ArticleBioMed research international2018
Identification of the Key MicroRNAs and the miRNA-mRNA Regulatory Pathways in Prostate Cancer by Bioinformatics Methods.
Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 39 citations in OpenAlex.
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- CASC11 promotes aggressiveness of prostate cancer cells through miR-145/IGF1R axis.Prostate cancer and prostatic diseases · 2021Article
- Downregulation of microRNA-324-3p inhibits lung cancer by blocking the NCAM1-MAPK axis through ALX4.Cancer gene therapy · 2021Article
- Differential DNA Methylation in Prostate Tumors from Puerto Rican Men.International journal of molecular sciences · 2021Article
- Bioinformatic Analysis Identified Potentially Prognostic Long Noncoding RNAs and MicroRNAs for Gastric Cancer.BioMed research international · 2021Article
- Computational Recognition and Clinical Verification of TGF-β-Derived miRNA Signature With Potential Implications in Prognosis and Immunotherapy of Intrahepatic Cholangiocarcinoma.Frontiers in oncology · 2021Article
- KRT8 and KRT19, associated with EMT, are hypomethylated and overexpressed in lung adenocarcinoma and link to unfavorable prognosis.Bioscience reports · 2020Article
- Long non-coding RNA MALAT1 facilitates the tumorigenesis, invasion and glycolysis of multiple myeloma via miR-1271-5p/SOX13 axis.Journal of cancer research and clinical oncology · 2020Article
- Long non-coding RNA FER1L4 inhibits prostate cancer progression via sponging miR-92a-3p and upregulation of FBXW7.Cancer cell international · 2020Article
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Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify key microRNAs (miRNAs) and their regulatory networks in prostate cancer.
methodsFour miRNA and three gene expression microarray datasets were downloaded for analysis from Gene Expression Omnibus database. The differentially expressed miRNA and genes were accessed by a GEO2R. Functional and pathway enrichment analyses were performed using the DAVID program. Protein-protein interaction (PPI) and miRNA-mRNA regulatory networks were constructed using the STRING and Cytoscape tool. Moreover, the results and clinical significance were validated in TCGA data.
resultsWe identified 26 significant DEMs, 633 upregulated DEGs, and 261 downregulated DEGs. Functional enrichment analysis indicated that significant DEGs were related to TGF-beta signaling pathway and TNF signaling pathway in PCa. Key DEGs such as HSPA8, PPP2R1A, CTNNB1, ADCY5, ANXA1, and COL9A2 were found as hub genes in PPI networks. TCGA data supported our results and the miRNAs were correlated with clinical stages and overall survival.
conclusionsWe identified 26 miRNAs that may take part in key pathways like TGF-beta and TNF pathways in prostate cancer regulatory networks. MicroRNAs like miR-23b, miR-95, miR-143, and miR-183 can be utilized in assisting the diagnosis and prognosis of prostate cancer as biomarkers. Further experimental studies are required to validate our results.
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