Relationship between Expression of Plasma lncRNA-HEIH and Prognosis in Patients with Coronary Artery Disease

Diagnostic and Prognostic Value of Plasma lncRNA SRA1 in Chronic Heart Failure

Background

The pathogenesis and development of chronic heart failure (CHF) may involve long non-coding ribonucleic acid (lncRNA) steroid receptor RNA activator 1 (SRA1), a known cardiomyopathy risk factor and regulator of cardiac myofibroblast activation. This study aimed to investigate the application of SRA1 in the early detection and prediction of CHF.

Methods

SRA1 plasma expression was determined in CHF patients and healthy individuals/using real time-quantitative polymerase chain reaction (RT-qPCR). The diagnostic and prognostic value of SRA1 was assessed using receiver operating curve (ROC) and Cox regression analyses.

Results

Compared with the healthy controls, the patients with CHF had increased brain natriuretic peptide (BNP) levels, left atrial end-systolic diameter (LAD), left ventricular end-diastolic diameter (LVDd), and decreased left ventricular ejection fraction (LVEF). SRA1 was significantly upregulated in CHF patients as well as positively correlated with BNP level, LAD, and LVDd, and negatively correlated with LVEF. SRA1 could sensitively discriminate CHF patients from healthy individuals and was an independent predictor of adverse event-free survival in CHF patients.

Conclusions

Upregulated plasma SRA1 can discriminate patients with CHF from healthy individuals and predict adverse outcomes in CHF patients. Thus, SRA1 is a potential molecular indicator for monitoring chronic heart failure development.

Identification of prognostic models for glycosylation-related subtypes and tumor microenvironment infiltration characteristics in clear cell renal cell cancer

Background

One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC.

Methods

In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The "ConsensusClusterPlus" program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors.

Results

We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.

LncRNA CASC11 upregulation promotes HDAC4 to alleviate oxidized low-density lipoprotein-induced injury of cardiac microvascular endothelial cells

Long noncoding RNAs (LncRNAs) are essential to regulate the pathogenesis of coronary artery disease (CAD). This study was conducted to analyze the functionality of long noncoding RNA cancer susceptibility candidate 11 (lncRNA CASC11) in oxidized low-density lipoprotein (ox-LDL)-induced injury of cardiac microvascular endothelial cells (CMECs). CMECs were treated with ox-LDL to induce the CAD cell model. The cellular expression levels of CASC11 and histone deacetylase 4 (HDAC4) were determined by real-time quantitative polymerase chain reaction or Western blot assay. Cell absorbance, apoptosis, angiogenesis, and inflammation were evaluated by cell counting kit-8, flow cytometry, tube formation, and enzyme-linked immunosorbent assays. The subcellular localization of CASC11 was examined by the nuclear/cytoplasmic fractionation assay. The binding of human antigen R (HuR) to CASC11 and HDAC4 was analyzed by RNA immunoprecipitation. HDAC4 stability was determined after actinomycin D treatment. CASC11 was found to be decreased in the CAD cell model. CASC11 upregulation increased cell viability and angiogenesis and reduced apoptosis and inflammation. CASC11 bound to HuR and improved HDAC4 expression. HDAC4 downregulation counteracted the protective role of CASC11 overexpression in CMECs. In summary, CASC11 alleviated ox-LDL-induced injury of CMECs by binding to HuR and stabilizing HDAC4.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Ethacrynic Acid: A Promising Candidate for Drug Repurposing as an Anticancer Agent

Ethacrynic acid (ECA) is a diuretic that inhibits Na-K-2Cl cotransporter (NKCC2) present in the thick ascending loop of Henle and muculo dens and is clinically used for the treatment of edema caused by excessive body fluid. However, its clinical use is limited due to its low bioavailability and side effects, such as liver damage and hearing loss at high doses. Despite this, ECA has recently emerged as a potential anticancer agent through the approach of drug repositioning, with a novel mechanism of action. ECA has been shown to regulate cancer hallmark processes such as proliferation, apoptosis, migration and invasion, angiogenesis, inflammation, energy metabolism, and the increase of inhibitory growth factors through various mechanisms. Additionally, ECA has been used as a scaffold for synthesizing a new material, and various derivatives have been synthesized. This review explores the potential of ECA and its derivatives as anticancer agents, both alone and in combination with adjuvants, by examining their effects on ten hallmarks of cancer and neuronal contribution to cancer. Furthermore, we investigated the trend of synthesis research of a series of ECA derivatives to improve the bioavailability of ECA. This review highlights the importance of ECA research and its potential to provide a cost-effective alternative to new drug discovery and development for cancer treatment.

Ethacrynic acid suppresses B7-H4 expression involved in epithelial-mesenchymal transition of lung adenocarcinoma cells via inhibiting STAT3 pathway

Lung cancer is characterized by high incidence and mortality. 90% of cancer deaths are caused by metastases. The epithelial-mesenchymal transition (EMT) process in cancer cells is a prerequisite for the metastatic process. Ethacrynic acid (ECA) is a loop diuretic that inhibits the EMT process in lung cancer cells. EMT has been related to the tumour immunemicroenvironment. However, the effect of ECA on immune checkpoint molecules in the context of cancer has not been fully identified. In the present study, we found that sphingosylphosphorylcholine (SPC) and TGF-β1, awell-known EMT inducer, induced the expression of B7-H4 in lung cancer cells. We also investigated the involvement of B7-H4 in the SPC-induced EMT process. Knockdown of B7-H4 suppressed SPC-induced EMT, while B7-H4 overexpression enhanced EMT of lung cancer cells. ECA inhibited SPC/TGF-β1-induced B7-H4 expression via suppression of STAT3 activation. Moreover, ECA inhibits the colonization of mice lung by tail vein-injected LLC1 cells. ECA-treated mice increased the CD4-positive T cells in lung tumour tissues. In summary, these results suggested that ECA inhibits B7-H4 expression via STAT3 inhibition, leading to SPC/TGF-β1-induced EMT. Therefore, ECA might be an immune oncological drug for B7-H4-positive cancer, especially lung cancer.

Downregulated Circulating Long Non-coding RNA GAS6-AS1 Screens and Predicts Acute Myocardial Infarction

BACKGROUND

Acute myocardial infarction seriously threatens human health and life quality, which needs novel biomarkers to improve its early detection and development prediction. This study aimed to assess the potential of long non-coding RNA GAS6-AS1 in discriminating acute myocardial infarction patients and predicting patients' outcomes.

METHODS

The circulating expression of GAS6-AS1 in 83 acute myocardial infarction patients and 62 healthy individuals was evaluated using polymerase chain reaction. The value of GAS6-AS1 in the distinguishing acute myocardial infarction patients was evaluated with receiver operating characteristic analysis, and its prognosis predictive potential was assessed by Kaplan-Meier and Cox analysis. Additionally, the correlation of GAS6-AS1 with patients' critical features was evaluated by Spearman's correlation analysis.

RESULTS

Significant downregulation of GAS6-AS1 was observed in the plasma of acute myocardial infarction patients relative to healthy individuals. Reduced GAS6-AS1 could discriminate acute myocardial infarction patients from healthy controls and indicate patients' unoptimistic prognosis. Moreover, GAS6-AS1 was found to be negatively cor-related with the levels of creatine kinase, creatine kinasemyocardial bland, lactic dehy-drogenase, hydroxybutyrate dehydrogenase, troponin T, and positively correlated with the ejection fraction of acute myocardial infarction patients.

CONCLUSION

Changes in circulating GAS6-AS1 in acute myocardial infarction served as a potential diagnostic and prognostic biomarker of acute myocardial infarction.

lncRNA-TCONS_00008552 expression in patients with pulmonary arterial hypertension due to congenital heart disease

Long noncoding RNAs (lncRNAs) are potential regulators of a variety of cardiovascular diseases. Therefore, there is a series of differentially expressed lncRNAs in pulmonary arterial hypertension (PAH) that may be used as markers to diagnose PAH and even predict the prognosis. However, their specific mechanisms remain largely unknown. Therefore, we investigated the biological role of lncRNAs in patients with PAH. First, we screened patients with PAH secondary to ventricular septal defect (VSD) and those with VSD without PAH to assess differences in lncRNA and mRNA expression between the two groups. Our results revealed the significant upregulation of 813 lncRNAs and 527 mRNAs and significant downregulation of 541 lncRNAs and 268 mRNAs in patients with PAH. Then, we identified 10 hub genes in a constructed protein-protein interaction network. Next, we performed bioinformatics analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis and subsequently constructed coding-noncoding co-expression networks. We screened lncRNA-TCONS_00008552 and lncRNA-ENST00000433673 as candidate genes and verified the expression levels of the lncRNAs using quantitative reverse-transcription PCR. Although expression levels of lncRNA-TCONS_00008552 in the plasma from the PAH groups were significantly increased compared with the control groups, there was no significant difference in the expression of lncRNA-ENST00000433673 between the two groups. This study bolsters our understanding of the role of lncRNA in PAH occurrence and development and indicates that lncRNA-TCONS_00008552 is a novel potential molecular marker for PAH.

StackCirRNAPred: computational classification of long circRNA from other lncRNA based on stacking strategy

BACKGROUND

CircRNAs are essential for the regulation of post-transcriptional gene expression, including as miRNA sponges, and play an important role in disease development. Some computational tools have been proposed recently to predict circRNA, since only one classifier is used, there is still much that can be done to improve the performance.

RESULTS

StackCirRNAPred was proposed, the computational classification of long circRNA from other lncRNA based on stacking strategy. In order to cope with the potential problem that a single feature might not be able to distinguish circRNA well from other lncRNA, we first extracted features from different sources, including nucleic acid composition, sequence spatial features and physicochemical properties, Alu and tandem repeats. We innovatively apply the stacking strategy to integrate the more advantageous classifiers of RF, LightGBM, XGBoost. This allows the model to incorporate these features more flexibly. StackCirRNAPred was found to be significantly better than other tools, with precision, accuracy, F1, recall and MCC of 0.843, 0.833, 0.831, 0.819 and 0.666 respectively. We tested it directly on the mouse dataset. StackCirRNAPred was still significantly better than other methods, with precision, accuracy, F1, recall and MCC of 0.837, 0.839, 0.839, 0.841, 0.677.

CONCLUSIONS

We proposed StackCirRNAPred based on stacking strategy to distinguish long circRNAs from other lncRNAs. With the test results demonstrating the validity and robustness of StackCirRNAPred, we hope StackCirRNAPred will complement existing circRNA prediction methods and is helpful in down-stream research.

Circulating long non-coding RNA TTTY15 and HULC serve as potential novel biomarkers for predicting acute myocardial infarction

INTRODUCTION

Acute myocardial infarction (AMI) is a ubiquitous cardiovascular disease ensuing adverse prognosis caused by myocardial necrosis. Effective and rapid diagnosis of AMI is essential to following treatment in clinical practice while the existed biomarkers have inherent limitations. Consequently, exploration of novel biomarkers is needed. Long noncoding RNA (lncRNA) emerges as the upcoming biomarkers adopted in clinical use, and we aim at investigating the diagnostic power of lncRNA TTTY15 and HULC in AMI patients.

METHOD

We measured lncRNA level in 80 AMI patients and 36 healthy volunteers in discovering cohort and 50 AMI patients and 20 healthy volunteers in verification cohort with quantitative RT-PCR method. Receiver operating characteristic (ROC) analysis was administered to detect the diagnostic power of selected lncRNAs. Regression and correlation analyses were performed to explore the related factors.

RESULTS

ROC analysis reveals the superiority of TTTY15 and HULC as biomarkers against conventional AMI biomarkers CKMB (AUC of TTTY15: 0.915 versus CKMB: 0.768 versus TnT: 0.869); AUC of HULC: 0.905 versus CKMB: 0.768 versus TnT: 0.869). Regression and correlation analysis indicates that TTTY15 and HULC may be one of the contributing factors to AMI and related to accepted risk factors.

CONCLUSION

Our results revealed the diagnostic potency of lncRNA TTTY15 and HULC, and they could also be treated as novel therapeutic targets in AMI therapy, hinting inspiration to the cardiologist in clinical practice.

Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning

Objectives

Synovial fibroblasts (SFs) play an important role in the development and progression of rheumatoid arthritis (RA). However, the pathogenic mechanism of SFs remains unclear. The objective of this study was to investigate how neuropeptides and N6-methyladenosine (m6A) played an important role in the underlying pathogenic processes of SFs that contribute to the development of RA.

Methods

Single-cell RNA sequencing data were examined using single-cell analysis and machine learning. SF subgroups were identified based on the clustering and annotation results of the single-cell analysis. Moreover, cell–cell communication was used to analyse neuropeptide-related receptor and ligand pairs on the surface of SF cell membranes. Machine learning was used to explore the m6A factors acting on these neuropeptide genes.

Results

NPR3, GHR, BDKRB2, and CALCRL, four neuropeptide genes, were shown to be differently expressed among SF subgroups. Further investigation of receptor–ligand interactions found that NPR3 (in conjunction with NPPC, OSTN, NPPB, and NPPA) and GHR (in conjunction with GH1 and GH2) may have a role in SF interactions. As predicted by machine learning, IGFBP2 and METTL3 were identified as key factors regulating m6A of NPR3 and GHR. The expression levels and enrichment pathways of METTL3 and IGFBP2 were different among SF subgroups.

Conclusions

Single-cell analysis and machine learning efficiently identified neuropeptide genes and m6A factors that perform important regulatory functions in RA. Our strategy may provide a basis for future studies to identify pathogenic cell subpopulations and molecular mechanisms in RA and other diseases.

Inhibition of circular RNA circ_0138959 alleviates pyroptosis of human gingival fibroblasts via the microRNA-527/caspase-5 axis

Circular RNA (circRNA) plays a regulatory role in periodontitis. This study explored whether circ_0138959 affected lipopolysaccharide (LPS)-induced pyroptosis in human gingival fibroblasts (HGFs). The periodontal ligament (PDL) tissues and HGFs were derived from patients with periodontitis and healthy volunteers. HGFs treated with LPS were considered to mimic periodontitis in vitro. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to evaluate the mRNA expression levels of circRNAs, miR-527, and caspase-5 (CASP5), and Western blotting assay was used to measure protein expression levels of caspase-1, caspase-4, and cleaved N-terminal gasdermin D (GSDMD-N). Cell viability was evaluated by cell counting kit-8 (CCK-8) assay. The concentration of lactate dehydrogenase (LDH), interleukin (IL)-1β, and IL-18 and the pyroptosis rate were determined to evaluate pyroptosis. The interaction between miR-527 and circ_0138959 or CASP5 was verified by dual-luciferase reporter and RNA pull-down assays. Circ_0138959 expression was higher in the PDL tissues of patients with periodontitis than in the healthy group; likewise, circ_0138959 was also upregulated in LPS-treated HGFs. Suppressed circ_0138959 increased cell viability and decreased pyroptosis of HGFs induced by LPS. miR-527 was a target of circ_0138959, and inhibition of miR-527 contributed to the dysfunction of LPS-treated HGFs and reversed the protective effects of downregulated circ_0138959. Additionally, miR-527 targeted CASP5. Increased CASP5 abrogated the effects of overexpressed miR-527 on cell viability and pyroptosis of LPS-treated HGFs. Inhibition of circ_0138959 promoted cell viability and suppressed pyroptosis of HGFs via the miR-527/CASP5 axis. Therefore, knockdown of circ_0138959 may be a promising therapy for periodontitis.