls using data obtained from the GEO database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was utilized to identify key gene modules. The least absolute shrinkage and selection operator (LASSO) and random forest were used to identify hub genes. We also analyzed immune cell infiltration using CIBERSORT. Additionally, we investigated the relationships between hub genes and clinicopathological features, as well as examined the distribution and expression of hub genes in the kidney.

Results

A total of 270 DEGs were identified in LN. Using weighted gene co-expression network analysis (WGCNA), we clustered these DEGs into 14 modules. Among them, the turquoise module displayed a significant correlation with LN (cor=0.88, p<0.0001). Machine learning techniques identified four hub genes, namely CD53 (AUC=0.995), TGFBI (AUC=0.997), MS4A6A (AUC=0.994), and HERC6 (AUC=0.999), which are involved in inflammation response and immune activation. CIBERSORT analysis suggested that these hub genes may contribute to immune cell infiltration. Furthermore, these hub genes exhibited strong correlations with the classification, renal function, and proteinuria of LN. Interestingly, the highest hub gene expression score was observed in macrophages.

Conclusion

CD53, TGFBI, MS4A6A, and HERC6 have emerged as promising candidate driver genes for LN. These hub genes hold the potential to offer valuable insights into the molecular diagnosis and treatment of LN.

Diversity of Megakaryocytes

Megakaryocytes are commonly known as large, polyploid, bone marrow resident cells that contribute to hemostasis through the production of platelets. Soon after their discovery in the 19th century, megakaryocytes were described in tissue locations other than the bone marrow, specifically in the lungs and the blood circulation. However, the localization of megakaryocytes in the lungs and the contribution of lung megakaryocytes to the general platelet pool has only recently been appreciated. Moreover, the conception of megakaryocytes as uniform cells with the sole purpose of platelet production has been challenged. Here, we review the literature on megakaryocyte cell identity and location with a special focus on recent observations of megakaryocyte subpopulations identified by transcriptomic analyses.

Single-cell transcriptome analysis reveals the key genes associated with macrophage polarization in liver cancer

BACKGROUND

The aim of this study was to reveal the key genes associated with macrophage polarization in liver cancer.

METHODS

Data were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas databases (TCGA). R package Seurat 4.0 was used to preprocess the downloaded single-cell sequencing data, principal component analysis, and clustering. R package SingleR was used to annotate cell types and calculate macrophage polarization scores. Spearman correlation analysis was performed to obtain key genes highly correlated with macrophage polarization in liver cancer. The Tumor IMmune Estimation Resource algorithm was used to analyze the correlation between genes and the infiltration level of macrophages. Finally, the prognostic model was constructed based on 6 macrophage polarization-related genes by multivariate Cox regression analysis. Kaplan-Meier curves and receiver operating characteristic curves validated the prognostic value of the prognostic model.

RESULTS

Two thousand highly variable genes were obtained after the normalization of single-cell profiles. In all, 16 principal components and 15 cell clusters were obtained. Monocytes and macrophages were the main immune cells in the microenvironment of liver cancer tissues. Macrophage polarization scores showed that cluster 5 had the highest degree of polarization. Spearman analysis yielded that a total of 6 key genes associated with macrophage polarization (CD53, TGFBI, S100A4, pyruvate kinase M, LSP1, SPP1), and Tumor IMmune Estimation Resource analysis showed that 6 key genes were significantly positively correlated with macrophage infiltration levels. The model constructed by 6 key genes could effectively evaluate the prognosis of patients with liver cancer.

CONCLUSIONS

The key genes associated with macrophage polarization, namely CD53, TGFBI, S100A4, pyruvate kinase M, LSP1, and SPP1, may be potential therapeutic targets for liver cancer.

EBV-Associated Hub Genes as Potential Biomarkers for Predicting the Prognosis of Nasopharyngeal Carcinoma

This study aimed to develop a model using Epstein-Barr virus (EBV)-associated hub genes in order to predict the prognosis of nasopharyngeal carcinoma (NPC). Differential expression analysis, univariate regression analysis, and machine learning were performed in three microarray datasets (GSE2371, GSE12452, and GSE102349) collected from the GEO database. Three hundred and sixty-six EBV-DEGs were identified, 25 of which were found to be significantly associated with NPC prognosis. These 25 genes were used to classify NPC into two subtypes, and six genes (C16orf54, CD27, CD53, CRIP1, RARRES3, and TBC1D10C) were found to be hub genes in NPC related to immune infiltration and cell cycle regulation. It was shown that these genes could be used to predict the prognosis of NPC, with functions related to tumor proliferation and immune infiltration, making them potential therapeutic targets. The findings of this study could aid in the development of screening and prognostic methods for NPC based on EBV-related features.

Bioinformatics analysis of potential common pathogenic mechanism for carotid atherosclerosis and Parkinson's disease

Background

Cerebrovascular disease (CVD) related to atherosclerosis and Parkinson's disease (PD) are two prevalent neurological disorders. They share common risk factors and frequently occur together. The aim of this study is to investigate the association between atherosclerosis and PD using genetic databases to gain a comprehensive understanding of underlying biological mechanisms.

Methods

The gene expression profiles of atherosclerosis (GSE28829 and GSE100927) and PD (GSE7621 and GSE49036) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for these two disorders, we constructed protein-protein interaction (PPI) networks and functional modules, and further identified hub genes using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The diagnostic effectiveness of these hub genes was evaluated using Receiver Operator Characteristic Curve (ROC) analysis. Furthermore, we used single sample gene set enrichment analysis (ssGSEA) to analyze immune cell infiltration and explored the association of the identified hub genes with infiltrating immune cells through Spearman's rank correlation analysis in R software.

Results

A total of 50 shared DEGs, with 36 up-regulated and 14 down-regulated genes, were identified through the intersection of DEGs of atherosclerosis and PD. Using LASSO regression, we identified six hub genes, namely C1QB, CD53, LY96, P2RX7, C3, and TNFSF13B, in the lambda.min model, and CD14, C1QB, CD53, P2RX7, C3, and TNFSF13B in the lambda.1se model. ROC analysis confirmed that both models had good diagnostic efficiency for atherosclerosis datasets GSE28829 (lambda.min AUC = 0.99, lambda.1se AUC = 0.986) and GSE100927 (lambda.min AUC = 0.922, lambda.1se AUC = 0.933), as well as for PD datasets GSE7621 (lambda.min AUC = 0.924, lambda.1se AUC = 0.944) and GSE49036 (lambda.min AUC = 0.894, lambda.1se AUC = 0.881). Furthermore, we found that activated B cells, effector memory CD8 + T cells, and macrophages were the shared correlated types of immune cells in both atherosclerosis and PD.

Conclusion

This study provided new sights into shared molecular mechanisms between these two disorders. These common hub genes and infiltrating immune cells offer promising clues for further experimental studies to explore the common pathogenesis of these disorders.

GBP2 promotes M1 macrophage polarization by activating the notch1 signaling pathway in diabetic nephropathy

Background

Diabetic nephropathy (DN) is one of the most common diabetic complications, which has become the primary cause of end-stage renal disease (ESRD) globally. Macrophage infiltration has been proven vital in the occurrence and development of DN. This study was designed to investigate the hub genes involved in macrophage-mediated inflammation of DN via bioinformatics analysis and experimental validation.

Methods

Gene microarray datasets were obtained from the Gene Expression Omnibus (GEO) public website. Integrating the CIBERSORT, weighted gene co-expression network analysis (WGCNA) and DEGs, we screened macrophage M1-associated key genes with the highest intramodular connectivity. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression was utilized to further mine hub genes. GSE104954 acted as an external validation to predict the expression levels and diagnostic performance of these hub genes. The Nephroseq online platform was employed to evaluate the clinical implications of these hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to elucidate the dominant biological functions and signal pathways. Finally, we conducted experiments to verify the role of GBP2 in M1 macrophage-mediated inflammatory response and the underlying mechanism of this role.

Results

Sixteen DEGs with the highest connectivity in M1 macrophages-associated module (paleturquoise module) were determined. Subsequently, we identified four hub genes through LASSO regression analysis, including CASP1, MS4A4A, CD53, and GBP2. Consistent with the training set, expression levels of these four hub genes manifested memorably elevated and the ROC curves indicated a good diagnostic accuracy with an area under the curve of greater than 0.8. Clinically, enhanced expression of these four hub genes predicted worse outcomes of DN patients. Given the known correlation between the first three hub genes and macrophage-mediated inflammation, experiments were performed to demonstrate the effect of GBP2, which proved that GBP2 contributed to M1 polarization of macrophages by activating the notch1 signaling pathway.

Conclusion

Our findings detected four hub genes, namely CASP1, MS4A4A, CD53, and GBP2, may involve in the progression of DN via pro-inflammatory M1 macrophage phenotype. GBP2 could be a promising prognostic biomarker and intervention target for DN by regulating M1 polarization.

A Blood-Based Immune Gene Signature with Prognostic Significance in Localized Prostate Cancer

Prostate cancer (PCa) is one of the most common male cancers worldwide and one of the deadliest if unsuccessfully treated. Τhe need for reliable, easily accessible immune-related molecular biomarkers that could be combined with clinically defined criteria, including PSA and Gleason score, to accurately predict PCa patients' clinical outcomes is emerging. Herein, we describe for the first time a blood-identified immune-related gene signature comprising eight upregulated multi-functional genes associated with poor prognosis. Next-generation sequencing (NGS) analysis of PCa patients' peripheral blood samples revealed a more than three-fold upregulation of each of the eight genes as compared to samples originating from healthy donors. The construction of gene and protein interaction networks revealed different extents of the functional implications of these genes in the regulation of cell proliferation and immune responses. Analysis of the available data from The Cancer Genome Atlas (TCGA) regarding gene expression and survival of prostate adenocarcinoma (PRAD) and pan-cancer (PANCAN) patients revealed that intra-tumoral upregulation of this eight-gene signature (8-GS) was associated with poor 5-year progression-free intervals in PCa patients, even in those with high Gleason scores, and also with an unfavorable prognosis for cancer patients irrespective of the cancer type and even in the early stages. These observations suggest that further investigation of the 8-GS prospectively in randomized clinical trials, in which clinical benefit in terms of evaluating time to disease progression can be assessed, is warranted.

Single-Cell Discovery and Multiomic Characterization of Therapeutic Targets in Multiple Myeloma

Multiple myeloma (MM) is a highly refractory hematologic cancer. Targeted immunotherapy has shown promise in MM but remains hindered by the challenge of identifying specific yet broadly representative tumor markers. We analyzed 53 bone marrow (BM) aspirates from 41 MM patients using an unbiased, high-throughput pipeline for therapeutic target discovery via single-cell transcriptomic profiling, yielding 38 MM marker genes encoding cell-surface proteins and 15 encoding intracellular proteins. Of these, 20 candidate genes were highlighted that are not yet under clinical study, 11 of which were previously uncharacterized as therapeutic targets. The findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry of MM cell lines and patient BM, demonstrating high overall concordance across data types. Independent discovery using bulk RNA sequencing reiterated top candidates, further affirming the ability of single-cell transcriptomics to accurately capture marker expression despite limitations in sample size or sequencing depth. Target dynamics and heterogeneity were further examined using both transcriptomic and immuno-imaging methods. In summary, this study presents a robust and broadly applicable strategy for identifying tumor markers to better inform the development of targeted cancer therapy.

SIGNIFICANCE

Single-cell transcriptomic profiling and multiomic cross-validation to uncover therapeutic targets identifies 38 myeloma marker genes, including 11 transcribing surface proteins with previously uncharacterized potential for targeted antitumor therapy.

Neutrophilic granulocyte-derived B-cell activating factor supports B cells in skin lesions in hidradenitis suppurativa

BACKGROUND

Hidradenitis suppurativa (HS) is a chronic inflammatory disease characterized by painful inflamed nodules, abscesses, and pus-draining tunnels appearing in axillary, inguinal, and perianal skin areas. HS lesions contain various types of immigrated immune cells.

OBJECTIVE

This study aimed to characterize mediators that support lesional B/plasma cell persistence in HS.

METHODS

Skin samples from several cohorts of HS patients and control cohorts were assessed by mRNA sequencing, quantitative PCR on reverse-transcribed RNA, flow cytometry, and immunohistofluorescence. Blood plasma and cultured skin biopsy samples, keratinocytes, dermal fibroblasts, neutrophilic granulocytes (neutrophils), monocytes, and B cells were analyzed. Complex systems biology approaches were used to evaluate bulk and single-cell RNA sequencing data.

RESULTS

Proportions of B/plasma cells, neutrophils, CD8+ T cells, and M0 and M1 macrophages were elevated in HS lesions compared to skin of healthy and perilesional intertriginous areas. There was an association between B/plasma cells, neutrophils, and B-cell activating factor (BAFF, aka TNFSF13B). BAFF was abundant in HS lesions, particularly in nodules and abscesses. Among the cell types present in HS lesions, myeloid cells were the main BAFF producers. Mechanistically, granulocyte colony-stimulating factor in the presence of bacterial products was the major stimulus for neutrophils' BAFF secretion. Lesional upregulation of BAFF receptors was attributed to B cells (TNFRSF13C/BAFFR and TNFRSF13B/TACI) and plasma cells (TNFRSF17/BCMA). Characterization of the lesional BAFF pathway revealed molecules involved in migration/adhesion (eg, CXCR4, CD37, CD53, SELL), proliferation/survival (eg, BST2), activation (eg, KLF2, PRKCB), and reactive oxygen species production (eg, NCF1, CYBC1) of B/plasma cells.

CONCLUSION

Neutrophil-derived BAFF supports B/plasma cell persistence and function in HS lesions.

The tetraspanin transmembrane protein CD53 mediates dyslipidemia and integrates inflammatory and metabolic signaling in hepatocytes

Tetraspanins are transmembrane signaling and proinflammatory proteins. Prior work demonstrates that the tetraspanin, CD53/TSPAN25/MOX44, mediates B-cell development and lymphocyte migration to lymph nodes and is implicated in various inflammatory diseases. However, CD53 is also expressed in highly metabolic tissues, including adipose and liver; yet its function outside the lymphoid compartment is not defined. Here, we show that CD53 demarcates the nutritional and inflammatory status of hepatocytes. High-fat exposure and inflammatory stimuli induced CD53 in vivo in liver and isolated primary hepatocytes. In contrast, restricting hepatocyte glucose flux through hepatocyte glucose transporter 8 deletion or through trehalose treatment blocked CD53 induction in fat- and fructose-exposed contexts. Furthermore, germline CD53 deletion in vivo blocked Western diet-induced dyslipidemia and hepatic inflammatory transcriptomic activation. Surprisingly, metabolic protection in CD53 KO mice was more pronounced in the presence of an inciting inflammatory event. CD53 deletion attenuated tumor necrosis factor alpha-induced and fatty acid + lipopolysaccharide-induced cytokine gene expression and hepatocyte triglyceride accumulation in isolated murine hepatocytes. In vivo, CD53 deletion in nonalcoholic steatohepatitis diet-fed mice blocked peripheral adipose accumulation and adipose inflammation, insulin tolerance, and liver lipid accumulation. We then defined a stabilized and trehalase-resistant trehalose polymer that blocks hepatocyte CD53 expression in basal and over-fed contexts. The data suggest that CD53 integrates inflammatory and metabolic signals in response to hepatocyte nutritional status and that CD53 blockade may provide a means by which to attenuate pathophysiology in diseases that integrate overnutrition and inflammation, such as nonalcoholic steatohepatitis and type 2 diabetes.

Genomic evidence for adaptation to tuberculosis in the Andes before European contact

Most studies focusing on human high-altitude adaptation in the Andean highlands have thus far been focused on Peruvian populations. We present high-coverage whole genomes from Indigenous people living in the Ecuadorian highlands and perform multi-method scans to detect positive natural selection. We identified regions of the genome that show signals of strong selection to both cardiovascular and hypoxia pathways, which are distinct from those uncovered in Peruvian populations. However, the strongest signals of selection were related to regions of the genome that are involved in immune function related to tuberculosis. Given our estimated timing of this selection event, the Indigenous people of Ecuador may have adapted to Mycobacterium tuberculosis thousands of years before the arrival of Europeans. Furthermore, we detect a population collapse that coincides with the arrival of Europeans, which is more severe than other regions of the Andes, suggesting differing effects of contact across high-altitude populations.

Integration of mRNA and protein expression data for the identification of potential biomarkers associated with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most death-dealing tumors, with a tremendously poor prognosis. Here, we, through interrogation of mRNA and protein data combined with a system biology approach, identified several key genes, functional processes, and pathways that can have critical roles in PDAC. We detected an interesting module related to the clinical traits that enriched in the ribosome, hematopoietic cell lineage, and cell adhesion molecules-related pathways. We also identified several hub genes in important modules that are associated with immune system processes. The results also indicated some lncRNAs, such as FAM30A, and MIR223HG with essential functions that are involved in PDAC. Additionally, five genes, including CD53, ITGAL, WDFY4, TLX1, and LMAN1L were screened by survival analysis and can be considered as candidate biomarkers or therapeutic targets. According to our strategy, the findings of this study may provide a better understanding of the molecular mechanisms and suggest potential prognostic and therapeutic targets for PDAC.

How cell migration helps immune sentinels

The immune system relies on the migratory capacity of its cellular components, which must be mobile in order to defend the host from invading micro-organisms or malignant cells. This applies in particular to immune sentinels from the myeloid lineage, i.e. macrophages and dendritic cells. Cell migration is already at work during mammalian early development, when myeloid cell precursors migrate from the yolk sac, an extra embryonic structure, to colonize tissues and form the pool of tissue-resident macrophages. Later, this is accompanied by a migration wave of precursors and monocytes from the bone marrow to secondary lymphoid organs and the peripheral tissues. They differentiate into DCs and monocyte-derived macrophages. During adult life, cell migration endows immune cells with the ability to patrol their environment as well as to circulate between peripheral tissues and lymphoid organs. Hence migration of immune cells is key to building an efficient defense system for an organism. In this review, we will describe how cell migratory capacity regulates the various stages in the life of myeloid cells from development to tissue patrolling, and migration to lymph nodes. We will focus on the role of the actin cytoskeletal machinery and its regulators, and how it contributes to the establishment and function of the immune system.

The expression of Hexokinase 2 and its hub genes are correlated with the prognosis in glioma

BACKGROUND

Hexokinase 2 (HK2) is an enzyme that catalyses the conversion of glucose to glucose-6-phosphate, which has been found to be associated with malignant tumour growth. However, the potential immunological and clinical significance of HK2, especially in terms of prognostic prediction for patients with glioma, has not been fully elucidated.

METHODS

To investigate the expression, immunological and clinical significance of HK2 in patients with glioma, several databases, including ONCOMINE, TIMER2.0, GEPIA, CGGA, UCSC, LinkedOmics, Metascape, STRING, GSCA, and TISIDB, as well as biochemical, cellular, and pathological analyses, were used in this study. In addition, we performed univariate, multivariate Cox regression and nomogram analyses of the hub genes positively and negatively correlated with HK2 to explore the potential regulatory mechanism in the initiation and development of glioma.

RESULTS

Our results demonstrated that HK2 was highly expressed in most malignant cancers. HK2 expression was significantly higher in lower grade glioma (LGG) and glioblastoma (GBM) than in adjacent normal tissue. In addition, HK2 expression was significantly correlated with clinical parameters, histological manifestations, and prognosis in glioma patients. Specifically, the data from The Cancer Genome Atlas downloaded from UCSC Xena database analysis showed that high expression of HK2 was strongly associated with poor prognosis in glioma patients. The LinkedOmics database indicated that HK2-related genes were mainly enriched in immune-related cells. In LGG and GBM tissues, HK2 expression is usually correlated with recognized immune checkpoints and the abundance of multiple immune infiltrates. Similarly, the Metascape database revealed that HK2-related genes were mainly enriched and annotated in immune-related pathways and immune cells. Further investigations also confirmed that the inhibition of HK2 expression remarkably suppressed metastasis and vasculogenic mimicry (VM) formation in glioma cells through regulating the gene expression of inflammatory and immune modulators.

CONCLUSION

HK2 expression was closely associated with the malignant properties of glioma through activating multiple immune-related signalling pathways to regulate immune responses and the infiltration of immune cells. Thus, HK2 and its hub genes may be a potential target for the treatment of glioma.

Tetraspanin CD53 controls T cell immunity through regulation of CD45RO stability, mobility, and function

T cells depend on the phosphatase CD45 to initiate T cell receptor signaling. Although the critical role of CD45 in T cells is established, the mechanisms controlling function and localization in the membrane are not well understood. Moreover, the regulation of specific CD45 isoforms in T cell signaling remains unresolved. By using unbiased mass spectrometry, we identify the tetraspanin CD53 as a partner of CD45 and show that CD53 controls CD45 function and T cell activation. CD53-negative T cells (Cd53^-/-) exhibit substantial proliferation defects, and Cd53^-/- mice show impaired tumor rejection and reduced IFNγ-producing T cells compared with wild-type mice. Investigation into the mechanism reveals that CD53 is required for CD45RO expression and mobility. In addition, CD53 is shown to stabilize CD45 on the membrane and is required for optimal phosphatase activity and subsequent Lck activation. Together, our findings reveal CD53 as a regulator of CD45 activity required for T cell immunity.

Anti-inflammatory Properties of the Alpha-Melanocyte-Stimulating Hormone in Models of Granulomatous Inflammation

Purpose

Alpha-melanocyte stimulating hormone (α-MSH) is known to have anti-inflammatory effects. However, the anti-inflammatory properties of α-MSH on normal bronchial epithelial cells are largely unknown, especially in the context of in vitro sarcoidosis models.

Methods

We evaluated the anti-inflammatory effects of α-MSH on two different in vitro sarcoidosis models (lung-on-membrane model; LOMM and three-dimensional biochip pulmonary sarcoidosis model; 3D-BSGM) generated from NBECs and an in vivo sarcoidosis mouse model.

Results

Treatment with α-MSH decreased inflammatory cytokine levels and downregulated type I interferon pathway genes and related proteins in LOMM and 3D-BSGM models. Treatment with α-MSH also significantly decreased macrophages and cytotoxic T-cells counts in a sarcoidosis mice model.

Conclusion

Our results confirm the direct role of type I IFNs in the pathogenesis of sarcoid lung granulomas and highlight α-MSH as a potential novel therapeutic agent for treating pulmonary sarcoidosis.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00408-022-00546-x.

Identification of Immune-Related Markers in Hepatocellular Carcinoma Based on Gene Co-expression Network

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death throughout the world, with constant increasing morbidity and mortality. Existing studies suggest that immunotherapy is beneficial to the treatment of advanced HCC. At present, it is imperative to identify biomarkers suitable for HCC immunotherapy. In this paper, the mRNA expression data of HCC were downloaded from The Cancer Genome Atlas, and Stromal Score, Immune Score and ESTIMATE Score of each sample were calculated. Weighted gene co-expression network analysis clustered the pretreated genes into eight modules. The brown module that was remarkably associated with Immune Score was identified by module eigengene-immune trait analysis, in which genes were mainly enriched in immune-related pathways. Four hub genes (CCR5, CD53, ITGB2, and TYROBP) related to tumor immunity, were screened out by intramodular gene connectivity combined with protein-protein interaction network topology analysis. Kaplan-Meier survival analysis presented a correlation between high expression of CCR5 and CD53, and better prognoses of HCC patients. TIMER analysis revealed a positive correlation between expression of each hub gene and immune cell infiltration level, and a positive correlation between the expression of each hub gene and the expression of immunosuppressive factors CTLA4 and PDCD1. Gene set enrichment analysis displayed that there was an evident difference in the activation of cytokines and the activation of immune signal transduction-related pathways between high- and low-expression groups of each hub gene. In conclusion, this study identified four potential genetic markers associated with HCC immunity and assessed their association with HCC patient's prognosis and immune microenvironment. The study results are expected to provide theoretical guidance for immunotherapy of HCC patients.

Identification of hub genes and transcription factors in patients with rheumatoid arthritis complicated with atherosclerosis

The aim of this study was to explore the overlapping key genes, pathway networks and transcription factors (TFs) related to the pathogenesis of rheumatoid arthritis (RA) and atherosclerosis. The gene expression profiles of RA and atherosclerosis were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between RA and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analysis. Hub genes were identified using protein–protein interaction networks. TFs were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. The hub genes and TFs were validated with other datasets. The networks between TFs and hub genes were constructed by CytoScape software. A total of 131 DEGs (all upregulated) were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in leukocyte migration, neutrophil activation, and phagocytosis. CytoScape demonstrated 12 hub genes and one gene cluster module. Four of the 12 hub genes (CSF1R, CD86, PTPRC, and CD53) were validated by other datasets. TRRUST predicted two TFs, including Spi-1 proto-oncogene (SPI1) and RUNX family transcription factor 1(RUNX1). The expression of RUNX1 was validated with another dataset. Our study explored the common pathogenesis of RA and atherosclerosis. These results may guide future experimental research and clinical transformation.

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

Background

The endometrium is a heterogeneous tissue composed of luminal epithelial (LE), glandular epithelial (GE), and stromal cells (ST), experiencing progesterone regulated dynamic changes during the estrous cycle. In the cow, this regulation at the transcriptomic level was only evaluated in the whole tissue. This study describes specific gene expression in the three types of cells isolated from endometrial biopsies following laser capture microdissection and the transcriptome changes induced by progesterone in GE and ST cells.

Results

Endometrial LE, GE, and ST cells show specific transcriptomic profiles. Most of the differentially expressed genes (DEGs) in response to progesterone are cell type-specific (96%). Genes involved in cell cycle and nuclear division are under-expressed in the presence of progesterone in GE, highlighting the anti-proliferative action of progesterone in epithelial cells. Elevated progesterone concentrations are also associated with the under-expression of estrogen receptor 1 (ESR1) in GE and oxytocin receptor (OXTR) in GE and ST cells. In ST cells, transcription factors such as SOX17 and FOXA2, known to regulate uterine epithelial-stromal cross-talk conveying to endometrial receptivity, are over-expressed under progesterone influence.

Conclusions

The results from this study show that progesterone regulates endometrial function in a cell type-specific way, which is independent of the expression of its main receptor PGR. These novel insights into uterine physiology present the cell compartment as the physiological unit rather than the whole tissue.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08323-z.

Tetraspanins as Potential Modulators of Glutamatergic Synaptic Function

Tetraspanins (Tspans) comprise a membrane protein family structurally defined by four transmembrane domains and intracellular N and C termini that is found in almost all cell types and tissues of eukaryotes. Moreover, they are involved in a bewildering multitude of diverse biological processes such as cell adhesion, motility, protein trafficking, signaling, proliferation, and regulation of the immune system. Beside their physiological roles, they are linked to many pathophysiological phenomena, including tumor progression regulation, HIV-1 replication, diabetes, and hepatitis. Tetraspanins are involved in the formation of extensive protein networks, through interactions not only with themselves but also with numerous other specific proteins, including regulatory proteins in the central nervous system (CNS). Interestingly, recent studies showed that Tspan7 impacts dendritic spine formation, glutamatergic synaptic transmission and plasticity, and that Tspan6 is correlated with epilepsy and intellectual disability (formerly known as mental retardation), highlighting the importance of particular tetraspanins and their involvement in critical processes in the CNS. In this review, we summarize the current knowledge of tetraspanin functions in the brain, with a particular focus on their impact on glutamatergic neurotransmission. In addition, we compare available resolved structures of tetraspanin family members to those of auxiliary proteins of glutamate receptors that are known for their modulatory effects.

Bioinformatics Analysis of the Mechanisms of Diabetic Nephropathy via Novel Biomarkers and Competing Endogenous RNA Network

Diabetic nephropathy (DN) is one of the common chronic complications of diabetes with unclear molecular mechanisms, which is associated with end-stage renal disease (ESRD) and chronic kidney disease (CKD). Our study intended to construct a competing endogenous RNA (ceRNA) network via bioinformatics analysis to determine the potential molecular mechanisms of DN pathogenesis. The microarray datasets (GSE30122 and GSE30529) were downloaded from the Gene Expression Omnibus database to find differentially expressed genes (DEGs). GSE51674 and GSE155188 datasets were used to identified the differentially expressed microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), respectively. The DEGs between normal and DN renal tissues were performed using the Linear Models for Microarray (limma) package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal the mechanisms of DEGs in the progression of DN. The protein-protein interactions (PPI) of DEGs were carried out by STRING database. The lncRNA-miRNA-messenger RNA (mRNA) ceRNA network was constructed and visualized via Cytoscape on the basis of the interaction generated through the miRDB and TargetScan databases. A total of 94 significantly upregulated and 14 downregulated mRNAs, 31 upregulated and 121 downregulated miRNAs, and nine upregulated and 81 downregulated lncRNAs were identified. GO and KEGG pathways enriched in several functions and expression pathways, such as inflammatory response, immune response, identical protein binding, nuclear factor kappa b (NF-κB) signaling pathway, and PI3K-Akt signaling pathway. Based on the analysis of the ceRNA network, five differentially expressed lncRNAs (DElncRNAs) (SNHG6, KCNMB2-AS1, LINC00520, DANCR, and PCAT6), five DEmiRNAs (miR-130b-5p, miR-326, miR-374a-3p, miR-577, and miR-944), and five DEmRNAs (PTPRC, CD53, IRF8, IL10RA, and LAPTM5) were demonstrated to be related to the pathogenesis of DN. The hub genes were validated by using receiver operating characteristic curve (ROC) and real-time PCR (RT-PCR). Our research identified hub genes related to the potential mechanism of DN and provided new lncRNA-miRNA-mRNA ceRNA network that contributed to diagnostic and potential therapeutic targets for DN.

Bioinformatic Analysis Identified Hub Genes Associated with Heterocyclic Amines Induced Cytotoxicity of Peripheral Blood Mononuclear Cells

Heterocyclic amines (HCAs) are a set of food contaminants that may exert a cytotoxic effect on human peripheral blood mononuclear cells (PBMC). However, the genetic mechanism underlying the cytotoxicity of HCAs on PBMC has not been investigated. In the study, bioinformatic analysis on gene dataset GSE19078 was performed. The results of weighted correlation network analysis and linear models for microarray and RNA-seq data analysis showed that four gene modules were relevant to 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) exposure while one gene module was correlated with 2-amino-3-methyl-3H-imidazo[4,5f]quinoline (IQ) exposure. Gene functional analysis showed that the five modules were annotated mainly with mRNA transcriptional regulation, mitochondrial function, RNA catabolic process, protein targeting, and immune function. Five genes, MIER1, NDUFA4, MLL3, CD53 and CSF3 were recognized as the feature genes for each hub gene network of the corresponding gene module, and the expression of feature genes was observed with a significant difference between the PhIP/IQ samples and the other samples. Our results provide novel genes and promising mechanisms for exploration on the genetic mechanism of HCAs on PBMC.

Host Blood Gene Signatures Can Detect the Progression to Severe and Cerebral Malaria

Malaria is a major international public health problem that affects millions of patients worldwide especially in sub-Saharan Africa. Although many tests have been developed to diagnose malaria infections, we still lack reliable diagnostic biomarkers for the identification of disease severity, especially in endemic areas where the diagnosis of cerebral malaria is very difficult and requires the exclusion of all other possible causes. Previous host and pathogen transcriptomic studies have not yielded homogenous results that can be harnessed into a reliable diagnostic tool. Here we utilized a multi-cohort analysis approach using machine-learning algorithms to identify blood gene signatures that can distinguish severe and cerebral malaria from moderate and non-cerebral cases. Using a Regularized Random Forest model, we identified 28-gene and 32-gene signatures that can reliably distinguish severe and cerebral malaria, respectively. We tested the specificity of both signatures against other common infectious diseases to ensure the signatures reliability and suitability as diagnostic markers. The severe and cerebral malaria gene-signatures were further integrated through k-top scoring pairs classifiers into ten and nine gene pairs that could distinguish severe and cerebral malaria, respectively. These signatures have various implications that can be utilized as blood diagnostic tools for malaria severity in endemic countries.

Single-cell analysis of ploidy and the transcriptome reveals functional and spatial divergency in murine megakaryopoiesis

Megakaryocytes (MKs), the platelet progenitor cells, play important roles in hematopoietic stem cell (HSC) maintenance and immunity. However, it is not known whether these diverse programs are executed by a single population or by distinct subsets of cells. Here, we manually isolated primary CD41+ MKs from the bone marrow (BM) of mice and human donors based on ploidy (2N-32N) and performed single-cell RNA sequencing analysis. We found that cellular heterogeneity existed within 3 distinct subpopulations that possess gene signatures related to platelet generation, HSC niche interaction, and inflammatory responses. In situ immunostaining of mouse BM demonstrated that platelet generation and the HSC niche-related MKs were in close physical proximity to blood vessels and HSCs, respectively. Proplatelets, which could give rise to platelets under blood shear forces, were predominantly formed on a platelet generation subset. Remarkably, the inflammatory responses subpopulation, consisting generally of low-ploidy LSP1+ and CD53+ MKs (≤8N), represented ∼5% of total MKs in the BM. These MKs could specifically respond to pathogenic infections in mice. Rapid expansion of this population was accompanied by strong upregulation of a preexisting PU.1- and IRF-8-associated monocytic-like transcriptional program involved in pathogen recognition and clearance as well as antigen presentation. Consistently, isolated primary CD53+ cells were capable of engulfing and digesting bacteria and stimulating T cells in vitro. Together, our findings uncover new molecular, spatial, and functional heterogeneity within MKs in vivo and demonstrate the existence of a specialized MK subpopulation that may act as a new type of immune cell.

Identification of key genes in the tumor microenvironment of lung adenocarcinoma

The tumor microenvironment plays an important role in tumor development and progression, but the role of immune and stromal cells in this environment has not been sufficiently studied. In this study, we aimed to identify key genes associated with the microenvironment of lung adenocarcinoma (LUAD). Raw data for stromal and immune cells in malignant tumors were downloaded from The Cancer Genome Atlas (TCGA). These expression data were used to identify the differentially expressed genes (DEGs) in tissue samples of LUAD with high and low immune scores. A protein-protein interaction (PPI) network based on genes with significant differential expression was constructed. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to functionally annotate putative hub genes. These genes were assessed via Kaplan Meier analysis to determine their correlation with overall survival. In total, we identified 216 DEGs which were correlated with immune and stromal scores, including 30 hub genes which were identified based on the PPI network. Further analysis suggested that the expression levels of 10 of these genes were significantly correlated with overall survival of LUAD patients. These key hub genes included CCR2, CCR5, CD53, CYBB, HCK, IRF8, LCP2, PLEK, PTPRC, and TLR7. Moreover, the expression level of CCR2 was found to have strong prognostic value for LUAD patients. Additionally, high expression of CYBB was also correlated with better survival of patients with LUAD. The results of this study open several new avenues to explore in the treatment of LUAD.

Differentially Expressed Genes and Enriched Signaling Pathways in the Adipose Tissue of Obese People

As the prevalence of obesity increases, so does the occurrence of obesity-related complications, such as cardiovascular and cerebrovascular diseases, diabetes, and some cancers. Increased adipose tissue is the main cause of harm in obesity. To better understand obesity and its related complications, we analyzed the mRNA expression profiles of adipose tissues from 126 patients with obesity and 275 non-obese controls. Using an integrated bioinformatics method, we explored the functions of 113 differentially expressed genes (DEGs) between them. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses revealed that upregulated DEGs were enriched in immune cell chemotaxis, complement-related cascade activation, and various inflammatory signaling pathways, while downregulated DEGs enriched in nutrient metabolism. The CIBERSORT algorithm indicated that an increase in macrophages may be the main cause of adipose tissue inflammation, while decreased γδ T cells reduce sympathetic action, leading to dysregulation of adipocyte thermogenesis. A protein-protein interaction network was constructed using the STRING database, and the top 10 hub genes were identified using the cytoHubba plug-in in Cytoscape. All were confirmed to be obesity-related using a separate dataset. In addition, we identified chemicals related to these hub genes that may contribute to obesity. In conclusion, we have successfully identified several hub genes in the development of obesity, which provide insights into the possible mechanisms controlling obesity and its related complications, as well as potential biomarkers and therapeutic targets for further research.

A mixture model to detect edges in sparse co-expression graphs with an application for comparing breast cancer subtypes

We develop a method to recover a gene network's structure from co-expression data, measured in terms of normalized Pearson's correlation coefficients between gene pairs. We treat these co-expression measurements as weights in the complete graph in which nodes correspond to genes. To decide which edges exist in the gene network, we fit a three-component mixture model such that the observed weights of 'null edges' follow a normal distribution with mean 0, and the non-null edges follow a mixture of two lognormal distributions, one for positively- and one for negatively-correlated pairs. We show that this so-called L2 N mixture model outperforms other methods in terms of power to detect edges, and it allows to control the false discovery rate. Importantly, our method makes no assumptions about the true network structure. We demonstrate our method, which is implemented in an R package called edgefinder, using a large dataset consisting of expression values of 12,750 genes obtained from 1,616 women. We infer the gene network structure by cancer subtype, and find insightful subtype characteristics. For example, we find thirteen pathways which are enriched in each of the cancer groups but not in the Normal group, with two of the pathways associated with autoimmune diseases and two other with graft rejection. We also find specific characteristics of different breast cancer subtypes. For example, the Luminal A network includes a single, highly connected cluster of genes, which is enriched in the human diseases category, and in the Her2 subtype network we find a distinct, and highly interconnected cluster which is uniquely enriched in drug metabolism pathways.

Molecular mechanisms of dendritic cell migration in immunity and cancer

Dendritic cells (DCs) are a heterogeneous population of antigen-presenting cells that act to bridge innate and adaptive immunity. DCs are critical in mounting effective immune responses to tissue damage, pathogens and cancer. Immature DCs continuously sample tissues and engulf antigens via endocytic pathways such as phagocytosis or macropinocytosis, which result in DC activation. Activated DCs undergo a maturation process by downregulating endocytosis and upregulating surface proteins controlling migration to lymphoid tissues where DC-mediated antigen presentation initiates adaptive immune responses. To traffic to lymphoid tissues, DCs must adapt their motility mechanisms to migrate within a wide variety of tissue types and cross barriers to enter lymphatics. All steps of DC migration involve cell-cell or cell-substrate interactions. This review discusses DC migration mechanisms in immunity and cancer with a focus on the role of cytoskeletal processes and cell surface proteins, including integrins, lectins and tetraspanins. Understanding the adapting molecular mechanisms controlling DC migration in immunity provides the basis for therapeutic interventions to dampen immune activation in autoimmunity, or to improve anti-tumour immune responses.