Dataset Information

Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.

ABSTRACT: BACKGROUND It is widely known that hepatocellular carcinoma (HCC) has high rates of morbidity and mortality. A large number of studies have indicated that pseudogenes have an important effect on the carcinogenesis of HCC. Pseudogenes can play a role through the ceRNA network. There have been numerous studies on lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. However, the pseudogene-miRNA-mRNA network in HCC has rarely been researched or reported on. MATERIAL AND METHODS The Cancer Genome Atlas (TCGA) database was researched and differences between selected genes were studied. A pseudogene-miRNA-mRNA network was then constructed and clustering of pseudogenes was studied. The diagnostic value of the selected pseudogenes, their functions, and pathways were investigated using available databases to understand their possible pathogenic mechanism in HCC. The protein-protein interaction network of target genes was found and the top 10 hub genes were identified. Expression of hub genes in HCC tissues was then detected by RT-qPCR. RESULTS By analyzing the gene difference and clinical data of HCC, we constructed a ceRNA network composed of 4 pseudogenes, 8 miRNAs, and 30 mRNAs. The pseudogenes AP000769.1, KRT16P1, KRT16P3, and RPLP0P2 were all correlated with the diagnosis and prognosis of HCC. Functional analyses through the Kyoto Encyclopedia of Genes and Genomes and the Gene Ontology databases indicated that pseudogenes can affect the physiological process of HCC through the p53 pathway. The top 10 hub genes identified were all highly expressed in HCC tissues and affected the patient survival rate. CONCLUSIONS In this study, 4 pseudogenes related to the diagnosis and prognosis of liver cancer were found through the construction of a ceRNA network. These 4 pseudogenes might constitute new therapeutic targets for liver cancer patients.

SUBMITTER: Yan L

PROVIDER: S-EPMC7249743 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.

Yan Lijun L Yue Chaosen C Xu Yingchen Y Jiang Xincen X Zhang Lijun L Wu Jixiang J

Medical science monitor : international medical journal of experimental and clinical research 20200516

BACKGROUND It is widely known that hepatocellular carcinoma (HCC) has high rates of morbidity and mortality. A large number of studies have indicated that pseudogenes have an important effect on the carcinogenesis of HCC. Pseudogenes can play a role through the ceRNA network. There have been numerous studies on lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. However, the pseudogene-miRNA-mRNA network in HCC has rarely been researched or reported on. MATERIAL AND METHODS The Cancer Genome Atla ...[more]

PMID: 32457285

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Project description:Liver hepatocellular carcinoma (LIHC) is one of the major causes of cancer-related death worldwide with increasing incidences, however there are very few studies about the underlying mechanisms and pathways in the development of LIHC. We obtained LIHC samples from The Cancer Genome Atlas (TCGA) to screen differentially expressed mRNAs, lncRNAs, miRNAs and driver mutations. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses and protein-protein interaction (PPI) network were performed. Moreover, we constructed a competing endogenous lncRNAs-miRNAs-mRNAs network. Finally, cox proportional hazards regression analysis was used to identify important prognostic differentially expressed genes. Total of 1284 mRNAs, 123 lncRNAs, 47 miRNAs were identified within different tissues of LIHC patients. GO analysis indicated that upregulated and downregulated differentially expressed mRNAs (DEmRNAs) were mainly associated with cell division, DNA replication, mitotic sister chromatid segregation and complement activation respectively. Meanwhile, KEGG terms revealed that upregulated and downregulated DEmRNAs were primarily involved in DNA replication, Metabolic pathways, cell cycle and Metabolic pathways, chemical carcinogenesis, retinol metabolism pathway respectively. Among the DERNAs, 542 lncRNAs-miRNAs-mRNAs pairs were predicted to construct a ceRNA regulatory network including 35 DElncRNAs, 26 DEmiRNAs and 112 DEmRNAs. In the Kaplan-Meier analysis, total of 43 mRNAs, 14 lncRNAs and 3 miRNAs were screened out to be significantly correlated with overall survival of LIHC. The mutation signatures were analyzed and its correlation with immune infiltrates were evaluated using the TIMER in LIHC. Among the mutation genes, TTN mutation is often associated with poor immune infiltration and a worse prognosis in LIHC. This work conducted a novel lncRNAs-miRNAs-mRNAs network and mutation signatures for finding potential molecular mechanisms underlying the development of LIHC. The biomarkers also can be used for predicting prognosis of LIHC.

Project description:BACKGROUND:Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML is still rarely reported. METHOD:We obtained transcriptome data of AML and normal samples from The Cancer Genome Atlas (TCGA), Genotype-tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, and identified differentially expressed (DE) mRNAs, lncRNAs, and circRNAs. Then, the targeting relationships among lncRNA-miRNA, circRNA-miRNA, and miRNA-mRNA were predicted, and the survival related hub mRNAs were further screened by univariate and multivariate Cox proportional hazard regression. Finally, the AML prognostic circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. RESULTS:We identified prognostic 6 hub mRNAs (TM6SF1, ZMAT1, MANSC1, PYCARD, SLC38A1, and LRRC4) through Cox regression model, and divided the AML samples into high and low risk groups according to the risk score obtained by multivariate Cox regression. Survival analysis verified that the survival rate of the high-risk group was significantly reduced (p < 0.0001). The prognostic ceRNA network of 6 circRNAs, 32 lncRNAs, 8 miRNAs, and 6 mRNAs was established according to the targeting relationship between 6 hub mRNAs and other RNAs. CONCLUSION:In this study, ceRNA network jointly participated by circRNAs and lncRNAs was established for the first time. It comprehensively elucidated the post-transcriptional regulatory mechanism of AML, and identified novel AML prognostic biomarkers, which has important guiding significance for the clinical diagnosis, treatment, and further scientific research of AML.

Dataset Information

Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.

Publications

Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.

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