Dataset Information

CircUBAP2-mediated competing endogenous RNA network modulates tumorigenesis in pancreatic adenocarcinoma.

ABSTRACT: We investigated the role of the competing endogenous RNA (ceRNA) network in the development and progression of pancreatic adenocarcinoma (PAAD). We analyzed the expression profiles of PAAD and normal pancreatic tissues from multiple GEO databases and identified 457 differentially expressed circular RNAs (DEcircRNAs), 19 microRNAs (DEmiRNAs) and 1993 mRNAs (DEmRNAs). We constructed a ceRNA network consisting of 4 DEcircRNAs, 3 DEmiRNAs and 149 DEmRNAs that regulates the NF-kappa B, PI3K-Akt, and Wnt signaling pathways. We then identified and validated five hub genes, CXCR4, HIF1A, ZEB1, SDC1 and TWIST1, which are overexpressed in PAAD tissues. The expression of CXCR4, HIF1A, ZEB1, and SDC1 in PAAD was regulated by circ-UBAP2 and hsa-miR-494. The expression of CXCR4 and ZEB1 correlated with the levels of M2 macrophages, T-regulatory cells (Tregs) and exhausted T cells in the PAAD tissues. The expression of CXCR4 and ZEB1 positively correlated with the expression of CTLA-4 and PD-1. This suggests that CXCR4 and ZEB1 proteins inhibit antigen presentation and promote immune escape mechanisms in PAAD cells. In summary, our data suggest that the circUBAP2-mediated ceRNA network modulates PAAD by regulating the infiltration and function of immune cells.

SUBMITTER: Zhao R

PROVIDER: S-EPMC6814619 | biostudies-other | 2019 Oct

REPOSITORIES: biostudies-other

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CircUBAP2-mediated competing endogenous RNA network modulates tumorigenesis in pancreatic adenocarcinoma.

Zhao Rongjie R Ni Junjie J Lu Si S Jiang Sujing S You Liangkun L Liu Hao H Shou Jiawei J Zhai Chongya C Zhang Wei W Shao Shengpeng S Yang Xinmei X Pan Hongming H Han Weidong W

Aging 20191004 19

We investigated the role of the competing endogenous RNA (ceRNA) network in the development and progression of pancreatic adenocarcinoma (PAAD). We analyzed the expression profiles of PAAD and normal pancreatic tissues from multiple GEO databases and identified 457 differentially expressed circular RNAs (DEcircRNAs), 19 microRNAs (DEmiRNAs) and 1993 mRNAs (DEmRNAs). We constructed a ceRNA network consisting of 4 DEcircRNAs, 3 DEmiRNAs and 149 DEmRNAs that regulates the NF-kappa B, PI3K-Akt, and ...[more]

PMID: 31584877

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Project description:Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function and application of circRNAs in lung adenocarcinoma (LUAD) are still unknown. In this study, we constructed a circRNA-associated competitive endogenous RNA (ceRNA) network to investigate the regulatory mechanism of LUAD procession and further constructed a prognostic signature to predict overall survival for LUAD patients. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network. Based on the TargetScan prediction tool and Pearson correlation coefficient, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs, and 49 DEmRNAs. GO and KEGG enrichment indicated that the ceRNA network might be involved in the regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate Cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using the LASSO method in the TCGA-LUAD training cohort. By applying the signature, patients could be categorized into the high-risk or low-risk subgroups with significant survival differences (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009). The prognostic performance was confirmed in an independent GEO cohort (GSE42127, HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004). Multivariate Cox regression analysis proved that the three-gene signature was an independent prognostic factor. Combining the three-gene signature with clinical characters, a nomogram was constructed. The primary and external verification C-indexes were 0.717 and 0.716, respectively. The calibration curves for the probability of 3- and 5-year OS showed significant agreement between nomogram predictions and actual observations. Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and further constructed a useful prognostic signature to guide personalized treatment of LUAD patients.

Project description:BackgroundPancreatic cancer is an insidious and heterogeneous malignancy with poor prognosis that is often locally unresectable. Therefore, determining the underlying mechanisms and effective prognostic indicators of pancreatic cancer may help optimize clinical management. This study was conducted to develop a prognostic model for pancreatic cancer based on a competing endogenous RNA (ceRNA) network.MethodsWe obtained transcriptomic data and corresponding clinicopathological information of pancreatic cancer samples from The Cancer Genome Atlas (TCGA) database (training set). Based on the ceRNA interaction network, we screened candidate genes to build prediction models. Univariate Cox regression analysis was performed to screen for genes associated with prognosis, and least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive model. A receiver operating characteristic (ROC) curve was drawn, and the C-index was calculated to evaluate the accuracy of the prediction model. Furthermore, we downloaded transcriptomic data and related clinical information of pancreatic cancer samples from the Gene Expression Omnibus database (validation set) to evaluate the robustness of our prediction model.ResultsEight genes (ANLN, FHDC1, LY6D, SMAD6, ACKR4, RAB27B, AUNIP, and GPRIN3) were used to construct the prediction model, which was confirmed as an independent predictor for evaluating the prognosis of patients with pancreatic cancer through univariate and multivariate Cox regression analysis. By plotting the decision curve, we found that the risk score model is an independent predictor has the greatest impact on survival compared to pathological stage and targeted molecular therapy.ConclusionsAn eight-gene prediction model was constructed for effectively and independently predicting the prognosis of patients with pancreatic cancer. These eight genes identified show potential as diagnostic and therapeutic targets.

Dataset Information

CircUBAP2-mediated competing endogenous RNA network modulates tumorigenesis in pancreatic adenocarcinoma.

Publications

CircUBAP2-mediated competing endogenous RNA network modulates tumorigenesis in pancreatic adenocarcinoma.

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