MicroRNAs signatures, bioinformatics analysis of miRNAs, miRNA mimics and antagonists, and miRNA therapeutics in osteosarcoma

Background: Gastric cancer (GC) is one of the most common malignancies worldwide. However, the biomarkers for the prognosis and diagnosis of Gastric cancer were still need. Objective: The present study aimed to evaluate whether CPZ could be a potential biomarker for GC. Method: Kaplan-Meier plotter (http://kmplot.com/analysis/) was used to determine the correlation between CPZ expression and overall survival (OS) and disease-free survival (DFS) time in GC [9]. We analyzed CPZ expression in different types of cancer and the correlation of CPZ expression with the abundance of immune infiltrates, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, via gene modules using TIMER Database. Results: The present study identified that CPZ was overexpressed in multiple types of human cancer, including Gastric cancer. We found that overexpression of CPZ correlates to the poor prognosis of patients with STAD. Furthermore, our analyses show that immune infiltration levels and diverse immune marker sets are correlated with levels of CPZ expression in STAD. Bioinformatics analysis revealed that CPZ was involved in regulating multiple pathways, including PI3K-Akt signaling pathway, cGMP-PKG signaling pathway, Rap1 signaling pathway, TGF-beta signaling pathway, regulation of cell adhesion, extracellular matrix organization, collagen fibril organization, collagen catabolic process. Conclusion: This study for the first time provides useful information to understand the potential roles of CPZ in tumor immunology and validate it to be a potential biomarker for GC.

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Identification of key mRNAs and lncRNAs involved in the effects of anti-TWEAK on Osteosarcoma

Current Bioinformatics ◽

10.2174/1574893615999200626191405 ◽

2020 ◽

Vol 15 ◽

Author(s):

Mingxuan Yang ◽

Liangtao Zhao ◽

Xuchang Hu ◽

Haijun Feng ◽

Xuewen Kang

Keyword(s):

Dna Replication ◽

Signaling Pathway ◽

Bioinformatics Analysis ◽

Mapk Signaling ◽

Migration And Invasion ◽

Type I ◽

Interferon Signaling ◽

Nf Kappa B ◽

Ppi Networks ◽

Coexpression Networks

Background: Osteosarcoma (OS) is one of the most common primary malignant bone tumors in teenagers. Emerging studies demonstrated TWEAK and Fn14 were involved in regulating cancer cell differentiation, proliferation, apoptosis, migration and invasion. Objective: The present study identified differently expressed mRNAs and lncRNAs after anti-TWEAK treatment in OS cells using GSE41828. Methods: We identified 922 up-regulated mRNAs, 863 downregulated mRNAs, 29 up-regulated lncRNAs, and 58 down-regulated lncRNAs after anti-TWEAK treatment in OS cells. By constructing PPI networks, we identified several key proteins involved in anti-TWEAK treatment in OS cells, including MYC, IL6, CD44, ITGAM, STAT1, CCL5, FN1, PTEN, SPP1, TOP2A, and NCAM1. By constructing lncRNAs coexpression networks, we identified several key lncRNAs, including LINC00623, LINC00944, PSMB8-AS1, LOC101929787. Result: Bioinformatics analysis revealed DEGs after anti-TWEAK treatment in OS were involved in regulating type I interferon signaling pathway, immune response related pathways, telomere organization, chromatin silencing at rDNA, and DNA replication. Bioinformatics analysis revealed differently expressed lncRNAs after antiTWEAK treatment in OS were related to telomere organization, protein heterotetramerization, DNA replication, response to hypoxia, TNF signaling pathway, PI3K-Akt signaling pathway, Focal adhesion, Apoptosis, NF-kappa B signaling pathway, MAPK signaling pathway, FoxO signaling pathway. Conclusion: : This study provided useful information for understanding the mechanisms of TWEAK underlying OS progression and identifying novel therapeutic markers for OS.

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Bioinformatics Analysis and Validation of Differentially Expressed MicroRNAs with Their Target Genes Involved in GLP-1RA Facilitated Osteogenesis

Current Bioinformatics ◽

10.2174/1574893615999200508091615 ◽

2020 ◽

Vol 15 ◽

Author(s):

Na Wang ◽

Yukun Li ◽

Sijing Liu ◽

Liu Gao ◽

Chang Liu ◽

...

Keyword(s):

High Throughput Sequencing ◽

Target Genes ◽

Bioinformatics Analysis ◽

Differentially Expressed ◽

Functional Study ◽

Regulation Network ◽

Glucagon Like Peptide 1 ◽

G Protein Coupled ◽

Lower Expression

Background: Recent studies revealed that the hypoglycemic hormone, glucagon-like peptide-1 (GLP-1), acted as an important modulator in osteogenesis of bone marrow derived mesenchymal stem cells (BMSCs). Objectives: The aim of this study was to identify the specific microRNA (miRNA) using bioinformatics analysis and validate the presence of differentially expressed microRNAs with their target genes after GLP-1 receptor agonist (GLP-1RA) administration involved in ostogenesis of BMSCs. Methods: MiRNAs were extracted from BMSCs after 5 days’ treatment and sent for high-throughput sequencing for differentially expressed (DE) miRNAs analyses. Then the expression of the DE miRNAs verified by the real-time RT-PCR analyses. Target genes were predicted, and highly enriched GOs and KEGG pathway analysis were conducted using bioinformatics analysis. For the functional study, two of the target genes, SRY (sex determining region Y)-box 5 (SOX5) and G protein-coupled receptor 84 (GPR84), were identified. Results: A total of 5 miRNAs (miRNA-509-5p, miRNA-547-3p, miRNA-201-3p, miRNA-201-5p, and miRNA-novel-272-mature) were identified differentially expressed among groups. The expression of miRNA-novel-272-mature were decreased during the osteogenic differentiation of BMSCs, and GLP-1RA further decreased its expression. MiRNA-novel-272-mature might interact with its target mRNAs to enhance osteogenesis. The lower expression of miRNA-novel-272-mature led to an increase in SOX5 and a decrease in GPR84 mRNA expression, respectively. Conclusions: Taken together, these results provide further insights to the pharmacological properties of GLP-1RA and expand our knowledge on the role of miRNAs-mRNAs regulation network in BMSCs’ differentiation.

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