A novel lncRNA-miRNA-mRNA triple network identifies lncRNA TWF1 as an important regulator of miRNA and gene expression in coronary artery disease

Potential roles of microRNAs and long noncoding RNAs as diagnostic, prognostic and therapeutic biomarkers in coronary artery disease

Coronary artery disease (CAD), which is mainly caused by atherosclerotic processes in coronary arteries, became a significant health issue. MicroRNAs (miRNAs), and long noncoding RNAs (lncRNAs), have been shown to be stable in plasma and could thereby be adopted as biomarkers for CAD diagnosis and treatment. MiRNAs can regulate CAD development through different pathways and mechanisms, including modulation of vascular smooth muscle cell (VSMC) activity, inflammatory responses, myocardial injury, angiogenesis, and leukocyte adhesion. Similarly, previously studies have indicated that the causal effects of lncRNAs in CAD pathogenesis and their utility in CAD diagnosis and treatment, has been found to lead to cell cycle transition, proliferation dysregulation, and migration in favour of CAD development. Differential expression of miRNAs and lncRNAs in CAD patients has been identified and served as diagnostic, prognostic and therapeutic biomarkers for the assessment of CAD patients. Thus, in the current review, we summarize the functions of miRNAs and lncRNAs, which aimed to identify novel targets for the CAD diagnosis, prognosis, and treatment.

Competitive Endogenous RNA Network Activates Host Immune Response in SARS-CoV-2-, panH1N1 (A/California/07/2009)-, and H7N9 (A/Shanghai/1/2013)-Infected Cells

The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still ongoing, as is research on the molecular mechanisms underlying cellular infection by coronaviruses, with the hope of developing therapeutic agents against this pandemic. Other important respiratory viruses such as 2009 pandemic H1N1 and H7N9 avian influenza virus (AIV), influenza A viruses, are also responsible for a possible outbreak due to their respiratory susceptibility. However, the interaction of these viruses with host cells and the regulation of post-transcriptional genes remains unclear. In this study, we detected and analyzed the comparative transcriptome profiling of SARS-CoV-2, panH1N1 (A/California/07/2009), and H7N9 (A/Shanghai/1/2013) infected cells. The results showed that the commonly upregulated genes among the three groups were mainly involved in autophagy, pertussis, and tuberculosis, which indicated that autophagy plays an important role in viral pathogenicity. There are three groups of commonly downregulated genes involved in metabolic pathways. Notably, unlike panH1N1 and H7N9, SARS-CoV-2 infection can inhibit the m-TOR pathway and activate the p53 signaling pathway, which may be responsible for unique autophagy induction and cell apoptosis. Particularly, upregulated expression of IRF1 was found in SARS-CoV-2, panH1N1, and H7N9 infection. Further analysis showed SARS-CoV-2, panH1N1, and H7N9 infection-induced upregulation of lncRNA-34087.27 could serve as a competitive endogenous RNA to stabilize IRF1 mRNA by competitively binding with miR-302b-3p. This study provides new insights into the molecular mechanisms of influenza A virus and SARS-CoV-2 infection.

Knockdown of LINC00511 decreased cisplatin resistance in non-small cell lung cancer by elevating miR-625 level to suppress the expression of leucine rich repeat containing eight volume-regulated anion channel subunit E

BACKGROUND

LINC00511 has been reported as a biomarker related to the prognosis of non-small cell lung cancer (NSCLC), but the molecular mechanism and exact functions of LINC00511 in chemoresistance of NSCLC remain to be elucidated.

METHODS

RT-qPCR was used to evaluate the mRNA expression of LINC00511, miR-625, and leucine rich repeat containing 8 volume-regulated anion channel subunit E (LRRC8E). Western blotting detected the protein levels of Ki-67, MMP-9, cleaved-caspase-3. The interaction between miR-625 and LINC00511 or LRRC8E was verified by luciferase reporter assays. CCK-8, TUNEL, and Transwell assays were used to evaluate IC₅₀ value, proliferation, migration, and invasion of NSCLC cells.

RESULTS

In our study, it was discovered that the levels of LINC00511 and LRRC8E were increased, while miR-625 expression was decreased in NSCLC tissues, DDP-resistant NSCLC cells, and non-resistant NSCLC cells. LINC00511 depletion significantly curbed cell growth, IC₅₀ value, and metastasis in DDP-resistant NSCLC cells. In addition, the influence of LINC00511 deficiency on the DDP resistance in NSCLC was overturned by suppressing miR-625. Furthermore, LRRC8E overexpression abolished the promotive effect of miR-625 abundance on the DDP sensitivity in DDP-resistant NSCLC cells.

CONCLUSION

Our results demonstrated that LINC00511 increased DDP resistance in NSCLC by suppressing miR-625 to upregulate LRRC8E.

Identification of Two Long Non-Coding RNAs AC010082.1 and AC011443.1 as Biomarkers of Coronary Heart Disease Based on Logistic Stepwise Regression Prediction Model

Coronary heart disease (CHD) is a global health concern with high morbidity and mortality rates. This study aimed to identify the possible long non-coding RNA (lncRNA) biomarkers of CHD. The lncRNA- and mRNA-related data of patients with CHD were downloaded from the Gene Expression Omnibus database (GSE113079). The limma package was used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively). Then, miRcode, TargetScan, miRDB, and miRTarBase databases were used to form the competing endogenous RNA (ceRNA) network. Furthermore, SPSS Modeler 18.0 was used to construct a logistic stepwise regression prediction model for CHD diagnosis based on DElncRNAs. Of the microarray data, 70% was used as a training set and 30% as a test set. Moreover, a validation cohort including 30 patients with CHD and 30 healthy controls was used to verify the hub lncRNA expression through real-time reverse transcription-quantitative PCR (RT-qPCR). A total of 185 DElncRNAs (114 upregulated and 71 downregulated) and 382 DEmRNAs (162 upregulated and 220 downregulated) between CHD and healthy controls were identified from the microarray data. Furthermore, through bioinformatics prediction, a 38 lncRNA-21miRNA-40 mRNA ceRNA network was constructed. Next, by constructing a logistic stepwise regression prediction model for 38 DElncRNAs, we screened two hub lncRNAs AC010082.1 and AC011443.1 (p < 0.05). The sensitivity, specificity, and area under the curve were 98.41%, 100%, and 0.995, respectively, for the training set and 93.33%, 91.67%, and 0.983, respectively, for the test set. We further verified the significant upregulation of AC010082.1 (p < 0.01) and AC011443.1 (p < 0.05) in patients with CHD using RT-qPCR in the validation cohort. Our results suggest that lncRNA AC010082.1 and AC011443.1 are potential biomarkers of CHD. Their pathological mechanism in CHD requires further validation.

Dysregulated Circulating Apoptosis- and Autophagy-Related lncRNAs as Diagnostic Markers in Coronary Artery Disease

Objective

Increasing evidence emphasizes the implications of dysregulated apoptosis and autophagy cellular processes in coronary artery disease (CAD). Herein, we aimed to explore apoptosis- and autophagy-related long noncoding RNAs (lncRNAs) in peripheral blood of CAD patients.

Methods

The mRNA and lncRNA expression profiles were retrieved from the Gene Expression Omnibus (GEO) database. With ∣fold change | >1.5 and adjusted p value < 0.05, differentially expressed apoptosis- and autophagy-related mRNAs were screened between CAD and healthy blood samples. Also, differentially expressed lncRNAs were identified for CAD. Using the psych package, apoptosis- and autophagy-related lncRNAs were defined with Spearson's correlation analysis. Receiver operating characteristic (ROC) curves were conducted for the assessment of the diagnosed efficacy of these apoptosis- and autophagy-related lncRNAs.

Results

Our results showed that 24 apoptosis- and autophagy-related mRNAs were abnormally expressed in CAD than normal controls. 12 circulating upregulated and 1 downregulated apoptosis- and autophagy-related lncRNAs were identified for CAD. The ROCs confirmed that AC004485.3 (AUC = 0.899), AC004920.3 (AUC = 0.93), AJ006998.2 (AUC = 0.776), H19 (AUC = 0.943), RP5-902P8.10 (AUC = 0.956), RP5-1114G22.2 (AUC = 0.883), RP11-247A12.1 (AUC = 0.885), RP11-288L9.4 (AUC = 0.928), RP11-344B5.2 (AUC = 0.858), RP11-452C8.1 (AUC = 0.929), RP11-565A3.1 (AUC = 0.893), and XXbac-B33L19.4 (AUC = 0.932) exhibited good performance in differentiating CAD from healthy controls.

Conclusion

Collectively, our findings proposed that circulating apoptosis- and autophagy-related lncRNAs could become underlying diagnostic markers for CAD in clinical practice.

Long noncoding RNA ZFAS1 suppresses chondrocytes apoptosis via miR-302d-3p/SMAD2 in osteoarthritis

Osteoarthritis (OA) seriously affects people's quality of life due to joint pain, stiffness, disability, and dyskinesia worldwide. Long noncoding RNA zinc finger antisense 1 (ZFAS1) is downregulated and tightly associated with proliferation, migration, apoptosis, and matrix synthesis of chondrocyte in OA. However, the molecular mechanisms of ZFAS1 in OA remain unknown. The expression correlation between ZFAS1, miR-302d-3p, and SMAD2 in OA tissues was analyzed by Pearson correlation analysis. ZFAS1 was a lower expression, and expedited proliferation and repressed apoptosis of chondrocytes. MiR-302d-3p was a direct target of ZFAS1. MiR-302d-3p hindered proliferation and facilitated apoptosis of chondrocytes. MiR-302d-3p partially reversed the effect of ZFAS1 on proliferation and apoptosis of chondrocytes. SMAD2 was positively regulated by the ZFAS1/miR-302d-3p. MiR-302d-3p-mediated proliferation and apoptosis were partly abrogated by targeting SMAD2. ZFAS1 promoted chondrocytes proliferation and repressed apoptosis possibly by regulating miR-302d-3p/SMAD2 axis, providing a potential target for OA treatment.

Integrated regulatory network based on lncRNA-miRNA-mRNA-TF reveals key genes and sub-networks associated with dilated cardiomyopathy

Dilated Cardiomyopathy (DCM) is a multifactorial condition often leading to heart failure in many clinical cases. Due to the high number of DCMincidence reported as familial, a gene level network based study was conducted utilizing high throughput next generation sequencing data. We exploited the exome and transcriptome sequencing data in NCBI-SRA database to construct a high confidence scale-free regulatory network consisting of lncRNA, miRNA, mRNA and Transcription Factors (TFs). Analysis of RNA-Seq data revealed 477 differentially expressed coding transcripts and 77 lncRNAs. 268 miRNAs regulated either lncRNAs or mRNAs. Out of the 477 coding transcripts that are deregulated, 82 were TFs. We identified three major hub nodeslncRNA (XIST), miRNA (hsa-miR-195-5p) and mRNA (NOVA1) from the network. We also found putative disease associations of DCM with diabetes and DCM with hypoventillation syndrome. Five highly connected modules were also identified from the network. The hubs showed significant connectivity with the modules.Through this study we were able to gain insights into the underlying lncRNA-miRNA-mRNA-TF network. From a high throughput dataset we have isolated a handful of probable targets that may be utilized for studying the mechanisms of DCM development and progression to heart failure.

Roles of noncoding RNAs in the initiation and progression of myocardial ischemia-reperfusion injury

The morbidity and mortality of myocardial ischemia-reperfusion injury (MIRI) have increased in modern society. Noncoding RNAs (ncRNAs), including lncRNAs, circRNAs, piRNAs and miRNAs, have been reported in a variety of studies to be involved in pathological initiation and developments of MIRI. Hence this review focuses on the current research regarding these ncRNAs in MIRI. We comprehensively introduce the important features of lncRNAs, circRNAs, piRNA and miRNAs and then summarize the published studies of ncRNAs in MIRI. A clarification of lncRNA-miRNA-mRNA, lncRNA-transcription factor-mRNA and circRNA-miRNA-mRNA axes in MIRI follows, to further elucidate the crucial roles of ncRNAs in MIRI. Bioinformatics analysis has revealed the biological correlation of mRNAs with MIRI. We provide a comprehensive perspective for the roles of these ncRNAs and their related networks in MIRI, providing a theoretical basis for preclinical and clinical studies on ncRNA-based gene therapy for MIRI treatment.

Integrated Weighted Gene Co-expression Network Analysis Identified That TLR2 and CD40 Are Related to Coronary Artery Disease

The current research attempted to identify possible hub genes and pathways of coronary artery disease (CAD) and to detect the possible mechanisms. Array data from GSE90074 were downloaded from the Gene Expression Omnibus (GEO) database. Integrated weighted gene co-expression network analysis (WGCNA) was performed to analyze the gene module and clinical characteristics. Gene Ontology annotation (GO), Disease Ontology (DO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by clusterProfiler and the DOSE package in R. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection (MCODE) to identify hub genes. Then, further functional validation of hub genes in other microarrays and population samples was performed, and survival analysis was performed to investigate the prognosis. A total of 660 genes were located in three modules and associated with CAD. GO functions identified 484 biological processes, 39 cellular components, and 22 molecular functions with an adjusted P < 0.05. In total, 38 pathways were enriched in KEGG pathway analysis, and 147 DO items were identified with an adjusted P < 0.05 (false discovery rate, FDR set at < 0.05). There was a total of four modules with a score > 10 after PPI network analysis using the MCODE app, and two hub genes (TLR2 and CD14) were identified. Then, we validated the information from the GSE60993 dataset using the GSE59867 dataset and population samples, and we found that these two genes were associated with plaque vulnerability. These two genes varied at different time points after myocardial infarction, and both of them had the lowest prognosis of heart failure when they were expressed at low levels. We performed an integrated WGCNA and validated that TLR2 and CD14 were closely associated with the severity of coronary artery disease, plaque instability and the prognosis of heart failure after myocardial infarction.

Weighted gene coexpression network analysis identifies the key role associated with acute coronary syndrome

The present study sought to identify potential hub genes and pathways of acute coronary syndrome (ACS). We downloaded the dataset (GSE56045) from the Gene Expression Omnibus (GEO) database and analyzed weighted gene coexpression networks (WGCNA). Gene Ontology annotation, Disease Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software. The protein-protein interaction (PPI) network was constructed using Cytoscape, and the Molecular Complex Detection app was employed to identify significant modules and hub genes. The hub genes were then validated in other microarrays and patients by RT-PCR. Two modules were identified and associated with coronary artery disease (CAD) and included 219 genes. After function and PPI analyses, 24 genes were identified to be potentially associated with CAD. Linear correlation was performed to calculate the relationship between the gene expression levels and coronary artery calcification score and found that CCR7 (R = -0.081, P = 0.0065), CD2 (R = -0.075, P = 0.0012), CXCR5 (R = -0.065, P = 0.029) and IL7R (R = -0.06, P = 0.043) should be validated in other dataset. By comparing the gene expression levels in different groups in GSE23561, GSE34822, GSE59867, GSE60993 and GSE129935, only two genes (CCR7 and CXCR5) showed significance. The nomogram showed that CXCR5 showed the risk of ACS. Further analysis in chest patients found CXCR5 played a key role resulting in ACS. Our WGCNA analysis identified CXCR5 as a risk factor for ACS, and the potential pathogenesis may be associated with immune inflammation.

LncRNA MALAT1 Regulates the Progression and Cisplatin Resistance of Ovarian Cancer Cells via Modulating miR-1271-5p/E2F5 Axis

Background

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) were reported to be related to the development of ovarian cancer (OC). In this study, the functional mechanisms of lncRNA metastasis associated with lung adenocarcinoma transcript 1 (MALAT1) and microRNA-1271-5p (miR-1271-5p) were explored in OC.

Methods

The level of MALAT1, miR-1271-5p, or E2F transcription factor 5 (E2F5) was detected by qRT-PCR. MTT assay, flow cytometry analysis and transwell migration and invasion assays were performed to determine cell proliferation, apoptosis, migration and invasion, respectively. E2F5 protein expression was detected by Western blot. The interaction between miR-1271-5p and MALAT1 or E2F transcription factor 5 (E2F5) was confirmed by the dual-luciferase reporter assay.

Results

MALAT1 and E2F5 level were increased, while miR-1271-5p level was decreased in cisplatin (DDP)-resistant OC tissues and cells. MALAT1 knockdown or miR-1271-5p upregulation decreased IC₅₀ of cisplatin, and inhibited cell proliferation, migration, invasion, and facilitated cell apoptosis in DDP-resistant OC cells. Moreover, MALAT1 sponged miR-1271-5p to upregulate E2F5 expression. Besides, MALAT1 knockdown decreased DDP resistance, inhibited cell proliferation, migration, invasion, and promoted cell apoptosis by sponging miR-1271-5p to downregulate E2F5 expression in DDP-resistant OC cell.

Conclusion

We demonstrated that MALAT1 mediated DDP-resistant OC development through miR-1271-5p/E2F5 axis, providing the theoretical basis for OC therapy.

Unravelling host-pathogen interactions: ceRNA network in SARS-CoV-2 infection (COVID-19)

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Bioinformatics analysis of mouse mRNA expression dataset for presumptive SARS-CoV-2 targets.

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Induction of ISGs-Isg15, Oasl1, Usp18 and Ddx58 with no marked changes in the expression of IFNs.

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No induction of ACE2 and TMPRSS2, raising implications for host factor limitations.

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Identification of ceRNA network including miR-124-3p, Ddx58, lncRNA (Gm26917) and circRNAs (Ppp1r10, C330019G07RiK).

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Virus regulates the expression of lnc and circRNAs, acting as sponges for miR-124-3p targeting Ddx58.

COVID-19 is a lurking calamitous disease caused by an unusual virus, SARS-CoV-2, causing massive deaths worldwide. Nonetheless, explicit therapeutic drugs or clinically approved vaccines are not available for COVID-19. Thus, a comprehensive research is crucially needed to decode the pathogenic tools, plausible drug targets, committed to the development of efficient therapy. Host-pathogen interactions via host cellular components is an emerging field of research in this respect. miRNAs have been established as vital players in host-virus interactions. Moreover, viruses have the capability to manoeuvre the host miRNA networks according to their own obligations. Besides protein coding mRNAs, noncoding RNAs might also be targeted in infected cells and viruses can exploit the host miRNA network via ceRNA effect. We have predicted a ceRNA network involving one miRNA (miR-124-3p), one mRNA (Ddx58), one lncRNA (Gm26917) and two circRNAs (Ppp1r10, C330019G07RiK) in SARS-CoV infected cells. We have identified 4 DEGs-Isg15, Ddx58, Oasl1, Usp18 by analyzing a mRNA GEO dataset. There is no notable induction of IFNs and IFN-induced ACE2, significant receptor responsible for S-protein binding mediated viral entry. Pathway enrichment and GO analysis conceded the enrichment of pathways associated with interferon signalling and antiviral-mechanism by IFN-stimulated genes. Further, we have identified 3 noncoding RNAs, playing as potential ceRNAs to the genes associated with immune mechanisms. This integrative analysis has identified noncoding RNAs and their plausible targets, which could effectively enhance the understanding of molecular mechanisms associated with viral infection. However, validation of these targets is further corroborated to determine their therapeutic efficacy.

The Emerging Role of Major Regulatory RNAs in Cancer Control

Alterations and personal variations of RNA interactions have been mechanistically coupled with disease etiology and phenotypical variations. RNA biomarkers, RNA mimics, and RNA antagonists have been developed for diagnostic, prognostic, and therapeutic uses. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are two major types of RNA molecules with regulatory roles, deregulation of which has been implicated in the initiation and progression of many human malignancies. Accumulating evidence indicated the clinical roles of regulatory RNAs in cancer control, stimulating a surge in exploring the functionalities of regulatory RNAs for improved understanding on disease pathogenesis and management. In this review, we highlight the critical roles of lncRNAs and miRNAs played in tumorigenesis, scrutinize their potential functionalities as diagnostic/prognostic biomarkers and/or therapeutic targets in clinics, outline opportunities that ncRNAs may bring to complement current clinical practice for improved cancer management and identify challenges faced by translating frontier knowledge on non-coding RNAs (ncRNAs) to bedside clinics as well as possible solutions.