Pancreatic cancer remains one of the leading causes of cancer-related deaths worldwide. Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic tumor. Many circular RNAs (circRNAs) have proven to play vital roles in the physiological and pathological processes of tumorigenesis; however, their biogenesis in PDAC remains unclear. In this study, the expression profiles of circRNAs from 10 PDAC tissues and their paired adjacent nontumor tissues were analyzed through RNA sequencing analysis. An enrichment analysis was employed to predict the functions of the differentially expressed circRNAs. Sequence alignment information and mRNA microarray projects were used to predict the RNA regulatory network. The knockdown of circRNAs by small interfering RNAs followed by wound healing and western blot assays was used to confirm their functions in a PDAC cell line. A total of 278 circRNAs were identified as differentially expressed in PDAC tissue. Of these, we found that hsa_circRNA_0007334 was significantly upregulated and may serve as a competing endogenous RNA to regulate matrix metallopeptidase 7 (MMP7) and collagen type I alpha 1 chain (COL1A1) by the competitive adsorption of hsa-miR-144-3p and hsa-miR-577 to enhance the expression and functions of MMP7 and COL1A1 in PDAC. In vitro experiments confirmed these results. The present study is the first to propose two regulatory pathways in PDAC: hsa_circRNA_0007334–hsa-miR-144-3p–MMP7 and hsa_circRNA_0007334–hsa-miR-577–COL1A1.
Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.
BackgroundOsteosarcoma (OS) is a primary malignant bone tumor with a high fatality rate. Many circRNAs have been proved to play important roles in the pathogenesis of some diseases. However, the occurrence of circRNAs in OS remains little known.MethodsThe circular RNA (circRNA) expression file GSE96964 dataset, which included seven osteosarcoma cell lines and one control sample (osteoblast cell line), was downloaded from the Gene Expression Omnibus (GEO) database to explore the potential function of circRNAs in osteosarcoma by competing endogenous RNA (ceRNA) analysis. Three gene expression profiles of OS were downloaded from GEO database and then used for the pathway enrichment analysis, Venn analysis and protein-protein interaction (PPI) network analysis. Real-time qPCR validation and RNA interference were conducted to verify our prediction.ResultsDifferentially expressed circRNAs between OS and control, including 8 up-regulated and 102 down-regulated circRNAs, were generated and ceRNA analysis for 5 most up-regulated or 5 most down-regulated circRNAs in OS were then performed. The pathway enrichment analysis of gene expression profiles indicated differentially expressed genes (DEGs) of three gene profiles significantly enriched in cell cycle pathway, cell adhesion molecules (CAMs) pathway, oxidative phosphorylation pathway, cytokine-cytokine receptor interaction pathway, p53 signaling pathway and proteoglycans in cancer pathway, which were critical important pathways in the pathogenesis of OS. The Venn analysis showed that 2 (one is a pseudogene) up-regulated and 39 down-regulated DEGs were co-expressed in all three gene profiles. Then PPI networks of 41 co-expressed DEGs (up- and down-regulated DEGs) were constructed to predict their functions using the GeneMANIA. The expression levels of these related RNAs also matched our predictions really well.ConclusionUltimately, we found cell adhesion molecule 1 (CADM1) gene was not only a co-expression mRNA of the three mRNA expression profiles of OS, but also are predicted to be regulated by hsa_circ_0032462, hsa_circ_0028173, hsa_circ_0005909 by functioning as miRNAs ‘Sponge’ in human osteosarcoma. These over-expressed circRNAs may result in the over expression of CADM1 which promote the development of OS. We envision this discovery of these important moleculars, incuding hsa_circ_0032462, hsa_circ_0028173, hsa_circ_0005909 and CADM1 may lead to further development of new concepts, thus allowing for more opportunities in diagnosis and therapy of OS.
Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathways are largely unclear. The aim of this study was to screen and verify hub genes involved in OA and explore potential molecular mechanisms. The expression profiles of GSE12021 and GSE55235 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 39 samples, including 20 osteoarthritis synovial membranes and 19 matched normal synovial membranes. The raw data were integrated to obtain differentially expressed genes (DEGs) and were deeply analyzed by bioinformatics methods. The Gene Ontology (GO) and pathway enrichment of DEGs were performed by DAVID and Kyoto Encyclopedia of Genes and Genomes (KEGG) online analyses, respectively. The protein-protein interaction (PPI) networks of the DEGs were constructed based on data from the STRING database. The top 10 hub genes VEGFA, IL6, JUN, IL1β, MYC, IL4, PTGS2, ATF3, EGR1, and DUSP1 were identified from the PPI network. Module analysis revealed that OA was associated with significant pathways including TNF signaling pathway, cytokine-cytokine receptor interaction, and osteoclast differentiation. The qRT-PCR result showed that the expression level of IL6, VEGFA, JUN, IL-1β, and ATF3 was significantly increased in OA samples (p < 0.05), and these candidate genes could be used as potential diagnostic biomarkers and therapeutic targets of OA.
Osteosarcoma (OS) is one of the most common primary malignant bone tumors in adolescents with a high mortality rate. MicroRNA (miRNA) is a kind of noncoding RNAs and has been proved to participate in many physiological processes. Many miRNAs have been reported to act as function regulators in OS. In our study, the miRNA and gene expression profiles of OS were downloaded from GEO Datasets and the differential expression analysis was performed using GEO2R. 58 up- and 126 downregulated miRNAs were found. In the three OS gene profiles, 125 up- and 27 downregulated genes were found to be differentially expressed in at least two profiles. The miRNA-mRNA networks were constructed to predict the potential target genes of 10 most up- and downregulated miRNA. Venn analysis was used to detect the coexpressed differentially expressed genes (DEGs). EBF2, one of the upregulated DEGs, was also a potential target gene of miR-182-3p. Knockdown and overexpression of miR-182-3p resulted in overexpression and downexpression of EBF2 separately. Luciferase reporter gene experiment further verified the binding site of miR-182-3p and EBF2. CCK8 assay showed that miR-182-3p knockdown can further enhance the proliferation activity of OS cells, while overexpressing miR-182-3p can inhibit the proliferation activity of OS cells. Our research indicated that downexpression of miR-182-3p in OS cells results in overexpression of EBF2 and promotes the progression of OS.
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