Silencing of long non-coding RNA MALAT1 suppresses inflammation in septic mice: role of microRNA-23a in the down-regulation of MCEMP1 expression

Snhg14/miR-181a-5p axis-mediated "M1" macrophages aggravate LPS-induced myocardial cell injury

An increasing number of studies have suggested that macrophages participate in sepsis-induced myocardial injury. Our study highlights the function and mechanism of the lncRNA Snhg14 in "M1" polarized macrophage-mediated myocardial cell damage. Lipopolysaccharide (LPS) was used to treat H9c2 cells to construct an in vitro myocardial injury model. M1 and M2 polarization of RAW264.7 cells were induced and the exosomes were obtained from the supernatant through ultracentrifugation. Moreover, cecal ligation and puncture (CLP) surgery was implemented to establish a mouse sepsis-induced myocardial injury model, and Snhg14 was knocked down with sh-Snhg14. The results showed that the conditioned medium (CM) and the exosomes (Exo) of M1 macrophages substantially augmented LPS-induced apoptosis and oxidative stress in myocardial cells. Notably, M1-CM and M1-Exo contributed to nearly 50 % of myocardial cell viability decline. Snhg14 was highly expressed in M1 macrophages and exosomes derived from M1-MΦ (M1-Exo). Snhg14 overexpression aggravated myocardial cell damage and increased 10 to 50 times expression of proinflammatory cytokines in MΦ. Snhg14 knockdown reversed M1-Exo-mediated myocardial cell damage and inhibited the production of proinflammatory cytokines (50 %-75 % decline) of MΦ. Moreover, Snhg14 targeted and inhibited miR-181a-5p expression. miR-181a-5p upregulation partly reversed Snhg4 overexpression-mediated myocardial cell damage and MΦ activation. In vivo, sh-Snhg14 dramatically ameliorated cardiac damage in septic mice by enhancing miR-181a-5p and inhibiting the HMGB1/NF-κB pathway. In conclusion, "M1" macrophage-derived exosomal Snhg14 aggravates myocardial cell damage by modulating the miR-181a-5p/HMGB1/NF-κB pathway.

Identification of a novel immune infiltration-related gene signature, MCEMP1, for coronary artery disease

Background

This study aims to identify a novel gene signature for coronary artery disease (CAD), explore the role of immune cell infiltration in CAD pathogenesis, and assess the cell function of mast cell-expressed membrane protein 1 (MCEMP1) in human umbilical vein endothelial cells (HUVECs) treated with oxidized low-density lipoprotein (ox-LDL).

Methods

To identify differentially expressed genes (DEGs) of CAD, datasets GSE24519 and GSE61145 were downloaded from the Gene Expression Omnibus (GEO) database using the R "limma" package with p < 0.05 and |log2 FC| > 1. Gene ontology (GO) and pathway analyses were conducted to determine the biological functions of DEGs. Hub genes were identified using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO). The expression levels of these hub genes in CAD were validated using the GSE113079 dataset. CIBERSORT program was used to quantify the proportion of immune cell infiltration. Western blot assay and qRT-PCR were used to detect the expression of hub genes in ox-LDL-treated HUVECs to validate the bioinformatics results. Knockdown interference sequences for MCEMP1 were synthesized, and cell proliferation and apoptosis were examined using a CCK8 kit and Muse® Cell Analyzer, respectively. The concentrations of IL-1β, IL-6, and TNF-α were measured with respective enzyme-linked immunosorbent assay (ELISA) kits.

Results

A total of 73 DEGs (four down-regulated genes and 69 up-regulated genes) were identified in the metadata (GSE24519 and GSE61145) cohort. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results indicated that these DEGs might be associated with the regulation of platelet aggregation, defense response or response to bacterium, NF-kappa B signaling pathway, and lipid and atherosclerosis. Using SVM-RFE and LASSO, seven hub genes were obtained from the metadata. The upregulated expression of DIRC2 and MCEMP1 in CAD was confirmed in the GSE113079 dataset and in ox-LDL-treated HUVECs. The associations between the two hub genes (DIRC2 and MCEMP1) and the 22 types of immune cell infiltrates in CAD were found. MCEMP1 knockdown accelerated cell proliferation and suppressed cell apoptosis for ox-LDL-treated HUVECs. Additionally, MCEMP1 knockdown appeared to decrease the expression of inflammatory factors IL-1β, IL-6, and TNF-α.

Conclusions

The results of this study indicate that MCEMP1 may play an important role in CAD pathophysiology.

Association between IL-6, miRNA-146a, MALAT1 genetic polymorphisms and risk of rheumatoid arthritis

Aim: This study aimed to investigate the associations between single nucleotide polymorphisms (SNPs) of IL-6 (-174G/C), microRNA146a (rs2910164C/G) and MALAT1 (rs619586A/G) and susceptibility to rheumatoid arthritis (RA) in Egyptians.Methods: SNPs were genotyped in 101 RA patients and 104 controls. Expression levels were evaluated either by Enzyme-linked immunosorbent assay (ELISA) for IL-6 or quantitative real-time PCR (qRT-PCR) for miR-146a and MALAT1.Results: IL-6-174 GC (OR = 3.422) genotype, IL-6-174 C allele (OR = 2.565), miR-146a (rs2910164) CG (OR = 2.190) and MALAT1 (rs619586) AA (OR = 4.125) genotypes and A allele (OR = 6.122) could be considered as risk factors for RA. An increase in the expression of IL-6, miR-146a and MALAT1 was detected in RA patients, which was independent of any SNP.Conclusion: SNPs of IL-6, miR-146a and MALAT1were linked to RA predisposition in Egyptians.

Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis

BACKGROUND

Sepsis is a life-threatening condition caused by an excessive inflammatory response to an infection, associated with high mortality. However, the regulatory mechanism of sepsis remains unclear.

RESULTS

In this study, bioinformatics analysis revealed the novel key biomarkers associated with sepsis and potential regulators. Three public datasets (GSE28750, GSE57065 and GSE95233) were employed to recognize the differentially expressed genes (DEGs). Taking the intersection of DEGs from these three datasets, GO and KEGG pathway enrichment analysis revealed 537 shared DEGs and their biological functions and pathways. These genes were mainly enriched in T cell activation, differentiation, lymphocyte differentiation, mononuclear cell differentiation, and regulation of T cell activation based on GO analysis. Further, pathway enrichment analysis revealed that these DEGs were significantly enriched in Th1, Th2 and Th17 cell differentiation. Additionally, five hub immune-related genes (CD3E, HLA-DRA, IL2RB, ITK and LAT) were identified from the protein-protein interaction network, and sepsis patients with higher expression of hub genes had a better prognosis. Besides, 14 drugs targeting these five hub related genes were revealed on the basis of the DrugBank database, which proved advantageous for treating immune-related diseases.

CONCLUSIONS

These results strengthen the new understanding of sepsis development and provide a fresh perspective into discriminating the candidate biomarkers for predicting sepsis as well as identifying new drugs for treating sepsis.

LncRNA AC006064.4-201 serves as a novel molecular marker in alleviating cartilage senescence and protecting against osteoarthritis by destabilizing CDKN1B mRNA via interacting with PTBP1

BACKGROUND

Osteoarthritis (OA) is the most prevalent age-related disease in the world. Chondrocytes undergo an age-dependent decline in their proliferation and synthetic capacity, which is the main cause of OA development. However, the intrinsic mechanism of chondrocyte senescence is still unclear. This study aimed to investigate the role of a novel long non-coding RNA (lncRNA), AC006064.4-201 in the regulation of chondrocyte senescence and OA progression and to elucidate the underlying molecular mechanisms.

METHODS

The function of AC006064.4-201 in chondrocytes was assessed using western blotting, quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence (IF) and β-galactosidase staining. The interaction between AC006064.4-201 and polypyrimidine tract-binding protein 1 (PTBP1), as well as cyclin-dependent kinase inhibitor 1B (CDKN1B), was evaluated using RPD-MS, fluorescence in situ hybridization (FISH), RNA immunoprecipitation (RIP) and RNA pull-down assays. Mice models were used to investigate the role of AC006064.4-201 in post-traumatic and age-related OA in vivo.

RESULTS

Our research revealed that AC006064.4-201 was downregulated in senescent and degenerated human cartilage, which could alleviate senescence and regulate metabolism in chondrocytes. Mechanically, AC006064.4-201 directly interacts with PTBP1 and blocks the binding between PTBP1 and CDKN1B mRNA, thereby destabilizing CDKN1B mRNA and decreasing the translation of CDKN1B. The in vivo experiments were consistent with the results of the in vitro experiments.

CONCLUSIONS

The AC006064.4-201/PTBP1/CDKN1B axis plays an important role in OA development and provides new molecular markers for the early diagnosis and treatment of OA in the future. Schematic diagram of AC006064.4-201 mechanism. A schematic diagram of the mechanism underlying the effect of AC006064.4-201.

Early peripheral blood MCEMP1 and HLA-DRA expression predicts COVID-19 prognosis

BACKGROUND

Mass vaccination has dramatically reduced the incidence of severe COVID-19, with most cases now presenting as self-limiting upper respiratory tract infections. However, those with co-morbidities, the elderly and immunocompromised, as well as the unvaccinated, remain disproportionately vulnerable to severe COVID-19 and its sequelae. Furthermore, as the effectiveness of vaccination wanes with time, immune escape SARS-CoV-2 variants could emerge to cause severe COVID-19. Reliable prognostic biomarkers for severe disease could be used as early indicator of re-emergence of severe COVID-19 as well as for triaging of patients for antiviral therapy.

METHODS

We performed a systematic review and re-analysis of 7 publicly available datasets, analysing a total of 140 severe and 181 mild COVID-19 patients, to determine the most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients. In addition, we included an independent cohort where blood transcriptomics of COVID-19 patients were prospectively and longitudinally monitored previously, to track the time in which these gene expression changes occur before nadir of respiratory function. Single cell RNA-sequencing of peripheral blood mononuclear cells from publicly available datasets was then used to determine the immune cell subsets involved.

FINDINGS

The most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients were MCEMP1, HLA-DRA and ETS1 across the 7 transcriptomics datasets. Moreover, we found significantly heightened MCEMP1 and reduced HLA-DRA expression as early as four days before the nadir of respiratory function, and the differential expression of MCEMP1 and HLA-DRA occurred predominantly in CD14+ cells. The online platform which we developed is publicly available at https://kuanrongchan-covid19-severity-app-t7l38g.streamlitapp.com/, for users to query gene expression differences between severe and mild COVID-19 patients in these datasets.

INTERPRETATION

Elevated MCEMP1 and reduced HLA-DRA gene expression in CD14+ cells during the early phase of disease are prognostic of severe COVID-19.

FUNDING

K.R.C is funded by the National Medical Research Council (NMRC) of Singapore under the Open Fund Individual Research Grant (MOH-000610). E.E.O. is funded by the NMRC Senior Clinician-Scientist Award (MOH-000135-00). J.G.H.L. is funded by the NMRC under the Clinician-Scientist Award (NMRC/CSAINV/013/2016-01). S.K. is funded by the NMRC under the Transition Award. This study was sponsored in part by a generous gift from The Hour Glass.

Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers

The Coronavirus disease 2019 (COVID-19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2), continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.

Modes of action and diagnostic value of miRNAs in sepsis

Sepsis is a clinical syndrome defined as a dysregulated host response to infection resulting in life-threatening organ dysfunction. Sepsis is a major public health concern associated with one in five deaths worldwide. Sepsis is characterized by unbalanced inflammation and profound and sustained immunosuppression, increasing patient susceptibility to secondary infections and mortality. microRNAs (miRNAs) play a central role in the control of many biological processes, and deregulation of their expression has been linked to the development of oncological, cardiovascular, neurodegenerative and metabolic diseases. In this review, we discuss the role of miRNAs in sepsis pathophysiology. Overall, miRNAs are seen as promising biomarkers, and it has been proposed to develop miRNA-based therapies for sepsis. Yet, the picture is not so straightforward because of the versatile and dynamic features of miRNAs. Clearly, more research is needed to clarify the expression and role of miRNAs in sepsis, and to promote the use of miRNAs for sepsis management.

MCEMP1 is a potential therapeutic biomarker associated with immune infiltration in advanced gastric cancer microenvironment

BACKGROUND

Over the last decade, breakthroughs have been made in cancer immunotherapy. However, for advanced gastric cancer (AGC), the complexity and heterogeneity of the tumor microenvironment (TME) has been the biggest challenge for immunotherapy. Therefore, an intensive study on TME of AGC is necessary.

METHODS

ESTIMATE and CIBERSORT algorithms were applied to analyze the transcriptome data of AGC using TCGA database systematically. We identified mast cell-expressed membrane protein 1 (MCEMP1) as a potential prognostic marker by protein-protein interaction (PPI) and Univariate Cox regression. The expression of MCEMP1 was evaluated by immunohistochemistry (IHC) and quantitative real time PCR. We assessed prognostic values of MCEMP1 with use of Kaplan-Meier and Multivariate Cox regression analysis. Gene set enrichment analysis (GSEA) was used to analyze the molecular mechanism of MCEMP1. The correlation between MCEMP1 expression and tumor immune infiltration was analyzed by the TIMER database and CIBERSORT algorithm, which was confirmed by IHC.

RESULTS

The mRNA and protein expression of MCEMP1 was up-regulated substantially and related to poor survival in AGC. GSEA analysis revealed that MCEMP1 was involved in the immune-related signaling pathways. We further demonstrated that the expression of MCEMP1 was correlated with multiple immune cells and immune checkpoints. The results of IHC indicated that there was a positive correlation between PD-L1 expression and MCEMP1, suggesting that MCEMP1 may affect the prognosis of AGC patients by regulating immune infiltration and the function of immune cells.

CONCLUSION

MCEMP1 may serve as a biomarker associated with immune infiltration in TME and could be a potential therapeutic target for AGC patients.

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Sepsis has high fatality rates. Early diagnosis could increase its curating rates. There were no reliable molecular biomarkers to distinguish between infected and uninfected patients currently, which limit the treatment of sepsis. To this end, we analyzed gene expression datasets from the GEO database to identify its mRNA signature. First, two gene expression datasets (GSE154918 and GSE131761) were downloaded to identify the differentially expressed genes (DEGs) using Limma package. Totally 384 common DEGs were found in three contrast groups. We found that as the condition worsens, more genes were under disorder condition. Then, random forest model was performed with expression matrix of all genes as feature and disease state as label. After which 279 genes were left. We further analyzed the functions of 279 important DEGs, and their potential biological roles mainly focused on neutrophil threshing, neutrophil activation involved in immune response, neutrophil-mediated immunity, RAGE receptor binding, long-chain fatty acid binding, specific granule, tertiary granule, and secretory granule lumen. Finally, the top nine mRNAs (MCEMP1, PSTPIP2, CD177, GCA, NDUFAF1, CLIC1, UFD1, SEPT9, and UBE2A) associated with sepsis were considered as signatures for distinguishing between sepsis and healthy controls. Based on 5-fold cross-validation and leave-one-out cross-validation, the nine mRNA signature showed very high AUC.

The Expression, Prognostic Value, and Immunological Correlation of MCEMP1 and its Potential Role in Gastric Cancer

Purpose

Gastric cancer (GC) is a lethal cancer with a poor 5-year relative survival, which requires a new research perspective. Our study aims to explore the biological impact of the mast cell-expressed membrane protein 1 (MCEMP1) in GC, which includes its expression and potential biological functions.

Methods

The expression of MCEMP1 was assessed through public databases. The GO, KEGG, and GESA analyses were conducted to explore the biofunction of MCEMP1. And ssGSEA was used to analyze the infiltration of the immune cells for MCEMP1. The proliferation, migration, and invasion of GC cells were analyzed through CCK8, colony-forming, wound healing, Transwell, and Western blot assay.

Results

The expression of MCEMP1 was higher in GC tissues. Further, we found a close relationship between MCEMP1 and poorer prognosis of gastric cancer by prognostic analysis. The functional analysis showed that MCEMP1 is involved in immune, inflammation, and metabolism-related pathways. The ssGSEA analysis indicated MCEMP1 mRNA expression was associated with immune infiltration of multiple immune cells. In cellular experiments, the invasion and metastasis of gastric cancer cells could be promoted by regulating the rise of MCEMP1 expression. Western blot analysis showed that regulation of MCEMP1 expression can affect EMT-related protein expression and that NF-κB expression is involved in this process.

Conclusion

MCEMP1 shows a potential value for the prognosis in GC. And, abnormal expression of MCEMP1 in GC is correlated with tumor immune cell infiltration. In in vitro experiments, MCEMP1 can affect the proliferation, migration, and invasion of GC cells by regulating EMT, in which TLR4/NOD2/NF-κB was involved.

Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis

Background

Aortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis.

Method

Nine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO).

Results

DEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD.

Conclusion

Our analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.

Knockdown of LncRNA MALAT1 Alleviates Coxsackievirus B3-Induced Acute Viral Myocarditis in Mice via Inhibiting Th17 Cells Differentiation

Acute viral myocarditis (AVMC), most often caused by coxsackievirus B3 (CVB3) infection, is characterized by myocardial inflammation associated with high morbidity and mortality. A pathogenic role for T helper (Th) 17 cells in AVMC is well established. Long noncoding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been shown to play a key role in various inflammatory diseases. However, the expression of MALAT1 and its impact on Th17 cells differentiation in AVMC remain unclear. In the present study, we found that MALAT1 was highly expressed in mice with AVMC, and the expression was correlated positively with cardiac pathological scores, cardiac IL-17 mRNA expression, and the percentages of splenic Th17 cells. We further demonstrated that MALAT1 knockdown could significantly alleviate the severity of disease and inhibit the differentiation of Th17 cells, accompanying the reduced mRNA expression of RORγt and productions of Th17-related pro-inflammatory cytokines in vivo. Additionally, in vitro analysis showed that MALAT1 knockdown suppressed naïve CD4⁺ T cells differentiation towards Th17 cells. In conclusion, our results suggest that MALAT1 knockdown alleviates CVB3-induced AVMC in mice, which may be partially attributable to the decline in Th17 cells responses. MALAT1 may serve as a novel therapeutic option in AVMC.

Identification and Verification of Five Potential Biomarkers Related to Skin and Thermal Injury Using Weighted Gene Co-Expression Network Analysis

Background: Burn injury is a life-threatening disease that does not have ideal biomarkers. Therefore, this study first applied weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening methods to identify pivotal genes and diagnostic biomarkers associated with the skin burn process.

Methods: After obtaining transcriptomic datasets of burn patient skin and normal skin from Gene Expression Omnibus (GEO) and performing differential analysis and functional enrichment, WGCNA was used to identify hub gene modules associated with burn skin processes in the burn patient peripheral blood sample dataset and determine the correlation between modules and clinical features. Enrichment analysis was performed to identify the functions and pathways of key module genes. Differential analysis, WGCNA, protein-protein interaction analysis, and enrichment analysis were utilized to screen for hub genes. Hub genes were validated in two other GEO datasets, tested by immunohistochemistry for hub gene expression in burn patients, and receiver operating characteristic curve analysis was performed. Finally, we constructed the specific drug activity, transcription factors, and microRNA regulatory network of the five hub genes.

Results: A total of 1,373 DEGs in GSE8056 were obtained, and the top 5 upregulated genes were S100A12, CXCL8, CXCL5, MMP3, and MMP1, whereas the top 5 downregulated genes were SCGB1D2, SCGB2A2, DCD, TSPAN8, and KRT25. DEGs were significantly enriched in the immunity, epidermal development, and skin development processes. In WGCNA, the yellow module was identified as the most closely associated module with tissue damage during the burn process, and the five hub genes (ANXA3, MCEMP1, MMP9, S100A12, and TCN1) were identified as the key genes for burn injury status, which consistently showed high expression in burn patient blood samples in the GSE37069 and GSE13902 datasets. Furthermore, we verified using immunohistochemistry that these five novel hub genes were also significantly elevated in burn patient skin. In addition, MCEMP1, MMP9, and S100A12 showed perfect diagnostic performance in the receiver operating characteristic analysis.

Conclusion: In conclusion, we analyzed the changes in genetic processes in the skin during burns and used them to identify five potential novel diagnostic markers in blood samples from burn patients, which are important for burn patient diagnosis. In particular, MCEMP1, MMP9, and S100A12 are three key blood biomarkers that can be used to identify skin damage in burn patients.

Identification of potential biomarkers and immune infiltration in pediatric sepsis via multiple-microarray analysis

Immune adjustment has become a sepsis occurring in the development of an important mechanism that cannot be ignored. This article from the perspective of immune infiltration of pediatric sepsis screening markers, and promote the understanding of disease mechanisms. Bioinformatics integrated six data sets of pediatric sepsis by using the surrogate variable analysis package and then analyzed differentially expressed genes (DEGs), immune infiltration and weighted gene co-expression network analysis of characteristics (WGCNA) of immune infiltration between pediatric sepsis and the control. Common genes of WGCNA and DEGs were used to functional annotation, pathway enrichment analysis and protein-protein interaction network. Support vector machine (SVM), least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to confirm the key genes for the diagnosis of pediatric sepsis. Receiver operating characteristic (ROC) curve, C index, principal component analysis (PCA) and GiViTi calibration band were used to evaluate the diagnostic performance of key genes. Decision curve analysis (DCA) was used to evaluate the clinical application value of key genes. Lastly, the correlation between key genes and immune cells was analyze. NK cells Resting and NK cell activated in pediatric sepsis during immune infiltration were significantly lower than those in the control group, while M1 Macrophages were higher than those in the control group. ROC, C-index, PCA, GiViTi calibration band and DCA indicated that MCEMP1, CD177, MMP8 and OLFM4 had high diagnostic performance for pediatric sepsis. There is a negative correlation between 4 key genes and NK cells resting, NK cells activated. Except for MCEMP1, the other 3 genes were positively correlated with M1 Macrophages. This study revealed differences in immune responses in pediatric sepsis and identified four key genes as potential biomarkers. Pediatric sepsis in pathology maybe understood better by learning about how it develops.

Identification and verification of YBX3 and its regulatory gene HEIH as an oncogenic system: A multidimensional analysis in colon cancer

The novel gene YBX3 is important for regulating translation and RNA catabolism and encodes a protein with a highly conserved cold-shock domain. However, its pathogenic roles across cancers (e.g., colon cancer) and its regulation remain unclear. We identified the pathogenic roles of YBX3 and its regulatory lncRNA HEIH in various cancers and investigated their effects on tumor progression in colon cancer. Methods including RNA pull-down, MS, and TMA of 93 patients, qPCR of 12 patients with diverse clinicopathologic stages, and western blotting were performed. The pancancer analysis showed that YBX3 expression varies significantly among not only cancer types but also molecular and immune subtypes of the same cancer. Furthermore, its expression in colon cancer is clinically significant, and there is an obvious negative regulatory association between HEIH and YBX3. Among various cancers, especially colon cancer, YBX3 is more related than HEIH expression to the clinical features and prognosis of subgroups. The receiver operating characteristic analysis showed that HEIH and YBX3 have similar predictive capacity in various cancers. The analysis of differentially expressed genes in colon cancer revealed that they have similar hub gene networks, indicating an oncogenic system with a strong overlap. The results also suggest that YBX3 is associated with tumor immune evasion via different mechanisms involving T-cell exclusion in different cancer types and by the tumor infiltration of immune cells. Interestingly, scRNA-seq revealed that HEIH inhibits this phenomenon. Our results also suggest that YBX3 expression is associated with immune or chemotherapeutic outcomes in various cancers, and YBX3 exhibited a higher predictive power than two of seven standardized biomarkers for response outcomes and overall survival of immune checkpoint blockade subcohorts. In colon cancer cell lines, lncRNA-HEIH and YBX3 associate. MS confirmed that YBX3 was pulled down with HEIH, and western blot showed that HEIH knockdown disinhibited YBX3. This study strongly suggests that lncRNA-HEIH/YBX3 is a pancancer immune-oncogenic system and could serve as a biomarker for diagnosis and prognosis and as a therapeutic target, especially in colon cancer.

Regulatory Role of Non-Coding RNAs on Immune Responses During Sepsis

Sepsis is resulted from a systemic inflammatory response to bacterial, viral, or fungal agents. The induced inflammatory response by these microorganisms can lead to multiple organ system failure with devastating consequences. Recent studies have shown altered expressions of several non-coding RNAs such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and circular RNAs (circRNAs) during sepsis. These transcripts have also been found to participate in the pathogenesis of multiple organ system failure through different mechanisms. NEAT1, MALAT1, THRIL, XIST, MIAT and TUG1 are among lncRNAs that participate in the pathoetiology of sepsis-related complications. miR-21, miR-155, miR-15a-5p, miR-494-3p, miR-218, miR-122, miR-208a-5p, miR-328 and miR-218 are examples of miRNAs participating in these complications. Finally, tens of circRNAs such as circC3P1, hsa_circRNA_104484, hsa_circRNA_104670 and circVMA21 and circ-PRKCI have been found to affect pathogenesis of sepsis. In the current review, we describe the role of these three classes of noncoding RNAs in the pathoetiology of sepsis-related complications.

Identification of driver genes for critical forms of COVID-19 in a deeply phenotyped young patient cohort

[Figure: see text].

Long Noncoding RNA: Regulatory Mechanisms and Therapeutic Potential in Sepsis

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and is characterized by a hyperinflammatory state accompanied by immunosuppression. Long noncoding RNAs (lncRNAs) are noncoding RNAs longer than 200 nucleotides and have important roles in mediating various biological processes. Recently, lncRNAs were found to exert both promotive and inhibitory immune functions in sepsis, thus participating in sepsis regulation. Additionally, several studies have revealed that lncRNAs are involved in sepsis-induced organ dysfunctions, including cardiovascular dysfunction, acute lung injury, and acute kidney injury. Considering the lack of effective biomarkers for early identification and specific treatment for sepsis, lncRNAs may be promising biomarkers and even targets for sepsis therapies. This review systematically highlights the recent advances regarding the roles of lncRNAs in sepsis and sheds light on their use as potential biomarkers and treatment targets for sepsis.

The Role of Long Non-coding RNAs in Sepsis-Induced Cardiac Dysfunction

Sepsis is a syndrome with life-threatening organ dysfunction induced by a dysregulated host response to infection. The heart is one of the most commonly involved organs during sepsis, and cardiac dysfunction, which is usually indicative of an extremely poor clinical outcome, is a leading cause of death in septic cases. Despite substantial improvements in the understanding of the mechanisms that contribute to the origin and responses to sepsis, the prognosis of sepsis-induced cardiac dysfunction (SICD) remains poor and its molecular pathophysiological changes are not well-characterized. The recently discovered group of mediators known as long non-coding RNAs (lncRNAs) have presented novel insights and opportunities to explore the mechanisms and development of SICD and may provide new targets for diagnosis and therapeutic strategies. LncRNAs are RNA transcripts of more than 200 nucleotides with limited or no protein-coding potential. Evidence has rapidly accumulated from numerous studies on how lncRNAs function in associated regulatory circuits during SICD. This review outlines the direct evidence of the effect of lncRNAs on SICD based on clinical trials and animal studies. Furthermore, potential functional lncRNAs in SICD that have been identified in sepsis studies are summarized with a proven biological function in research on other cardiovascular diseases.

Hypoxia-Induced MALAT1 Promotes the Proliferation and Migration of Breast Cancer Cells by Sponging MiR-3064-5p

Hypoxia, a common process during tumor growth, can lead to tumor aggressiveness and is tightly associated with poor prognosis. Long noncoding RNAs (lncRNAs) are long ribonucleotides (>200 bases) with limited ability to translate proteins, and are known to affect many aspects of cellular function. One of their regulatory mechanisms is to function as a sponge for microRNA (miRNA) to modulate its biological functions. Previously, MALAT1 was identified as a hypoxia-induced lncRNA. However, the regulatory mechanism and functions of MALAT1 in breast cancer are still unclear. Therefore, we explored whether MALAT1 can regulate the functions of breast cancer cells through miRNAs. Our results showed the expression levels of MALAT1 were significantly up-regulated under hypoxia and regulated by HIF-1α and HIF-2α. Next, in contrast to previous reports, nuclear and cytoplasmic fractionation assays and fluorescence in situ hybridization indicated that MALAT1 was mainly located in the cytoplasm. Therefore, the labeling of MALAT1 as a nuclear marker should be done with the caveat. Furthermore, expression levels of miRNAs and RNA immunoprecipitation using antibody against AGO2 showed that MALAT1 functioned as a sponge of miRNA miR-3064-5p. Lastly, functional assays revealed that MALAT1 could promote cellular migration and proliferation of breast cancer cells. Our findings provide evidence that hypoxia-responsive long non-coding MALAT1 could be transcriptionally activated by HIF-1α and HIF-2α, act as a miRNA sponge of miR-3064-5p, and promote tumor growth and migration in breast cancer cells. These data suggest that MALAT1 may be a candidate for therapeutic targeting of breast cancer progression.

MicroRNA-23a reduces lipopolysaccharide-induced cellular apoptosis and inflammatory cytokine production through Rho-associated kinase 1/sirtuin-1/nuclear factor-kappa B crosstalk

Background:

MicroRNAs are closely associated with the progression and outcomes of multiple human diseases, including sepsis. In this study, we examined the role of miR-23a in septic injury.

Methods:

Lipopolysaccharide (LPS) was used to induce sepsis in a rat model and H9C2 and HK-2 cells. miR-23a expression was evaluated in rat myocardial and kidney tissues, as well as H9C2 and HK-2 cells. A miR-23a mimic was introduced into cells to identify the role of miR-23a in cell viability, apoptosis, and the secretion of inflammatory cytokines. Furthermore, the effect of Rho-associated kinase 1 (ROCK1), a miR-23a target, on cell damage was evaluated, and molecules involved in the underlying mechanism were identified.

Results:

In the rat model, miR-23a was poorly expressed in myocardial (sham vs. sepsis 1.00 ± 0.06 vs. 0.27 ± 0.03, P < 0.01) and kidney tissues (sham vs. sepsis 0.27 ± 0.03 vs. 1.00 ± 0.06, P < 0.01). Artificial overexpression of miR-23a resulted in increased proliferative activity (DNA replication rate: Control vs. LPS vs. LPS + Mock vs. LPS + miR-23a: H9C2 cells: 34.13 ± 3.12 vs. 12.94 ± 1.21 vs. 13.31 ± 1.43 vs. 22.94 ± 2.26, P < 0.05; HK-2 cells: 15.17 ± 1.43 vs. 34.52 ± 3.46 vs. 35.19 ± 3.12 vs. 19.87 ± 1.52, P < 0.05), decreased cell apoptosis (Control vs. LPS vs. LPS + Mock vs. LPS + miR-23a: H9C2 cells: 11.39 ± 1.04 vs. 32.57 ± 2.29 vs. 33.08 ± 3.12 vs. 21.63 ± 2.35, P < 0.05; HK-2 cells: 15.17 ± 1.43 vs. 34.52 ± 3.46 vs. 35.19 ± 3.12 vs. 19.87 ± 1.52, P < 0.05), and decreased production of inflammatory cytokines, including interleukin-6 (Control vs. LPS vs. LPS + Mock vs. LPS + miR-23a: H9C2 cells: 59.61 ± 5.14 vs. 113.54 ± 12.30 vs. 116.51 ± 10.69 vs. 87.69 ± 2.97 ng/mL; P < 0.05, F = 12.67, HK-2 cells: 68.12 ± 6.44 vs. 139.65 ± 16.62 vs. 143.51 ± 13.64 vs. 100.82 ± 9.74 ng/mL, P < 0.05, F = 9.83) and tumor necrosis factor-α (Control vs. LPS vs. LPS + Mock vs. LPS + miR-23a: H9C2 cells: 103.20 ± 10.31 vs. 169.67 ± 18.84 vs. 173.61 ± 15.91 vs. 133.36 ± 12.32 ng/mL, P < 0.05, F = 12.67, HK-2 cells: 132.51 ± 13.37 vs. 187.47 ± 16.74 vs. 143.51 ± 13.64 vs. 155.79 ± 15.31 ng/mL, P < 0.05, F = 9.83) in cells. However, ROCK1 was identified as a miR-23a target, and further up-regulation of ROCK1 mitigated the protective function of miR-23a in LPS-treated H9C2 and HK-2 cells. Moreover, ROCK1 suppressed sirtuin-1 (SIRT1) expression to promote the phosphorylation of nuclear factor-kappa B (NF-κB) p65, indicating the possible involvement of this signaling pathway in miR-23a-mediated events.

Conclusion:

Our results indicate that miR-23a could suppress LPS-induced cell damage and inflammatory cytokine secretion by binding to ROCK1, mediated through the potential participation of the SIRT1/NF-κB signaling pathway.

Targeting MALAT1 and miRNA-181a-5p for the intervention of acute lung injury/acute respiratory distress syndrome

BACKGROUND

ALI/ARDS is a severe lung injury leading to refractory respiratory failure, accounting for high morbidity and mortality. However, therapeutic approaches are rather limited. Targeting long non-coding RNA MALAT1 and microRNA miR-181a-5p might be potential option for ALI/ARDS intervention.

OBJECTIVE

We aimed to investigate the role of MALAT and miR-181a-5p in the pathogenesis of ALI/ARDS, and test the therapeutic effects of targeting MALAT and miR-181a-5p for ALI/ARDS intervention in vitro.

METHODS

MALAT1 and miR-181a-5p levels were measured in plasma from ALI/ARDS patients. In vitro human pulmonary microvascular endothelial cell (HPMEC) injury was induced by LPS treatment, and molecular targets of MALAT1 and miR-181a-5p were explored by molecular biology approaches, mainly focusing on cell apoptosis and vascular inflammation. Interaction between MALAT1 and miR-181a-5p was also detected. Finally, the effects of targeting MALAT1 and miR-181a-5p for ALI/ARDS intervention were validated in a rat ALI/ARDS model.

RESULTS

MALAT1 upregulation and miR-181a-5p downregulation were observed in ALI/ARDS patients. Transfection of mimic miR-181a-5p into HPMECs revealed decreased Fas and apoptosis, along with reduced inflammatory factors. Fas was proved to be a direct target of miR-181a-5p. Similar effects were also present upon MALAT1 knockdown. As for the interaction between MALAT1 and miR-181a-5p, MALAT1 knockdown increased miR-181a-5p expression. Knocking down of MALAT1 and miR-181a-5p could both improve the outcome in ALI/ARDS rats.

CONCLUSION

MALAT1 antagonism or miR-181a-5p could both be potential therapeutic strategies for ALI/ARDS. Mechanistically, miR-181a-5p directly inhibits Fas and apoptosis, along with reduced inflammation. MALAT1 negatively regulates miR-181a-5p.

Identifying Potential Candidate Hub Genes and Functionally Enriched Pathways in the Immune Responses to Quadrivalent Inactivated Influenza Vaccines in the Elderly Through Co-Expression Network Analysis

Insights into the potential candidate hub genes may facilitate the generation of safe and effective immunity against seasonal influenza as well as the development of personalized influenza vaccines for the elderly at high risk of influenza virus infection. This study aimed to identify the potential hub genes related to the immune induction process of the 2018/19 seasonal quadrivalent inactivated influenza vaccines (QIVs) in the elderly ≥60 years by using weighted gene co-expression network analysis (WGCNA). From 63 whole blood samples from16 elderly individuals, a total of 13,345 genes were obtained and divided into eight co-expression modules, with two modules being significantly correlated with vaccine-induced immune responses. After functional enrichment analysis, genes under GO terms of vaccine-associated immunity were used to construct the sub-network for identification and functional validation of hub genes. MCEMP1 and SPARC were confirmed as the hub genes with an obvious effect on QIVs-induced immunity. The MCEMP1 expression was shown to be negatively correlated with the QIVs-associated reactogenicity within 7 days after vaccination, which could be suppressed by the CXCL 8/IL-8 and exacerbated by the Granzyme-B cytotoxic mediator. Meanwhile, the SPARC expression was found to increase the immune responses to the QIVs and contribute to the persistence of protective humoral antibody titers. These two genes can be used to predict QIVs-induced adverse reaction, the intensity of immune responses, and the persistence of humoral antibody against influenza. This work has shed light on further research on the development of personalized QIVs with appropriate immune responses and long-lasting immunity against the forthcoming seasonal influenza.

Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis

Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack of easy-to-use predictive tools that can accurately diagnose sepsis in children. This study aimed to develop an optimal gene model for the diagnosis of pediatric sepsis using statistics and machine learning approaches. Combining gene expression profiles from a training cohort of 364 pediatric samples with a Least Absolute Shrinkage and Selection Operator analysis produced eighteen genes as diagnostic markers. With the implementation of a Gradient Boosting algorithm, a model designated PEDSEPS-GBM, that aggregated these markers was developed with optimal performance for the diagnosis of pediatric samples in the validation and two independent cohorts. Moreover, a web calculator with a user-friendly interface was established for PEDSEPS-GBM. This study presents a diagnostic model that holds great potential for the detection of pediatric sepsis, and demonstrates the biologic and clinical relevance of this model.