CD56dim Natural Killer Cells Research Articles

Distinct granzyme k expression in immune cells: a single-cell rna-seq meta-analysis.

Granzymes are essential serine proteases in cytotoxic T cells and natural killer (NK) cells, with GZMK's expression being less understood. This study aims to uncover GZMK expression profiles across various immune cell types using single-cell RNA sequencing meta-analysis. This study aims to uncover GZMK expression profiles across various immune cell types using single-cell RNA sequencing meta-analysis. We conducted a meta-analysis using cellxgene, an interactive data exploration platform developed by the Chan Zuckerberg Initiative. We focused on mature T cells, NK cells, B cells, and NKT cells. We also checked transcription factor binding sites at the granzyme gene promoter regions using JASPAR. Comparative analysis was also done using mouse single-cell RNA sequencing data. GZMK was the most lowly expressed in NK cells and mature NKT cells in most tissues except for colon and lymph nodes. In mature T cells, GZMK is similarly or more highly expressed than other granzymes. HBCA data revealed weak expression of GZMK in NK cells but strong expression in effector memory CD8-positive, alpha-beta T cells. Combined data shows no significant difference in GZMK expression between cell types. Subtype analysis shows that GZMK expression was higher in CD16-negative, CD56-bright NK cells when compared to CD16-positive, CD56-dim NK cells. We also identified unique transcription factor binding sites for GZMK. While this pattern in mouse data with low Gzmk expression in NK cells and higher T cells was repeated. GZMK expression is distinctively regulated among immune cells and tissues, with unique promoter regions and transcription factor binding sites contributing to this differential expression. These insights into GZMK's role in immune function and regulation offer potential therapeutic targets.

Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms

BackgroundPatients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers.MethodsGene expression profiles for AF and stable CAD were downloaded from the Gene Expression Omnibus database. Overlapping genes related to both diseases were identified using weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Hub genes were then identified using the machine learning algorithm. Immune cell infiltration and correlations with hub genes were explored, followed by drug predictions. Hub gene expression in AF and CAD patients was validated by real-time qPCR.ResultsWe obtained 28 common overlapping genes in AF and stable CAD, mainly enriched in the PI3K-Akt, ECM-receptor interaction, and relaxin signaling pathway. Two hub genes, COL6A3 and FKBP10, were positively correlated with the abundance of MDSC, plasmacytoid dendritic cells, and regulatory T cells in AF and negatively correlated with the abundance of CD56dim natural killer cells in CAD. The AUCs of COL6A3 and FKBP10 were all above or close to 0.7. Drug prediction suggested that collagenase clostridium histolyticum and ocriplasmin, which target COL6A3, may be potential drugs for AF and stable CAD. Additionally, COL6A3 and FKBP10 were upregulated in patients with AF and CAD.ConclusionCOL6A3 and FKBP10 may be key biomarkers for AF and CAD, providing new insights into the diagnosis and treatment of this disease.

HLA and KIR genetic association and NK cells in anti-NMDAR encephalitis.

Genetic predisposition to autoimmune encephalitis with antibodies against N-methyl-D-aspartate receptor (NMDAR) is poorly understood. Given the diversity of associated environmental factors (tumors, infections), we hypothesized that human leukocyte antigen (HLA) and killer-cell immunoglobulin-like receptors (KIR), two extremely polymorphic gene complexes key to the immune system, might be relevant for the genetic predisposition to anti-NMDAR encephalitis. Notably, KIR are chiefly expressed by Natural Killer (NK) cells, recognize distinct HLA class I allotypes and play a major role in anti-tumor and anti-infection responses. We conducted a Genome Wide Association Study (GWAS) with subsequent control-matching using Principal Component Analysis (PCA) and HLA imputation, in a multi-ethnic cohort of anti-NMDAR encephalitis (n=479); KIR and HLA were further sequenced in a large subsample (n=323). PCA-controlled logistic regression was then conducted for carrier frequencies (HLA and KIR) and copy number variation (KIR). HLA-KIR interaction associations were also modeled. Additionally, single cell sequencing was conducted in peripheral blood mononuclear cells from 16 cases and 16 controls, NK cells were sorted and phenotyped. Anti-NMDAR encephalitis showed a weak HLA association with DRB1*01:01~DQA1*01:01~DQB1*05:01 (OR=1.57, 1.51, 1.45; respectively), and DRB1*11:01 (OR=1.60); these effects were stronger in European descendants and in patients without an underlying ovarian teratoma. More interestingly, we found increased copy number variation of KIR2DL5B (OR=1.72), principally due to an overrepresentation of KIR2DL5B*00201. Further, we identified two allele associations in framework genes, KIR2DL4*00103 (25.4% vs. 12.5% in controls, OR=1.98) and KIR3DL3*00302 (5.3% vs. 1.3%, OR=4.44). Notably, the ligands of these KIR2DL4 and KIR3DL3, respectively, HLA-G and HHLA2, are known to act as immune checkpoint with immunosuppressive functions. However, we did not find differences in specific KIR-HLA ligand interactions or HLA-G polymorphisms between cases and controls. Similarly, gene expression of CD56dim or CD56bright NK cells did not differ between cases and controls. Our observations for the first time suggest that the HLA-KIR axis might be involved in anti-NMDAR encephalitis. While the genetic risk conferred by the identified polymorphisms appears small, a role of this axis in the pathophysiology of this disease appears highly plausible and should be analyzed in future studies.

Unraveling Crucial Mitochondria-Related Genes in the Transition from Ulcerative Colitis to Colorectal Cancer.

To clarify the significance of mitochondria-related differentially expressed genes (MTDEGs) in UC carcinogenesis through a bioinformatics analysis and provide potential therapeutic targets for patients with UC associated colorectal cancer. Microarray GSE37283 was utilized to investigate differentially expressed genes (DEGs) in UC and UC with neoplasia (UCN). MTDEGs were identified by intersecting DEGs with human mitochondrial genes. Utilizing LASSO and random forest analyses, we identified three crucial genes. Subsequently, using ROC curve to investigate the predictive ability of three key genes. Following, three key genes were confirmed in AOM/DSS mice model by Real-time PCR. Finally, single-sample gene set enrichment analysis (ssGSEA) was employed to explore the correlation between the hub genes and immune cells infiltration in UC carcinogenesis. The three identified hub MTDEGs (HMGCS2, MAVS, RDH13) may exhibit significant diagnostic specificity in the transition from UC to UCN. Real-time PCR assay further confirmed that the expressions of HMGCS2 and RDH13 were significantly downregulated in UCN mice than that in UC mice. ssGSEA analysis revealed the hub genes were highly associated with CD56dim natural killer cells. RDH13, HMGCS2, and MAVS may become diagnostic indicators and potential biomarkers for UCN. Our research has the potential to enhance our understanding of the mechanisms underlying carcinogenesis in UC.

Construction of the circRNA-miRNA-mRNA axis based on ferroptosis-related gene AKR1C1 to explore the potential pathogenesis of abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a cardiovascular disease that seriously threatens human health and brings huge economic burden. At present, its pathogenesis remains unclear and its treatment is limited to surgical treatment. With the deepening and analysis of studies on the mechanism of ferroptosis, a new idea has been provided for the clinical management of AAA patients, including diagnosis, treatment and prevention. Therefore, this paper aims to construct a competitive endogenous RNA (ceRNA) regulatory axis based on ferroptosis to preliminarily explore the pathogenesis and potential therapeutic targets of AAA. We obtained upregulated and downregulated ferroptosis-related DEGs (FRGs) from GSE144431 dataset and 60 known ferroptosis-related genes. Pearson correlation analysis was used to find aldoketone reductase 1C (AKR1C1) in AAA samples. Enrichment analysis of these genes was performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Correlation test between immune cells and AKR1C1 was investigated through single-sample gene set enrichment analysis (ssGSEA). The AKR1C1-miRNA pairs were predicted by the TargetScan database and miRWalk database. Circular RNA (CircRNA)-miRNA pairs were selected by the CircInteractome database. Overlapping miRNA between circRNA-miRNA and AKR1C1-miRNA pairs was visualized by Venn diagram. Finally, the circRNA-miRNA-mRNA axis was constructed by searching for upstream circRNA and downstream mRNA of overlapping miRNA. Only one downregulated AKR1C1 gene was found in GSE144431 and 60 ferroptosis-related genes. Functional Enrichment and Pathway Analysis of AKR1C1-related genes were further explored, and it was observed that they were mainly enriched in "response to oxidative stress," "glutathione biosynthetic process" and "nonribosomal peptide biosynthetic process," "Ferroptosis," "Glutathione metabolism" and "Chemical carcinogenesis-reactive oxygen species." They were also found to be significantly associated with most immune cells, including Activated Dendritic cells, CD56dim Natural killer cells, Gamma Delta T cells, Immature B cells, Plasmacytoid dendritic cell, Type 2 T helper cell, Activated CD4 T cell and Type 1 T helper cell. Has_circ_0005073-miRNA-543 and AKR1C1-miRNA-543 were identified by Online Database analysis. Therefore, we have established the has_circ_0005073/miRNA-543/AKR1C1 axis in AAA. We found AKR1C1 was differentially expressed between normal and AAA groups. Based on AKR1C1, we constructed the has_circ_0005073/miRNA-543/AKR1C1 axis to analyze AAA.

NK cells with adhesion defects and reduced cytotoxic functions are associated with a poor prognosis in multiple myeloma

AbstractThe promising results obtained with immunotherapeutic approaches for multiple myeloma (MM) call for a better stratification of patients based on immune components. The most pressing being cytotoxic lymphocytes such as natural killer (NK) cells that are mandatory for MM surveillance and therapy. Here, we performed a single-cell RNA sequencing analysis of NK cells from 10 patients with MM and 10 age/sex–matched healthy donors that revealed important transcriptomic changes in the NK cell landscape affecting both the bone marrow (BM) and peripheral blood compartment. The frequency of mature cytotoxic CD56dim NK cell subsets was reduced in patients with MM at the advantage of late-stage NK cell subsets expressing NF-κB and interferon-I inflammatory signatures. These NK cell subsets accumulating in patients with MM were characterized by low CD16 and CD226 expression and poor cytotoxic functions. MM CD16/CD226Lo NK cells also had adhesion defects with reduced lymphocyte function-associated antigen 1 (LFA-1) integrin activation and actin polymerization that may account for their limited effector functions in vitro. Finally, analysis of BM-infiltrating NK cells in a retrospective cohort of 177 patients with MM from the Intergroupe Francophone du Myélome (IFM) 2009 trial demonstrated that a high frequency of NK cells and their low CD16 and CD226 expression were associated with a shorter overall survival. Thus, CD16/CD226Lo NK cells with reduced effector functions accumulate along MM development and negatively affect patients’ clinical outcomes. Given the growing interest in harnessing NK cells to treat myeloma, this improved knowledge around MM–associated NK cell dysfunction will stimulate the development of more efficient immunotherapeutic drugs against MM.

Distinct developmental pathways generate functionally distinct populations of natural killer cells.

Natural killer (NK) cells function by eliminating virus-infected or tumor cells. Here we identified an NK-lineage-biased progenitor population, referred to as early NK progenitors (ENKPs), which developed into NK cells independently of common precursors for innate lymphoid cells (ILCPs). ENKP-derived NK cells (ENKP_NK cells) and ILCP-derived NK cells (ILCP_NK cells) were transcriptionally different. We devised combinations of surface markers that identified highly enriched ENKP_NK and ILCP_NK cell populations in wild-type mice. Furthermore, Ly49H+ NK cells that responded to mouse cytomegalovirus infection primarily developed from ENKPs, whereas ILCP_NK cells were better IFNγ producers after infection with Salmonella and herpes simplex virus. Human CD56dim and CD56bright NK cells were transcriptionally similar to ENKP_NK cells and ILCP_NK cells, respectively. Our findings establish the existence of two pathways of NK cell development that generate functionally distinct NK cell subsets in mice and further suggest these pathways may be conserved in humans.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Identification of Molecular Subtypes Associated with PCD in Esophageal Squamous Cell Carcinoma and Analysis of Immune Microenvironment.

Esophageal squamous cell carcinoma (ESCC) is a highly fatal malignancy with increasing incidence, and programmed cell death (PCD) plays an important role in homeostasis. This study aimed to explore the ESCC of heterogeneity based on the PCD signatures for the diagnosis and treatment of patients. The clinical information and RNA-seq data of patients with ESCC and the PCD-related genes set were used to identify PCD signatures.The "limma" package was used to identify the differentially expressed genes (DEGs). "Clusterprofiler" package was used for function enrichment analysis, and the "ConsensusClusterPlus" package was performed for consensus clustering. Finally, the "GSVA" package and the Cibersort algorithm were used for the immune infiltration analysis. We performed differential expression analysis between ESCC and normal samples and identified 1659 DEGs, of which 124 DEGs were PCD genes. Then, the patients were divided into cluster1 and cluster2 based on the expression of 124 PCD genes. There was a significant difference in immune infiltration between the two clusters. The patients in cluster 1 had a higher immune score and more CD56dim natural killer cells, monocytes, activated CD4 T cells, eosinophil, and activated B cells infiltration, while cluster2 had a higher stromal score, more immune regulation, and immune checkpoint genes expression. We identified two clusters based on PCD gene expression and characterized their tumor microenvironment and immune checkpoint difference. Our findings may provide some new insight into the treatment of ESCC.

Genomic and Transcriptomic Significance of Multiple Primary Lung Cancers Detected by Next-Generation Sequencing in Clinical Settings.

Effective diagnosis and understanding of the mechanism of intrapulmonary metastasis (IM) from multiple primary lung cancers (MPLC) aid clinical management. However, the actual detection panels used in the clinic are variable. Current research on tumor microenvironment (TME) of MPLC and IM is insufficient. Therefore, additional investigation into the differential diagnosis and discrepancies in TME between two conditions is crucial. 214 non-small cell lung cancer patients with multiple tumors were enrolled, and 507 samples were subjected to DNA sequencing (NGS 10). Then, DNA and RNA sequencing (master panel) were performed on the specimens from 32 patients, the TME profiles between tumors within each patient and across patients and the differentially expressed genes were compared. 4 patients were regrouped with NGS 10 results. Master panel resolved the classifications of 6 undetermined patients. The TME in MPLC exhibited a high degree of infiltration by natural killer (NK) cells, CD56dim NK cells, endothelial cells etc., P < 0.05. Conversely, B cells, activated B cells, regulatory cells, immature dendritic cells etc., P < 0.001, were heavily infiltrated in the IM. NECTIN4 and LILRB4 mRNA were downregulated in the MPLC (P < 0.0001). Additionally, NECTIN4 (P < 0.05) and LILRB4 were linked to improved disease-free survival in the MPLC. In conclusion, IM is screened from MPLC by pathology joint NGS 10 detections, followed by a large NGS panel for indistinguishable patients. A superior prognosis of MPLC may be associated with an immune-activating TME and the downregulation of NECTIN4 and LILRB4 considered as potential drug therapeutic targets.

The ratio of circulating CD56dim NK cells to follicular T helper cells as a promising predictor for disease activity of relapsing-remitting multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system primarily mediated by CD4+ T helper cells. This study investigated the dynamic changes of natural killer (NK) cells and follicular T helper (Tfh) cells and their associations in relapsing-remitting MS patients. The findings revealed inverse relationships between NK cells and CD4+ T cells or Tfh cells. Specifically, CD56dim NK cells, not CD56bright NK cells, were negatively correlated with CD4+ T cells and Tfh cells. However, no significant correlations were found between NK cells and sNfL levels or EDSS scores. The ratio of CD56dim NK cells to circulating Tfh (cTfh) cells demonstrated superior discriminatory ability in distinguishing relapsing MS patients from healthy controls (HCs) and remitting patients, as determined by receiver operating characteristic (ROC) analysis. Following treatment with immunosuppressants or disease-modifying therapies (DMTs), a significant increase in the CD56dim NK/cTfh ratio was observed. These findings suggest that the CD56dim NK/cTfh ratio holds promise as a prognostic indicator for clinical relapse and treatment response in MS.

Immunoglobulin-like transcript 2 as an impaired anti-tumor cytotoxicity marker of natural killer cells in patients with hepatocellular carcinoma.

Natural killer (NK) cells play a pivotal role in immune surveillance in the liver. We aimed to identify potential targets for NK cell-mediated immune intervention by revealing the functional molecules on NK cells in HCC patients. To evaluate the impact of aging on NK cell phenotypes, we examined NK cells from healthy volunteers (HVs) of various ages. Because ILT2 expression on CD56dim NK cells increased with increasing age, we enrolled age-matched HCC patients and HVs. We determined the NK cell phenotypes in blood mononuclear cells (PBMCs) and intrahepatic lymphocytes (IHLs) from cancerous and non-cancerous tissues. We evaluated cytotoxicity and antibody-dependent cellular cytotoxicity (ADCC) of NK cells in vitro. ILT2-positive CD56dim NK cells in PBMCs were increased in HCC patients compared with HVs. In HCC patients, ILT2-positive CD56dim NK cells were increased in cancerous IHLs compared with non-cancerous IHLs and PBMCs. We examined the impact of macrophage migration inhibitory factor (MIF) on ILT2 expression in co-cultures of HCC cells and NK cells. The enhanced expression of ILT2 on CD56dim NK cells from HCC patients was inhibited by masking antibodies against MIF and CXCR4. ILT2-positive CD56dim NK cells exhibited lower capacities for cytotoxicity and ADCC than ILT2-negative cells, which were partially restored by ILT2 blockade. In HCC patients, ILT2 is a signature molecule for cancerous CD56dim NK cells with impaired cytolytic capacity. The MIF-CXCR4 interaction is associated with ILT2 induction on CD56dim NK cells and ILT2 serves as a target for functional NK cell restoration.

Identification of Key Immune Infiltration Related Genes Involved in Aortic Dissection Using Bioinformatic Analyses and Experimental Verification.

Immune microenvironment plays an important role in aortic dissection (AD). Therefore, novel immune biomarkers may facilitate AD prevention, diagnosis, and treatment. This study aimed at mining key immune-related genes and relevant mechanisms involved in AD pathogenesis. Key immune cells in AD were identified by ssGESA algorithm. Next, genes associated with key immune cells were screened by weighted gene coexpression network analysis (WGCNA). Then hub immune genes were picked from protein-protein interaction network of overlapped genes from differential expression and WGCNA analyses by cytohubba plug-in. Their diagnostic potential was evaluated in two independent cohorts from GEO database. In addition, the expressions of hub immune genes were determined by quantitative RT-PCR, immunohistochemistry, and Western blotting in dissected and normal aortic tissues. Activated B cells, CD56dim natural killer cells, eosinophils, gamma delta T cells, immature B cells, natural killer cells and type 17 T helper cells were identified as key immune cells in AD. Thereafter, a gene module significantly correlated with key immune cells were found by WGCNA method. Subsequently, KDR, IGF1, NOS3, PECAM1, GAPDH, FLT1, DLL4, CDH5, VWF, and TEK were identified as hub immune cell related genes by PPI network analysis, which may be potential diagnostic markers for AD, as evidenced by ROC curves. Moreover, the decreased expression of VWF in AD was validated at both mRNA and protein levels, and its expression was significantly positive correlated with the marker of smooth muscle cells, ACTA2, in AD. Further immunofluorescent results showed that VWF was colocalized with ACTA2 in aortic tissues. We identified key immune cells and hub immune cell-related genes involved in AD. Moreover, we found that VWF was co-expressed with the smooth muscle cell marker ACTA2, indicating the important role of VWF in smooth muscle cell loss in AD pathogenesis.

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis

BackgroundThis study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP).MethodsData sets were downloaded from the Gene Expression Omnibus database, and differentially programmed cell death-related genes were screened. Functional analyses were performed to predict the biological processes associated with these genes. Least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF) machine learning algorithms were used to screen for characteristic genes, and receiver operating characteristics were used to evaluate the diagnosis of disease characteristic gene values. Gene set enrichment analysis (GSEA) and single-sample GSEA were conducted to analyze the correlation between characteristic genes and immune infiltrates. Cytoscape and the Drug Gene Interaction Database (DGIdb) were used to construct the mitochondrial RNA-mRNA-transcription factor network and explore small-molecule drugs. Reverse transcription real-time quantitative PCR (RT-qPCR) analysis was performed to evaluate the expression of biomarker genes in clinical samples.ResultsIn total, 25 differential cell death genes were identified. Among these, two genes were screened using the LASSO, SVM, and RF algorithms as characteristic genes, including BRSK2 and VPS35. In GSE56815, the area under the receiver operating characteristic curve of BRSK2 was 0.761 and that of VPS35 was 0.789. In addition, immune cell infiltration analysis showed that BRSK2 positively correlated with CD56dim natural killer cells and negatively correlated with central memory CD4 + T cells. Based on the data from DGIdb, hesperadin was associated with BRSK2, and melagatran was associated with VPS35. BRSK2 and VPS35 were expectably upregulated in OP group compared with controls (all p < 0.05).ConclusionsBRSK2 and VPS35 may be important diagnostic biomarkers of OP.

Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes.

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS.

Machine learning and experimental validation identified autophagy signature in hepatic fibrosis.

The molecular mechanisms of hepatic fibrosis (HF), closely related to autophagy, remain unclear. This study aimed to investigate autophagy characteristics in HF. Gene expression profiles (GSE6764, GSE49541 and GSE84044) were downloaded, normalized, and merged. Autophagy-related differentially expressed genes (ARDEGs) were determined using the limma R package and the Wilcoxon rank sum test and then analyzed by GO, KEGG, GSEA and GSVA. The infiltration of immune cells, molecular subtypes and immune types of healthy control (HC) and HF were analyzed. Machine learning was carried out with two methods, by which, core genes were obtained. Models of liver fibrosis in vivo and in vitro were constructed to verify the expression of core genes and corresponding immune cells. A total of 69 ARDEGs were identified. Series functional cluster analysis showed that ARDEGs were significantly enriched in autophagy and immunity. Activated CD4 T cells, CD56bright natural killer cells, CD56dim natural killer cells, eosinophils, macrophages, mast cells, neutrophils, and type 17 T helper (Th17) cells showed significant differences in infiltration between HC and HF groups. Among ARDEGs, three core genes were identified, that were ATG5, RB1CC1, and PARK2. Considerable changes in the infiltration of immune cells were observed at different expression levels of the three core genes, among which the expression of RB1CC1 was significantly associated with the infiltration of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. In the mouse liver fibrosis experiment, ATG5, RB1CC1, and PARK2 were at higher levels in HF group than those in HC group. Compared with HC group, HF group showed low positive area in F4/80, IL-17 and CD56, indicating decreased expression of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. Meanwhile, knocking down RB1CC1 was found to inhibit the activation of hepatic stellate cells and alleviate liver fibrosis. ATG5, RB1CC1, and PARK2 are promising autophagy-related therapeutic biomarkers for HF. This is the first study to identify RB1CC1 in HF, which may promote the progression of liver fibrosis by regulating macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell.

Analysis and validation of potential ICD-related biomarkers in development of myopia using machine learning.

We aimed to identify and verify potential biomarkers in the development of myopia associated with immunogenic cell death (ICD). We download high myopia (HM) dataset GSE136701 from Gene Expression Omnibus. Differentially expressed genes in HM were identified to overlapped with ICD-related genes. Least absolute shrinkage and selection operator were used to select the Hub genes. Furthermore, the correlation between the hub genes and immune infiltration, immune response activities, and hub genes Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis was investigated using Spearman's rank correlation. Prediction of the miRNAs upstream of the Hub genes was based on the TargetScan database. We used guinea pig lens-induced myopia model's scleral tissues performed quantitative real-time polymerase chain reaction. We identified overlapped with ICD-related genes (LY96, IL1A, IL33, and AGER) and two genes (LY96 and AGER) as hub genes. Single sample gene set enrichment analysis and Spearman's rank correlation revealed that hub gene expression levels in HM were significantly correlated with the infiltration percentages of CD56dim natural killer cells, macrophages, immature B cells, and the immune response activities of APC co-stimulation and Kyoto Encyclopedia of Genes and Genomes pathways, such as terpenoid backbone biosynthesis, aminoacyl-trna biosynthesis, Huntington's disease, oxidative phosphorylation; there were a few additional signaling pathways compared to normal samples. Additionally, several miRNA were predicted as upstream regulators of LY96 and AGER. LY96 was identified as a significantly differentially expressed biomarker in myopia guinea pig's scleral tissues, as verified by qPCR. LY96 was identified and verified as a ICD-related potential myopia biomarker. Molecular mechanisms or pathways involved in myopia development by LY96 requires further research.

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.

Identification of CD8+ T cell-related biomarkers and immune infiltration characteristic of rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune rheumatic disease, which do not respond well to current treatment partially. Therefore, further in-depth elucidation of the molecular mechanism and pathogenesis of RA is urgently needed for the diagnosis, personalized therapy and drug development. Herein, we collected 111 RA samples from Gene Expression Omnibus (GEO) database, and conducted differentially expressed genes and GESA analysis. Abnormal activation and imbalance of immune cells in RA were observed. WGCNA was utilized to explore the gene modules and CD8+ T cell-related genes (CRGs) were chosen for KEGG and GO analysis. Besides, to explore biomarkers of RA in depth, machine learning algorithms and bioinformatics analysis were used, and we identified GDF15, IGLC1, and IGHM as diagnostic markers of RA, which was confirmed by clinical samples. Next, ssGSEA algorithms were adopted to investigate the differences in immune infiltration of 23 immune cell subsets between RA and healthy control group. Finally, optimal classification analysis based on consensus clustering combined with ssGSEA algorithms were conducted. GDF15 was revealed that to be positively correlated with mast cells and type 2 T helper cells, but negatively correlated with most other immune cells. On the other hand, IGHM and IGLC1 were negatively correlated with CD56dim natural killer cells, while positively associated with other immune cells. Finally, RA samples in subtype A exhibited a higher immune infiltration status. This study could provide guidance for individualized treatment of RA patients and provide new targets for drug design.

Identification and experimental validation of programmed cell death- and mitochondria-associated biomarkers in osteoporosis and immune microenvironment.

Background: Prior research has demonstrated that programmed cell death (PCD) and mitochondria assume pivotal roles in controlling cellular metabolism and maintaining bone cell equilibrium. Nonetheless, the comprehensive elucidation of their mode of operation in osteoporosis (OP) warrants further investigation. Therefore, this study aimed at analyzing the role of genes associated with PCD (PCD-RGs) and mitochondria (mortality factor-related genes; MRGs) in OP. Methods: Differentially expressed genes (DEGs) were identified by subjecting the GSE56815 dataset obtained from the Gene Expression Omnibus database to differential expression analysis and comparing OP patients with healthy individuals. The genes of interest were ascertained through the intersection of DEGs, MRGs, and PCD-RGs; these genes were filtered using machine learning methodologies to discover potential biomarkers. The prospective biomarkers displaying uniform patterns and statistically meaningful variances were identified by evaluating their levels in the GSE56815 dataset and conducting quantitative real-time polymerase chain reaction-based assessments. Moreover, the functional mechanisms of these biomarkers were further delineated by constructing a nomogram, which conducted gene set enrichment analysis, explored immune infiltration, generated regulatory networks, predicted drug responses, and performed molecular docking analyses. Results: Eighteen candidate genes were documented contingent upon the intersection between 2,354 DEGs, 1,136 MRGs, and 1,548 PCD-RGs. The biomarkers DAP3, BIK, and ACAA2 were upregulated in OP and were linked to oxidative phosphorylation. Furthermore, the predictive ability of the nomogram designed based on the OP biomarkers exhibited a certain degree of accuracy. Correlation analysis revealed a strong positive correlation between CD56dim natural killer cells and ACAA2 and a significant negative correlation between central memory CD4+ T cells and DAP3. DAP3, BIK, and ACAA2 were regulated by multiple factors; specifically, SETDB1 and ZNF281 modulated ACAA2 and DAP3, whereas TP63 and TFAP2C governed DAP3 and BIK. Additionally, a stable binding force was observed between the drugs (estradiol, valproic acid, and CGP52608) and the biomarkers. Conclusion: This investigation evidenced that the biomarkers DAP3, BIK, and ACAA2 are associated with PCD and mitochondria in OP, potentially facilitate the diagnosis of OP in clinical settings.