TransmiR v2.0: an updated transcription factor-microRNA regulation database

Target repositioning using multi-layer networks and machine learning: The case of prostate cancer

The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties. Consequently, they are widely employed to predict new therapeutic targets by characterizing potential candidates, often based on their interactions within a Protein-Protein Interaction (PPI) network, and their proximity to genes associated with the disease. However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. First, by exploiting a multi-layer network which incorporates additional information such as gene regulation, metabolite interactions, metabolic pathways, and several disease signatures such as Differentially Expressed Genes, mutated genes, Copy Number Alteration, and structural variants. Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. Using prostate cancer as a case study, the best features were identified and utilized to train machine learning algorithms to predict 5 novel promising therapeutic targets for prostate cancer: IGF2R, C5AR, RAB7, SETD2 and NPBWR1.

Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods

Gene regulatory networks are powerful tools for modeling genetic interactions that control the expression of genes driving cell differentiation, and single-cell sequencing offers a unique opportunity to build these networks with high-resolution genomic data. There are many proposed computational methods to build these networks using single-cell data, and different approaches are used to benchmark these methods. However, a comprehensive discussion specifically focusing on benchmarking approaches is missing. In this article, we lay the GRN terminology, present an overview of common gold-standard studies and data sets, and define the performance metrics for benchmarking network construction methodologies. We also point out the advantages and limitations of different benchmarking approaches, suggest alternative ground truth data sets that can be used for benchmarking, and specify additional considerations in this context.

Investigation of chromatin remodeling-related biomarkers and associated molecular mechanism in pulpitis

The current study aimed to identify potential chromatin remodeling-related biomarkers and the associated molecular mechanisms in pulpitis. Differentially expressed genes associated with chromatin remodeling (DECRGs) were identified using datasets from an online database. Enrichment and protein-protein interaction (PPI) network analyses were performed based on the DECRGs to identify biomarkers for pulpitis, followed by GSEA (gene set enrichment analysis). The diagnostic value of these biomarkers were evaluated by ROC (Receiver operating characteristic) and nomogram investigation. Next, microRNA(miRNA)-mRNA-TF (transcription factor), ceRNA (competing endogenous RNA), and drug prediction networks were constructed based on the biomarkers. Finally, reverse transcription-real-time quantitative PCR analysis and western blot were performed to validate the results of the bioinformatic analysis. This study identified 87 DECRGs between pulpitis and normal dental pulp samples that were mainly enriched in chromatin remodeling functions and pathways in cancer. A PPI network identified five biomarkers: TNF, STAT3, MYC, ACTB, and MAPK8. ROC and nomogram analyses demonstrated the diagnostic value of these biomarkers. GSEA of biomarkers such as STAT3 was mainly enriched in functions such as the B cell receptor signaling pathway. A biomarker-disease network and miRNA-mRNA-TF interactions were constructed using these biomarkers. A ceRNA network was constructed with interactions including chr22-38_28785274-29006793.1-miR-125b-5p-STAT3. A drug-gene network was established using 170 drugs and five biomarkers. Finally, qRT-PCR was used to validate the expression of all five biomarkers identified by the bioinformatics analysis. TNF, STAT3, MYC, ACTB, and MAPK8 are potential chromatin remodeling-related diagnostic markers for pulpitis. Moreover, long non-coding RNA (lncRNA) chr22-38_28785274-29006793.1 might function as a ceRNA to regulate the expression of the chromatin remodeling gene STAT3 by sponging miR-125b-5p in pulpitis.

Investigating the Causal Effects of Exercise-Induced Genes on Sarcopenia

Exercise is increasingly recognized as an effective strategy to counteract skeletal muscle aging and conditions such as sarcopenia. However, the specific exercise-induced genes responsible for these protective effects remain unclear. To address this, we conducted an eight-week aerobic exercise regimen on late-middle-aged mice and developed an integrated approach that combines mouse exercise-induced genes with human GWAS datasets to identify causal genes for sarcopenia. This approach led to significant improvements in the skeletal muscle phenotype of the mice and the identification of exercise-induced genes and miRNAs. By constructing a miRNA regulatory network enriched with transcription factors and GWAS signals related to muscle function and traits, we focused on 896 exercise-induced genes. Using human skeletal muscle cis-eQTLs as instrumental variables, 250 of these exercise-induced genes underwent two-sample Mendelian randomization analysis, identifying 40, 68, and 62 causal genes associated with sarcopenia and its clinical indicators-appendicular lean mass (ALM) and hand grip strength (HGS), respectively. Sensitivity analyses and cross-phenotype validation confirmed the robustness of our findings. Consistently across the three outcomes, RXRA, MDM1, RBL2, KCNJ2, and ADHFE1 were identified as risk factors, while NMB, TECPR2, MGAT3, ECHDC2, and GINM1 were identified as protective factors, all with potential as biomarkers for sarcopenia progression. Biological activity and disease association analyses suggested that exercise exerts its anti-sarcopenia effects primarily through the regulation of fatty acid oxidation. Based on available drug-gene interaction data, 21 of the causal genes are druggable, offering potential therapeutic targets. Our findings highlight key genes and molecular pathways potentially responsible for the anti-sarcopenia benefits of exercise, offering insights into future therapeutic strategies that could mimic the safe and mild protective effects of exercise on age-related skeletal muscle degeneration.

A SRC-slug-TGFβ2 signaling axis drives poor outcomes in triple-negative breast cancers

BACKGROUND

Treatment options for the Triple-Negative Breast Cancer (TNBC) subtype remain limited and the outcome for patients with advanced TNBC is very poor. The standard of care is chemotherapy, but approximately 50% of tumors develop resistance.

METHODS

We performed gene expression profiling of 58 TNBC tumor samples by microarray, comparing chemosensitive with chemoresistant tumors, which revealed that one of the top upregulated genes was TGFβ2. A connectivity mapping bioinformatics analysis predicted that the SRC inhibitor Dasatinib was a potential pharmacological inhibitor of chemoresistant TNBCs. Claudin-low TNBC cell lines were selected to represent poor-outcome, chemoresistant TNBC, for in vitro experiments and in vivo models.

RESULTS

In vitro, we identified a signaling axis linking SRC, AKT and ERK2, which in turn upregulated the stability of the transcription factors, Slug and Snail. Slug was shown to repress TGFβ2-antisense 1 to promote TGFβ2 signaling, upregulating cell survival via apoptosis and DNA-damage responses. Additionally, an orthotopic allograft in vivo model demonstrated that the SRC inhibitor Dasatinib reduced tumor growth as a single agent, and enhanced responses to the TNBC mainstay drug, Epirubicin.

CONCLUSION

Targeting the SRC-Slug-TGFβ2 axis may therefore lead to better treatment options and improve patient outcomes in this highly aggressive subpopulation of TNBCs.

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.

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.

Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models

Protein interaction databases are critical resources for network bioinformatics and integrating molecular experimental data. Interaction databases may also enable construction of predictive computational models of biological networks, although their fidelity for this purpose is not clear. Here, we benchmark protein interaction databases X2K, Reactome, Pathway Commons, Omnipath and Signor for their ability to recover manually curated edges from three logic-based network models of cardiac hypertrophy, mechano-signalling and fibrosis. Pathway Commons performed best at recovering interactions from manually reconstructed hypertrophy (137 of 193 interactions, 71%), mechano-signalling (85 of 125 interactions, 68%) and fibroblast networks (98 of 142 interactions, 69%). While protein interaction databases successfully recovered central, well-conserved pathways, they performed worse at recovering tissue-specific and transcriptional regulation. This highlights a knowledge gap where manual curation is critical. Finally, we tested the ability of Signor and Pathway Commons to identify new edges that improve model predictions, revealing important roles of protein kinase C autophosphorylation and Ca2+/calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy. This study provides a platform for benchmarking protein interaction databases for their utility in network model construction, as well as providing new insights into cardiac hypertrophy signalling. KEY POINTS: Protein interaction databases are used to recover signalling interactions from previously developed network models. The five protein interaction databases benchmarked recovered well-conserved pathways, but did poorly at recovering tissue-specific pathways and transcriptional regulation, indicating the importance of manual curation. We identify new signalling interactions not previously used in the network models, including a role for Ca2+/calmodulin-dependent protein kinase II phosphorylation of CREB in cardiomyocyte hypertrophy.

Extracellular Vesicle-Enclosed Oxidative Stress- and Inflammation-Related microRNAs as Potential Biomarkers of Vitamin D Responsivity: A Pilot Study on Inflammatory Bowel Disease Patients with or without COVID-19

The relationship between serum 25-hydroxyvitamin D (25(OH)D) levels, genomic response to vitamin D (Vit.D), and positivity to SARS-CoV-2 remains understudied. In this pilot study, during the follow-up of patients with Inflammatory Bowel Disease (IBD) and COVID-19, we investigated this issue by analyzing the molecular contents of serum extracellular vesicles (EVs) from six groups of IBD patients (n = 32), classified according to anti-SARS-CoV-2 status, 25(OH)D level, and Vit.D supplementation, by small RNA-seq. This analysis revealed differentially expressed miRNAs, PIWI-RNA, transfer RNA, small nucleolar RNAs, and protein-coding RNAs in the EVs obtained from these cohorts of IBD patients. Experimental validation evidenced a statistically significant increase in miR30d-5p, miR150-5p, Let-7f-5p, and Let-7a-5p in the anti-SARS-CoV-2-positive and low 25(OH)D and Vit.D supplemented groups with respect to the non-Vit.D supplemented group, indicating their responsiveness to Vit.D treatment. Bioinformatics analysis highlighted the regulation of these validated miRNAs by oxidative stress and inflammation, hallmarks of IBD and COVID-19. Our study reports an unprecedented panel of circulating EV-enclosed inflammation- and oxidative stress-related miRNAs, the potentiality of which, as biomarkers for Vit.D responsivity in IBD patients, needs to be explored in future studies on larger cohorts in order to allow clinicians to optimize current treatment strategies upon viral infection.

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.

Targeting the RUNX3-miR-186-3p-DAT-IGF1R axis as a therapeutic strategy in a Parkinson's disease model

With the increasing age of the population worldwide, the incidence rate of Parkinson's disease (PD) is increasing annually. Currently, the treatment strategy for PD only improves clinical symptoms. No effective treatment strategy can slow down the progression of the disease. In the present study, whole transcriptome sequencing was used to obtain the mRNA and miRNA expression profiles in a PD mouse model, which revealed the pathogenesis of PD. The transcription factor RUNX3 upregulated the miR-186-3p expression in the PD model. Furthermore, the high miR-186-3p expression in PD can be targeted to inhibit the DAT expression, resulting in a decrease in the dopamine content of dopaminergic neurons. Moreover, miR-186-3p can be targeted to inhibit the IGF1R expression and prevent the activation of the IGF1R-P-PI3K-P-AKT pathway, thus increasing the apoptosis of dopaminergic neurons by regulating the cytochrome c-Bax-cleaved caspase-3 pathway. Our research showed that the RUNX3-miR-186-3p-DAT-IGF1R axis plays a key role in the pathogenesis of PD, and miR-186-3p is a potential target for the treatment of PD.

Extracellular vesicles miR-31-5p promotes pancreatic cancer chemoresistance via regulating LATS2-Hippo pathway and promoting SPARC secretion from pancreatic stellate cells

Pancreatic cancer remains one of the most lethal malignant diseases. Gemcitabine-based chemotherapy is still one of the first-line systemic treatments, but chemoresistance occurs in the majority of patients. Recently, accumulated evidence has demonstrated the role of the tumour microenvironment in promoting chemoresistance. In the tumour microenvironment, pancreatic stellate cells (PSCs) are among the main cellular components, and extracellular vesicles (EVs) are common mediators of cell‒cell communication. In this study, we showed that SP1-transcribed miR-31-5p not only targeted LATS2 in pancreatic cancer cells but also regulated the Hippo pathway in PSCs through EV transfer. Consequently, PSCs synthesized and secreted protein acidic and rich in cysteins (SPARC), which was preferentially expressed in stromal cells, stimulating Extracellular Signal regulated kinase (ERK) signalling in pancreatic cancer cells. Therefore, pancreatic cancer cell survival and chemoresistance were improved due to both the intrinsic Hippo pathway regulated by miR-31-5p and external SPARC-induced ERK signalling. In mouse models, miR-31-5p overexpression in pancreatic cancer cells promoted the chemoresistance of coinjected xenografts. In a tissue microarray, pancreatic cancer patients with higher miR-31-5p expression had shorter overall survival. Therefore, miR-31-5p regulates the Hippo pathway in multiple cell types within the tumour microenvironment via EVs, ultimately contributing to the chemoresistance of pancreatic cancer cells.

NF-κB factors cooperate with Su(Hw)/E4F1 to balance Drosophila/human immune responses via modulating dynamic expression of miR-210

MicroRNAs (miRNAs) play crucial regulatory roles in controlling immune responses, but their dynamic expression mechanisms are poorly understood. Here, we firstly confirm that the conserved miRNA miR-210 negatively regulates innate immune responses of Drosophila and human via targeting Toll and TLR6, respectively. Secondly, our findings demonstrate that the expression of miR-210 is dynamically regulated by NF-κB factor Dorsal in immune response of Drosophila Toll pathway. Thirdly, we find that Dorsal-mediated transcriptional inhibition of miR-210 is dependent on the transcriptional repressor Su(Hw). Mechanistically, Dorsal interacts with Su(Hw) to modulate cooperatively the dynamic expression of miR-210 in a time- and dose-dependent manner, thereby controlling the strength of Drosophila Toll immune response and maintaining immune homeostasis. Fourthly, we reveal a similar mechanism in human cells, where NF-κB/RelA cooperates with E4F1 to regulate the dynamic expression of hsa-miR-210 in the TLR immune response. Overall, our study reveals a conservative regulatory mechanism that maintains animal innate immune homeostasis and provides new insights into the dynamic regulation of miRNA expression in immune response.

Expression and Functional Analysis of Immuno-Micro-RNAs mir-146a and mir-326 in Colorectal Cancer

Micro-RNAs (miRNAs) are non-coding RNAs with importance in the development of cancer. They are involved in both tumor development and immune processes in tumors. The present study aims to characterize the behavior of two miRNAs, the proinflammatory miR-326-5p and the anti-inflammatory miR-146a-5p, in colorectal cancer (CRC), to decipher the mechanisms that regulate their expression, and to study potential applications. Tissue levels of miR-326-5p and miR-146a-5p were determined by qrt-PCR (real-time quantitative reverse transcription polymerase chain reaction) in 45 patients with colorectal cancer in tumoral and normal adjacent tissue. Subsequent bioinformatic analysis was performed to characterize the transcriptional networks that control the expression of the two miRNAs. The biomarker potential of miRNAs was assessed. The expression of miR-325-5p and miR-146a-5p was decreased in tumors compared to normal tissue. The two miRNAs are regulated through a transcriptional network, which originates in the inflammatory and proliferative pathways and regulates a set of cellular functions related to immunity, proliferation, and differentiation. The miRNAs coordinate distinct modules in the network. There is good biomarker potential of miR-326 with an AUC (Area under the curve) of 0.827, 0.911 sensitivity (Sn), and 0.689 specificity (Sp), and of the combination miR-326-miR-146a, with an AUC of 0.845, Sn of 0.75, and Sp of 0.89. The miRNAs are downregulated in the tumor tissue. They are regulated by a transcriptional network in which they coordinate distinct modules. The structure of the network highlights possible therapeutic approaches. MiR-326 and the combination of the two miRNAs may serve as biomarkers in CRC.

Adipose-derived miRNAs as potential biomarkers for predicting adulthood obesity and its complications: A systematic review and bioinformatic analysis

Adipose tissue is the first and primary target organ of obesity and the main source of circulating miRNAs in patients with obesity. This systematic review aimed to analyze and summarize the generation and mechanisms of adipose-derived miRNAs and their role as early predictors of various obesity-related complications. Literature searches in the PubMed and Web of Science databases using terms related to miRNAs, obesity, and adipose tissue. Pre-miRNAs from the Human MicroRNA Disease Database, known to regulate obesity-related metabolic disorders, were combined for intersection processing. Validated miRNA targets were sorted through literature review, and enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes via the KOBAS online tool, disease analysis, and miRNA transcription factor prediction using the TransmiR v. 2.0 database were also performed. Thirty miRNAs were identified using both obesity and adipose secretion as criteria. Seventy-nine functionally validated targets associated with 30 comorbidities of these miRNAs were identified, implicating pathways such as autophagy, p53 pathways, and inflammation. The miRNA precursors were analyzed to predict their transcription factors and explore their biosynthesis mechanisms. Our findings offer potential insights into the epigenetic changes related to adipose-driven obesity-related comorbidities.

Integrative Bioinformatics Analysis Reveals a Transcription Factor EB-Driven MicroRNA Regulatory Network in Endothelial Cells

Various human diseases are triggered by molecular alterations influencing the fine-tuned expression and activity of transcription factors, usually due to imbalances in targets including protein-coding genes and non-coding RNAs, such as microRNAs (miRNAs). The transcription factor EB (TFEB) modulates human cellular networks, overseeing lysosomal biogenesis and function, plasma-membrane trafficking, autophagic flux, and cell cycle progression. In endothelial cells (ECs), TFEB is essential for the maintenance of endothelial integrity and function, ensuring vascular health. However, the comprehensive regulatory network orchestrated by TFEB remains poorly understood. Here, we provide novel mechanistic insights into how TFEB regulates the transcriptional landscape in primary human umbilical vein ECs (HUVECs), using an integrated approach combining high-throughput experimental data with dedicated bioinformatics analysis. By analyzing HUVECs ectopically expressing TFEB using ChIP-seq and examining both polyadenylated mRNA and small RNA sequencing data from TFEB-silenced HUVECs, we have developed a bioinformatics pipeline mapping the different gene regulatory interactions driven by TFEB. We show that TFEB directly regulates multiple miRNAs, which in turn post-transcriptionally modulate a broad network of target genes, significantly expanding the repertoire of gene programs influenced by this transcription factor. These insights may have significant implications for vascular biology and the development of novel therapeutics for vascular disease.

Exploring the potential biological significance of KDELR family genes in lung adenocarcinoma

The Lys-Asp-Glu-Leu receptor (KDELR) family genes play critical roles in a variety of biological processes in different tumors. Our study aimed to provide a comprehensive analysis of the potential roles of KDELRs in lung adenocarcinoma (LUAD). Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as clinical samples, we conducted a series of analyses and validations using R software tools and various online resources. The results showed that KDELR family genes and proteins were highly expressed and associated with a poor prognosis of LUAD. Promoter hypomethylation and the competing endogenous RNA (ceRNA) network of PCAT6/hsa-miR-326/KDELR1 might be potential causes of aberrant KDELR1 overexpression in LUAD. Three key Transcription factors (TFs) (SPI1, EP300, and MAZ) and a TFs-miRNAs-KDELRs network (involving 11 TFs) might be involved in modulating KDELRs expression abnormalities. Gene Set Enrichment Analysis (GSEA) indicated enrichment of genes highly expressing KDELR1, KDELR2, and KDELR3 in MTORC1_SIGNALING, P53_PATHWAY, and ANGIOGENESIS. Negative correlations between KDELRs expression and CD8 + T cell infiltration, as well as CTLA-4 expression. Our multiple analyses suggested that the KDELRs are important signaling molecules in LUAD. These results provided novel insights for developing prognostic markers and novel therapies of LUAD.

Identification of Biomarkers Associated with Oxidative Stress and Immune Cells in Acute Pancreatitis

Purpose

Oxidative stress promotes disease progression by stimulating the humoral and cellular immune responses. However, the molecular mechanisms underlying oxidative stress and immune responses in acute pancreatitis (AP) have not been extensively studied.

Patients and Methods

We analyzed the GSE194331 dataset and oxidative stress-related genes (OSRGs). We identified differentially expressed immune cell-associated OSRGs (DE-ICA-OSRGs) by overlapping key module genes from weighted gene co-expression network analysis, OSRGs, and DEGs between AP and normal samples. Functional enrichment analysis was performed to investigate the functions of DE-ICA-OSRGs. We then filtered diagnostic genes using receiver operating characteristic curves and investigated their molecular mechanisms using single-gene set enrichment analysis (GSEA). We also explored the correlation between diagnostic genes and differential immune cells. Finally, we constructed a transcription factor-microRNA-messenger RNA (TF-miRNA-mRNA) network of biomarkers.

Results

In this study, three DE-ICA-OSRGs (ARG1, NME8 and VNN1) were filtered by overlapping key module genes, OSRGs and DEGs. Functional enrichment results revealed that DE-ICA-OSRGs were involved in the cellular response to reactive oxygen species and arginine biosynthesis. Latterly, a total of two diagnostic genes (ARG1 and VNN1) were derived and their expression was higher in the AP group than in the normal group. The single-gene GSEA enrichment results revealed that diagnostic genes were mainly enriched in macroautophagy and Toll-like receptor signaling pathways. Correlation analysis revealed that CD8 T cells, resting memory T CD4 cells, and resting NK cells were negatively correlated with ARG1, and neutrophils were positively correlated with ARG1, which was consistent with that of VNN1. The TF-miRNA-mRNA regulatory network included 11 miRNAs, 2 mRNAs, 10 transcription factors (TFs), and 26 pairs of regulatory relationships, like NFKB1-has-miR-2909-VNN1.

Conclusion

In this study, two immune cell oxidative stress-related AP diagnostic genes (ARG1 and VNN1) were screened to offer a new reference for the diagnosis of patients with AP.

Regulatory network analysis based on integrated miRNA-TF reveals key genes in heart failure

The etiology and pathophysiology of heart failure are still unknown. Increasing evidence suggests that abnormal microRNAs (miRNAs) and transcription factors (TFs) expression may be associated with the development of heart failure. Therefore, this study aims to explore key miRNAs, TFs, and related genes in heart failure to gain a greater understanding of the pathogenesis of heart failure. To search and download the dataset of mRNA chips related to heart failure from the GEO database (GSE59867, GSE9128, and GSE134766), we analyzed differential genes and screened the common differentially expressed genes on two chips using R language software. The binary interactions and circuits among miRNAs, TFs, and corresponding genes were determined by Pearson correlation coefficient. A regulatory network of miRNAs, TFs, and target genes was constructed based on bioinformatics. By comparing the sequences of patients with and without heart failure, five downregulated genes with hypermethylated mRNA and three upregulated genes with hypomethylated mRNA were identified. The miRNA-TF gene regulatory network consisted of 26 miRNAs, 22 TFs and six genes. GO and KEGG analysis results revealed that BP terms like cellular response to organic substance, cellular response to cytokine stimulus, and KEGG pathways like osteoclast differentiation, MAPK signaling pathway, and legionellosis were enriched of the DEGs. TMEM87A, PPP2R2A, DUSP1, and miR-92a have great potential as biomarkers for heart failure. The integrated analysis of the mRNA expression spectrum and microRNA-transcription factor-gene revealed the regulatory network of heart failure, which may provide clues to its alternative treatment.

MiR-135a-5p regulates window of implantation by suppressing pinopodes development and decidualization of endometrial stromal cells

PURPOSE

The window of implantation (WOI) is a brief period during which the endometrium is receptive to embryo implantation. This study investigated the relationship between miR-135a-5p and endometrial receptivity.

METHODS

Peripheral blood was collected on the day of ovulation and the 5th day after ovulation for high-throughput sequencing from women who achieved clinical pregnancy through natural cycle frozen embryo transfer. RT-qPCR assessed miR-135a-5p expression in the endometrium tissue or cells during the mouse implantation window or decidualization. Scanning electron microscopy was utilized to observe pinopode morphology and quantity in mice overexpressing miR-135a-5p during the WOI. Human endometrial stromal cells (HESC) and artificial induction of mouse uterine decidualization were used to explore whether miR-135a-5p overexpression inhibits decidualization by regulating HOXA10 and BMPR2. Furthermore, the impact of miR-135a-5p on HESC proliferation and HTR8/SVneo invasion was explored.

RESULTS

A total of 54 women were enrolled in the study. bioinformatics analysis and animal models demonstrated that miR-135a-5p was significantly downregulated during the WOI, and its high expression can lead to abnormal pregnancy outcomes. Overexpression of miR-135a-5p resulted in the absence of pinopode in mouse endometrial tissue during the WOI. High miR-135a-5p levels were found to potentially inhibit endometrial tissue decidualization by downregulating HOXA10 and BMPR2 expression. Finally, CEBPD was identified as a potential regulator of miR-135a-5p, which would explain the decreased miR-135a-5p expression during the WOI.

CONCLUSION

MiR-135a-5p expression is significantly downregulated during the WOI. High miR-135a-5p levels suppress pinopode development and endometrial tissue decidualization through HOXA10 and BMPR2, contributing to inadequate endometrial receptivity.

Bioinformatics Research and qRT-PCR Verify Hub Genes and a Transcription Factor-MicroRNA Feedback Network in Intervertebral Disc Degeneration

The present study explores the potentials of bioinformatics analysis to identify hub genes linked to intervertebral disc degeneration (IDD) and explored the potential molecular mechanism of transcription factor-microRNA regulatory network. Furthermore, the hub genes were identified through quantitative reverse transcriptase PCR (qRT-PCR). GEO database expression profile datasets for candidate genes (GSE124272) were downloaded. Genes that were differentially expressed (DEGs) were detected utilizing limma technique in the R programming language. Search Tool for the Retrieval of Interacting Genes/Proteins and NetworkAnalyst software identified hub genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis as well as Gene Ontology annotation of the DEGs were performed using Metascape. Using Bioinformatics data from the TRRUST, StarBase, and TransmiR databases, a TF-miRNA-hub genes network was constructed. qRT-PCR was utilized to confirm the result. As compared to healthy persons, 521 DEGs, comprising 203 down-regulated and 318 up-regulated genes, as well as 7 core genes, were found in people with IDD. Analysis revealed that all seven essential genes were under-expressed. qRT-PCR further confirmed the low expression of these seven important genes. Based on the TRRUST database, 16 TFs that could target five junction genes were then predicted. According to the StarBase database, four miRNAs were linked to crucial genes, while the TransmiR database predicted regulatory connections between four miRNAs and five TFs. The expression of the TP53-(hsa-miR-183-5p)-CCNB1 TF-miRNA-mRNA interaction network was discovered to be correlated with IDD. Throughout this investigation, a network of TF-miRNA-mRNA connections was built for investigation of the probable molecular mechanisms responsible for IDD. The identification of hub genes associated with IDD may reveal promising IDD treatment strategies.

Deciphering the similarities and disparities of molecular mechanisms behind respiratory epithelium response to HCoV-229E and SARS-CoV-2 and drug repurposing, a systems biology approach

PURPOSE

Identifying the molecular mechanisms behind SARS-CoV-2 disparities and similarities will help find new treatments. The present study determines networks' shared and non-shared (specific) crucial elements in response to HCoV-229E and SARS-CoV-2 viruses to recommend candidate medications.

METHODS

We retrieved the omics data on respiratory cells infected with HCoV-229E and SARS-CoV-2, constructed PPIN and GRN, and detected clusters and motifs. Using a drug-gene interaction network, we determined the similarities and disparities of mechanisms behind their host response and drug-repurposed.

RESULTS

CXCL1, KLHL21, SMAD3, HIF1A, and STAT1 were the shared DEGs between both viruses' protein-protein interaction network (PPIN) and gene regulatory network (GRN). The NPM1 was a specific critical node for HCoV-229E and was a Hub-Bottleneck shared between PPI and GRN in HCoV-229E. The HLA-F, ADCY5, TRIM14, RPF1, and FGA were the seed proteins in subnetworks of the SARS-CoV-2 PPI network, and HSPA1A and RPL26 proteins were the seed in subnetworks of the PPI network of HCOV-229E. TRIM14, STAT2, and HLA-F played the same role for SARS-CoV-2. Top enriched KEGG pathways included cell cycle and proteasome in HCoV-229E and RIG-I-like receptor, Chemokine, Cytokine-cytokine, NOD-like receptor, and TNF signaling pathways in SARS-CoV-2. We suggest some candidate medications for COVID-19 patient lungs, including Noscapine, Isoetharine mesylate, Cycloserine, Ethamsylate, Cetylpyridinium, Tretinoin, Ixazomib, Vorinostat, Venetoclax, Vorinostat, Ixazomib, Venetoclax, and epoetin alfa for further in-vitro and in-vivo investigations.

CONCLUSION

We suggested CXCL1, KLHL21, SMAD3, HIF1A, and STAT1, ADCY5, TRIM14, RPF1, and FGA, STAT2, and HLA-F as critical genes and Cetylpyridinium, Cycloserine, Noscapine, Ethamsylate, Epoetin alfa, Isoetharine mesylate, Ribavirin, and Tretinoin drugs to study further their importance in treating COVID-19 lung complications.

Pancreatic cancer cells hijack tumor suppressive microRNA-26a to promote radioresistance and potentiate tumor repopulation

Pancreatic cancer is one of the most lethal cancers with significant radioresistance and tumor repopulation after radiotherapy. As a type of short non-coding RNA that regulate various biological and pathological processes, miRNAs might play vital role in radioresistance. We found by miRNA sequencing that microRNA-26a (miR-26a) was upregulated in pancreatic cancer cells after radiation, and returned to normal state after a certain time. miR-26a was defined as a tumor suppressive miRNA by conventional tumor biology experiments. However, transient upregulation of miR-26a after radiation significantly promoted radioresistance, while stable overexpression inhibited radioresistance, highlighting the importance of molecular dynamic changes after treatment. Mechanically, transient upregulation of miR-26a promoted cell cycle arrest and DNA damage repair to promote radioresistance. Further experiments confirmed HMGA2 as the direct functional target, which is an oncogene but enhances radiosensitivity. Moreover, PTGS2 was also the target of miR-26a, which might potentiate tumor repopulation via delaying the synthesis of PGE2. Overall, this study revealed that transient upregulation of miR-26a after radiation promoted radioresistance and potentiated tumor repopulation, highlighting the importance of dynamic changes of molecules upon radiotherapy.

A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework

Neuroblastoma (NB) is one of the leading causes of cancer-associated death in children. MYCN amplification is a prominent genetic marker for NB, and its targeting to halt NB progression is difficult to achieve. Therefore, an in-depth understanding of the molecular interactome of NB is needed to improve treatment outcomes. Analysis of NB multi-omics unravels valuable insight into the interplay between MYCN transcriptional and miRNA post-transcriptional modulation. Moreover, it aids in the identification of various miRNAs that participate in NB development and progression. This study proposes an integrated computational framework with three levels of high-throughput NB data (mRNA-seq, miRNA-seq, and methylation array). Similarity Network Fusion (SNF) and ranked SNF methods were utilized to identify essential genes and miRNAs. The specified genes included both miRNA-target genes and transcription factors (TFs). The interactions between TFs and miRNAs and between miRNAs and their target genes were retrieved where a regulatory network was developed. Finally, an interaction network-based analysis was performed to identify candidate biomarkers. The candidate biomarkers were further analyzed for their potential use in prognosis and diagnosis. The candidate biomarkers included three TFs and seven miRNAs. Four biomarkers have been previously studied and tested in NB, while the remaining identified biomarkers have known roles in other types of cancer. Although the specific molecular role is yet to be addressed, most identified biomarkers possess evidence of involvement in NB tumorigenesis. Analyzing cellular interactome to identify potential biomarkers is a promising approach that can contribute to optimizing efficient therapeutic regimens to target NB vulnerabilities.

Repression of developmental transcription factor networks triggers aging-associated gene expression in human glial progenitor cells

Human glial progenitor cells (hGPCs) exhibit diminished expansion competence with age, as well as after recurrent demyelination. Using RNA-sequencing to compare the gene expression of fetal and adult hGPCs, we identify age-related changes in transcription consistent with the repression of genes enabling mitotic expansion, concurrent with the onset of aging-associated transcriptional programs. Adult hGPCs develop a repressive transcription factor network centered on MYC, and regulated by ZNF274, MAX, IKZF3, and E2F6. Individual over-expression of these factors in iPSC-derived hGPCs lead to a loss of proliferative gene expression and an induction of mitotic senescence, replicating the transcriptional changes incurred during glial aging. miRNA profiling identifies the appearance of an adult-selective miRNA signature, imposing further constraints on the expansion competence of aged GPCs. hGPC aging is thus associated with acquisition of a MYC-repressive environment, suggesting that suppression of these repressors of glial expansion may permit the rejuvenation of aged hGPCs.

Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as β-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.

Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome

MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline that the complexity in the analysis of miRNA function ranges from their modes of biogenesis to the target diversity in diverse biological conditions. Therefore, it is imperative to first ascertain the miRNA coding potential of genomes and understand the regulatory mechanisms of their expression. This knowledge enables the efficient classification of miRNA precursors and the identification of their mature forms and respective target genes. Second, and because one miRNA can target multiple mRNAs and vice versa, another challenge is the assessment of the miRNA-mRNA target interaction network. Furthermore, long-noncoding RNA (lncRNA)and circular RNAs (circRNAs) also contribute to this complexity. ML has been used to tackle these challenges at the high-dimensional data level. The present expert review covers more than 100 tools adopting various ML approaches pertaining to, for example, (1) miRNA promoter prediction, (2) precursor classification, (3) mature miRNA prediction, (4) miRNA target prediction, (5) miRNA- lncRNA and miRNA-circRNA interactions, (6) miRNA-mRNA expression profiling, (7) miRNA regulatory module detection, (8) miRNA-disease association, and (9) miRNA essentiality prediction. Taken together, we unpack, critically examine, and highlight the cutting-edge synergy of ML approaches and miRNA research so as to develop a dynamic and microlevel understanding of human health and diseases.

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

The Potential Roles of Host Cell miRNAs in Fine-Tuning Bovine Coronavirus (BCoV) Molecular Pathogenesis, Tissue Tropism, and Immune Regulation

Bovine coronavirus (BCoV) infection causes significant economic loss to the dairy and beef industries worldwide. BCoV exhibits dual tropism, infecting the respiratory and enteric tracts of cattle. The enteric BCoV isolates could also induce respiratory manifestations under certain circumstances. However, the mechanism of this dual tropism of BCoV infection has not yet been studied well. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and play a dual role in virus infection, mediating virus or modulating host immune regulatory genes through complex virus-host cell interactions. However, their role in BCoV infection remains unclear. This study aims to identify bovine miRNAs crucial for regulating virus-host interaction, influencing tissue tropism, and explore their potential as biomarkers and therapeutic agents against BCoV. We downloaded 18 full-length BCoV genomes (10 enteric and eight respiratory) from GenBank. We applied several bioinformatic tools to study the host miRNAs targeting various regions in the viral genome. We used the criteria of differential targeting between the enteric/respiratory isolates to identify some critical miRNAs as biological markers for BCoV infection. Using various online bioinformatic tools, we also searched for host miRNA target genes involved in BCoV infection, immune evasion, and regulation. Our results show that four bovine miRNAs (miR-2375, miR-193a-3p, miR-12059, and miR-494) potentially target the BCoV spike protein at multiple sites. These miRNAs also regulate the host immune suppressor pathways, which negatively impacts BCoV replication. Furthermore, we found that bta-(miR-2338, miR-6535, miR-2392, and miR-12054) also target the BCoV genome at certain regions but are involved in regulating host immune signal transduction pathways, i.e., type I interferon (IFN) and retinoic acid-inducible gene I (RIG-I) pathways. Moreover, both miR-2338 and miR-2392 also target host transcriptional factors RORA, YY1, and HLF, which are potential diagnostic markers for BCoV infection. Therefore, miR-2338, miR-6535, miR-2392, and miR-12054 have the potential to fine-tune BCoV tropism and immune evasion and enhance viral pathogenesis. Our results indicate that host miRNAs play essential roles in the BCoV tissue tropism, pathogenesis, and immune regulation. Four bovine miRNAs (miR-2375, bta-miR-193a-3p, bta-miR-12059, and bta-miR-494) target BCoV-S glycoprotein and are potentially involved in several immune suppression pathways during the viral infection. These miRNA candidates could serve as good genetic markers for BCoV infection. However, further studies are urgently needed to validate these identified miRNAs and their target genes in the context of BCoV infection and dual tropism and as genetic markers.

Distinctive physical properties of DNA shared by RNA polymerase II gene promoters and 5'-flanking regions of tRNA genes

Numerous noncoding (nc)RNAs have been identified. Similar to the transcription of protein-coding (mRNA) genes, long noncoding (lnc)RNA genes and most of micro (mi)RNA genes are transcribed by RNA polymerase II (Pol II). In the transcription of mRNA genes, core promoters play an indispensable role; they support the assembly of the preinitiation complex (PIC). However, the structural and/or physical properties of the core promoters of lncRNA and miRNA genes remain largely unexplored, in contrast with those of mRNA genes. Using the core promoters of human genes, we analyzed the repertoire and population ratios of residing core promoter elements (CPEs) and calculated the following five DNA physical properties (DPPs): duplex DNA free energy, base stacking energy, protein-induced deformability, rigidity and stabilizing energy of Z-DNA. Here, we show that their CPE and DPP profiles are similar to those of mRNA gene promoters. Importantly, the core promoters of these three classes of genes have two highly distinctive sites in their DPP profiles around the TSS and position -27. Similar characteristics in DPPs are also found in the 5'-flanking regions of tRNA genes, indicating their common essential roles in transcription initiation over the kingdom of RNA polymerases.

Trials and Tribulations of MicroRNA Therapeutics

The discovery of the link between microRNAs (miRNAs) and a myriad of human diseases, particularly various cancer types, has generated significant interest in exploring their potential as a novel class of drugs. This has led to substantial investments in interdisciplinary research fields such as biology, chemistry, and medical science for the development of miRNA-based therapies. Furthermore, the recent global success of SARS-CoV-2 mRNA vaccines against the COVID-19 pandemic has further revitalized interest in RNA-based immunotherapies, including miRNA-based approaches to cancer treatment. Consequently, RNA therapeutics have emerged as highly adaptable and modular options for cancer therapy. Moreover, advancements in RNA chemistry and delivery methods have been pivotal in shaping the landscape of RNA-based immunotherapy, including miRNA-based approaches. Consequently, the biotechnology and pharmaceutical industry has witnessed a resurgence of interest in incorporating RNA-based immunotherapies and miRNA therapeutics into their development programs. Despite substantial progress in preclinical research, the field of miRNA-based therapeutics remains in its early stages, with only a few progressing to clinical development, none reaching phase III clinical trials or being approved by the US Food and Drug Administration (FDA), and several facing termination due to toxicity issues. These setbacks highlight existing challenges that must be addressed for the broad clinical application of miRNA-based therapeutics. Key challenges include establishing miRNA sensitivity, specificity, and selectivity towards their intended targets, mitigating immunogenic reactions and off-target effects, developing enhanced methods for targeted delivery, and determining optimal dosing for therapeutic efficacy while minimizing side effects. Additionally, the limited understanding of the precise functions of miRNAs limits their clinical utilization. Moreover, for miRNAs to be viable for cancer treatment, they must be technically and economically feasible for the widespread adoption of RNA therapies. As a result, a thorough risk evaluation of miRNA therapeutics is crucial to minimize off-target effects, prevent overdosing, and address various other issues. Nevertheless, the therapeutic potential of miRNAs for various diseases is evident, and future investigations are essential to determine their applicability in clinical settings.

DNI-MDCAP: improvement of causal MiRNA-disease association prediction based on deep network imputation

BACKGROUND

MiRNAs are involved in the occurrence and development of many diseases. Extensive literature studies have demonstrated that miRNA-disease associations are stratified and encompass ~ 20% causal associations. Computational models that predict causal miRNA-disease associations provide effective guidance in identifying novel interpretations of disease mechanisms and potential therapeutic targets. Although several predictive models for miRNA-disease associations exist, it is still challenging to discriminate causal miRNA-disease associations from non-causal ones. Hence, there is a pressing need to develop an efficient prediction model for causal miRNA-disease association prediction.

RESULTS

We developed DNI-MDCAP, an improved computational model that incorporated additional miRNA similarity metrics, deep graph embedding learning-based network imputation and semi-supervised learning framework. Through extensive predictive performance evaluation, including tenfold cross-validation and independent test, DNI-MDCAP showed excellent performance in identifying causal miRNA-disease associations, achieving an area under the receiver operating characteristic curve (AUROC) of 0.896 and 0.889, respectively. Regarding the challenge of discriminating causal miRNA-disease associations from non-causal ones, DNI-MDCAP exhibited superior predictive performance compared to existing models MDCAP and LE-MDCAP, reaching an AUROC of 0.870. Wilcoxon test also indicated significantly higher prediction scores for causal associations than for non-causal ones. Finally, the potential causal miRNA-disease associations predicted by DNI-MDCAP, exemplified by diabetic nephropathies and hsa-miR-193a, have been validated by recently published literature, further supporting the reliability of the prediction model.

CONCLUSIONS

DNI-MDCAP is a dedicated tool to specifically distinguish causal miRNA-disease associations with substantially improved accuracy. DNI-MDCAP is freely accessible at http://www.rnanut.net/DNIMDCAP/ .

Construction of hub transcription factor-microRNAs-messenger RNA regulatory network in recurrent implantation failure

PURPOSE

Recurrent implantation failure (RIF) affects up to 10% of in vitro fertilization (IVF) patients worldwide. However, the pathogenesis of RIF remains unclear. This study was aimed at identifying hub transcription factors (TFs) of RIF in bioinformatics approaches.

METHODS

The GSE111974 (mRNA), GSE71332 (miRNA), and GSE103465 (mRNA) datasets were downloaded from the Gene Expression Omnibus database from human endometrial tissue using R version 4.2.1 and used to identify differentially expressed TFs (DETFs), differentially expressed miRNAs, and differentially expressed genes for RIF, respectively. DETFs were subjected to functional enrichment analysis and the protein-protein interaction network analysis using the Search Tool for the Retrieval of Interacting Genes (version 11.5) database. Hub TFs were identified using the cytoHubb plug-in, after which a hub TF-miRNA-mRNA network was constructed using Cytoscape v3.8.2.

RESULTS

Fifty-seven DETFs were identified, in which Gene Ontology analysis revealed to be mainly involved in the regulation of transcription. Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that DETFs were enriched in transcriptional misregulation in cancer, aldosterone synthesis and secretion, AMPK signaling pathway, and cGMP-PKG signaling pathway. EOMES, NKX2-1, and POU5F1 were identified as hub TFs, and a hub TF-miRNA-mRNA regulatory network was constructed using these three hub TFs, four miRNAs, and four genes.

CONCLUSION

Collectively, we identified three promising molecular biomarkers for the diagnosis of RIF, which may further be potential therapeutic targets. This study provides novel insights into the molecular mechanisms underlying RIF. However, further experiments are required to verify these results.

Hepatitis B Virus Modulated Transcriptional Regulatory Map of Hepatic Cellular MicroRNAs

Hepatitis B virus (HBV) is an enveloped, hepatotropic, noncytopathic virus with a partially double-stranded DNA genome. It infects hepatocytes and is associated with progression to liver fibrosis and cirrhosis, culminating in hepatocellular carcinoma (HCC), accounting for 55% of total HCC cases. MicroRNAs (miRNAs) regulated by HBV play an important role in these pathologies. Mapping the miRNAs responsive to HBV and HBV-specific proteins, including HBV X protein (HBx) that harbor the majority of HBV-human protein interactions, could aid accelerate the diagnostics and therapeutics innovation against the infection and associated diseases. With this in mind, we used a unique annotation strategy whereby we first amassed 362 mature HBV responsive-human Differentially Expressed miRNAs (HBV-hDEmiRs). The core experimentally-validated messenger RNA targets of the HBV-hDEmiRs were mostly associated with viral infections and hepatic inflammation processes. Moreover, our annotation strategy enabled the characterization of HBx-dependent/independent HBV-hDEmiRs as a tool for evaluation of the impact of HBx as a therapeutic target. Bioinformatics analysis of the HBV-human protein-protein interactome revealed new insights into the transcriptional regulatory network of the HBV-hDEmiRs. We performed a comparative analysis of data on miRNAs gathered from HBV infected cell line studies and from tissue studies of fibrosis, cirrhosis, and HCC. Accordingly, we propose hsa-miR-15a-5p that is downregulated by multiple HBV proteins, including HBx, as a potential biomarker of HBV infection, and its progression to HCC. In all, this study underscores (1) the complexity of miRNA regulation in response to HBV infection and its progression into other liver pathologies and (2) provides a regulatory map of HBV-hDEmiRs and the underlying mechanisms modulating their expression through a cross talk between HBV viral proteins and human transcription factors.

ETS2 overexpression ameliorates cartilage injury in osteoarthritis by the ETS2/miR-155/STAT1/DNMT1 feedback loop pathway

Osteoarthritis (OA) is the most common irreversible chronic joint dysfunction disease, which is pathologically characterized by disturbance of articular cartilage homeostasis leading to subsequent inflammatory response and cartilage extracellular matrix (ECM) degradation. Increasing evidence has demonstrated the dysregulation of transcription factors play crucial roles in the occurrence and development of osteoarthritis (OA), but the potential functions and mechanism of most transcription factors in OA has not been completely illuminated. In this study, we identified that transcription factor V-ets erythroblastosis virus E26 oncogene homolog 2 (ETS2) was significantly down-regulated in OA cartilage and IL-1β-induced OA chondrocytes. Functional experiments in vitro demonstrated that the overexpressed ETS2 strikingly enhanced proliferation, outstandingly suppressed apoptosis, and dramatically reduced inflammation and ECM degradation in IL-1β-induced OA chondrocytes, whereas the knockdown of ETS2 led to the opposite effects. Further in vivo studies have shown that up-regulated ETS2 dramatically ameliorates cartilage injury in DMM-induced OA mice. Mechanical studies have disclosed that DNMT1-mediated downregulation of ETS2 dramatically promotes STAT1 by inhibiting miR-155 transcription, and increased STAT1 initiates a feedback loop that may enhance DNMT1-mediated hypermethylation of ETS2 to inhibit ETS2 expression, thus forming a DNMT1/ETS2/miR-155/STAT1 feedback loop that inhibits MAPK signaling pathways and aggravates OA cartilage injury. In all, our results revealed that overexpression of ETS2 markedly ameliorated OA cartilage injury through the ETS2/miR-155/STAT1/DNMT1 feedback loop, providing a new perspective on the pathogenesis and therapeutic strategies for OA.

Diagnostic potential and pathogenic performance of circulating miR-146b, miR-194, and miR-214 in liver fibrosis

Liver fibrosis is the excessive accumulation of extracellular matrix proteins. Due to the lack of an accurate test for an early diagnosis of liver fibrosis and the invasiveness of the liver biopsy procedure, there is an urgent need for effective non-invasive biomarkers for screening the patients. we aimed to evaluate the diagnostic performance of circulating miRNAs (miR-146b, -194, -214) and their related mechanisms in the pathogenesis of liver fibrosis. The expression levels of miR-146b, -194, and -214 were quantified in whole blood samples from NAFLD patients using real-time PCR. The competing endogenous RNA (ceRNA) network was constructed and a gene set enrichment analysis (GSEA) was performed for HSC activation-related genes. Also, the transcription factor (TF)-miR co-regulatory network and the survival plot for three miRNAs and core genes were illustrated. The qPCR results showed that the relative expression of miR-146b and miR-214 significantly increased in NAFLD patients, while miR-194 showed significant down-regulation. The ceRNA network analysis implicated NEAT1 and XIST as sponge candidates for these miRNAs. The GSEA results identified 15 core genes involved in HSC activation, primarily enriched in NF-κB activation and autophagy pathways. STAT3, TCF3, RELA, and RUNX1 were considered potential transcription factors connected to miRNAs in the TF-miR network. Our study elucidated three candidate circulating miRNAs differentially expressed in NAFLD that could serve as a promising non-invasive diagnostic tool for early detection strategies. Also, NF-κB activation, autophagy, and negative regulation of the apoptotic process are the main potential underlying mechanisms regulated by these miRNAs in liver fibrosis pathogenesis.

Muscle miRNAs are influenced by sex at baseline and in response to exercise

BACKGROUND

Sex differences in microRNA (miRNA) expression profiles have been found across multiple tissues. Skeletal muscle is one of the most sex-biased tissues of the body. MiRNAs are necessary for development and have regulatory roles in determining skeletal muscle phenotype and have important roles in the response to exercise in muscle. Yet there is limited research into the role and regulation of miRNAs in the skeletal muscle at baseline and in response to exercise, a well-known modulator of miRNA expression. The aim of this study was to investigate the effect of sex on miRNA expression in the skeletal muscle at baseline and after an acute bout of high-intensity interval exercise. A total of 758 miRNAs were measured using Taqman®miRNA arrays in the skeletal muscle of 42 healthy participants from the Gene SMART study (23 males and 19 females of comparable fitness levels and aged 18-45 years), of which 308 were detected. MiRNAs that differed by sex at baseline and whose change in expression following high-intensity interval exercise differed between the sexes were identified using mixed linear models adjusted for BMI and Wpeak. We performed in silico analyses to identify the putative gene targets of the exercise-induced, sex-specific miRNAs and overrepresentation analyses to identify enriched biological pathways. We performed functional assays by overexpressing two sex-biased miRNAs in human primary muscle cells derived from male and female donors to understand their downstream effects on the transcriptome.

RESULTS

At baseline, 148 miRNAs were differentially expressed in the skeletal muscle between the sexes. Interaction analysis identified 111 miRNAs whose response to an acute bout of high-intensity interval exercise differed between the sexes. Sex-biased miRNA gene targets were enriched for muscle-related processes including proliferation and differentiation of muscle cells and numerous metabolic pathways, suggesting that miRNAs participate in programming sex differences in skeletal muscle function. Overexpression of sex-biased miRNA-30a and miRNA-30c resulted in profound changes in gene expression profiles that were specific to the sex of the cell donor in human primary skeletal muscle cells.

CONCLUSIONS

We uncovered sex differences in the expression levels of muscle miRNAs at baseline and in response to acute high-intensity interval exercise. These miRNAs target regulatory pathways essential to skeletal muscle development and metabolism. Our findings highlight that miRNAs play an important role in programming sex differences in the skeletal muscle phenotype.

Cardiomyocyte-specific disruption of the circadian BMAL1-REV-ERBα/β regulatory network impacts distinct miRNA species in the murine heart

Circadian disruption increases cardiovascular disease (CVD) risk, through poorly understood mechanisms. Given that small RNA species are critical modulators of cardiac physiology/pathology, we sought to determine the extent to which cardiomyocyte circadian clock (CCC) disruption impacts cardiac small RNA species. Accordingly, we collected hearts from cardiomyocyte-specific Bmal1 knockout (CBK; a model of CCC disruption) and littermate control (CON) mice at multiple times of the day, followed by small RNA-seq. The data reveal 47 differentially expressed miRNAs species in CBK hearts. Subsequent bioinformatic analyses predict that differentially expressed miRNA species in CBK hearts influence processes such as circadian rhythmicity, cellular signaling, and metabolism. Of the induced miRNAs in CBK hearts, 7 are predicted to be targeted by the transcriptional repressors REV-ERBα/β (integral circadian clock components that are directly regulated by BMAL1). Similar to CBK hearts, cardiomyocyte-specific Rev-erbα/β double knockout (CM-RevDKO) mouse hearts exhibit increased let-7c-1-3p, miR-23b-5p, miR-139-3p, miR-5123, and miR-7068-3p levels. Importantly, 19 putative targets of these 5 miRNAs are commonly repressed in CBK and CM-RevDKO heart (of which 16 are targeted by let-7c-1-3p). These observations suggest that disruption of the circadian BMAL1-REV-ERBα/β regulatory network in the heart induces distinct miRNAs, whose mRNA targets impact critical cellular functions.

Role of dysregulated ferroptosis‑related genes in cardiomyocyte ischemia‑reperfusion injury: Experimental verification and bioinformatics analysis

Acute myocardial infarction is a life-threatening condition with high mortality and complication rates. Although myocardial reperfusion can preserve ischemic myocardial tissue, it frequently exacerbates tissue injury, a phenomenon known as ischemia-reperfusion injury (IRI). However, the underlying pathological mechanisms of IRI remain to be completely understood. Ferroptosis is a novel type of regulated cell death that is associated with various pathological conditions, including angiocardiopathy. The purpose of this article was to elucidate the possible mechanistic role of ferroptosis in IRI through bioinformatics analysis and experimental validation. Healthy and IRI heart samples were screened for differentially expressed ferroptosis-related genes and functional enrichment analysis was performed to determine the potential crosstalk and pathways involved. A protein-protein interaction network was established for IRI, and 10 hub genes that regulate ferroptosis, including HIF1A, EGFR, HMOX1, and ATF3 were identified. In vitro, an anoxia/reoxygenation (A/R) injury model was established using H9c2 cardiomyoblasts to validate the bioinformatics analysis results, and extensive ferroptosis was detected. A total of 4 key hub genes and 3 key miRNAs were also validated. It was found that IRI was related to the aberrant infiltration of immune cells and the small-molecule drugs that may protect against IRI by preventing ferroptosis were identified. These results provide novel insights into the role of ferroptosis in IRI, which can help identify novel therapeutic targets.

Identification of characteristic genes and construction of regulatory network in gallbladder carcinoma

BACKGROUND

Gallbladder carcinoma (GBC) is a highly malignant tumor with a poor overall prognosis. This study aimed to identify the characteristic microRNAs (miRNAs) of GBC and the competing endogenous RNA (ceRNA) regulatory mechanisms.

METHODS

The microarray data of GBC tissue samples and normal gallbladder (NGB) tissue samples from the Gene Expression Omnibus (GEO) database was downloaded. GBC-related differentially expressed miRNAs (DE-miRNAs) were identified by inter-group differential expression analysis and weighted gene co-expression network analysis (WGCNA). Machine learning algorithms were used to screen the characteristic miRNA based on the intersect between least absolute shrinkage and selection operator (LASSO) and Support vector machine-recursive feature elimination (SVM-RFE). Based on the differential expression analysis of GEO database, the ceRNA network of characteristic miRNA was predicted and constructed. The biological functions of the ceRNA network were revealed by carrying out the gene enrichment analysis was implemented. We further screened the key genes of ceRNA network and constructed a protein-protein interaction (PPI) network, and predicted and generated the transcription factors (TFs) network of signature miRNAs. The expression of characteristic miRNA in clinical samples was verified by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

A total of 131 GBC-related DE-miRNAs were obtained. The hsa-miR-4770 was defined as characteristic miRNA for GBC. The ceRNA network containing 211 mRNAs, one miRNA, two lncRNAs, and 48 circRNAs was created. Gene enrichment analysis suggested that the downstream genes were mainly involved in actin filament organization, cell-substrate adhesion, cell-matrix adhesion, reactive oxygen species metabolic process, glutamine metabolic process and extracellular matrix (ECM)-receptor interaction pathway. 10 key genes in the network were found to be most correlated with disease, and involved in cell cycle-related processes, p53, and extrinsic apoptotic signaling pathways. The qRT-PCR result demonstrated that hsa-miR-4770 is down-regulated in GBC, and the expression trend is consistent with the public database.

CONCLUSIONS

We identified hsa-miR-4770 as the characteristic miRNA for GBC. The ceRNA network of hsa-miR-4770 may play key roles in GBC. This study provided some basis for potential pathogenesis of GBC.

Epididymal segment-specific miRNA and mRNA regulatory network at the single cell level

Spermatozoa released from the testis cannot fertilize an egg before becoming mature and motile in the epididymis. Based on three bulk and one single-cell RNA-seq (scRNA-seq) data series, we compared mRNA or miRNA expression between epididymal segment-specific samples and the other samples. Hereby, we identified 570 differentially expressed mRNAs (DE-mRNAs) and 23 differentially expressed miRNAs (DE-miRNAs) in the caput, 175 DE-mRNAs and 15 DE-miRNAs in the corpus, 946 DE-mRNAs and 12 DE-miRNAs in the cauda. In accordance with respective DE-miRNAs, we predicted upstream transcription factors (TFs) and downstream target genes. Subsequently, we intersected target genes of respective DE-miRNAs with corresponding DE-mRNAs, thereby obtaining 127 upregulated genes in the caput and 92 upregulated genes in cauda. Enriched upregulated pathways included cell motility-related pathways for the caput, smooth muscle-related pathways for the corpus, and immune-associated pathways for the cauda. Protein-protein interaction (PPI) network was constructed to extract key module for the caput and cauda, followed by identifying hub genes through cytohubba. Epididymis tissues from six mice were applied to validate hub genes expression using qRT-PCR, and 7 of the 10 genes displayed identical expression trends in mice caput/cauda. These hub genes were found to be predominantly distributed in spermatozoa using scRNA-seq data. In addition, target genes of DE-miRNAs were intersected with genes in the PPI network for each segment. Subsequently, the miRNA and mRNA regulatory networks for the caput and cauda were constructed. Conclusively, we uncover segment-specific miRNA-mRNA regulatory network, upstream TFs, and downstream pathways of the human epididymis, warranting further investigation into epididymal segment-specific functions.

DEJKMDR: miRNA-disease association prediction method based on graph convolutional network

Numerous studies have shown that miRNAs play a crucial role in the investigation of complex human diseases. Identifying the connection between miRNAs and diseases is crucial for advancing the treatment of complex diseases. However, traditional methods are frequently constrained by the small sample size and high cost, so computational simulations are urgently required to rapidly and accurately forecast the potential correlation between miRNA and disease. In this paper, the DEJKMDR, a graph convolutional network (GCN)-based miRNA-disease association prediction model is proposed. The novelty of this model lies in the fact that DEJKMDR integrates biomolecular information on miRNA and illness, including functional miRNA similarity, disease semantic similarity, and miRNA and disease similarity, according to their Gaussian interaction attribute. In order to minimize overfitting, some edges are randomly destroyed during the training phase after DropEdge has been used to regularize the edges. JK-Net, meanwhile, is employed to combine various domain scopes through the adaptive learning of nodes in various placements. The experimental results demonstrate that this strategy has superior accuracy and dependability than previous algorithms in terms of predicting an unknown miRNA-disease relationship. In a 10-fold cross-validation, the average AUC of DEJKMDR is determined to be 0.9772.

Somatic mutation effects diffused over microRNA dysregulation

MOTIVATION

As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest disease and dictate prognosis. Previous studies that tried to correlate mutation with gene expression dysregulation neglected to adjust for the disparate multitudes of false positives associated with unequal sample sizes and uneven class balancing scenarios.

RESULTS

To properly address this issue, we developed a statistical framework to rigorously assess the extent of mutation impact on microRNAs in relation to a permutation-based null distribution of a matching sample structure. Carrying out the framework in a pan-cancer study, we ascertained 9008 protein-coding genes with statistically significant mutation impacts on miRNAs. Of these, the collective miRNA expression for 83 genes showed significant prognostic power in nine cancer types. For example, in lower-grade glioma, 10 genes' mutations broadly impacted miRNAs, all of which showed prognostic value with the corresponding miRNA expression. Our framework was further validated with functional analysis and augmented with rich features including the ability to analyze miRNA isoforms; aggregative prognostic analysis; advanced annotations such as mutation type, regulator alteration, somatic motif, and disease association; and instructive visualization such as mutation OncoPrint, Ideogram, and interactive mRNA-miRNA network.

AVAILABILITY AND IMPLEMENTATION

The data underlying this article are available in MutMix, at http://innovebioinfo.com/Database/TmiEx/MutMix.php.

The intracellular parasite Anncaliia algerae induces a massive miRNA down-regulation in human cells

Anncaliia algerae belongs to microsporidia, a group of obligate intracellular parasites related to fungi. These parasites are largely spread in water and food-webs and can infect a wide variety of hosts ranging from invertebrates to vertebrates including humans. In humans, microsporidian infections are mainly opportunistic as immunocompetent hosts can clear parasites naturally. Recent studies however have reported persistent microsporidian infections and have highlighted them as a risk factor in colon cancer. This may be a direct result of cell infection or may be an indirect effect of the infectious microenvironment and the host's response. In both cases, this raises the question of the effects of microsporidian infection at the host and host-cell levels. We aimed to address the question of human host intracellular response to microsporidian infection through a transcriptomic kinetic study of human foreskin fibroblasts (HFF) infected with A.algerae, a human infecting microsporidia with an exceptionally wide host range. We focused solely on host response studying both coding and small non-coding miRNA expression. Our study revealed a generalized down-regulation of cell miRNAs throughout infection with up to 547 different miRNAs downregulated at some timepoints and also transcriptomic dysregulations that could facilitate parasite development with immune and lipid metabolism genes modulation. We also hypothesize possible small nucleic acid expropriation explaining the miRNA downregulation. This work contributes to a better understanding of the dialogue that can occur between an intracellular parasite and its host at the cellular level, and can guide future studies on microsporidian infection biology to unravel the mode of action of these minimalist parasites at the tissue or host levels.We have also generated a kinetic and comprehensive transcriptomic data set of an infectious process that can help support comparative studies in the broader field of parasitology. Lastly, these results may warrant for caution regarding microsporidian exposure and persistent infections.

MiR-375 promotes cisplatin sensitivity of lung adenocarcinoma

BACKGROUND

Cisplatin-based chemotherapy has been widely used in the treatment of lung adenocarcinoma (LUAD). However, the development of cisplatin resistance becomes a major obstacle impeding the curative effect. It remains necessary to uncover the molecular mechanism of cisplatin resistance.

METHODS

Based on the CCLE database, lung cancer cell lines were divided into cisplatin-resistant and cisplatin-sensitive groups. The differentially expressed miRNAs were filtered and further identified by survival prognosis analysis. After transfection with miR-375 inhibitor or mimic, cell cytotoxicity assay, flow cytometry and western blot were conducted to validate the role of miR-375. The transcription factor (TF)-miRNA network was constructed based on TransmiR. The target genes of miR-375 were predicted by Starbase and further verified by RT-qPCR and immunohistochemistry results in the Human Protein Atlas. Functional enrichment analysis was performed with GO terms and KEGG.

RESULTS

In this study, miR-375 showed the ability to promote cisplatin sensitivity and apoptosis of LUAD. Genes correlated with miR-375 in LUAD were analyzed and ABCC8 showed the strongest positive correlation. Moreover, transcription factors that regulate miR-375 expression were predicted. MBNL1, PTPN3, PRKD1 and RPN1 were identified as the target genes of miR-375. Enrichment analysis demonstrated that miR-375-related genes associated with promoting cell proliferation and anti-apoptosis were involved in the MAPK signaling pathway.

CONCLUSION

Overall, this study provides new insights into the role of miR-375 in the cisplatin sensitivity of LUAD. Our present findings may serve as a theoretical basis for new therapeutic strategies and predictive models of cisplatin resistance in LUAD.

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer-Advances and Challenges

There is an urgent unmet need for robust and reliable biomarkers for early diagnosis, prognosis, and prediction of response to specific treatments of many aggressive and deadly cancers, such as pancreatic cancer, and liquid biopsy-based miRNA profiling has the potential for this. MiRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many cancers, functioning as either oncomes or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling of dysregulated miRNAs in pancreatic cancer has been shown to correlate with disease diagnosis, indicate optimal treatment options and predict response to a specific therapy. Specific miRNA signatures can track the stages of pancreatic cancer and hold potential as diagnostic, prognostic, and predictive markers, as well as therapeutics such as miRNA mimics and miRNA inhibitors (antagomirs). Furthermore, identified specific miRNAs and genes they regulate in pancreatic cancer along with downstream pathways can be used as potential therapeutic targets. However, a limited understanding and validation of the specific roles of miRNAs, lack of tissue specificity, methodological, technical, or analytical reproducibility, harmonization of miRNA isolation and quantification methods, the use of standard operating procedures, and the availability of automated and standardized assays to improve reproducibility between independent studies limit bench-to-bedside translation of the miRNA biomarkers for clinical applications. Here I review recent findings on miRNAs in pancreatic cancer pathogenesis and their potential as diagnostic, prognostic, and predictive markers.

Identification of Renal Transplantation Rejection Biomarkers in Blood Using the Systems Biology Approach

Background

Renal transplantation plays an essential role in the quality of life of patients with end-stage renal disease. At least 12% of the renal patients receiving transplantations show graft rejection. One of the methods used to diagnose renal transplantation rejection is renal allograft biopsy. This procedure is associated with some risks such as bleeding and arteriovenous fistula formation. In this study, we applied a bioinformatics approach to identify serum markers for graft rejection in patients receiving a renal transplantation.

Methods

Transcriptomic data were first retrieved from the blood of renal transplantation rejection patients using the GEO database. The data were then used to construct the protein-protein interaction and gene regulatory networks using Cytoscape software. Next, network analysis was performed to identify hub-bottlenecks, and key blood markers involved in renal graft rejection. Lastly, the gene ontology and functional pathways related to hub-bottlenecks were detected using PANTHER and DAVID servers.

Results

In PPIN and GRN, SYNCRIP, SQSTM1, GRAMD1A, FAM104A, ND2, TPGS2, ZNF652, RORA, and MALAT1 were the identified critical genes. In GRN, miR-155, miR17, miR146b, miR-200 family, and GATA2 were the factors that regulated critical genes. The MAPK, neurotrophin, and TNF signaling pathways, IL-17, and human cytomegalovirus infection, human papillomavirus infection, and shigellosis were identified as significant pathways involved in graft rejection.

Concusion

The above-mentioned genes can be used as diagnostic and therapeutic serum markers of transplantation rejection in renal patients. The newly predicted biomarkers and pathways require further studies.

Identification of potential biomarkers for idiopathic pulmonary fibrosis and validation of TDO2 as a potential therapeutic target

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with a high mortality rate. On this basis, exploring potential therapeutic targets to meet the unmet needs of IPF patients is important.

AIM

To explore novel hub genes for IPF therapy.

METHODS

Here, we used public datasets to identify differentially expressed genes between IPF patients and healthy donors. Potential targets were considered based on multiple bioinformatics analyses, especially the correlation between hub genes and carbon monoxide diffusing capacity of carbon monoxide, forced vital capacity, and patient survival rate. The mRNA levels of the hub genes were determined through quantitative real-time polymerase chain reaction.

RESULTS

We found that TDO2 was upregulated in IPF patients and predicted poor prognosis. Surprisingly, single-cell RNA sequencing data analysis revealed significant enrichment of TDO2 in alveolar fibroblasts, indicating that TDO2 may participate in the regulation of proliferation and survival. Therefore, we verified the upregulated expression of TDO2 in an experimental mouse model of transforming growth factor-β (TGF-β)-induced pulmonary fibrosis. Furthermore, the results showed that a TDO2 inhibitor effectively suppressed TGF-β-induced fibroblast activation. These findings suggest that TDO2 may be a potential target for IPF treatment. Based on transcription factors-microRNA prediction and scRNA-seq analysis, elevated TDO2 promoted the IPF proliferation of fibroblasts and may be involved in the P53 pathway and aggravate ageing and persistent pulmonary fibrosis.

CONCLUSION

We provided new target genes prediction and proposed blocking TGF-β production as a potential treatment for IPF.

In-silico engineering of RNA nanoplatforms to promote the diabetic wound healing

One of the most notable required features of wound healing is the enhancement of angiogenesis, which aids in the acceleration of regeneration. Poor angiogenesis during diabetic wound healing is linked to a shortage of pro-angiogenic or an increase in anti-angiogenic factors. As a result, a potential treatment method is to increase angiogenesis promoters and decrease suppressors. Incorporating microRNAs (miRNAs) and small interfering RNAs (siRNAs), two forms of quite small RNA molecules, is one way to make use of RNA interference. Several different types of antagomirs and siRNAs are now in the works to counteract the negative effects of miRNAs. The purpose of this research is to locate novel antagonists for miRNAs and siRNAs that target multiple genes to promote angiogenesis and wound healing in diabetic ulcers.In this context, we used gene ontology analysis by exploring across several datasets. Following data analysis, it was processed using a systems biology approach. The feasibility of incorporating the proposed siRNAs and miRNA antagomirs into polymeric bioresponsive nanocarriers for wound delivery was further investigated by means of a molecular dynamics (MD) simulation study. Among the three nanocarriers tested (Poly (lactic-co-glycolic acid) (PLGA), Polyethylenimine (PEI), and Chitosan (CTS), MD simulations show that the integration of PLGA/hsa-mir-422a is the most stable (total energy = -1202.62 KJ/mol, Gyration radius = 2.154 nm, and solvent-accessible surface area = 408.416 nm2). With values of -25.437 KJ/mol, 0.047 nm for the Gyration radius, and 204.563 nm2 for the SASA, the integration of the second siRNA/ Chitosan took the last place. The results of the systems biology and MD simulations show that the suggested RNA may be delivered through bioresponsive nanocarriers to speed up wound healing by boosting angiogenesis.

A comprehensive investigation of histotype-specific microRNA and their variants in Stage I epithelial ovarian cancers

isomiRs, the sequence-variants of microRNA, are known to be tissue and cell type specific but their physiological role is largely unknown. In our study, we explored for the first time the expression of isomiRs across different Stage I epithelial ovarian cancer (EOC) histological subtypes, in order to shed new light on their biological role in tumor growth and progression. In a multicentric retrospective cohort of tumor biopsies (n = 215) we sequenced small RNAs finding 971 expressed miRNAs, 64% of which are isomiRs. Among them, 42 isomiRs showed a clear histotype specific pattern, confirming our previously identified miRNA markers (miR192/194 and miR30a-3p/5p for mucinous and clear cell subtypes, respectively) and uncovering new biomarkers for all the five subtypes. Using integrative models, we found that the 38% of these miRNA expression alterations is the result of copy number variations while the 17% of differential transcriptional activities. Our work represents the first attempt to characterize isomiRs expression in Stage I EOC within and across subtypes and to contextualize their alterations in the framework of the large genomic heterogeneity of this tumor.