Integrated mRNA and miRNA analysis reveals the regulatory network of oxidative stress and inflammation in Coilia nasus brains during air exposure and salinity mitigation.

BACKGROUND: Air exposure is an inevitable source of stress that leads to significant mortality in Coilia nasus. Our previous research demonstrated that adding 10‰ NaCl to aquatic water could enhance survival rates, albeit the molecular mechanisms involved in air exposure and salinity mitigation remained unclear. Conversely, salinity mitigation resulted in decreased plasma glucose levels and improved antioxidative activity. To shed light on this phenomenon, we characterized the transcriptomic changes in the C. nasus brain upon air exposure and salinity mitigation by integrated miRNA-mRNA analysis. RESULTS: The plasma glucose level was elevated during air exposure, whereas it decreased during salinity mitigation. Antioxidant activity was suppressed during air exposure, but was enhanced during salinity mitigation. A total of 629 differentially expressed miRNAs (DEMs) and 791 differentially expressed genes (DEGs) were detected during air exposure, while 429 DEMs and 1016 DEGs were identified during salinity mitigation. GO analysis revealed that the target genes of DEMs and DEGs were enriched in biological process and cellular component during air exposure and salinity mitigation. KEGG analysis revealed that the target genes of DEMs and DEGs were enriched in metabolism. Integrated analysis showed that 24 and 36 predicted miRNA-mRNA regulatory pairs participating in regulating glucose metabolism, Ca2+ transport, inflammation, and oxidative stress. Interestingly, most of these miRNAs were novel miRNAs. CONCLUSION: In this study, substantial miRNA-mRNA regulation pairs were predicted via integrated analysis of small RNA sequencing and RNA-Seq. Based on predicted miRNA-mRNA regulation and potential function of DEGs, miRNA-mRNA regulatory network involved in glucose metabolism and Ca2+ transport, inflammation, and oxidative stress in C. nasus brain during air exposure and salinity mitigation. They regulated the increased/decreased plasma glucose and inhibited/promoted antioxidant activity during air exposure and salinity mitigation. Our findings would propose novel insights to the mechanisms underlying fish responses to air exposure and salinity mitigation.

miRNA-mRNA Network in PBMCs of PCOS Women Identifies Overactivated Stress-Activated Kinases.

BACKGROUND/AIMS: Earlier studies have revealed the miRNAs and mRNAs involved in Polycystic Ovarian Syndrome (PCOS), but little is known about their regulatory networks. METHODS: To address this issue, we applied a comprehensive miRNA, mRNA profiling approach in peripheral blood of PCOS patients. We identified 30 differential miRNAs and 3310 differential transcripts. A robust computational framework was created to integrate matched miRNA and mRNA expression profiles in PCOS using feed-forward loops. RESULTS: The network consisted of differential miRNAs, transcription factors (TFs), and their common predicted target genes. The key network consisted of 14 non-orphan network clusters with 50 TF-gene pairs, 8 TF-TF pairs, 6 miRNA-TF pairs and 36 miRNA- gene pairs which were later dissected into 16 subclusters. Gene ontology annotations revealed that a host of signals (hormone, growth factors -EGF/ PDGF, thrombopoietin, oxidative stress and vitamin/nutrition) regulate MAPK signaling altering angiogenesis, JAK-STAT signaling, apoptosis, inflammatory and immune response and steroidogenesis in PCOS women. CONCLUSION: MAPK signaling is identified as the syndrome´s major dysregulated pathway. Our data imparts a robust foundation to expand the work and pave the way to focus efforts on p38MAPK targeted therapeutic strategies in PCOS.

Significance of a tumor microenvironment-mediated P65-miR-30a-5p-BCL2L11 amplification loop in multiple myeloma.

Despite significant progress in the treatment of myeloma, multiple myeloma (MM) remains an incurable hematological malignancy due to cell adhesion-mediated drug resistance (CAM-DR) phenotype. However, data on the molecular mechanisms underlying the CAM-DR remains scanty. Here, we identified a miRNA-mRNA regulatory network in myeloma cells that are directly adherent to bone marrow stromal cells (BMSCs). Our data showed that the BMSCs up-regulated miR-30a-5p and down-regulated BCL2L11 at both mRNA and protein level in the myeloma cells. Besides, luciferase reporter genes demonstrated direct interaction between miR-30a-5p and BCL2L11 gene. Moreover, the BMSCs activated NF-ΚB signaling pathway in myeloma cells and the NF-κB P65 was shown to directly bind the miR-30a-5p promoter region. Moreover, suppression of the miR-30a-5p or upregulation of the BCL2L11 promoted apoptosis of the myeloma cells independent of the BMSCs, thus suggesting clinical significance of miR-30a-5p inhibitor and PLBCL2L11 plasmid in CAM-DR. Together, our data demonstrated the role of P65-miR-30a-5p-BCL2L11 loop in CAM-DR myeloma cells. These findings give new insights into the role of tumor microenvironment in the treatment of patients with myeloma.

Interactions between circRNAs and miR-141 in Cancer: From Pathogenesis to Diagnosis and Therapy.

The function of non-coding RNAs (ncRNAs) in the pathogenesis and development of cancer is indisputable. Molecular mechanisms underlying carcinogenesis involve the aberrant expression of ncRNAs, including circular RNAs (circRNAs), and microRNAs (miRNAs). CircRNAs are a class of single-stranded, covalently closed RNAs responsible for maintaining cellular homeostasis through their diverse functions. As a part of the competing endogenous RNA (ceRNAs) network, they play a central role in the regulation of accessibility of miRNAs to their mRNA targets. The interplay between these molecular players is based on the primary role of circRNAs that act as miRNAs sponges, and the circRNA/miRNA imbalance plays a central role in different pathologies including cancer. Herein, we present the latest state of knowledge about interactions between circRNAs and miR-141, a well-known member of the miR-200 family, in malignant transformation, with emphasis on the biological role of circRNA/miR-141/mRNA networks as a future target for novel anti-cancer therapies.

Integrated microarray for identifying the hub mRNAs and constructed miRNA-mRNA network in coronary in-stent restenosis.

As a major complication after percutaneous coronary intervention (PCI) in patients who suffer from coronary artery disease, in-stent restenosis (ISR) poses a significant challenge for clinical management. A miRNA-mRNA regulatory network of ISR can be constructed to better reveal the occurrence of ISR. The relevant data set from the Gene Expression Omnibus (GEO) database was downloaded, and 284 differentially expressed miRNAs (DE-miRNAs) and 849 differentially expressed mRNAs (DE-mRNAs) were identified. As predicted by online tools, 65 final functional genes (FmRNAs) were overlapping DE-mRNAs and DE-miRNAs target genes. In the biological process (BP) terms of gene ontology (GO) functional analysis, the FmRNAs were mainly enriched in the cellular response to peptide, epithelial cell proliferation, and response to peptide hormone. In the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the FmRNAs were mainly enriched in breast cancer, endocrine resistance, and Cushing syndrome. Jun proto-oncogene, activator protein-1 (AP-1) transcription factor subunit (JUN), insulin-like growth factor 1 receptor (IGF1R), member RAS oncogene family (RAB14), specificity protein 1 (SP1), protein tyrosine phosphatase nonreceptor type 1 (PTPN1), DDB1 and CUL4 associated factor 10 (DCAF10), retinoblastoma-binding protein 5 (RBBP5), and eukaryotic initiation factor 4A-I (EIF4A1) were hub genes in the protein-protein interaction network (PPI network). The miRNA-mRNA network containing DE-miRNAs and hub genes was built. Hsa-miR-139-5p-JUN, hsa-miR-324-5p-SP1 axis pairs were found in the miRNA-mRNA network, which could promote ISR development. The aforementioned results indicate that the miRNA-mRNA network constructed in ISR has a regulatory role in the development of ISR and may provide new approaches for clinical treatment and experimental development.

Using biological information to analyze potential miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer.

BACKGROUND: Lung cancer is the most common malignant tumor, and it has a high mortality rate. However, the study of miRNA-mRNA regulatory networks in the plasma of patients with non-small cell lung cancer (NSCLC) is insufficient. Therefore, this study explored the differential expression of mRNA and miRNA in the plasma of NSCLC patients. METHODS: The Gene Expression Omnibus (GEO) database was used to download microarray datasets, and the differentially expressed miRNAs (DEMs) were analyzed. We predicted transcription factors and target genes of the DEMs by using FunRich software and the TargetScanHuman database, respectively. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for GO annotation and KEGG enrichment analysis of downstream target genes. We constructed protein-protein interaction (PPI) and DEM-hub gene networks using the STRING database and Cytoscape software. The GSE20189 dataset was used to screen out the key hub gene. Using The Cancer Genome Atlas (TCGA) and UALCAN databases to analyze the expression and prognosis of the key hub gene and DEMs. Then, GSE17681 and GSE137140 datasets were used to validate DEMs expression. Finally, the receiver operating characteristic (ROC) curve was used to verify the ability of the DEMs to distinguish lung cancer patients from healthy patients. RESULTS: Four upregulated candidate DEMs (hsa-miR199a-5p, hsa-miR-186-5p, hsa-miR-328-3p, and hsa-let-7d-3p) were screened from 3 databases, and 6 upstream transcription factors and 2253 downstream target genes were predicted. These genes were mainly enriched in cancer pathways and PI3k-Akt pathways. Among the top 30 hub genes, the expression of KLHL3 was consistent with the GSE20189 dataset. Except for let-7d-3p, the expression of other DEMs and KLHL3 in tissues were consistent with those in plasma. LUSC patients with high let-7d-3p expression had poor overall survival rates (OS). External validation demonstrated that the expression of hsa-miR-199a-5p and hsa-miR-186-5p in peripheral blood of NSCLC patients was higher than the healthy controls. The ROC curve confirmed that the DEMs could better distinguish lung cancer patients from healthy people. CONCLUSION: The results showed that miR-199a-5p and miR-186-5p may be noninvasive diagnostic biomarkers for NSCLC patients. MiR-199a-5p-KLHL3 may be involved in the occurrence and development of NSCLC.

Comprehensive analysis of differentially expressed mRNA and circRNA in Ankylosing spondylitis patients' platelets.

Ankylosing spondylitis (AS) is a chronic inflammatory disease significantly decreasing the quality of life. Platelets play an important and active role in the development of AS. Accumulating evidence demonstrated platelets contain diverse RNA repository inherited from megakaryocytes or microvesicles. Platelet RNAs are dynamically affected by pathological conditions and could be used as diagnostic or prognostic biomarkers. However, the role of the platelet RNAs in AS is elusive. In this study, we compared mRNA and circRNA profiles in platelets between AS patients and healthy controls using RNA sequencing and bioinformatic analysis, and found 4996 mRNAs and 2942 circRNAs were differently expressed. The significantly over-expressed mRNAs in AS patients are involved in platelet activity, gap junction, focal adhesion, rap1 and toll and Imd signaling pathway. The previous identified platelet-derived immune mediators such as P2Y1, P2Y12, PF4, GPIbα, CD40L, ICAM2, CCL5 (RANTES), TGF-ß (TGF-ß1 and TGF-ß2) and PDGF (PDGFB and PDGFA) are also included in these over expressed mRNAs, implying these factors may trigger inflammatory cascades and promote the development of AS. Additionally, we found two down-regulated circRNA (circPTPN22 and circFCHSD2) from the intersection analyses of platelets and spinal ligament tissues of AS patients. The circRNA-miRNA-mRNA regulatory network of these two circRNAs was constructed, and the target mRNAs were enriched in Th17 cell differentiation, inflammatory bowel disease, cell adhesion molecules, cytokine-cytokine receptor interaction, Jak-STAT and Wnt signaling pathway, all these pathways participate in the bone remodeling and pro/anti-inflammatory immune regulation in AS. Then, qRT-PCR was performed to validate the expression of selected key mRNAs and circRNAs and the results demonstrated that the expression levels of P2Y12, GPIbα, circPTPN22 and circFCHSD2 were consistent with the sequencing analysis. In addition, the high expression of five predicted miRNAs interacting with circPTPN22 and circFCHSD2 were also detected in AS by qRT-PCR. Taken together, our study presents a comprehensive overview of mRNAs and circRNAs in platelets in AS patients and offers new insight into the mechanisms of platelet involving in the pathogenesis of AS. The mRNAs and circRNAs identified in this study may serve as candidates for diagnosis and targeted treatment of AS.

Developing metabolic gene signatures to predict intrahepatic cholangiocarcinoma prognosis and mining a miRNA regulatory network.

BACKGROUND: Metabolic disturbance is closely correlated with intrahepatic cholangiocarcinoma (IHCC), and we aimed to identify metabolic gene marker for the prognosis of IHCC. METHODS: We obtained expression and clinical data from 141 patients with IHCC from public databases. Prognostic metabolic genes were selected using univariate Cox regression analysis. Unsupervised cluster analysis was applied to identify IHCC subtypes, and CIBERSORT was used for immune infiltration analysis of different subtypes. Then, the metabolic gene signature was screened using multivariate Cox regression analysis and the LASSO algorithm. The prognostic potential and regulatory network of the metabolic gene signature were further investigated. RESULTS: We screened 228 prognosis-related metabolic genes. Based on their expression levels, IHCC samples were divided into two subtypes, which showed significant differences in survival and immune cell infiltration. After LASSO analysis, eight metabolic genes including CYP19A1, SCD5, ACOT8, SRD5A3, MOGAT2, PFKFB3, PPARGC1B, and RPL17 were identified as the optimal genes for the prognosis signature. The prognostic model had excellent predictive abilities, with areas under the receiver-operating characteristic curves over 0.8. A nomogram model was also established based on two independent prognostic clinical factors (pathologic stage and prognostic model), and the generated calibration curves and c-indexes determined its excellent accuracy and discriminative ability to predict 1- and 5-year survival status (c-indexes>0.7). Finally, we found that miR-26a-5p, miR-27a-3p, and miR-27b-3p were the upstream regulators that mediate the involvement of gene signatures in metabolic pathways. CONCLUSION: We developed eight metabolic gene signatures to predict IHCC prognosis and proposed potential upstream regulatory axes of gene signatures.

Integrated analysis of microRNA and mRNA expression profiles in homozygous familial hypercholesterolemia patients and validation of atherosclerosis associated critical regulatory network.

Homozygous familial hypercholesterolemia (HoFH) is a rare, life-threatening genetic disorder characterized by an extremely elevated serum level of low-density lipoprotein cholesterol (LDL-C) and accelerated premature atherosclerotic cardiovascular diseases (ASCVD). However, the detailed mechanism of how the pathogenic mutations of HoFH trigger the acceleration of ASCVD is not well understood. Therefore, we performed high-throughput RNA and small RNA sequencing on the peripheral blood RNA samples of six HoFH patients and three healthy controls. The gene and miRNA expression differences were analyzed, and seven miRNAs and six corresponding genes were screened out through regulatory network analysis. Validation through quantitative PCR of genes and miRNAs from 52 HoFH patients and 20 healthy controls revealed that the expression levels of hsa-miR-486-3p, hsa-miR-941, and BIRC5 were significantly upregulated in HoFH, while ID1, PLA2G4C, and CACNA2D2 were downregulated. Spearman correlation analysis found that the levels of ID1, hsa-miR-941, and hsa-miR-486-3p were significantly correlated with additional ASCVD risk factors in HoFH patients. This study represents the first integrated analysis of transcriptome and miRNA expression profiles in patients with HoFH, a rare disease, and as a result, six differentially expressed miRNAs/genes that may be related to atherosclerosis in HoFH are reported. The miRNA-mRNA regulatory network may be the critical regulation mechanism by which ASCVD is accelerated in HoFH.

Integrated Microarray to Identify the Hub miRNAs and Constructed miRNA-mRNA Network in Neuroblastoma Via Bioinformatics Analysis.

Neuroblastomas (NB) are childhood malignant tumors originating in the sympathetic nervous system. MicroRNAs (miRNAs) play an essential regulatory role in tumorigenesis and development. In this study, NB miRNA and mRNA expression profile data in the Gene Expression Omnibus database were used to screen for differentially expressed miRNAs (DEMs) and genes (DEGs). We used the miRTarBase and miRSystem databases to predict the target genes of the DEMs, and we selected target genes that overlapped with the DEGs as candidate genes for further study. Annotations, visualization, and the DAVID database were used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the candidate genes. Additionally, the protein-protein interaction (PPI) network and miRNA-mRNA regulatory network were constructed and visualized using the STRING database and Cytoscape, and the hub modules were analyzed for function and pathway enrichment using the DAVID database and BiNGO plug-in. 107 DEMs and 1139 DEGs were identified from the miRNA and mRNA chips, respectively. 4390 overlapping target genes were identified using the two databases, and 405 candidate genes which intersected with the DEGs were selected. These candidate genes were enriched in 363 GO terms and 24 KEGG pathways. By constructing a PPI network and a miRNA-mRNA regulatory network, three hub miRNAs (hsa-miR-30e-5p, hsa-miR-15a, and hsa-miR-16) were identified. The target genes of the hub miRNAs were significantly enriched in the following pathways: microRNAs in cancer, the PI3K-Akt signaling pathway, pathways in cancer, the p53 signaling pathway, and the cell cycle. In summary, our results have identified candidate genes and pathways related to the underlying molecular mechanism of NB. These findings provide a new perspective for NB research and treatment.

Integrated small RNA and Degradome sequencing provide insights into salt tolerance in sesame (Sesamum indicum L.).

BACKGROUND: MicroRNAs (miRNAs) exhibit important regulatory roles in the response to abiotic stresses by post-transcriptionally regulating the target gene expression in plants. However, their functions in sesame response to salt stress are poorly known. To dissect the complex mechanisms underlying salt stress response in sesame, miRNAs and their targets were identified from two contrasting sesame genotypes by a combined analysis of small RNAs and degradome sequencing. RESULTS: A total of 351 previously known and 91 novel miRNAs were identified from 18 sesame libraries. Comparison of miRNA expressions between salt-treated and control groups revealed that 116 miRNAs were involved in salt stress response. Using degradome sequencing, potential target genes for some miRNAs were also identified. The combined analysis of all the differentially expressed miRNAs and their targets identified miRNA-mRNA regulatory networks and 21 miRNA-mRNA interaction pairs that exhibited contrasting expressions in sesame under salt stress. CONCLUSIONS: This comprehensive integrated analysis may provide new insights into the genetic regulation mechanism of miRNAs underlying the adaptation of sesame to salt stress.

Identification of lncRNA-miRNA-mRNA regulatory network associated with primary open angle glaucoma.

BACKGROUND: Primary open angle glaucoma (POAG) is a multifactorial disorder characterized by a progressive permanent degeneration of retinal ganglion cell (RGCs) death. An increasing number of studies have suggested that long noncoding RNAs (lncRNAs) have the ability to regulate gene expression; however, thus far, the mechanisms and functions of lncRNAs in the development of POAG are still unclear. METHODS: Using the data from Gene Expression Omnibus (GEO), differentially expressed lncRNAs and differentially expressed mRNAs between POAG patients and controls were identified. Then, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed, and the key lncRNAs in POAG were identified. A Gene Ontology (GO) analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to assess the enriched biological functions of mRNA in the ceRNA network. RESULTS: During this study, a POAG-related ceRNA network with 37 miRNA nodes, 248 lncRNA nodes, 178 mRNA nodes, and 1985 edges was constructed. In addition, four lncRNAs (DNAJC27-AS1, AF121898, OIP5-AS1, and SNX29P2) were established as hub RNAs in this ceRNA network. The functional assay showed that 18 GO terms and 17 pathways were enriched. CONCLUSION: This study provides novel insights into the lncRNA-related ceRNA network in POAG, and the four lncRNAs were identified in the development of POAG.

microRNA-messenger RNA regulatory network of esophageal squamous cell carcinoma and the identification of miR-1 as a biomarker of patient survival.

Emerging evidence indicates that microRNAs (miRNAs) play an important role in tumor carcinogenesis and progression by targeting gene expression. The goal of this study was to comprehensively analyze the vital functional miRNAs and their target genes in esophageal squamous cell carcinoma (ESCC) and to explore the clinical significance and mechanisms of miR-1 in ESCC. First, the miRNA and messenger RNA (mRNA) expression profiles of ESCC were determined with microarray technology. Using an integrated analysis of miRNAs and their target genes with multistep bioinformatics methods, the miRNA-mRNA regulatory network in ESCC was constructed. Next, miR-1 expression in 292 ESCC patients and its relationship with clinicopathological features and prognosis were detected by in situ hybridization. Furthermore, the biological functions of miR-1 were determined with in vitro and in vivo functional experiments. Finally, real-time quantitative reverse transcription polymerase chain reaction, Western blot analysis, and luciferase reporter assays were performed to verify the target genes of miR-1. In this study, 67 miRNAs and 2992 genes were significantly differentially expressed in ESCC tissues compared with their expression in adjacent normal tissues, and an miRNA-mRNA regulatory network comprising 59 miRNAs and 162 target mRNAs was identified. Low miR-1 expression was correlated with pathological T stage, lymph node metastasis, vessel invasion, and poor clinical outcome. miR-1 suppressed ESCC cell proliferation and invasion and promoted ESCC cell apoptosis. Fibronectin 1 (FN1) was verified as a direct target of miR-1. Taken together, the present results suggest that miR-1 may be a valuable prognostic predictor for ESCC, and the miR-1/FN1 axis may be a therapeutic target.

Systems biology based meth-miRNA-mRNA regulatory network identifies metabolic imbalance and hyperactive cell cycle signaling involved in hepatocellular carcinoma onset and progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading cause of cancer associated deaths worldwide. Independent studies have proposed altered DNA methylation pattern and aberrant microRNA (miRNA) levels leading to abnormal expression of different genes as important regulators of disease onset and progression in HCC. Here, using systems biology approaches, we aimed to integrate methylation, miRNA profiling and gene expression data into a regulatory methylation-miRNA-mRNA (meth-miRNA-mRNA) network to better understand the onset and progression of the disease. METHODS: Patients' gene methylation, miRNA expression and gene expression data were retrieved from the NCBI GEO and TCGA databases. Differentially methylated genes, and differentially expressed miRNAs and genes were identified by comparing respective patients' data using two tailed Student's t-test. Functional annotation and pathway enrichment, miRNA-mRNA inverse pairing and gene set enrichment analyses (GSEA) were performed using DAVID, miRDIP v4.1 and GSEA tools respectively. meth-miRNA-mRNA network was constructed using Cytoscape v3.5.1. Kaplan-Meier survival analyses were performed using R script and significance was calculated by Log-rank (Mantel-Cox) test. RESULTS: We identified differentially expressed mRNAs, miRNAs, and differentially methylated genes in HCC as compared to normal adjacent tissues by analyzing gene expression, miRNA expression, and methylation profiling data of HCC patients and integrated top miRNAs along with their mRNA targets and their methylation profile into a regulatory meth-miRNA-mRNA network using systems biology approach. Pathway enrichment analyses of identified genes revealed suppressed metabolic pathways and hyperactive cell cycle signaling as key features of HCC onset and progression which we validated in 10 different HCC patients' datasets. Next, we confirmed the inverse correlation between gene methylation and its expression, and between miRNA and its targets' expression in various datasets. Furthermore, we validated the clinical significance of identified methylation, miRNA and mRNA signatures by checking their association with clinical features and survival of HCC patients. CONCLUSIONS: Overall, we suggest that simultaneous (1) reversal of hyper-methylation and/or oncogenic miRNA driven suppression of genes involved in metabolic pathways, and (2) induction of hyper-methylation and/or tumor suppressor miRNA driven suppression of genes involved in cell cycle signaling have potential of inhibiting disease aggressiveness, and predicting good survival in HCC.

Identification of differentially expressed circRNAs and a novel hsa_circ_0000144 that promote tumor growth in gastric cancer.

BACKGROUND: Circular RNAs (circRNAs) are involved in regulating tumor pathogenesis. The mechanism of circRNAs in gastric cancer (GC) is still unknown. Our study aimed to identify differentially expressed circRNAs and assess a novel circRNA (hsa_circ_0000144) in the proliferation, migration, and invasion in GC. METHODS: Gene ontology (GO) enrichment and analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, pathway network, and the ceRNA regulatory network of hsa_circ_0000144 targeting miRNAs and mRNAs were performed with the help of bioinformatics using R language and Perl software. hsa_circ_0000144 expression and circRNA knockdown in GC cell lines were detected using quantitative PCR (qPCR) in vitro. Cell proliferation, migration, and invasion after circRNA knockdown were measured using the cell counting kit-8 assay and Transwell assay. RESULTS: The circRNA expression profile GSE78092 downloaded from the Gene Expression Omnibus database included three GC patients and three normal tissues. Thirty-two differentially expressed circRNAs comprised six upregulated circRNAs and 26 downregulated circRNAs. In particular, the ErbB signaling pathway, neurotrophin signaling pathway, cellular senescence, and pathways in bladder cancer and GC played the most important roles in the pathway network. The expression of hsa_circ_0000144 was upregulated in GC cell lines. Hsa_circ_0000144 knockdown suppressed tumor growth in vitro. CONCLUSIONS: Hsa_circ_0000144 promotes GC cell proliferation, migration, and invasion, and the ceRNA regulatory network of hsa_circ_0000144 targeting miRNAs and mRNAs might be biomarkers for GC diagnosis and targeted therapy.

Comprehensive analysis of gene signatures associated with aging in human aortic dissection.

Background: Aortic dissection (AD) is a lethal aortic disease with limited effective therapeutic strategies. Aging increases the risk of AD, yet the underlying mechanisms remain unclear. This study aims to analyze the association of aging-related genes (Args) and AD using bioinformatic analysis. This helps provide novel insights into AD pathogenesis and contributes to developing novel therapeutic strategies. Methods: mRNA (GSE52093, GSE153434), miRNA (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded from GEO database. Args were downloaded from Aging Atlas database. Differentially-expressed Args were determined by intersecting Args and differentially-expressed mRNAs of two mRNA datasets. Cytoscape was used to identify hub genes and construct hub gene regulatory networks related to miRNAs. Seurat and clusterProfiler R package were used for investigating expression patterns of hub genes at single-cell level, and functional analysis, respectively. To validate the cellular expression pattern of hub genes, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determined using the DGIdb database. Results: HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD. miR-221-3p was predicted to interact with ESR1. A decreased ESR1 expression in smooth muscle cell subpopulation 4 (SMC4) was observed in AD versus normal aortic tissues, which was validated by sequencing 197,605 aortic cells from 13 AD patients. Additionally, upregulated genes of SMC4 in AD tissues were enriched in the "cellular senescence" pathway. These data indicated that decreased ESR1 might promote SMC4 aging during AD formation. Eleven existing drugs targeting hub genes were identified, including ruxolitinib and filgrastim, which are associated with AD. Conclusions: By sequencing transcriptomic data, this study revealed aging-related hub genes and regulatory network involved in AD formation. Additionally, this study proposed a noteworthy hypothesis that downregulated ESR1 may exacerbate AD by promoting SMC aging, which requires further investigation.

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data.

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Systematic Analysis to Identify the MIR99AHG-has-miR-21-5p-EHD1 CeRNA Regulatory Network as Potential Biomarkers in Lung Cancer.

Lung cancer (LC) remains an extremely lethal disease worldwide, and effective prognostic biomarkers are at top priority. With the rapid development of high-throughput sequencing and bioinformatic analysis methods, the quest to characterize cancer transcriptomes continues to move forward. However, the integrated systematic analysis of lncRNA-miRNA-mRNA regulatory network in LC is lacking. In this study, we collected samples of cancer tissues and adjacent normal tissues from patients with lung cancer and conducted transcriptome and small RNA sequencing to identify differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs). The regulatory roles of miRNAs in LC were explained by functional analysis on DEM-targeted genes. The lncRNA-miRNA pairs, miRNA-mRNA pairs, and lncRNA-mRNA pairs were identified and combined to construct the interplay of lncRNA-miRNA-mRNA. We evaluated the prognostic value of selected lncRNA-miRNA-mRNA by Kaplan-Meier analysis. Finally, we analyzed the expression levels of selected DEM, DELs, and DEGs in lung cancer patients and healthy people to verify our findings. A total of 1492 DEGs, 12 DEMs, and 604 DELs were identified in LC patients. Based on the bioinformatic analysis and the regulatory mechanism of ceRNAs, 3 lncRNAs (GATA2-AS1, LINC00632, MIR99AHG), 1 miRNA (hsa-miR-21-5p) and 5 targeted genes (RECK, TIMP3, EHD1, RASGRP1 and ERG) were figured out first. Through further Kaplan-Meier analysis screening the prognostic value, we finally found the hub subnetwork (MIR99AHG-hsa-miR-21-5p-EHD1) by collating lncRNA-miRNA pairs, miRNA-mRNA pairs and lncRNA-mRNA pairs. As the key of ceRNA regulatory network, the expression of miRNA-21-5p in lung cancer patients was significantly higher than that in healthy people (P < 0.01), and its high expression was significantly associated with poor prognosis (P = 0.0025). Our study successfully constructed a MIR99AHG-hsa-miR-21-5p-EHD1 mutually regulatory network, suggesting the potential efficient biomarkers in LC.

Construction of miRNA-mRNA regulatory network indicates potential biomarkers for primary open-angle glaucoma.

BACKGROUND: Trabecular meshwork (TM) dysfunction-induced elevation of intraocular pressure has been identified as the main risk factor of irreversible optic nerve injury in Primary open­angle glaucoma (POAG). Increasing evidences suggest that microRNA (miRNA) plays a vital role in the pathogenesis of POAG. This study aims to construct a miRNA-mRNA regulatory network and identify biomarkers for POAG. METHODS: miRNAs and mRNAs expression profiling of TM samples from controls and POAG patients were assessed through microarray analysis. Target genes of differentially expressed miRNAs (DEmiRNAs) were predicted by miEAA and miRNet. Then GO and KEGG pathway analysis of differentially expressed mRNAs (DEmRNAs) were performed. PPI of top 30 hub genes was identified and miRNA-mRNA network was established by STRING database and Cytoscape software. GSE27276 and GSE105269 datasets were used to verify the expression of hub genes and to predict potential biomarkers in TM and aqueous humor (AH) for POAG, respectively. Finally, GSEA analysis was conducted to estimate the main signaling pathway of POAG pathogenesis. RESULTS: A total of 29 up-regulated and 7 down-regulated miRNAs, 923 up-regulated and 887 down-regulated mRNAs were identified in TM of POAG compared with controls. Target genes and DEmRNAs were mainly enriched in nitric oxide biosynthetic process, vasopressin-regulated water reabsorption, and so on. Through miRNA-mRNA network construction, top 30 hub genes were regulated by 24 DEmiRNAs. 8 genes were aberrantly expressed in dataset GSE27276. 3 genes (CREB1, CAPZA2, SLC2A3) and 2 miRNAs (miR-106b-5p, miR-15a-5p) were identified as potential biomarkers for POAG in TM and AH, respectively. GSEA analysis revealed that these 3 genes modulated POAG through different pathways. CONCLUSION: In this study, construction of miRNA-mRNA network and identification of biomarkers provide a novel insight into the pathogenesis, early diagnosis and treatment for POAG.

Comprehensive Analysis of the miRNA-mRNA Pathological Regulatory Network of Intestinal CD4 + T Cells in Parkinson's Disease.

Infiltration of CD4 + T cells was found in brain tissue samples from PD patients, suggesting their involvement in developing central nervous system (CNS) disease. The idea of the gut-brain axis further corroborates intestinal T cells' activation as the central immune response initiation. However, the specific factors and molecular pathways regulating intestinal T-cell activation are unclear. We used the GSE156287 and GSE145814 datasets from the GEO database to analyze and obtain the miRNAs, which are aberrantly expressed in intestinal CD4 + T cells in PD patients and predict their regulatory target mRNAs. Further, combined with the GSE174473 dataset of CD4 + T cells sequencing in PD patients, we finally clarified the aberrant genes expressed in CD4 + T cells from the intestine of PD patients and constructed a miRNA-mRNA regulatory network. The highlight of our findings showed pathways, networks, biological functions, and key molecules potentially involved in the miRNA-mediated functional effects in CD4 + T cell from the intestine of PD patients. The hsa-miR-3180-3p mediated CBX8, etc. were determined as most effective in enhancing T cell survival. PEG10, etc. regulated by hsa-miR-20a-3p targets were possibly involved in T cell differentiation. The JPT2 regulated by hsa-miR-1281 were involved in influencing T cell infiltration. The discovery of this interaction between miRNA and mRNA in CD4 + T cell has important implications for understanding the intestinal initial of PD pathological molecular and anti-inflammation of T cell activation.