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Identification of a new pseudogenes/lncRNAs-hsa-miR-26b-5p-COL12A1 competing endogenous RNA network associated with prognosis of pancreatic cancer using bioinformatics analysis.

ABSTRACT: BACKGROUND:Pancreatic carcinoma is one of the most malignant cancers globally. However, a systematic mRNA-miRNA-lncRNA/pseudogene network associated with the molecular mechanism of pancreatic cancer progression has not been described. RESULTS:The significant DEGs identified comprised 159 up-regulated and 92 down-regulated genes. According to the expression and survival analysis, three genes (COL12A1, APOL1, and MMP14) were significantly higher in tumor samples when compared with normal controls and their upregulation indicated a poor prognosis. Subsequently, 28, 17, and 11 miRNAs were predicted to target COL12A1, APOL1, and MMP14, respectively. The hsa-miR-26b-5p-COL12A1 axis showed a potential in suppressing the progression of pancreatic cancer. Moreover, 12 lncRNAs and 92 pseudogenes were predicted to potentially bind to the hsa-miR-26b-5p. Based on the results from expression and correlation analysis, NAMPTP1/HCG11-hsa-miR-26b-5p-COL12A1 competing endogenous RNA (ceRNA) sub-network was associated with the prognosis of pancreatic cancer. CONCLUSIONS:In a word, we elucidate a new NAMPTP1/ HCG11-hsa-miR-26b-5p-COL12A sub-network in the progression of pancreatic cancer, which may serve as a promising diagnostic biomarker or effective therapeutic target for pancreatic cancer. MATERIALS AND METHODS:Differentially expressed genes (DEGs) were first identified by mining GSE28735, GSE62452 and GSE41368 datasets. Functional enrichment analysis was conducted using the DAVID database. Protein-protein interaction (PPI) network was performed using the STRING database, and hub genes were identified by Cytoscape. Upstream miRNAs and pseudogenes /lncRNAs of mRNAs were forecast using miRTarBase, miRNet, and starBase. Expression, survival, and correlation analysis of genes, miRNAs, and pseudogenes /lncRNAs were validated using GEPIA, Kaplan-Meier, and starBase.

SUBMITTER: Jing S

PROVIDER: S-EPMC7732303 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Identification of a new pseudogenes/lncRNAs-hsa-miR-26b-5p-COL12A1 competing endogenous RNA network associated with prognosis of pancreatic cancer using bioinformatics analysis.

Jing Shilei S Tian Jiao J Zhang Yanpeng Y Chen Xinhua X Zheng Shusen S

Aging 20201007 19

<h4>Background</h4>Pancreatic carcinoma is one of the most malignant cancers globally. However, a systematic mRNA-miRNA-lncRNA/pseudogene network associated with the molecular mechanism of pancreatic cancer progression has not been described.<h4>Results</h4>The significant DEGs identified comprised 159 up-regulated and 92 down-regulated genes. According to the expression and survival analysis, three genes (COL12A1, APOL1, and MMP14) were significantly higher in tumor samples when compared with n ...[more]

PMID: 33027767

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Project description:Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Dataset Information

Identification of a new pseudogenes/lncRNAs-hsa-miR-26b-5p-COL12A1 competing endogenous RNA network associated with prognosis of pancreatic cancer using bioinformatics analysis.

Publications

Identification of a new pseudogenes/lncRNAs-hsa-miR-26b-5p-COL12A1 competing endogenous RNA network associated with prognosis of pancreatic cancer using bioinformatics analysis.

Similar Datasets

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