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Previous studies have shown that long non-coding RNAs (lncRNAs) serve important roles in necrotizing enterocolitis (NEC). However, the underlying mechanisms remain largely unknown. In order to examine the potential role of lncRNAs in NEC, the present study investigated lncRNA and mRNA expression profiles in NEC lesions and adjacent intestinal tissues using Next Generation Sequencing. A total of 4,202 differentially expressed lncRNAs (fold-change >2; P<0.05) and 7,860 differentially expressed mRNAs (fold-change >2; P<0.05) were identified. Moreover, 5 dysregulated lncRNAs and 5 mRNAs were randomly selected, and further assessed by reverse transcription-quantitative PCR in vitro. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses demonstrated that the differentially expressed lncRNAs were closely associated with NEC, and were enriched in 'inflammatory response', 'Toll-like receptor binding', 'PPAR signaling pathway', 'PI3K-Akt signaling pathway', 'transforming growth factor-β signaling pathway' and 'hypoxia-inducible factor 1 signaling pathway'. In addition, co-expression analysis demonstrated that these lncRNAs, including lncRNA ENST00000623580, lncRNA NONHSAT180418.1, lncRNA NONHSAT125636.2 and NONHSAT087855.2, may mediate the pathogenesis and development of NEC via lncRNA-mRNA network interactions. Therefore, the present study provided a novel insight into the role of lncRNAs in NEC. [ABSTRACT FROM AUTHOR]

Asthma, a common but poorly controlled disease, is one of the most serious health problems worldwide; however, the mechanisms underlying the development of asthma remain unknown. Long non-coding RNAs (lncRNAs) and mRNAs serve important roles in the initiation and progression of various diseases. The present study aimed to investigate the role of differentially expressed lncRNAs and mRNAs associated with asthma. Differentially expressed lncRNAs and mRNAs were screened between the expression data of 62 patients with asthma and 43 healthy controls. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the biological functions and pathways associated with the lncRNAs and mRNAs identified. Protein-protein interaction (PPI) networks were subsequently generated. In addition, lncRNA-mRNA weighted co-expression networks were obtained. In total, 159 differentially expressed lncRNAs and 1,261 mRNAs were identified. GO and KEGG analyses revealed that differentially expressed mRNAs regulated asthma by participating in the 'vascular endothelial (VEGF) signaling pathway', 'oxidative phosphorylation', 'Fc ε RI signaling pathway', 'amino sugar and nucleotide sugar metabolism', 'histidine metabolism', 'β-alanine metabolism' and 'extracellular matrix-receptor interaction' (P<0.05). Furthermore, protein kinase B 1 had the highest connectivity degree in the PPI network, and was significantly enriched in the 'VEGF signaling pathway' and 'Fc ε RI signaling pathway'. A total of 8 lncRNAs in the lncRNA-mRNA co-expression network were reported to interact with 52 differentially expressed genes, which were enriched in asthma-associated GO and KEGG pathways. The results obtained in the present study may provide insight into the profile of differentially expressed lncRNAs associated with asthma. The identification of a cluster of dysregulated lncRNAs and mRNAs may serve as a potential therapeutic strategy to reverse the progression of asthma. [ABSTRACT FROM AUTHOR]

Cinobufotalin is a chemical compound extracted from the skin of dried bufo toads that may have curative potential for certain malignancies through different mechanisms; however, these mechanisms remain unexplored in breast cancer. The aim of the present study was to investigate the antitumor mechanism of cinobufotalin in breast cancer by using microarray data and in silico analysis. The microarray data set GSE85871, in which cinobufotalin exerted influences on the MCF-7 breast cancer cells, was acquired from the Gene Expression Omnibus database, and the differentially expressed genes (DEGs) were analyzed. Subsequently, protein interaction analysis was conducted, which clarified the clinical significance of core genes, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to analyze cinobufotalin-related pathways. The Connectivity Map (CMAP) database was used to select existing compounds that exhibited curative properties similar to those of cinobufotalin. A total of 1,237 DEGs were identified from breast cancer cells that were treated with cinobufotalin. Two core genes, SRC proto-oncogene non-receptor tyrosine kinase and cyclin-dependent kinase inhibitor 2A, were identified as serving a vital role in the onset and development of breast cancer, and their expression levels were markedly reduced following cinobufotalin treatment as detected by the microarray of GSE85871. It also was revealed that the 'neuroactive ligand-receptor interaction' and 'calcium signaling' pathways may be crucial for cinobufotalin to perform its functions in breast cancer. Conducting a matching search in CMAP, miconazole and cinobufotalin were indicated to possessed similar molecular mechanisms. In conclusion, cinobufotalin may serve as an effective compound for the treatment of a subtype of breast cancer that is triple positive for the presence of estrogen, progesterone and human epidermal growth factor receptor-2 receptors, and its mechanism may be related to different pathways. In addition, cinobufotalin is likely to exert its antitumor influences in a similar way as miconazole in MCF-7 cells. [ABSTRACT FROM AUTHOR]

Gastric adenocarcinoma (GAC) is a challenging disease with dim prognosis even after surgery; hence, novel treatments for GAC are in urgent need. The aim of the present study was to explore new potential compounds interfering with the key pathways related to GAC progression. The differentially expressed genes (DEGs) between GAC and adjacent tissues were identified from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. Connectivity Map (CMap) was performed to screen candidate compounds for treating GAC. Subsequently, pathways affected by compounds were overlapped with those enriched by the DEGs to further identify compounds which had anti-GAC potential. A total of 843 DEGs of GAC were identified. Via Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, 13 pathways were significantly enriched. Moreover, 78 compounds with markedly negative correlations with DEGs were revealed in CMap database (P<0.05 and Enrichment <0). Subpathways of cell cycle and p53 signaling pathways, and core genes of these compounds, cyclin B1 (CCNB1) and CDC6, were identified. This study further revealed seven compounds that may be effective against GAC; in particular methylbenzethonium chloride and alexidine have never yet been reported for GAC treatment. In brief, the candidate drugs identified in this study may provide new options to improve the treatment of patients with GAC. However, the biological effects of these drugs need further investigation. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most common type of malignant tumor of the central nervous system. The prognosis of patients with GBM is very poor, with a survival time of ~15 months. GBM is highly heterogeneous and highly aggressive. Surgical removal of intracranial tumors does provide a good advantage for patients as there is a high rate of recurrence. The understanding of this type of cancer needs to be strengthened, and the aim of the present study was to identify gene signatures present in GBM and uncover their potential mechanisms. The gene expression profiles of GSE15824 and GSE51062 were downloaded from the Gene Expression Omnibus database. Normalization of the data from primary GBM samples and normal samples in the two databases was conducted using R software. Then, joint analysis of the data was performed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the protein-protein interaction (PPI) network of the differentially expressed genes (DEGs) was constructed using Cytoscape software. Identification of prognostic biomarkers was conducted using UALCAN. In total, 9,341 DEGs were identified in the GBM samples, including 9,175 upregulated genes and 166 downregulated genes. The top 1,000 upregulated DEGs and all of the downregulated DEGs were selected for GO, KEGG and prognostic biomarker analyses. The GO results showed that the upregulated DEGs were significantly enriched in biological processes (BP), including immune response, cell division and cell proliferation, and the downregulated DEGs were also significantly enriched in BP, including cell growth, intracellular signal transduction and signal transduction by protein phosphorylation. KEGG pathway analysis showed that the upregulated DEGs were enriched in circadian entrainment, cytokine-cytokine receptor interaction and maturity onset diabetes of the young, while the downregulated DEGs were enriched in the TGF-β signaling pathway, MAPK signaling pathway and pathways in cancer. All of the downregulated genes and the top 1,000 upregulated genes were selected to establish the PPI network, and the sub-networks revealed that these genes were involved in significant pathways, including olfactory transduction, neuroactive ligand-receptor interaction and viral carcinogenesis. In total, seven genes were identified as good prognostic biomarkers. In conclusion, the identified DEGs and hub genes contribute to the understanding of the molecular mechanisms underlying the development of GBM and they may be used as diagnostic and prognostic biomarkers and molecular targets for the treatment of patients with GBM in the future. [ABSTRACT FROM AUTHOR]

Endometriosis is a common gynecological disease, affecting 6–10% of women of reproductive age. The precise mechanisms underlying the development of endometriosis remain unclear. In the present study, a bioinformatics approach was applied to systematically identify the pathways and genes involved in the development of endometriosis and to discover potential biomarkers. The gene expression profiles of GSE6364, a microarray dataset of endometrial biopsies obtained from women with or without endometriosis, was downloaded from the Gene Expression Omnibus DataSets database that stores original submitter-supplied records (series, samples and platforms), as well as curated datasets. Differentially expressed gene (DEG) analysis was performed with GEO2R. DAVID was used to analyze the gene ontology enrichment of the DEGs. Gene Set Enrichment Analysis (GSEA) was conducted using the GSEA v3.0 software. Protein-protein interactions (PPI) were evaluated with the Search Tool for the Retrieval of Interacting Genes, and PPI network visualization was performed with Cytoscape. In addition, Cell Counting kit-8 and Transwell assays were performed on human endometrial stromal cells (HESCs). A total of 172 DEGs were extracted. Inflammatory response genes were significantly upregulated in the endometriosis tissues and C-X-C motif chemokine receptor 2 (CXCR2), was one of the most up-regulated genes according to DEG analysis. Cell-based experiments confirmed that CXCR2 promoted the proliferation, migration and invasion of HESCs. In conclusion, a bioinformatics approach combined with in vitro experiments in the present study revealed that CXCR2 may be associated with the development of endometriosis and has potential as a biomarker for the diagnosis of endometriosis. [ABSTRACT FROM AUTHOR]

Although certain biomarkers that are directly associated with the overall survival (OS) of patients with pancreatic adenocarcinoma (PAAD) have been identified, the efficacy of a single factor is limited to predicting the prognosis. The aim of the present study was to identify a combination micro (mi)RNA signature that enhanced the prognostic prediction for PAAD. Following analysis of the data available from The Cancer Genome Atlas (TCGA), 175 PAAD samples were selected for the present study, and the associations between 494 miRNAs and OS were investigated. The prognostic value of all miRNAs was analyzed by multivariate Cox regression, and the miRNAs were ranked according to the hazard ratio (HR) and P-values. The top 5 miRNAs (miR-1301, miR-125a, miR-376c, miR-328 and miR-376b) were significantly associated with OS (HR=0.139; 95% confidence interval, 0.043-0.443; P<0.001), thus demonstrating that this panel was able to serve as an independent prognostic factor for PAAD. In addition, the present study also predicted the target genes of the top 10 miRNAs with the highest prognostic values using 12 different prediction software, and enrichment signaling pathway analyses elucidated that several pathways may be markedly associated with these miRNAs, including 'Pathways in cancer', 'Chronic myeloid leukemia', 'Glioma' and 'MicroRNAs in cancer'. Lastly, ubiquitin C, epidermal growth factor receptor, estrogen receptor 1, mitogen-activated protein kinase 1, mothers against decapentaplegic homolog 4 and androgen receptor may be the hub genes revealed by STRING analysis. The present study identified several miRNAs, particularly a five-miRNA-pool, that may be reliable, independent factors for predicting survival in patients with PAAD. However, the underlying molecular mechanisms require further investigation in the future. [ABSTRACT FROM AUTHOR]

Osteosarcoma is a common and highly malignant tumour in children and teenagers that is characterized by drug resistance and high metastatic potential. Patients often develop pulmonary metastasis and have a low survival rate. However, the mechanistic basis for pulmonary metastasis remains unclear. To identify key gene and pathways associated with pulmonary metastasis of osteosarcoma, the authors downloaded the gene expression dataset GSE85537 and obtained the differentially expressed genes (DEGs) by analyzing high‑throughput gene expression in primary tumours and lung metastases. Subsequently, the authors performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein‑protein interaction (PPI) network was constructed and analyzed by Cytoscape software. In total, 2,493 genes were identified as DEGs. Of these, 485 genes (19.45%) were upregulated, and the remaining 2,008 genes (80.55%) were downregulated. The authors identified the predominant GO categories and KEGG pathways that were significantly over‑represented in the metastatic OS samples compared with the non‑metastatic OS samples. A PPI network was constructed, and the results indicated that ALB, EGFR, INS, IL6, CDH1, FYN, ERBB2, IL8, CXCL12 and RAC2 were the top 10 core genes. The enrichment analyses of the genes involved in the top three significant modules demonstrated that the DEGs were principally related to neuroactive ligand‑receptor interaction, the Rap1 signaling pathway, and protein digestion and absorption. Together, these data elucidated the molecular mechanisms of OS patients with pulmonary metastasis and provide potential therapeutic targets. However, further experimental studies are needed to confirm these results. [ABSTRACT FROM AUTHOR]

The present study was designed to identify key genes or significant signaling pathways associated with spinal cord injury (SCI), and to clarify the underlying molecular mechanisms of SCI. Data from the GSE45550 array were downloaded from the Gene Expression Omnibus database. A total of 6 control samples, 6 samples at 3 days post-SCI (SCI3d), 6 samples at 8 days post-SCI (SCI8d) and 6 samples at 14 days post-SCI (SCI14d) were included. The microarray data was preprocessed by the robust multi-array average algorithm. The differentially expressed genes (DEGs) were identified using the limma package. The overlapping DEGs among groups were analyzed using the Venny 2.0 online tool. Modules enriched by DEGs were selected by weighted gene co-expression network analysis. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathways were identified for DEGs using the Database for Annotation, Visualization and Integrated Discovery. A total of 693 genes were obtained by combining the DEGs of the SCI3d, SCI8d and SCI14d groups. The pink module and green module with smaller P-values obtained from weighted gene co-expression network analysis module analyses of DEGs demonstrated a higher correlation with SCI. In addition, the peroxisome proliferator-activated receptor (PPAR) signaling pathway that the cluster of differentiation 36 (CD36) was significantly enriched in, was one of the significant pathways in the pink module. The p53 signaling pathway that Caspase-3 (Casp3) was significantly enriched in was one of the significant pathways in the green module. In conclusion, the results of the present study demonstrated that the PPAR and p53 signaling pathway may serve important roles in the progression of SCI. In addition, CD36 and Casp3 may be involved in the progression of SCI via the PPAR and p53 signaling pathways, respectively. [ABSTRACT FROM AUTHOR]

The aim of the present study was to explore the function and interaction of differentially expressed genes (DEGs) in pulmonary embolism (PE). The gene expression profile GSE13535, was downloaded from the Gene Expression Omnibus database. The DEGs 2 and 18 h post-PE initiation were identified using the affy package in R software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs were analyzed using Database for Annotation Visualization and Integrated Discovery (DAVID) online analytical tools. In addition, protein-protein interaction (PPI) networks of the DEGs were constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. The PPI network at 18 h was modularized using ClusterONE, and a functional enrichment analysis of the DEGs in the top three modules was performed with DAVID. Overall, 80 and 346 DEGs were identified 2 and 18 h after PE initiation, respectively. The KEGG pathways, including chemokine signaling and toll-like receptor signaling, were shown to be significantly enriched. The five highest degree nodes in the PPI networks at 2 or 18 h were screened. The module analysis of the PPI network at 18 h revealed 11 hub nodes. A Gene Ontology terms analysis demonstrated that the DEGs in the top three modules were associated with the inflammatory, defense and immune responses. The results of the present study suggest that the DEGs identified, including chemokine-related genes TFPI2 and TNF, may be potential target genes for the treatment of PE. The chemokine signaling pathway, inflammatory response and immune response were explored, and it may be suggested that these pathways have important roles in PE. [ABSTRACT FROM AUTHOR]