Identification of potential therapeutic target genes and miRNAs for primary myelofibrosis with microarray analysis.
ABSTRACT: The aim of the present study was to identify potential therapeutic target genes and miRNAs for primary myelofibrosis (PMF). The dataset GSE53482 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) of peripheral blood (PB) cluster of differentiation (CD)34+ cells from PMF patients (PB-PMF group) and peripheral blood CD34+ cells from healthy individuals (PB-control group) were analyzed using the Linear Models for Microarray Data package in R. The Kyoto Encyclopedia of Genes and Genomes was used for pathway enrichment analysis. MiRNA-gene joint enrichment analysis was performed by ENViz and a miRNAs-gene regulatory network was constructed. A total of 1,182 DEGs (773 upregulated and 109 downregulated) and 48 DEMs (28 upregulated and 20 downregulated) were identified. According to the pathway enrichment analysis, a number of DEGs were enriched in metabolic pathways, including IDH1 and DNMT1. Other DEGs were enriched in the citrate cycle (tricarboxylic acid cycle; IDH1 and IDH3A) and certain DEGs were enriched in pyrimidine metabolism, including CARD8. For downregulated genes, certain DEGs were enriched in the spliceosome, including SF3B1 and CDC40. Furthermore, hsa-miR-127-3p, hsa-miR-140-3p and hsa-miR345 were associated with cell cycle-related biological processes, signal transduction and cell surface receptor signaling pathway. The DEM-DEG regulatory network indicated that hsa-miR-543 regulated 113 genes, including CARD8 and TIFA. The present study identified a number of genes, including IDH1, DNMT1, SF3B1 and CARD8, and miRNAs, including hsa-miR-127-3p and hsa-miR-140-3p, which may be therapeutic targets in the treatment of PMF.
Project description:Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (miRNA/miR) expression profiles of GSE42657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between EPN and normal brain tissue samples were identified using the Limma package in R and GEO2R, respectively. Functional and pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed using the Search Tool for Retrieval of Interacting Genes database, which was visualized using Cytoscape. The targeted genes of DEMs were predicted using miRWalk2.0 and a miRNA-mRNA regulatory network was constructed. Following analysis, a total of 948 DEGs and 129 DEMs were identified. Functional enrichment analysis revealed that 609 upregulated DEGs were significantly enriched in 'PI3K-Akt signaling pathway', while 339 downregulated DEGs were primarily involved in 'cell junction' and 'retrograde endocannabinoid signaling'. In addition, 6 hub genes [cyclin dependent kinase 1, CD44 molecule (Indian blood group) (CD44), proliferating cell nuclear antigen (PCNA), MYC, synaptotagmin 1 (SYT1) and kinesin family member 4A] and 6 crucial miRNAs [homo sapiens (hsa)-miR-34a-5p, hsa-miR-449a, hsa-miR-106a-5p, hsa-miR-124-3p, hsa-miR-128-3p and hsa-miR-330-3p] were identified as biomarkers and potential therapeutic targets for EPN. Furthermore, a microRNA-mRNA regulatory network was constructed to highlight the interactions between DEMs and their target DEGs; this included the hsa-miR-449a-SYT1, hsa-miR-34a-5p-SYT1, hsa-miR-330-3p-CD44 and hsa-miR-124-3p-PCNA pairs, whose expression levels were confirmed using reverse transcription-quantitative polymerase chain reaction. In conclusion, the present study may provide important data for the investigation of the molecular mechanisms of EPN pathogenesis.
Project description:Accumulating evidence has indicated that noncoding RNAs are involved in intervertebral disc degeneration (IDD); however, the competing endogenous RNA (ceRNA)?mediated regulatory mechanisms in IDD remain rarely reported. The present study aimed to comprehensively investigate the alterations in expression levels of circular RNA (circRNA), long noncoding RNA (lncRNA), microRNA (miRNA/miR) and mRNA in the nucleus pulposus (NP) of patients with IDD. In addition, crucial lncRNA/circRNA?miRNA?mRNA ceRNA interaction axes were screened using the GSE67567 microarray dataset obtained from the Gene Expression Omnibus database. After data preprocessing, differentially expressed circRNAs (DECs), lncRNAs (DELs), miRNAs (DEMs) or genes (DEGs) between IDD and normal controls were identified using the Linear Models for Microarray data method. A protein?protein interaction (PPI) network was constructed for DEGs based on protein databases, followed by module analysis. The ceRNA network was constructed based on the interaction between miRNAs and mRNAs, and lncRNAs/circRNAs and miRNAs. The underlying functions of mRNAs were predicted using the Database for Annotation, Visualization and Integrated Discovery database. The present study identified 636 DECs, 115 DELs, 84 DEMs and 1,040 DEGs between patients with IDD and control individuals. PPI network analysis demonstrated that Fos proto?oncogene, AP?1 transcription factor subunit (FOS), mitogen?activated protein kinase 1 (MAPK1), hypoxia inducible factor 1 subunit ? (HIF1A) and transforming growth factor ?1 (TGFB1) were hub genes and enriched in modules. Metastasis?associated lung adenocarcinoma transcript 1 (MALAT1)/hsa_circRNA_102348?hsa??miR?185?5p?TGFB1/FOS, MALAT1?hsa?miR?155?5p?HIF1A, hsa_circRNA_102399?hsa?miR?302a?3p?HIF1A, MALAT1?hsa??miR?519d?3p?MAPK1 and hsa_circRNA_100086?hsa?miR?509?3p?MAPK1 ceRNA axes were obtained by constructing the ceRNA networks. In conclusion, these identified ceRNA interaction axes may be crucial targets for the treatment of IDD.
Project description:<h4>Background</h4> Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cell carcinoma which has the worst overall survival rate. Almost 30% of patients with localized cancers eventually develop to metastases despite of early surgical treatment carried out. MicroRNAs (miRNAs) play a critical role in human cancer initiation, progression, and prognosis. The aim of our study was to identify potential prognosis biomarkers to predict overall survival of KIRC. <h4>Methods</h4> All data were downloaded from an open access database The Cancer Genome Atlas. DESeq2 package in R was used to screening the differential expression miRNAs (DEMs) and genes (DEGs). RegParallel and Survival packages in R was used to analysis their relationships with the KIRC patients. David version 6.8 and STRING version 11 were used to take the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. <h4>Results</h4> We found 2 DEGs (TIMP3 and HMGCS1) and 3 DEMs (hsa-miR-21-5p, hsa-miR-223-3p, and hsa-miR-365a-3p) could be prognosis biomarkers for the prediction of KIRC patients. The constructed prognostic model based on those 2 DEGs could effectively predict the survival status of KIRC. And the constructed prognostic model based on those 3 DEMs could effectively predict the survival status of KIRC in 3-year and 5-year. <h4>Conclusion</h4> The current study provided novel insights into the miRNA related mRNA network in KIRC and those 2 DEGs biomarkers and 3 DEMs biomarkers may be independent prognostic signatures in predicting the survival of KIRC patients. <h4>Supplementary Information</h4> The online version contains supplementary material available at 10.1186/s12920-021-00932-z.
Project description:BACKGROUND To identify noninvasive diagnostic biomarkers for membranous nephropathy (MN). MATERIAL AND METHODS The mRNA microarray datasets GSE73953 using peripheral blood mononuclear cells (PBMCs) of 8 membranous nephropathy patients and 2 control patients; and microRNAs (miRNA) microarray dataset GSE64306 using urine sediments of 4 membranous nephropathy patients and 6 control patients were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were respectively identified from PBMCs and urine sediments of membranous nephropathy patients, followed with functional enrichment analysis, protein-protein interaction (PPI) analysis, and miRNA-target gene analysis. Finally, the DEGs and the target genes of DEMs were overlapped to obtain crucial miRNA-mRNA interaction pairs for membranous nephropathy. RESULTS A total of 1246 DEGs were identified from PBMCs samples, among them upregulated CCL5 was found to be involved in the chemokine signaling pathway, and BAX was found to be apoptosis related; while downregulated PPM1A and CDK1 were associated with the MAPK signaling pathway and the p53 signaling pathway, respectively. The hub role of CDK1 (degree=18) and CCL5 (degree=12) were confirmed after protein-protein interaction network analysis in which CKD1 could interact with RAB1A. A total of 28 DEMs were identified in urine sediments. The 276 target genes of DEMs were involved in cell cycle arrest (PPM1A) and intracellular signal transduction (BRSK1). Thirteen genes were shared between the DEGs in PMBCs and the target genes of DEMs in urine sediments, but only hsa-miR-192-3p-RAB1A, hsa-miR-195-5p-PPM1A, and hsa-miR-328-5p-BRSK1 were negatively related in their expression level. CONCLUSIONS Both peripheral blood and urinary miR-195-5p, miR-192-3p, miR-328-5p, and their target genes PPM1A, RAB1A, and BRSK1 may be potential biomarkers for membranous nephropathy by participating in inflammation and apoptosis.
Project description:To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.
Project description:Long non?coding RNAs (lncRNAs) have been implicated in the development and progression of cancer. However, the mechanisms of lncRNAs in hepatitis B virus (HBV) infection?induced hepatocellular carcinoma (HCC) remain unclear. The study aimed to reveal the roles of lncRNAs for HBV?HCC based on the hypothesis of competing endogenous RNA (ceRNA). The lncRNA (GSE27462), miRNA (GSE76903) and mRNA (GSE121248) expression profiles were collected from the Gene Expression Omnibus database. Differentially expressed lncRNAs (DELs), genes (DEGs) and miRNAs (DEMs) were identified using the LIMMA or EdgeR package, respectively. The ceRNA network was constructed based on interaction pairs between miRNAs and mRNAs/lncRNAs. The functions of DEGs in the ceRNA network were predicted using the DAVID database, which was overlapped with the known HCC pathways of Comparative Toxicogenomics Database (CTD) to construct the HCC?related ceRNA network. The prognosis values [overall survival, (OS); recurrence?free survival (RFS)] of genes were validated using the Cancer Genome Atlas (TCGA) data with Cox regression analysis. The present study screened 38 DELs, 127 DEMs and 721 DEGs. A ceRNA network was constructed among 17 DELs, 12 DEMs and 173 DEGs, including the FAM138B?hsa?miR?30c?CCNE2/RRM2 and SSTR5?AS1?hsa?miR?15b?5p?CA2 ceRNA axes. Function enrichment analysis revealed the genes in the ceRNA network that participated in the p53 signaling pathway [cyclin E2 (CCNE2), ribonucleotide reductase M2 subunit (RRM2)] and nitrogen metabolism [carbonic anhydrase 2 (CA2)], which were also included in the pathways of the CTD. Univariate Cox regression analysis revealed that six RNAs (2 DELs: FAM138B, SSTR5?AS1; 2 DEMs: hsa?miR?149, hsa?miR?7; 2 DEGs: CCNE2, RRM2) were significantly associated with OS; while seven RNAs (1 DEL: LINC00284; 3 DEMs: hsa?miR?7, hsa?miR?15b, hsa?miR?30c?2; and 3 DEGs: RRM2, CCNE2, CA2) were significantly associated with RFS. In conclusion, FAM138B?hsa?miR?30c?CCNE2/RRM2 and the SSTR5?AS1?hsa?miR?15b?5p?CA2 ceRNA axes may be important mechanisms for HBV?related HCC.
Project description:A number of recent studies have highlighted the causes of bone nonunion (BN), however, the rate of BN incidence continues to rise and available therapeutic options to treat this condition remain limited. Thus, to prevent disease progression and improve patient prognosis, it is vital that BN, or the risk thereof, be accurately identified in a timely manner. In the present study, bioinformatics analyses were used to screen for the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between patients with BN and those with bone union, using data from the Gene Expression Omnibus database. Furthermore, clinical samples were collected and analyzed by reverse transcription?quantitative PCR and western blotting. In vitro and in vivo experiments were carried out to confirm the relationship between BN and the DEGs of interest, in addition to being used to explore the underlying molecular mechanism of BN. Functional enrichment analysis of the downregulated DEGs revealed them to be enriched for genes associated with 'ECM?receptor interactions', 'focal adhesion', 'and the calcium signaling pathway'. When comparing DEM target genes with these DEGs, nine DEGs were identified as putative DEM targets, where hsa?microRNA (miR)?1225?5p?CCNL2, hsa?miR?339?5p?PRCP, and hsa?miR?193a?3p?mitogen?activated protein kinase 10 (MAPK10) were the only three pairs which were associated with decreased gene expression levels. Furthermore, hsa?miR?193a?3p was demonstrated to induce BN by targeting MAPK10. Collectively, the results of the present study suggest that hsa?miR?193a?3p may be a viable biomarker of BN.
Project description:The present study aimed to explore specific molecular targets for the diagnosis and treatment of non?small cell lung cancer (NSCLC). The expression profiles of microRNAs (miRNAs) and mRNAs were downloaded from the GEO (GSE102286 and GSE101929) and TCGA databases. After data preprocessing, differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in cancer and normal tissues were selected and used to construct a DEM?DEG regulatory network and a protein?protein interaction (PPI) network. The genes and miRNAs in these networks were subjected to functional enrichment and survival analyses. Several key DEMs and DEGs were verified using RT?qPCR, and the results were statistically interpreted using a multivariate logistic regression analysis. In this study, 25 DEMs and 789 DEGs common to all datasets were identified, which were then used for the construction of a DEM?DEG regulatory network and a PPI network module. Survival analyses of 19 DEMs in the DEM?DEG regulatory network and 36 DEGs in the PPI network module revealed that 34 DEGs (including TOP2A, CCNB1, BIRC5, and TTK) and two miRNAs (miR?21?5p and miR?31?5p) were significantly associated with NSCLC prognosis. Moreover, RT?qPCR analysis identified three DEGs and five DEMs that had changes in expression consistent with those observed in the bioinformatic analysis. Finally, a multivariate logistic regression analysis of the data showed that TOP2A, CCNB1, BIRC5, miR?21?5p, miR?193b?3p, miR?210?3p and miR?31?5p could be combined for the diagnosis of NSCLC. In conclusion, TOP2A, CCNB1, BIRC5, miR?21?5p, miR?193b?3p, miR?210?3p and miR?31?5p may therefore serve as important biomarkers and diagnostic targets for NSCLC.
Project description:Medullary thyroid carcinoma (MTC) is an endocrine tumor and comprises 5?10% of all primary thyroid malignancies. However, the biomechanical contribution to the development and progression of MTC remains unclear. In this study, To discover the key microRNAs (miRNAs or miRs) and their potential roles in the tumorigenesis of MTC, the microarray datasets GSE97070, GSE40807 and GSE27155 were analyzed. The datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed miRNAs (DEMs) and genes (DEGs) were accessed by R. Targets of DEMs and predicted using starBase, and functional and pathway enrichment analyses were performed using Metascape. A protein?protein interaction (PPI) network and an analysis of modules were constructed using NetworkAnalyst. Finally, a network was constructed to show the regulatory association between transcription factors (TFs), DEMs and downstream genes. A total of 5 DEMs were found both in GSE97070 and GSE40807, including 3 upregulated DEMs and 2 downregulated DEMs. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from Metascape revealed that the target genes of upregulated DEMs were significantly enriched in adherens junction, kinase and protein binding, while the target genes of downregulated DEMs were mainly involved in non?canonical Wnt signaling pathway and RNA transport. From the PPI network, 13 nodes were screened as hub genes. Pathway enrichment analysis revealed that the top 5 modules were mostly enriched in the neurotrophin signaling pathway, mRNA surveillance pathway and MAPK signaling pathway. In addition, the TF?DEMs?target gene and DEGs regulatory network revealed that 17 TFs regulated 2 miRNAs, including upregulated or downregulated DEMs, CREB1 regulated all upregulated DEMs, and TGFB1 was an activator of hsa?miR?199a?3p and a repressor of hsa?miR?429. Taken together, the present study identified several miRNAs and potential biological mechanisms involved in the tumorigenesis of MTC. This study identified the key DEMs and potential mechanisms underlying the development of MTC, and provided a series of biomarkers and targets for the management of MTC.
Project description:Background:Helicobacter pylori (H. pylori) is a common human pathogen, which is closely correlated with gastric cancer (GC). However, the mechanism of H. pylori-related GC has not been elucidated. This study aimed to explore the role of H. pylori infection in GC and find biomarkers for early diagnosis of H. pylori-related GC. Methods:We identified differentially expressed microRNAs (DEMs) and genes (DEGs) from the Gene Expression Omnibus (GEO) dataset, constructed microRNA-(miRNA-)mRNA expression networks, analyzed the function and signal pathway of cross-genes, analyzed the relations between cross-genes and GC prognosis with the Cancer Genome Atlas (TCGA) data, and verified the expression of cross-genes in patients with H. pylori infection. Results:22 DEMs and 68 DEGs were identified in GSE197694 and GSE27411 dataset. 16 miRNAs and 509 genes were involved in the expression network, while the cross-genes of the network were mainly enriched in MAP kinase (MAPK) signaling pathway and TGF-beta signaling pathway. Patients with higher expression of hsa-miR-196b-3p, CALML4, or SMAD6 or lower expression of PITX2 or TGFB2 had better outcomes than those with lower expression of hsa-miR-196b-3p, CALML4, or SMAD6 or higher expression of PITX2 or TGFB2 (P < 0.05). Patients with H. pylori infection had a higher expression of hsa-miR-196b-3p and CALML4 than those without H. pylori infection (P < 0.05). Conclusion:The study of miRNA-mRNA expression network would provide molecular support for early diagnosis and treatment of H. pylori-related GC.