DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA-gene interactions

Recent advances in the development and clinical application of miRNAs in infectious diseases

In the search for new biomarkers and therapeutic targets for infectious diseases, several molecules have been investigated. Small RNAs, known as microRNAs (miRs), are important regulators of gene expression, and have emerged as promising candidates for these purposes. MiRs are a class of small, endogenous non-coding RNAs that play critical roles in several human diseases, including host-pathogen interaction mechanisms. Recently, miRs signatures have been reported in different infectious diseases, opening new perspectives for molecular diagnosis and therapy. MiR profiles can discriminate between healthy individuals and patients, as well as distinguish different disease stages. Furthermore, the possibility of assessing miRs in biological fluids, such as serum and whole blood, renders these molecules feasible for the development of new non-invasive diagnostic and prognostic tools. In this manuscript, we will comprehensively describe miRs as biomarkers and therapeutic targets in infectious diseases and explore how they can contribute to the advance of existing and new tools. Additionally, we will discuss different miR analysis platforms to understand the obstacles and advances of this molecular approach and propose their potential clinical applications and contributions to public health.

PRIMITI: A computational approach for accurate prediction of miRNA-target mRNA interaction

Current medical research has been demonstrating the roles of miRNAs in a variety of cellular mechanisms, lending credence to the association between miRNA dysregulation and multiple diseases. Understanding the mechanisms of miRNA is critical for developing effective diagnostic and therapeutic strategies. miRNA-mRNA interactions emerge as the most important mechanism to be understood despite their experimental validation constraints. Accordingly, several computational models have been developed to predict miRNA-mRNA interactions, albeit presenting limited predictive capabilities, poor characterisation of miRNA-mRNA interactions, and low usability. To address these drawbacks, we developed PRIMITI, a PRedictive model for the Identification of novel miRNA-Target mRNA Interactions. PRIMITI is a novel machine learning model that utilises CLIP-seq and expression data to characterise functional target sites in 3'-untranslated regions (3'-UTRs) and predict miRNA-target mRNA repression activity. The model was trained using a reliable negative sample selection approach and the robust extreme gradient boosting (XGBoost) model, which was coupled with newly introduced features, including sequence and genetic variation information. PRIMITI achieved an area under the receiver operating characteristic (ROC) curve (AUC) up to 0.96 for a prediction of functional miRNA-target site binding and 0.96 for a prediction of miRNA-target mRNA repression activity on cross-validation and an independent blind test. Additionally, the model outperformed state-of-the-art methods in recovering miRNA-target repressions in an unseen microarray dataset and in a collection of validated miRNA-mRNA interactions, highlighting its utility for preliminary screening. PRIMITI is available on a reliable, scalable, and user-friendly web server at https://biosig.lab.uq.edu.au/primiti.

REMR: Identification of RNA Editing-mediated MiRNA Regulation in Cancers

Dysregulation of adenosine-to-inosine (A-to-I) RNA editing has been implicated in cancer progression. However, a comprehensive understanding of how A-to-I RNA editing is incorporated into miRNA regulation to modulate gene expression in cancer remains unclear, given the lack of effective identification methods. To this end, we introduced an information theory-based algorithm named REMR to systematically identify 12,006 A-to-I RNA editing-mediated miRNA regulatory triplets (RNA editing sites, miRNAs, and genes) across ten major cancer types based on multi-omics profiling data from The Cancer Genome Atlas (TCGA). Through analyses of functional enrichment, transcriptional regulatory networks, and protein-protein interaction (PPI) networks, we showed that RNA editing-mediated miRNA regulation potentially affects critical cancer-related functions, such as apoptosis, cell cycle, drug resistance, and immunity. Furthermore, triplets can serve as biomarkers for classifying cancer subtypes with distinct prognoses or drug responses, highlighting the clinical relevance of such regulation. In addition, an online resource (http://www.jianglab.cn/REMR/) was constructed to support the convenient retrieval of our findings. In summary, our study systematically dissected the RNA editing-mediated miRNA regulations, thereby providing a valuable resource for understanding the mechanism of RNA editing as an epitranscriptomic regulator in cancer.

Identification of key lncRNAs associated with oxaliplatin resistance in colorectal cancer cells and isolated exosomes: From In-Silico prediction to In-Vitro validation

One of the critical challenges in managing colorectal cancer (CRC) is the development of oxaliplatin (OXP) resistance. Long non-coding RNAs (lncRNAs) have a crucial role in CRC progression and chemotherapy resistance, with exosomal lncRNAs emerging as potential biomarkers. This study aimed to predict key lncRNAs involved in OXP-resistance using in-silico methods and validate them using RT-qPCR methods in CRC cells and their isolated exosomes. Two public datasets, GSE42387 and GSE119481, were downloaded from the GEO database to identify differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) associated with OXP-resistance in the HCT116 cell line. The analysis of GSE42387 revealed 210 DEGs, and GSE119481 identified 73 DEmiRNAs. A protein-protein interaction (PPI) network analysis of the DEGs identified 133 interconnected genes, from which the top ten genes with the highest degree scores were selected. By intersecting predicted miRNAs targeting these genes with the DEmiRNAs, 38 common miRNAs were found. Subsequently, 224 lncRNAs targeting these common miRNAs were predicted. LncRNA-miRNA-mRNA network were constructed and the top five lncRNAs with the highest degree scores were identified. Analysis using the Kaplan-Meier plotter database revealed that the key lncRNAs NEAT1, OIP5-AS1, and MALAT1 are significantly associated with the overall survival of CRC patients. To validate these lncRNAs, OXP-resistant HCT116 sub-cell line (HCT116/OXR) was developed by exposing parental HCT116 cells to gradually increasing concentrations of OXP. Exosomes derived from both HCT116 and HCT116/OXR cells were isolated and characterized utilizing dynamic light scattering (DLS), transmission electron microscopy (TEM), and Western blotting. RT-qPCR confirmed elevated levels of NEAT1, OIP5-AS1, and MALAT1 in HCT116/OXR cells and their exosomes compared to parental HCT116 cells and their exosomes. This study concludes that NEAT1, OIP5-AS1, and MALAT1 are associated with the OXP-resistance in CRC. The high levels of these lncRNAs in exosomes of resistant cells suggest their involvement in intercellular communication and resistance propagation. This positioning makes them promising biomarkers for OXP-resistance in CRC.

Picalm, a novel regulator of GLUT4-trafficking in adipose tissue

OBJECTIVE

Picalm (phosphatidylinositol-binding clathrin assembly protein), a ubiquitously expressed clathrin-adapter protein, is a well-known susceptibility gene for Alzheimer's disease, but its role in white adipose tissue (WAT) function has not yet been studied. Transcriptome analysis revealed differential expression of Picalm in WAT of diabetes-prone and diabetes-resistant mice, hence we aimed to investigate the potential link between Picalm expression and glucose homeostasis, obesity-related metabolic phenotypes, and its specific role in insulin-regulated GLUT4 trafficking in adipocytes.

METHODS

Picalm expression and epigenetic regulation by microRNAs (miRNAs) and DNA methylation were analyzed in WAT of diabetes-resistant (DR) and diabetes-prone (DP) female New Zealand Obese (NZO) mice and in male NZO after time-restricted feeding (TRF) and alternate-day fasting (ADF). PICALM expression in human WAT was evaluated in a cross-sectional cohort and assessed before and after weight loss induced by bariatric surgery. siRNA-mediated knockdown of Picalm in 3T3-L1-cells was performed to elucidate functional outcomes on GLUT4-translocation as well as insulin signaling and adipogenesis.

RESULTS

Picalm expression in WAT was significantly lower in DR compared to DP female mice, as well as in insulin-sensitive vs. resistant NZO males, and was also reduced in NZO males following TRF and ADF. Four miRNAs (let-7c, miR-30c, miR-335, miR-344) were identified as potential mediators of diabetes susceptibility-related differences in Picalm expression, while 11 miRNAs (including miR-23a, miR-29b, and miR-101a) were implicated in TRF and ADF effects. Human PICALM expression in adipose tissue was lower in individuals without obesity vs. with obesity and associated with weight-loss outcomes post-bariatric surgery. siRNA-mediated knockdown of Picalm in mature 3T3-L1-adipocytes resulted in amplified insulin-stimulated translocation of the endogenous glucose transporter GLUT4 to the plasma membrane and increased phosphorylation of Akt and Tbc1d4. Moreover, depleting Picalm before and during 3T3-L1 differentiation significantly suppressed adipogenesis, suggesting that Picalm may have distinct roles in the biology of pre- and mature adipocytes.

CONCLUSIONS

Picalm is a novel regulator of GLUT4-translocation in WAT, with its expression modulated by both genetic predisposition to diabetes and dietary interventions. These findings suggest a potential role for Picalm in improving glucose homeostasis and highlight its relevance as a therapeutic target for metabolic disorders.

SNX4 Is Correlated With Immune Infiltration and Prognosis in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is known as the most common and malignant histologic subtype of renal carcinoma. Sorting nexin 4 (SNX4) plays a regulatory role in recycling from endosomes to the plasma membrane and promotes autophagosome assembly and transport, which may exert the cancerous growth and progression. This study aimed to assess the biological role of SNX4 in ccRCC and their clinical association via public biological data platforms combined with experimental verification.

Methods

In our study, we analyzed the mRNA and protein expression of SNX4 in ccRCC under different clinicopathological characteristics through The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases. We used the Gene Expression Profiling Interactive Analysis (GEPIA) platform to conduct the survival analysis and figure out the immune cell infiltration level under different expression levels of SNX4 combined with Tumor Immune Estimation Resource (TIMER) database. Furthermore, we predicted competing endogenous RNA (ceRNA) regulatory network using TargetScan, miRDB, starBase and miRTarBase online databases. We totally collected six paired ccRCC tissues and adjacent tissues and applied quantitative real-time polymerase chain reaction (qRT-PCR) and western blot (WB) to detect the expression of SNX4 in the collected clinical specimens.

Results

The mRNA and protein expression level of SNX4 was significantly lower in ccRCC than those in normal tissues. The results proposed that lower SNX4 was expressed in patients with higher histologic grade and in male patients. Kaplan-Meier analysis demonstrated that lower mRNA expression level of SNX4 was correlated with poorer prognosis. SNX4 had positive correlation with immune cell infiltrating levels and programmed cell death-ligand 1 (PD-L1) expression. Furthermore, we constructed the SNX4/miR-221-3p/miR-222-3p/DHRS4-AS1 axis, which may be the underlying ceRNA interaction network. Finally, we verified the reduced expression of SNX4 in ccRCC by qRT-PCR and WB.

Conclusion

The expression of SNX4 in ccRCC was lower than adjacent tissues and its downregulated expression was associated with poor prognosis of ccRCC patients. SNX4 may exert critical roles in the tumorigenesis, development and migration of ccRCC via various mechanisms.

Scanning sample-specific miRNA regulation from bulk and single-cell RNA-sequencing data

BACKGROUND

RNA-sequencing technology provides an effective tool for understanding miRNA regulation in complex human diseases, including cancers. A large number of computational methods have been developed to make use of bulk and single-cell RNA-sequencing data to identify miRNA regulations at the resolution of multiple samples (i.e. group of cells or tissues). However, due to the heterogeneity of individual samples, there is a strong need to infer miRNA regulation specific to individual samples to uncover miRNA regulation at the single-sample resolution level.

RESULTS

Here, we develop a framework, Scan, for scanning sample-specific miRNA regulation. Since a single network inference method or strategy cannot perform well for all types of new data, Scan incorporates 27 network inference methods and two strategies to infer tissue-specific or cell-specific miRNA regulation from bulk or single-cell RNA-sequencing data. Results on bulk and single-cell RNA-sequencing data demonstrate the effectiveness of Scan in inferring sample-specific miRNA regulation. Moreover, we have found that incorporating the prior information of miRNA targets can generally improve the accuracy of miRNA target prediction. In addition, Scan can contribute to construct cell/tissue correlation networks and recover aggregate miRNA regulatory networks. Finally, the comparison results have shown that the performance of network inference methods is likely to be data-specific, and selecting optimal network inference methods is required for more accurate prediction of miRNA targets.

CONCLUSIONS

Scan provides a useful method to help infer sample-specific miRNA regulation for new data, benchmark new network inference methods and deepen the understanding of miRNA regulation at the resolution of individual samples.

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Background

Coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people's health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood.

Methods

We employed bioinformatics and systems biology to explore these links between GC and COVID-19. Gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were obtained from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed.

Results

We identified 209 shared DEGs between COVID-19 and GC. Functional analyses highlighted immune-related pathways as key players in both diseases. Ten hub genes (CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, IFIT2) were identified. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19.

Conclusion

This research offer valuable insights into the molecular interplay between COVID-19 and GC, potentially guiding future therapeutic strategies.

The plasma miRNAome in ADNI: Signatures to aid the detection of at-risk individuals

INTRODUCTION

MicroRNAs are short non-coding RNAs that control proteostasis at the systems level and are emerging as potential prognostic and diagnostic biomarkers for Alzheimer's disease (AD).

METHODS

We performed small RNA sequencing on plasma samples from 847 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants.

RESULTS

We identified microRNA signatures that correlate with AD diagnoses and help predict the conversion from mild cognitive impairment (MCI) to AD.

DISCUSSION

Our data demonstrate that plasma microRNA signatures can be used to not only diagnose MCI, but also, critically, predict the conversion from MCI to AD. Moreover, combined with neuropsychological testing, plasma microRNAome evaluation helps predict MCI to AD conversion. These findings are of considerable public interest because they provide a path toward reducing indiscriminate utilization of costly and invasive testing by defining the at-risk segment of the aging population.

HIGHLIGHTS

We provide the first analysis of the plasma microRNAome for the ADNI study. The levels of several microRNAs can be used as biomarkers for the prediction of conversion from MCI to AD. Adding the evaluation of plasma microRNA levels to neuropsychological testing in a clinical setting increases the accuracy of MCI to AD conversion prediction.

Mitigating off-target effects of small RNAs: conventional approaches, network theory and artificial intelligence

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics.

Protocol to infer and analyze miRNA sponge modules in heterogeneous data using miRSM 2.0

MicroRNA (miRNA) sponges synergistically modulate physiological and pathological processes in the form of modules or clusters. Here, we present a protocol for inferring and analyzing miRNA sponge modules in heterogeneous data using the R package miRSM 2.0. We describe steps for identifying gene modules, inferring miRNA sponge modules at multi-sample and single-sample levels, and performing modular analysis. From the perspective of computational biology, miRSM 2.0 has the potential to advance our understanding of the role of miRNA sponges in diseases. For complete details on the use and execution of this protocol, please refer to Zhang et al.1,2,3.

Polymorphisms in miRNA Genes Targeting the AMPK Signaling Pathway are Associated with Cervical Cancer Susceptibility in a Han Chinese Population

Purpose

Cervical cancer (CC) poses a significant threat to women's health worldwide, and multiple signaling pathways have been confirmed to be involved in its development. The AMPK signaling pathway plays a central role in maintaining energy homeostasis, and its dysregulation is closely associated with the occurrence of CC. Changes in microRNA (miRNA) expression levels might be related to the AMPK signaling pathway. Single nucleotide polymorphisms (SNPs) can affect the function of miRNA and result in the development of CC. To investigate the association between the SNPs of AMPK pathway-associated miRNAs and CC in a Han Chinese population, we selected eight miRNA genes located in the AMPK pathway and analyzed nine SNP loci within these genes to explore whether they are associated with genetic susceptibility to cervical intraepithelial neoplasia (CIN) and CC.

Methods

A total of 2,220 subjects were included in this study, including 928 healthy controls, 421 CIN patients, and 871 CC patients. Nine candidate SNPs (rs895819 in miR-27a, rs10061133 in miR-449b, rs41291179 in miR-216a, rs76481776 in miR-182, rs10406069 in miR-5196, rs12803915 and rs550894 in miR-612, rs66683138 in miR-3622b, and rs2620381 in miR-627) were genotyped using the TaqMan method.

Results

The results showed significant differences in the allele distribution of rs41291179 and rs12803915 between the control group and the CIN group, as well as between the control group and the CC group (all P values < 0.005). The A allele of rs41291179 and the G allele of rs12803915 were associated with decreased risk of CIN (OR = 0.05, 95% CI: 0.01-0.39; OR = 0.61, 95% CI: 0.49-0.76) and CC (OR = 0.08, 95% CI: 0.01-0.66; OR = 0.71, 95% CI: 0.59-0.86), respectively.

Conclusion

Our results suggest that polymorphisms in miRNA genes of the AMPK signaling pathway are associated with the development of CC.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

A comprehensive bioinformatic analysis of the role of TGF-β1-stimulated activating transcription factor 3 by non-coding RNAs during breast cancer progression

A potent growth inhibitor for normal mammary epithelial cells is transforming growth factor beta 1 (TGF-β1). When breast tissues lose the anti-proliferative activity of this factor, invasion and bone metastases increase. Human breast cancer (hBC) cells express more activating transcription factor 3 (ATF3) when exposed to TGF-β1, and this transcription factor is essential for BC development and bone metastases. Non-coding RNAs (ncRNAs), including circular RNAs (circRNAs) and microRNAs (miRNAs), have emerged as key regulators controlling several cellular processes. In hBC cells, TGF-β1 stimulated the expression of hsa-miR-4653-5p that putatively targets ATF3. Bioinformatics analysis predicted that hsa-miR-4653-5p targets several key signaling components and transcription factors, including NFKB1, STAT1, STAT3, NOTCH1, JUN, TCF3, p300, NRF2, SUMO2, and NANOG, suggesting the diversified role of hsa-miR-4653-5p under physiological and pathological conditions. Despite the high abundance of hsa-miR-4653-5p in hBC cells, the ATF3 level remained elevated, indicating other ncRNAs could inhibit hsa-miR-4653-5p's activity. In silico analysis identified several circRNAs having the binding sites for hsa-miR-4653-5p, indicating the sponging activity of circRNAs towards hsa-miR-4653-5p. The study's findings suggest that TGF-β1 regulates circRNAs and hsa-miR-4653-5p, which in turn affects ATF3 expression, thus influencing BC progression and bone metastasis. Therefore, focusing on the TGF-β1/circRNAs/hsa-miR-4653-5p/ATF3 network could lead to new ways of diagnosing and treating BC.

Analysis of macrophage polarization and regulation characteristics in ovarian tissues of polycystic ovary syndrome

Background

Polycystic ovary syndrome (PCOS) can lead to infertility and increase the risk of endometrial cancer. Analyzing the macrophage polarization characteristics in ovarian tissues of PCOS is crucial for clinical treatment.

Methods

We obtained 13 PCOS and nine control ovarian samples from the CEO database and analyzed differentially expressed genes (DEGs). Macrophage polarization-related genes (MPRGs) were sourced from the GeneCards and MSigDB databases. Intersection of DEGs with MPRGs identified DEGs associated with macrophage polarization (MPRDEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-protein interaction (PPI) Network analysis were conducted on MPRDEGs. Moreover, the top 10 genes from three algorithms were identified as the hub genes of MPRGs. In addition, miRNAs, transcription factors (TFs), and drugs were retrieved from relevant databases for regulatory network analysis of mRNA-miRNA, mRNA-TF, and mRNA-Drug interactions. Immune cell composition analysis between the PCOS and control groups was performed using the CIBERSORT algorithm to calculate correlations across 22 immune cell types.

Results

A total of 13 PCOS samples and nine control ovarian samples were obtained in this study. We identified 714 DEGs between the two groups, with 394 up-regulated and 320 down-regulated. Additionally, we identified 774 MPRGs, from which we derived 30 MPRDEGs by intersecting with DEGs, among which 21 exhibited interaction relationships. GO and KEGG analyses revealed the enrichment of MPRDEGs in five biological processes, five cell components, five molecular functions, and three biological pathways. Immune infiltration analysis indicated a strong positive correlation between activated nature killer (NK) cells and memory B cells, while neutrophils and monocytes showed the strongest negative correlation. Further investigation of MPRDEGs identified nine hub genes associated with 41 TFs, 82 miRNAs, and 44 drugs or molecular compounds. Additionally, qRT-PCR results demonstrated overexpression of the CD163, TREM1, and TREM2 genes in ovarian tissues from the PCOS group.

Conclusion

This study elucidated the polarization status and regulatory characteristics of macrophages in ovarian tissues of the PCOS subjects, confirming significant overexpression of CD163, TREM1, and TREM2. These findings contribute to a deeper understanding of the pathogenesis of PCOS.

Adopting Integrated Bioinformatics and Systems Biology Approaches to Pinpoint the COVID-19 Patients' Risk Factors That Uplift the Onset of Posttraumatic Stress Disorder

Owing to the recent emergence of COVID-19, there is a lack of published research and clinical recommendations for posttraumatic stress disorder (PTSD) risk factors in patients who contracted or received treatment for the virus. This research aims to identify potential molecular targets to inform therapeutic strategies for this patient population. RNA sequence data for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and PTSD (from the National Center for Biotechnology Information [NCBI]) were processed using the GREIN database. Protein-protein interaction (PPI) networks, pathway enrichment analyses, miRNA interactions, gene regulatory network (GRN) studies, and identification of linked drugs, chemicals, and diseases were conducted using STRING, DAVID, Enrichr, Metascape, ShinyGO, and NetworkAnalyst v3.0. Our analysis identified 15 potentially unique hub proteins within significantly enriched pathways, including PSMB9, MX1, HLA-DOB, HLA-DRA, IFIT3, OASL, RSAD2, and so on, filtered from a pool of 201 common differentially expressed genes (DEGs). Gene ontology (GO) terms and metabolic pathway analyses revealed the significance of the extracellular region, extracellular space, extracellular exosome, adaptive immune system, and interleukin (IL)-18 signaling pathways. In addition, we discovered several miRNAs (hsa-mir-124-3p, hsa-mir-146a-5p, hsa-mir-148b-3p, and hsa-mir-21-3p), transcription factors (TF) (WRNIP1, FOXC1, GATA2, CREB1, and RELA), a potentially repurposable drug carfilzomib and chemicals (tetrachlorodibenzodioxin, estradiol, arsenic trioxide, and valproic acid) that could regulate the expression levels of hub proteins at both the transcription and posttranscription stages. Our investigations have identified several potential therapeutic targets that elucidate the probability that victims of COVID-19 experience PTSD. However, they require further exploration through clinical and pharmacological studies to explain their efficacy in preventing PTSD in COVID-19 patients.

Circulating microRNAs targeting coagulation and fibrinolysis in patients with severe COVID-19

BACKGROUND

Coronavirus-19 disease (COVID-19) frequently causes coagulation disturbances. Data remains limited on the effects of microRNAs (miRNAs) on coagulation during COVID-19 infection. We aimed to analyze the comprehensive miRNA profile as well as coagulation markers and blood count in hospitalized COVID-19 patients.

METHODS

Citrated plasma samples from 40 patients (24 men and 16 women) hospitalized for COVID-19 were analyzed. Basic coagulation tests, von Willebrand factor (VWF), ADAMTS13, blood count, C-reactive protein, and 27 miRNAs known to associate with thrombosis or platelet activation were analyzed. MiRNAs were analyzed using quantitative reverse transcription polymerase chain reaction (RT qPCR), with 10 healthy controls serving as a comparator.

RESULTS

Among the patients, 15/36 (41%) had platelet count of over 360 × 109/L and 10/36 (28%) had low hemoglobin of < 100 g/L, while 26/37 (72%) had high VWF of over 200 IU/dL. Patients had higher levels of the miRNAs miR-27b-3p, miR-320a-3p, miR-320b-3p, and miR-424-5p, whereas levels of miR-103a-3p and miR-145-5p were lower than those in healthy controls. In total, 11 miRNAs were associated with platelet count. Let-7b-3p was associated with low hemoglobin levels of < 100 g/L. miR-24-3p, miR-27b-3p, miR-126-3p, miR-145-5p and miR-338-5p associated with high VWF.

CONCLUSION

COVID-19 patients differentially express miRNAs with target genes involved in fibrinolysis inhibition, coagulation activity, and increased inflammatory response. These findings support the notion that COVID-19 widely affects hemostasis, including platelets, coagulation and fibrinolysis.

A comprehensive identification of potential molecular targets and small drugs candidate for melanoma cancer using bioinformatics and network-based screening approach

Melanoma is the third most common malignant skin tumor and has increased in morbidity and mortality over the previous decade due to its rapid spread into the bloodstream or lymphatic system. This study used integrated bioinformatics and network-based methodologies to reliably identify molecular targets and small molecular medicines that may be more successful for Melanoma diagnosis, prognosis and treatment. The statistical LIMMA approach utilized for bioinformatics analysis in this study found 246 common differentially expressed genes (cDEGs) between case and control samples from two microarray gene-expression datasets (GSE130244 and GSE15605). Protein-protein interaction network study revealed 15 cDEGs (PTK2, STAT1, PNO1, CXCR4, WASL, FN1, RUNX2, SOCS3, ITGA4, GNG2, CDK6, BRAF, AGO2, GTF2H1 and AR) to be critical in the development of melanoma (KGs). According to regulatory network analysis, the most important transcriptional and post-transcriptional regulators of DEGs and hub-DEGs are ten transcription factors and three miRNAs. We discovered the pathogenetic mechanisms of MC by studying DEGs' biological processes, molecular function, cellular components and KEGG pathways. We used molecular docking and dynamics modeling to select the four most expressed genes responsible for melanoma malignancy to identify therapeutic candidates. Then, utilizing the Connectivity Map (CMap) database, we analyzed the top 4-hub-DEGs-guided repurposable drugs. We validated four melanoma cancer drugs (Fisetin, Epicatechin Gallate, 1237586-97-8 and PF 431396) using molecular dynamics simulation with their target proteins. As a result, the results of this study may provide resources to researchers and medical professionals for the wet-lab validation of MC diagnosis, prognosis and treatments.Communicated by Ramaswamy H. Sarma.

Common molecular and pathophysiological underpinnings of delirium and Alzheimer's disease: molecular signatures and therapeutic indications

BACKGROUND

Delirium and Alzheimer's disease (AD) are common causes of cognitive dysfunction among older adults. These neurodegenerative diseases share a common and complex relationship, and can occur individually or concurrently, increasing the chance of permanent mental dysfunction. However, the common molecular pathophysiology, key proteomic biomarkers, and functional pathways are largely unknown, whereby delirium is superimposed on AD and dementia.

METHODS

We employed an integrated bioinformatics and system biology analysis approach to decipher such common key proteomic signatures, pathophysiological links between delirium and AD by analyzing the gene expression data of AD-affected human brain samples and comparing them with delirium-associated proteins. The present study identified the common drug target hub-proteins examining the protein-protein interaction (PPI) and gene regulatory network analysis. The functional enrichment and pathway analysis was conducted to reveal the common pathophysiological relationship. Finally, the molecular docking and dynamic simulation was used to computationally identify and validate the potential drug target and repurposable drugs for delirium and AD.

RESULTS

We detected 99 shared differentially expressed genes (sDEGs) associated with AD and delirium. The sDEGs-set enrichment analysis detected the transmission across chemical synapses, neurodegeneration pathways, neuroinflammation and glutamatergic signaling pathway, oxidative stress, and BDNF signaling pathway as the most significant signaling pathways shared by delirium and AD. The disease-sDEGs interaction analysis highlighted the other disease risk factors with delirium and AD development and progression. Among the sDEGs of delirium and AD, the top 10 hub-proteins including ALB, APP, BDNF, CREB1, DLG4, GAD1, GAD2, GFAP, GRIN2B and GRIN2A were found by the PPI network analysis. Based on the maximum molecular docking binding affinities and molecular dynamic simulation (100 ns) results, the ALB and GAD2 were found as prominent drug target proteins when tacrine and donepezil were identified as potential drug candidates for delirium and AD.

CONCLUSION

The study outlined the common key biomolecules and biological pathways shared by delirium and AD. The computationally reported potential drug molecules need a deeper investigation including clinical trials to validate their effectiveness. The outcomes from this study will help to understand the typical pathophysiological relationship between delirium and AD and flag future therapeutic development research for delirium.

An ontology-based knowledge graph for representing interactions involving RNA molecules

The "RNA world" represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient's biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the "RNA world" is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the "RNA world". RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

Identification of TIMP1-induced dysregulation of epithelial-mesenchymal transition as a key pathway in inflammatory bowel disease and small intestinal neuroendocrine tumors shared pathogenesis

Inflammatory Bowel Disease (IBD) is believed to be a risk factor for Small Intestinal Neuroendocrine Tumors (SI-NET) development; however, the molecular relationship between IBD and SI-NET has yet to be elucidated. In this study, we use a systems biology approach to uncover such relationships. We identified a more similar transcriptomic-wide expression pattern between Crohn's Disease (CD) and SI-NET whereas a higher proportion of overlapping dysregulated genes between Ulcerative Colitis (UC) and SI-NET. Enrichment analysis indicates that extracellular matrix remodeling, particularly in epithelial-mesenchymal transition and intestinal fibrosis mediated by TIMP1, is the most significantly dysregulated pathway among upregulated genes shared between both IBD subtypes and SI-NET. However, this remodeling occurs through distinct regulatory molecular mechanisms unique to each IBD subtype. Specifically, myofibroblast activation in CD and SI-NET is mediated through IL-6 and ciliary-dependent signaling pathways. Contrarily, in UC and SI-NET, this phenomenon is mainly regulated through immune cells like macrophages and the NCAM signaling pathway, a potential gut-brain axis in the context of these two diseases. In both IBD and SI-NET, intestinal fibrosis resulted in significant metabolic reprogramming of fatty acid and glucose to an inflammatory- and cancer-inducing state. This altered metabolic state, revealed through enrichment analysis of downregulated genes, showed dysfunctions in oxidative phosphorylation, gluconeogenesis, and glycogenesis, indicating a shift towards glycolysis. Also known as the Warburg effect, this glycolytic switch, in return, exacerbates fibrosis. Corresponding to enrichment analysis results, network construction and subsequent topological analysis pinpointed 7 protein complexes, 17 hub genes, 11 microRNA, and 1 transcription factor related to extracellular matrix accumulation and metabolic reprogramming that are candidate biomarkers in both IBD and SI-NET. Together, these biological pathways and candidate biomarkers may serve as potential therapeutic targets for these diseases.

Analysis of lncRNA-miRNA-mRNA interactions identified a novel biomarker LINC00657 to improve prognosis prediction of papillary thyroid carcinoma

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. Identification of novel biomarkers can potentially help explore the underlying molecular mechanisms of PTC. Long non-coding RNAs (lncRNAs) are involved in cancer development. However, understanding the role of lncRNA in PTC remains challenging.

METHODS

Based on the competitive endogenous RNA (ceRNA) theory, we constructed a comprehensive PTC-related lncRNA-miRNA-mRNA network using data from The Cancer Genome Atlas. To evaluate the prognostic power, we performed survival analysis for patients with PTC with low and high lncRNA expression levels, and examined the relationship between lncRNA and immune-related functions.

RESULTS

We identified a hub node, long intergenic non-coding RNA, LINC00657, as a novel prognostic biomarker in PTC. LINC00657 was differentially expressed between tumor and adjacent normal samples. Low LINC00657 expression levels was significantly associated with better survival outcome. Our functional analyses showed that LINC00657 was related with infiltration of CD8+ T cell and macrophage; immune check point molecules; and immune metagenes such as IgG, LCK, MHC_I/II and etc. These results suggest that LINC00657 is an immune-related biomarker with potential clinical applicability. Additionally, cancer-related signaling pathway and high frequency of gene BRAF mutation were found in PTC samples with high LINC00657 expression level, which were consistent with previous findings.

CONCLUSION

LINC00657 is an immune-related biomarker that can potentially improve prognosis prediction in PTC. Our study provided new treatment target of PTC in clinical practice and offered the novel insights in elucidating the functional role of lncRNAs.

Extracellular Vesicle-Encapsulated microRNAs and Respiratory Health Among American Indians in the Strong Heart Study

BACKGROUND

American Indian populations have experienced marked disparities in respiratory disease burden. Extracellular vesicle-encapsulated microRNAs (EV-miRNAs) are a novel class of biomarkers that may improve recognition of lung damage in indigenous populations.

RESEARCH QUESTION

Are plasma EV-miRNAs viable biomarkers of respiratory health in American Indian populations?

STUDY DESIGN AND METHODS

The Strong Heart Study (SHS) is a prospective cohort study that enrolled American Indians aged 45 to 74 years. EV-miRNA expression was measured in plasma (1993-1995). Respiratory health outcomes, including pre-bronchodilator FEV1, FVC, and respiratory symptom burden, were ascertained in the same study visit. Club cell secretory protein (CC-16), an antiinflammatory pneumoprotein implicated in COPD pathogenesis, was measured in serum. Linear and logistic regression were used for statistical analyses. Biological pathway analyses were used to elucidate gene targets of significant EV-miRNAs.

RESULTS

Among 853 American Indian adults, three EV-miRNAs were associated with FEV1, four EV-miRNAs were associated with FVC, and one EV-miRNA was associated with FEV1/FVC (P < .05). Increased miR-1294 expression was associated with higher odds of airflow limitation (OR, 1.29; 95% CI, 1.07-1.55), whereas increased expression of miR-1294 (OR, 1.32; 95% CI, 1.07-1.63) and miR-532-5p (OR, 1.57; 95% CI, 1.02-2.40) was associated with higher odds of restriction. Increased miR-451a expression was associated with lower odds of exertional dyspnea (OR, 0.71; 95% CI, 0.59-0.85). Twenty-two EV-miRNAs were associated with serum CC-16 levels (q < 0.05), suggesting that EV-miRNAs may play a role in the pathway linking CC-16 to COPD pathogenesis. A pathway analysis showed key EV-miRNAs targeted biological pathways that modulate inflammation, immunity, and structural integrity in the lungs.

INTERPRETATION

Circulating EV-miRNAs are novel mechanistic biomarkers of respiratory health and may facilitate the early detection and treatment of lung damage in American Indian populations that have been disproportionately affected by chronic lung diseases.

Early changes in microRNA expression in Arabidopsis plants infected with the fungal pathogen Fusarium graminearum

Plants respond to biotic stressors by modulating various processes in an attempt to limit the attack by a pathogen or herbivore. Triggering these different defense processes requires orchestration of a network of proteins and RNA molecules that includes microRNAs (miRNAs). These short RNA molecules (20-22 nucleotides) have been shown to be important players in the early responses of plants to stresses because they can rapidly regulate the expression levels of a network of downstream genes. The ascomycete Fusarium graminearum is an important fungal pathogen that causes significant losses in cereal crops worldwide. Using the well-characterized Fusarium-Arabidopsis pathosystem, we investigated how plants change expression of their miRNAs globally during the early stages of infection by F. graminearum. In addition to miRNAs that have been previously implicated in stress responses, we have also identified evolutionarily young miRNAs whose levels change significantly in response to fungal infection. Some of these young miRNAs have homologs present in cereals. Thus, manipulating expression of these miRNAs may provide a unique path toward development of plants with increased resistance to fungal pathogens.

Exosomal Preconditioning of Human iPSC-Derived Cardiomyocytes Beneficially Alters Cardiac Electrophysiology and Micro RNA Expression

Experimental evidence, both in vitro and in vivo, has indicated cardioprotective effects of extracellular vesicles (EVs) derived from various cell types, including induced pluripotent stem cell-derived cardiomyocytes. The biological effects of EV secretion, particularly in the context of ischemia and cardiac electrophysiology, remain to be fully explored. Therefore, the goal of this study was to unveil the effects of exosome (EXO)-mediated cell-cell signaling during hypoxia by employing a simulated preconditioning approach on human-induced pluripotent stem cell-derived cardiomyocytes (hIPSC-CMs). Electrophysiological activity of hIPSC-CMs was measured using a multielectrode array (MEA) system. A total of 16 h of hypoxic stress drastically increased the beat period. Moreover, hIPSC-CMs preconditioned with EXOs displayed significantly longer beat periods compared with non-treated cells after 16 h of hypoxia (+15.7%, p < 0.05). Furthermore, preconditioning with hypoxic EXOs resulted in faster excitation-contraction (EC) coupling compared with non-treated hIPSC-CMs after 16 h of hypoxia (-25.3%, p < 0.05). Additionally, microRNA (miR) sequencing and gene target prediction analysis of the non-treated and pre-conditioned hIPSC-CMs identified 10 differentially regulated miRs and 44 gene targets. These results shed light on the intricate involvement of miRs, emphasizing gene targets associated with cell survival, contraction, apoptosis, reactive oxygen species (ROS) regulation, and ion channel modulation. Overall, this study demonstrates that EXOs secreted by hIPSC-CM during hypoxia beneficially alter electrophysiological properties in recipient cells exposed to hypoxic stress, which could play a crucial role in the development of targeted interventions to improve outcomes in ischemic heart conditions.

Identification and Validation of CXCL2 as a Key Gene for Childhood Obesity

This study aims to identify the key genes and their regulatory networks by bioinformatics, increasing understanding of childhood obesity. The data comes from the GEO and Immport database. The immune microenvironment was explored in GSE104815. Key genes were identified by intersection of DEGs with the immune gene set. Enrichment analysis revealed gene-related functions and correlation analysis explored the relationship. Regulatory networks were constructed based on miRcode, TarBase and TargetScan databases. GSE29718 was used to validate our findings. Intercellular communication and cell differentiation trends were further explored using single-cell data from GSE153643. Based on our research, the immune microenvironment in the obese group showed higher immune infiltration. We found 962 DEGs and CXCL2 was identified as the key gene. The co-regulatory network of lncRNA-miRNA-mRNA suggested that obtaining TM4SF19-AS1, GUSBP11, AC105020.1, LINC00189, COL4A2-AS2, VIPR1-AS1 and LINC00242 may regulate CXCL2 (r > 0.9 and P < 0.01). Differential expression of CXCL2 was validated in GSE29718 (P < 0.05) and CXCL2 was identified as a biomarker for childhood obesity (AUC = 0.885). GSVA enrichment analysis revealed many pathways of high group obtaining the TNF-α signaling via NF-κB pathway and interferon γ response pathway. In GSE153643, 11 cell types were identified and CXCL2 was highly expressed in monocyte, macrophage, endothelial cell and pericyte. In CXCL2 high expressing macrophages, there was a tendency for cells to polarize toward M1 macrophages (P < 0.05). In summary, we identified CXCL2 as a potential biomarker of childhood obesity. The development of childhood obesity may be associated with the activation of immune infiltration of macrophage M1 polarization by CXCL2 expression.

MiR-26a and miR-191 are upregulated while PLAG1 and HIF2 are downregulated in pleomorphic adenomas of the salivary glands compared to Warthin tumors

BACKGROUND

Salivary gland tumors (SGTs) are a heterogenous group of pathologies, which still represents a challenge regarding differential diagnosis and therapy. Although histological findings govern SGTs management, detection of molecular alterations is emerging as an effective additional tool. The aim of this study was to analyze the relative expression levels of three micro RNAs (miR-26a, miR-26b, and miR-191), and three pro-oncogenic molecular markers (PLAG1, MTDH, and HIF2) in SGTs and normal salivary gland (NSG) tissues and evaluate them as potential differential diagnosis markers.

METHODS

This cross-sectional study included 58 patients with SGTs (23 pleomorphic adenomas, 27 Warthin tumors, and 8 malignant SGTs) and 10 controls (normal salivary gland tissues). Relative gene expression levels of all investigated molecules were determined by reverse transcriptase-real-time polymerase chain reaction.

RESULTS

All three micro RNAs exhibited highest expression levels in benign SGTs, whereas miR-26a And miR-191 were significantly more expressed in PAs compared to WTs (p = 0.045 and p = 0.029, respectively). PLAG1 And HIF2 were both overexpressed in WTs compared to PAs (p = 0.048 and p = 0.053, respectively). Bioinformatic analysis suggested that all investigated micro RNAs function as negative regulators of MTDH.

CONCLUSION

The results of this study suggest that all three micro RNAs have a considerable negative impact on MTDH oncogene expression in malignant tumors, while the differences between levels of miR-26a, miR-191, PLAG1, and HIF2 in PA and WT represent possible differential diagnosis markers.

Key Genes in Olfactory Disorder in Experimental Autoimmune Encephalomyelitis Identified by Transcriptomic Analysis of the Olfactory Bulbs

Experimental autoimmune encephalomyelitis (EAE) is an animal model of multiple sclerosis that shows demyelination in the central nervous system and functional deficits, including olfactory impairment. However, the genes related to olfactory impairment in EAE are unknown. We evaluated hub genes of the olfactory bulb in EAE mice. Differentially expressed genes (cut-offs, fold change > 2 and adjusted p < 0.05) and their related pathways in olfactory bulbs were subjected to gene ontology (GO) pathway analysis, gene set enrichment analysis (GSEA). Protein-protein interactions with selected genes were evaluated using the Search Tool for the Retrieval of Interacting Genes/Proteins. Gene regulatory networks (GRNs) which were constructed at the post-transcriptional level, including the genes-transcription factors (TFs) and gene-microRNAs (miRNAs) interaction networks. Twelve hub genes were found, three of which (Ctss, Itgb2, and Tlr2) were validated by RT-qPCR to be related to GO pathways such as immune response and regulation of immune response. GSEA showed that neuron-related genes-including Atp6v1g2, Egr1, and Gap43-and their pathways were significantly downregulated. GRNs analysis of six genes (Ctss, Itgb2, Tlr2, Atp6v1g2, Egr1, and Gap43) revealed 37 TFs and 84 miRNAs were identified as potential regulators of six genes, indicating significant interaction among six genes, TFs, and miRNAs. Collectively, these results suggest that transcriptomic analysis of the olfactory bulb of EAE mice can provide insight into olfactory dysfunction and reveal therapeutic targets for olfactory impairment.

Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Computational approaches that predict miRNA target interactions (MTIs) facilitate the process of narrowing down potential targets for experimental validation. The availability of new datasets of high-throughput, direct MTIs has led to the development of machine learning (ML) based methods for MTI prediction. To train an ML algorithm, it is beneficial to provide entries from all class labels (i.e., positive and negative). Currently, no high-throughput assays exist for capturing negative examples. Therefore, current ML approaches must rely on either artificially generated or inferred negative examples deduced from experimentally identified positive miRNA-target datasets. Moreover, the lack of uniform standards for generating such data leads to biased results and hampers comparisons between studies. In this comprehensive study, we collected methods for generating negative data for animal miRNA-target interactions and investigated their impact on the classification of true human MTIs. Our study relies on training ML models on a fixed positive dataset in combination with different negative datasets and evaluating their intra- and cross-dataset performance. As a result, we were able to examine each method independently and evaluate ML models' sensitivity to the methodologies utilized in negative data generation. To achieve a deep understanding of the performance results, we analyzed unique features that distinguish between datasets. In addition, we examined whether one-class classification models that utilize solely positive interactions for training are suitable for the task of MTI classification. We demonstrate the importance of negative data in MTI classification, analyze specific methodological characteristics that differentiate negative datasets, and highlight the challenge of ML models generalizing interaction rules from training to testing sets derived from different approaches. This study provides valuable insights into the computational prediction of MTIs that can be further used to establish standards in the field.

Liver microRNA transcriptome reveals miR-182 as link between type 2 diabetes and fatty liver disease in obesity

Background

The development of obesity-associated comorbidities such as type 2 diabetes (T2D) and hepatic steatosis has been linked to selected microRNAs in individual studies; however, an unbiased genome-wide approach to map T2D induced changes in the miRNAs landscape in human liver samples, and a subsequent robust identification and validation of target genes are still missing.

Methods

Liver biopsies from age- and gender-matched obese individuals with (n=20) or without (n=20) T2D were used for microRNA microarray analysis. The candidate microRNA and target genes were validated in 85 human liver samples, and subsequently mechanistically characterized in hepatic cells as well as by dietary interventions and hepatic overexpression in mice.

Results

Here, we present the human hepatic microRNA transcriptome of type 2 diabetes in liver biopsies and use a novel seed prediction tool to robustly identify microRNA target genes, which were then validated in a unique cohort of 85 human livers. Subsequent mouse studies identified a distinct signature of T2D-associated miRNAs, partly conserved in both species. Of those, human-murine miR-182-5 p was the most associated with whole-body glucose homeostasis and hepatic lipid metabolism. Its target gene LRP6 was consistently lower expressed in livers of obese T2D humans and mice as well as under conditions of miR-182-5 p overexpression. Weight loss in obese mice decreased hepatic miR-182-5 p and restored Lrp6 expression and other miR-182-5 p target genes. Hepatic overexpression of miR-182-5 p in mice rapidly decreased LRP6 protein levels and increased liver triglycerides and fasting insulin under obesogenic conditions after only seven days.

Conclusions

By mapping the hepatic miRNA-transcriptome of type 2 diabetic obese subjects, validating conserved miRNAs in diet-induced mice, and establishing a novel miRNA prediction tool, we provide a robust and unique resource that will pave the way for future studies in the field. As proof of concept, we revealed that the repression of LRP6 by miR-182-5 p, which promotes lipogenesis and impairs glucose homeostasis, provides a novel mechanistic link between T2D and non-alcoholic fatty liver disease, and demonstrate in vivo that miR-182-5 p can serve as a future drug target for the treatment of obesity-driven hepatic steatosis.

Funding

This work was supported by research funding from the Deutsche Forschungsgemeinschaft (KI 1887/2-1, KI 1887/2-2, KI 1887/3-1 and CRC-TR296), the European Research Council (ERC, CoG Yoyo LepReSens no. 101002247; PTP), the Helmholtz Association (Initiative and Networking Fund International Helmholtz Research School for Diabetes; MB) and the German Center for Diabetes Research (DZD Next Grant 82DZD09D1G).

An integrative miRNA-mRNA expression analysis identifies miRNA signatures associated with SOD1 and TARDBP patient-derived motor neurons

MicroRNAs (miRNAs) are a subset of small non-coding single-stranded RNA molecules involved in the regulation of post-transcriptional gene expression of a variety of transcript targets. Therefore altered miRNA expression may result in the dysregulation of key genes and biological pathways that has been reported with the onset and progression of neurodegenerative diseases, such as Amyotrophic lateral sclerosis (ALS). ALS is marked by a progressive degeneration of motor neurons (MNs) present in the spinal cord, brain stem and motor cortex. Although the pathomechanism underlying molecular interactions of ALS remains poorly understood, alterations in RNA metabolism, including dysregulation of miRNA expression in familial as well as sporadic forms are still scarcely studied. In this study, we performed combined transcriptomic data and miRNA profiling in MN samples of the same samples of iPSC-derived MNs from SOD1- and TARDBP (TDP-43 protein)-mutant-ALS patients and healthy controls. We report a global upregulation of mature miRNAs, and suggest that differentially expressed (DE) miRNAs have a significant impact on mRNA-level in SOD1-, but not in TARDBP-linked ALS. Furthermore, in SOD1-ALS we identified dysregulated miRNAs such as miR-124-3p, miR-19b-3p and miR-218 and their potential targets previously implicated in important functional process and pathogenic pathways underlying ALS. These miRNAs may play key roles in the neuronal development and cell survival related functions in SOD1-ALS. Altogether, we provide evidence of miRNA regulated genes expression mainly in SOD1 rather than TDP43-ALS.

miR-122-3p targets UBE2I to regulate the immunosuppression of liver cancer and the intervention of Liujunzi formula

ETHNOPHARMACOLOGICAL RELEVANCE

Liujunzi formula has been used to treat liver cancer in China for many years, but its underlying mechanism remains unclear. We previously found that decreased expression of miR-122-3p was associated with liver cancer. In this study, we aimed to explore the target of miR-122-3p and the effect of the Liujunzi formula on miR-122-3p and its downstream events in liver cancer.

MATERIAL AND METHODS

Bioinformatics pinpointed potential targets of miR-122-3p. The actual target was confirmed by miRNA mimic/inhibitor transfections and a dual-luciferase reporter assay. RNA-seq looked at downstream genes impacted by this target. Flow cytometry checked for changes in T cell apoptosis levels after exposing them to liver cancer cells. Gene expression was measured by RT-qPCR, western blotting, and immunofluorescence staining.

RESULTS

Cell experiments found the Liujunzi extract (LJZ) upregulated miR-122-3p and in a dose-dependent manner. Bioinformatics analysis found UBE2I was a potential target of miR-122-3p, which was validated through experiments using miRNA mimics/inhibitors and a dual-luciferase reporter assay. RNA-seq data implicated the NF-κB pathway as being downstream of the miR-122-3p/UBE2I axis, further confirmed by forcing overexpression of UBE2I. Bioinformatic evidence suggested a link between UBE2I and T cell infiltration in liver cancer. Given that the NF-κB pathway drives PD-L1 expression, which can inhibit T cell infiltration, we investigated whether PD-L1 is a downstream effector of miR-122-3p/UBE2I. This was corroborated through mining public databases, UBE2I overexpression studies, and tumor-T cell co-culture assays. In addition, we also confirmed that LJZ downregulates UBE2I and NF-κB/PD-L1 pathways through miR-122-3p. LJZ also suppressed SUMOylation in liver cancer cells and protected PD-1+ T cells from apoptosis induced by co-culture with tumor cells. Strikingly, a miR-122-3p inhibitor abrogated LJZ's effects on UBE2I and PD-L1, and UBE2I overexpression rescued the LJZ-mediated effects on NF-κB and PD-L1.

CONCLUSIONS

miR-122-3p targets UBE2I, thereby suppressing the NF-κB signaling cascade and downregulating PD-L1 expression, which potentiates anti-tumor immune responses. LJZ bolsters anti-tumor immunity by modulating the miR-122-3p/UBE2I/NF-κB/PD-L1 axis in liver cancer cells.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

Integrative network analysis of miRNA-mRNA expression profiles during epileptogenesis in rats reveals therapeutic targets after emergence of first spontaneous seizure

Epileptogenesis is the process by which a normal brain becomes hyperexcitable and capable of generating spontaneous recurrent seizures. The extensive dysregulation of gene expression associated with epileptogenesis is shaped, in part, by microRNAs (miRNAs) - short, non-coding RNAs that negatively regulate protein levels. Functional miRNA-mediated regulation can, however, be difficult to elucidate due to the complexity of miRNA-mRNA interactions. Here, we integrated miRNA and mRNA expression profiles sampled over multiple time-points during and after epileptogenesis in rats, and applied bi-clustering and Bayesian modelling to construct temporal miRNA-mRNA-mRNA interaction networks. Network analysis and enrichment of network inference with sequence- and human disease-specific information identified key regulatory miRNAs with the strongest influence on the mRNA landscape, and miRNA-mRNA interactions closely associated with epileptogenesis and subsequent epilepsy. Our findings underscore the complexity of miRNA-mRNA regulation, can be used to prioritise miRNA targets in specific systems, and offer insights into key regulatory processes in epileptogenesis with therapeutic potential for further investigation.

Specific circulating miRNAs are associated with plasma lipids in a healthy American cohort

Low-density lipoprotein cholesterol (LDL-c) is both a therapeutic target and a risk factor for cardiovascular disease (CVD). MicroRNA (miRNA) has been shown to regulate cholesterol homeostasis, and miRNA in blood circulation has been linked to hypercholesterolemia. However, few studies to date have associated miRNA with phenotypes like LDL-c in a healthy population. To this end, we analyzed circulating miRNA in relation to LDL-c in a healthy cohort of 353 participants using two separate bioinformatic approaches. The first approach found that miR-15b-5p and miR-16-5p were upregulated in individuals with at-risk levels of LDL-c. The second approach identified two miRNA clusters, one that positively and a second that negatively correlated with LDL-c. Included in the cluster that positively correlated with LDL-c were miR-15b-5p and miR-16-5p, as well as other miRNA from the miR-15/107, miR-30, and let-7 families. Cross-species analyses suggested that several miRNAs that associated with LDL-c are conserved between mice and humans. Finally, we examined the influence of diet on circulating miRNA. Our results robustly linked circulating miRNA with LDL-c, suggesting that miRNA could be used as biomarkers for hypercholesterolemia or targets for developing cholesterol-lowering drugs.NEW & NOTEWORTHY This study explored the association between circulating microRNA (miRNA) and low-density lipoprotein cholesterol (LDL-c) in a healthy population of 353 participants. Two miRNAs, miR-15b-5p and miR-16-5p, were upregulated in individuals with at-risk LDL-c levels. Several miRNA clusters were positively and negatively correlated with LDL-c and are known to target mRNA involved in lipid metabolism. The study also investigated the influence of diet on circulating miRNA, suggesting potential biomarkers for hypercholesterolemia.

Profiling several key milk miRNAs and analysing their signalling pathways in dairy sheep breeds during peak and late lactation

BACKGROUND

The comprehensive understanding of microRNAs (miRNAs) in sheep milk during various lactation periods and their impact on milk yield and composition remains limited.

OBJECTIVES

This study aimed to investigate the expression patterns of four highly expressed miRNAs in sheep milk and their association with milk composition and yield parameters during peak and late lactation stages.

METHODS

A total of 40 healthy 4-year-old Akkaraman (n = 20) and Awassi (n = 20) ewes registered with the Ministry of Agriculture and Forestry of the Republic of Türkiye were used in the present study. For miRNA isolation from milk, the Qiagen miRNeasy Serum/Plasma Advanced Kit was utilised following the manufacturer's instructions. The expression levels of miRNAs were assessed using Qiagen miRNA PCR Assays.

RESULTS

The significant fold changes in the expression levels of oar-miR-30a-5p, oar-miR-148a and oar-miR-181a were observed between peak and late lactation periods in the Awassi sheep breed. Conversely, only oar-miR-30a-5p and oar-miR-148a exhibited statistically significant changes in the Akkaraman sheep breed during the same lactation periods. Furthermore, oar-miR-21-5p demonstrated a significant fold change exclusively in peak lactation compared to Akkaraman and Awassi ewes.

CONCLUSIONS

The findings suggest that the expression of the analysed miRNAs is influenced by both the lactation stage and different sheep breeds. This study offers valuable insights into the relationship between key miRNA expressions in sheep milk and milk composition and yield parameters during peak and late lactation, contributing to the existing knowledge in this field.

Identification of mitophagy-related hub genes during the progression of spinal cord injury by integrated multinomial bioinformatics analysis

Spinal cord injury (SCI) is a disturbance of peripheral and central nerve conduction that causes disability in sensory and motor function. Currently, there is no effective treatment for SCI. Mitophagy plays a vital role in mitochondrial quality control during various physiological and pathological processes. The study aimed to elucidate the role of mitophagy and identify potential mitophagy-related hub genes in SCI pathophysiology. Two datasets (GSE15878 and GSE138637) were analyzed. Firstly, the differentially expressed genes (DEGs) were identified and mitophagy-related genes were obtained from GeneCards, then the intersection between SCI and mitophagy-related genes was determined. Next, we performed gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein-protein interaction network (PPI network), least absolute shrinkage and selection operator (LASSO), and cluster analysis to identify and define the hub genes in SCI. Finally, the link between hub genes and infiltrating immune cells was investigated and the potential transcriptional regulation/small molecular compounds to target hub genes were predicted. In total, SKP1 and BAP1 were identified as hub genes of mitophagy-related DEGs during SCI development and regulatory T cells (Tregs)/resting NK cells/activated mast cells may play an essential role in the progression of SCI. LINC00324 and SNHG16 may regulate SKP1 and BAP1, respectively, through miRNAs. Eleven and eight transcriptional factors (TFs) regulate SKP1 and BAP1, respectively, and six small molecular compounds target BAP1. Then, the mRNA expression levels of BAP1 and SKP1 were detected in the injured sites of spinal cord of SD rats at 6 h and 72 h after injury using RT-qPCR, and found that the level were decreased. Therefore, the pathways of mitophagy are downregulated during the pathophysiology of SCI, and SKP1 and BAP1 could be accessible targets for diagnosing and treating SCI.

Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma

Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two diseases. To this end, we examined microarray datasets from GEO (Gene Expression Omnibus) to identify differentially expressed genes, common genes, and hub genes between the selected two diseases. Our analyses identified potential therapeutic molecules for the selected diseases based on 10 hub genes with the highest interactions according to the degree topology method and the maximum clique centrality (MCC). These therapeutic molecules may have the potential for simultaneous treatment of these diseases.

Kernel Bayesian logistic tensor decomposition with automatic rank determination for predicting multiple types of miRNA-disease associations

Identifying the association and corresponding types of miRNAs and diseases is crucial for studying the molecular mechanisms of disease-related miRNAs. Compared to traditional biological experiments, computational models can not only save time and reduce costs, but also discover potential associations on a large scale. Although some computational models based on tensor decomposition have been proposed, these models usually require manual specification of numerous hyperparameters, leading to a decrease in computational efficiency and generalization ability. Additionally, these linear models struggle to analyze complex, higher-order nonlinear relationships. Based on this, we propose a novel framework, KBLTDARD, to identify potential multiple types of miRNA-disease associations. Firstly, KBLTDARD extracts information from biological networks and high-order association network, and then fuses them to obtain more precise similarities of miRNAs (diseases). Secondly, we combine logistic tensor decomposition and Bayesian methods to achieve automatic hyperparameter search by introducing sparse-induced priors of multiple latent variables, and incorporate auxiliary information to improve prediction capabilities. Finally, an efficient deterministic Bayesian inference algorithm is developed to ensure computational efficiency. Experimental results on two benchmark datasets show that KBLTDARD has better Top-1 precision, Top-1 recall, and Top-1 F1 for new type predictions, and higher AUPR, AUC, and F1 values for new triplet predictions, compared to other state-of-the-art methods. Furthermore, case studies demonstrate the efficiency of KBLTDARD in predicting multiple types of miRNA-disease associations.

Gene and protein sequence features augment HLA class I ligand predictions

The sensitivity of malignant tissues to T cell-based immunotherapies depends on the presence of targetable human leukocyte antigen (HLA) class I ligands. Peptide-intrinsic factors, such as HLA class I affinity and proteasomal processing, have been established as determinants of HLA ligand presentation. However, the role of gene and protein sequence features as determinants of epitope presentation has not been systematically evaluated. We perform HLA ligandome mass spectrometry to evaluate the contribution of 7,135 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turnover, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of such "hard-coded" sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as experimental measures of gene expression. Our study highlights the value of gene and protein features for HLA ligand predictions.

Knockout of the longevity gene Klotho perturbs aging and Alzheimer's disease-linked brain microRNAs and tRNA fragments

Overexpression of the longevity gene Klotho prolongs lifespan, while its knockout shortens lifespan and impairs cognition via perturbation of myelination and synapse formation. However, comprehensive analysis of Klotho knockout effects on mammalian brain transcriptomics is lacking. Here, we report that Klotho knockout alters the levels of aging- and cognition related mRNAs, long non-coding RNAs, microRNAs and tRNA fragments. These include altered neuronal and glial regulators in murine models of aging and Alzheimer's disease and in human Alzheimer's disease post-mortem brains. We further demonstrate interaction of the knockout-elevated tRNA fragments with the spliceosome, possibly affecting RNA processing. Last, we present cell type-specific short RNA-seq datasets from FACS-sorted neurons and microglia of live human brain tissue demonstrating in-depth cell-type association of Klotho knockout-perturbed microRNAs. Together, our findings reveal multiple RNA transcripts in both neurons and glia from murine and human brain that are perturbed in Klotho deficiency and are aging- and neurodegeneration-related.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

The DNA-repair protein APE1 participates with hnRNPA2B1 to motif-enriched and prognostic miRNA secretion

The base excision repair (BER) Apurinic/apyrimidinic endonuclease 1 (APE1) enzyme is endowed with several non-repair activities including miRNAs processing. APE1 is overexpressed in many cancers but its causal role in the tumorigenic processes is largely unknown. We recently described that APE1 can be actively secreted by mammalian cells through exosomes. However, APE1 role in EVs or exosomes is still unknown, especially regarding a putative regulatory function on vesicular small non-coding RNAs. Through dedicated transcriptomic analysis on cellular and vesicular small RNAs of different APE1-depleted cancer cell lines, we found that miRNAs loading into EVs is a regulated process, dependent on APE1, distinctly conveying RNA subsets into vesicles. We identified APE1-dependent secreted miRNAs characterized by enriched sequence motifs and possible binding sites for APE1. In 33 out of 34 APE1-dependent-miRNA precursors, we surprisingly found EXO-motifs and proved that APE1 cooperates with hnRNPA2B1 for the EV-sorting of a subset of miRNAs, including miR-1246, through direct binding to GGAG stretches. Using TCGA-datasets, we showed that these miRNAs identify a signature with high prognostic significance in cancer. In summary, we provided evidence that the ubiquitous DNA-repair enzyme APE1 is part of the EV protein cargo with a novel post-transcriptional role for this ubiquitous DNA-repair enzyme that could explain its role in cancer progression. These findings could open new translational perspectives in cancer biology.

In silico identification and in vitro evaluation of MRPS30-DT lncRNA and MRPS30 gene expression in breast cancer

BACKGROUND

It has been reported that long non-coding RNAs (lncRNAs) can play important roles in a variety of biological processes and cancer regulatory networks, including breast cancer.

AIMS

This study aimed to identify a novel upregulated lncRNA in breast cancer and its associated gene using bioinformatics analysis, and then evaluate their potential roles in breast cancer.

METHODS AND RESULTS

Extensive in silico studies were performed using various bioinformatics databases and tools to identify a potential upregulated breast cancer-associated lncRNA and its co-expressed gene, and to predict their potential roles, functions, and interactions. The expression level of MRPS30-DT lncRNA and MRPS30 was assessed in both BC tissues and cell lines using qRT-PCR technology. MRPS30-DT lncRNA and MRPS30 were selected as target genes using bioinformatics analysis. We found that MRPS30-DT and MRPS30 were significantly overexpressed in BC tissues compared with normal tissues. Also, MRPS30 showed upregulation in all three BC cell lines compared with HDF. On the other hand, MRPS30-DT significantly increased in MDA-MB-231 compared with HDF. While the expression of MRPS30-DT was significantly dropped in the resistance cell line MCF/MX compared to HDF and MCF7. Moreover, bioinformatics analysis suggested that MRPS30-DT and MRPS30 may play a potential role in BC through their involvement in some cancer signaling pathways and processes, as well as through their interaction with TFs, genes, miRNAs, and proteins related to carcinogenesis.

CONCLUSIONS

Overall, our findings showed the dysregulation of MRPS30-DT lncRNA and MRPS30 may provide clues for exploring new therapeutic targets or molecular biomarkers in BC.

Etiologically Significant microRNAs in Hepatitis B Virus-Induced Hepatocellular Carcinoma

Hepatitis B virus (HBV) infection has been causally linked to hepatocellular carcinoma (HCC) in more than 50% cases. MicroRNAs (miRNAs) play cross-cutting mechanistic roles in the complex interplay between viral pathogenesis, host survival, and clinical outcomes. The present study set out to identify etiologically significant human miRNAs associated with HBV infection in liver-related pathologies leading to HCC. In diverse tissue types, we assembled 573 miRNAs differentially expressed in HBV-associated liver pathologies, HBV infection, fibrosis, cirrhosis, acute on chronic liver failure, and HCC. Importantly, 43 human differentially expressed miRNAs (hDEmiRs) were regulated in serum/plasma and liver tissue of patients with HBV-positive conditions. However, only two hDEmiRs, hsa-miR-21-5p and hsa-miR-143-3p, were regulated across all disease conditions. To shortlist the functional miRNAs in HBV-induced HCC pathogenesis, a reverse bioinformatics analysis was performed using eight GEO datasets and the TCGA database containing the list of differentially regulated mRNAs in HCC. A comparative study using these data with the identified targets of hDEmiRs, a set of unidirectionally regulated hDEmiRs with the potential to modulate mRNAs in HCC, were found. Moreover, our study identified five miRNAs; hsa-miR-98-5p, hsa-miR-193b-3p, hsa-miR-142-5p, hsa-miR-522-5p, and hsa-miR-370-3p targeting PIGC, KNTC1, CSTF2, SLC41A2, and RAB17, respectively, in HCC. These hDEmiRs and their targets could be pivotal in HBV infection and subsequent liver pathologies modulating HCC clinical progression. HBV infection is the largest contributor to HCC, and the present study comprises the first of its kind compendium of hDEmiRs related to HBV-related pathologies.

Hsa_circ_0001402 alleviates vascular neointimal hyperplasia through a miR-183-5p-dependent regulation of vascular smooth muscle cell proliferation, migration, and autophagy

INTRODUCTION

Vascular neointimal hyperplasia, a pathological process observed in cardiovascular diseases such as atherosclerosis and pulmonary hypertension, involves the abundant presence of vascular smooth muscle cells (VSMCs). The proliferation, migration, and autophagy of VSMCs are associated with the development of neointimal lesions. Circular RNAs (circRNAs) play critical roles in regulating VSMC proliferation and migration, thereby participating in neointimal hyperplasia. However, the regulatory roles of circRNAs in VSMC autophagy remain unclear.

OBJECTIVES

We aimed to identify circRNAs that are involved in VSMC autophagy-mediated neointimal hyperplasia, as well as elucidate the underlying mechanisms.

METHODS

Dual-luciferase reporter gene assay was performed to validate two competing endogenous RNA axes, hsa_circ_0001402/miR-183-5p/FKBP prolyl isomerase like (FKBPL) and hsa_circ_0001402/miR-183-5p/beclin 1 (BECN1). Cell proliferation and migration analyses were employed to investigate the effects of hsa_circ_0001402, miR-183-5p, or FKBPL on VSMC proliferation and migration. Cell autophagy analysis was conducted to reveal the role of hsa_circ_0001402 or miR-183-5p on VSMC autophagy. The role of hsa_circ_0001402 or miR-183-5p on neointimal hyperplasia was evaluated using a mouse model of common carotid artery ligation.

RESULTS

Hsa_circ_0001402 acted as a sponge for miR-183-5p, leading to the suppression of miR-183-5p expression. Through direct interaction with the coding sequence (CDS) of FKBPL, miR-183-5p promoted VSMC proliferation and migration by decreasing FKBPL levels. Besides, miR-183-5p reduced BECN1 levels by targeting the 3'-untranslated region (UTR) of BECN1, thus inhibiting VSMC autophagy. By acting as a miR-183-5p sponge, overexpression of hsa_circ_0001402 increased FKBPL levels to inhibit VSMC proliferation and migration, while simultaneously elevating BECN1 levels to activate VSMC autophagy, thereby alleviating neointimal hyperplasia.

CONCLUSION

Hsa_circ_0001402, acting as a miR-183-5p sponge, increases FKBPL levels to inhibit VSMC proliferation and migration, while enhancing BECN1 levels to activate VSMC autophagy, thus alleviating neointimal hyperplasia. The hsa_circ_0001402/miR-183-5p/FKBPL axis and hsa_circ_0001402/miR-183-5p/BECN1 axis may offer potential therapeutic targets for neointimal hyperplasia.

Psychosocial Stress and MicroRNA Expression Profiles in Myometrial Tissue of Women Undergoing Surgical Treatment for Uterine Fibroids

Uterine leiomyomas (fibroids) are the most common non-cancerous tumors affecting women. Psychosocial stress is associated with fibroid risk and severity. The relationship between psychosocial stress and fibroid pathogenesis may involve alterations in microRNAs (miRNAs) although this has yet to be examined. We investigated associations between two psychosocial stress measures, a composite measure of recent stressful life events and perceived social status, with expression levels of 401 miRNAs in myometrium (n = 20) and fibroids (n = 44; 20 with paired fibroid and myometrium samples) among pre-menopausal women who underwent surgery for fibroid treatment. We used linear regressions to identify psychosocial stressors associated with miRNAs, adjusting for covariates (age, body mass index, race/ethnicity, and oral contraceptive use). The association between psychosocial stressors and miRNAs was considered statistically significant at an FDR p < 0.10 and showed a monotonic response (nominal p-trend < 0.05). In the myometrium, 21 miRNAs were significantly associated with a composite measure of recent stressful events, and two miRNAs were associated with perceived social status. No fibroid miRNAs were associated with either stress measure. Pathway analyses revealed miRNA-mRNA targets were significantly enriched (FDR p < 0.05) in pathways relevant to cancer/tumor development. Of the 74 differentially expressed miRNAs between myometrium and fibroids, miR-27a-5p and miR-301b were also associated with stress exposure. Our pilot analysis suggests that psychosocial stress is associated with myometrial miRNA expression and, thus, may have a role in the pathogenesis of fibroids from healthy myometrium.

A comprehensive analysis of LINC00958 as a prognostic biomarker for head and neck squamous cell carcinoma

This work focused on exploring whether the long intergenic non-protein coding RNA LINC00958 is associated with the prognosis of head and neck squamous cell carcinoma (HNSCC). Associations of the LINC00958 expression level with clinicopathological features of HNSCC were investigated by logistic regression and Wilcoxon signed-rank test. The Kaplan-Meier method was applied to evaluate patient survival. Clinical data and expression profiles were obtained from The Cancer Genome Atlas (TCGA). Associations of patient clinical characteristics with overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) were assessed by univariate and multivariate analysis using the Cox proportional hazard model. Immune cell infiltration analysis and gene set enrichment analysis (GSEA) were applied to determine any significant effects of LINC00958. High LINC00958 expression was related to early pT stage (P < 0.01), primary therapy outcome (P < 0.01), HPV status (P < 0.001), lymphovascular invasion (P < 0.001), and perineural invasion (P < 0.01). The receiver operating characteristic curve showed strong prognostic power for LINC00958 (area under curve = 0.886). High LINC00958 expression predicted poor OS (P = 0.007), DSS (P = 0.036), and PFI (P = 0.040). LINC00958 was related to signalling pathways and the infiltration of certain immune cells. miR-27b-5p was significantly associated with LINC00958, and downstream NT5E predicted poor survival in HNSCC cases. LINC00958 may affect the prognosis by regulating NT5E via miR-27b-5p, and could serve as a possible factor to predict the prognosis of HNSCC, especially oral squamous cell carcinoma.

Exploring the microRNA-mRNA regulatory network associated with solasonine in bladder cancer

Background

Solasonine has been demonstrated to exert an inhibitory effect on bladder cancer (BC), but the potential mechanisms remain unclear. Therefore, the aim of this study is to explore the association between microRNAs (miRNAs)-mediated regulation and the anti-tumor activities of solasonine in BC.

Methods

MiRNA sequencing was performed to identify the differentially expressed microRNAs (DE-miRNAs) associated with solasonine in BC cells. Functional enrichment analyses of the DE-miRNAs activated and inhibited by solasonine were then conducted. The DE-miRNAs with prognostic value for BC and those differentially expressed in the BC samples were subsequently identified as the hub DE-miRNAs. After identifying the messenger RNAs (mRNAs) that were targeted by the hub DE-miRNAs and those differentially expressed in the BC samples, a protein-protein interaction analysis was performed to identify the core downstream genes, which were then used to construct a solasonine-miRNA-mRNA regulatory network.

Results

A total of 27 activated and 19 inhibited solasonine-mediated DE-miRNAs were identified that were found to be associated with several tumor-related biological functions and pathways. After integrating the results of the survival analysis and expression assessment, the following nine hub DE-miRNAs were identified: hsa-miR-127-3p, hsa-miR-450b-5p, hsa-miR-99a-5p, hsa-miR-197-3p, hsa-miR-423-3p, hsa-miR-4326, hsa-miR-625-3p, hsa-miR-625-5p, and hsa-miR-92a-3p. The DE-mRNAs targeted by the hub DE-miRNAs were predicted, and 30 core downstream genes were used to construct the solasonine-miRNA-mRNA regulatory network. miR-450b-5p was shown to be associated with the most mRNAs in this network, which suggests that it plays a crucial role in the solasonine-mediated anti-BC effect.

Conclusions

A regulatory network, including solasonine, miRNAs, and mRNAs related to BC, was constructed. This network provides extensive insights into the molecular regulatory mechanisms that underlie the anti-cancer efficacy of solasonine in BC.

The epithelial adherens junction component PLEKHA7 regulates ECM remodeling and cell behavior through miRNA-mediated regulation of MMP1 and LOX

Epithelial adherens junctions (AJs) are cell-cell adhesion complexes that are influenced by tissue mechanics, such as those emanating from the extracellular matrix (ECM). Here, we introduce a mechanism whereby epithelial AJs can also regulate the ECM. We show that the AJ component PLEKHA7 regulates levels and activity of the key ECM remodeling components MMP1 and LOX in well-differentiated colon epithelial cells, through the miR-24 and miR-30c miRNAs. PLEKHA7 depletion in epithelial cells results in LOX-dependent ECM remodeling in culture and in the colonic mucosal lamina propria in mice. Furthermore, PLEKHA7-depleted cells exhibit increased migration and invasion rates that are MMP1- and LOX- dependent, and form colonies in 3D cultures that are larger in size and acquire aberrant morphologies in stiffer matrices. These results reveal an AJ-mediated mechanism, through which epithelial cells drive ECM remodeling to modulate their behavior, including acquisition of phenotypes that are hallmarks of conditions such as fibrosis and tumorigenesis.