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Comprehensive analysis of the long non-coding RNA-associated competitive endogenous RNA network reveals novel prognostic biomarkers in Wilms' tumor.

ABSTRACT: Wilms' tumor (WT) is one of the most common types of renal carcinoma in children. The aim of the present study was to construct a competitive endogenous RNA (ceRNA) regulation network and explore novel prognostic biomarkers for WT. The expression profiles were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs). Based on the interactions between microRNAs (miRNAs) and mRNAs/long non-coding RNAs (lncRNAs), a ceRNA network was constructed. Functional enrichment analyses were subsequently conducted to explore the functions of the ceRNA-associated DEmRNAs. Survival analysis was performed to screen for prognosis-associated RNAs and the ?2 test was used to assess the associations between prognosis-associated RNA expression and histology classification/clinical staging. The present study identified 1,784 lncRNAs, 114 miRNAs and 3,337 mRNAs, which were abnormally expressed in WT compared with that in normal samples. By prediction, pairing and network analysis, a ceRNA network consisting of 38 DElncRNAs, 18 DEmiRNAs and 99 DEmRNAs was established. These DEmRNAs were significantly enriched in pathways associated with the occurrence and development of WT. By combining the expression data with survival analysis, seven prognosis-associated RNAs were identified (P<0.05). Of these seven RNAs, two (zinc finger and BTB domain containing 4; and deleted in lymphocytic leukemia 2) were significantly associated with clinical staging and histology classification. Lastly, the expression levels of the seven RNAs were verified in the Gene Expression Omnibus database. The present study revealed that 7 RNAs might be considered as novel prognostic biomarkers and potential treatment targets for therapy in WT. In addition, the ceRNA regulation network could provide novel strategies for further studies on lncRNAs and miRNAs in WT.

SUBMITTER: Liu Z

PROVIDER: S-EPMC7202313 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Comprehensive analysis of the long non-coding RNA-associated competitive endogenous RNA network reveals novel prognostic biomarkers in Wilms' tumor.

Liu Zifeng Z Zhao Wenbo W Ren Yuqing Y Liu Chang C Liu Xun X Xiao Jian J

Oncology letters 20200331 6

Wilms' tumor (WT) is one of the most common types of renal carcinoma in children. The aim of the present study was to construct a competitive endogenous RNA (ceRNA) regulation network and explore novel prognostic biomarkers for WT. The expression profiles were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs). Based on the interactions between microRNAs (miRNAs) and mRNAs/long non-coding RNAs (lncRNAs), a ceRNA network was constructed. Functional ...[more]

PMID: 32382326

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Project description:BackgroundLong non-coding RNA (lncRNA) functions as a competitive endogenous RNA (ceRNA) and plays an important role in the biological processes underlying tumorigenesis. However, studies describing the function of lncRNA in pheochromocytoma and paraganglioma (PCPG) remain largely unknown. Our study aims to construct a regulatory ceRNA network and explore prognostic biomarkers for PCPG through a comprehensive analysis.MethodsPCPG data from The Cancer Genome Atlas (TCGA) were utilized to obtain differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs). Kaplan-Meier analysis was used to detect prognostic biomarkers and Cytoscape was utilized to construct a regulatory network of ceRNA. Potential lncRNA-miRNA-mRNA axes were inferred by correlation analysis. GO and KEGG pathways were constructed using "clusterProfiler" and "DOSE" R-packages. Immunohistochemistry (IHC) staining was performed to validate differential protein expression levels of genes in the axes. Finally, the GSE19422 dataset and Pan-Cancer data were applied to validate the expression pattern and survival status of mRNAs, respectively.ResultsA total of 334 DElncRNAs, 116 DEmiRNAs, and 3496 DEmRNAs were identified and mainly enriched in hormone secretion, metabolism signaling, metastatic and proliferative pathways. Among these differentially expressed genes, 16 mRNAs, six lncRNAs, and two miRNAs were associated with overall survival of patients with PCPG and sequentially enrolled in the ceRNA network. Two lncRNA-miRNA-mRNA regulatory axes were predicted: AP001486.2/hsa-miR-195-5p/RCAN3 and AP006333.2/hsa-miR-34a-5p/PTPRJ. The GSE19422 dataset and IHC analysis validated that mRNA and protein levels of RCAN3 and PTPRJ were upregulated in PCPG tissues compared with adjacent adrenal gland medulla tissues. Pan-Cancer data showed that the upregulated expression of RCAN3 and PTPRJ was associated with favorable overall survival and disease-free survival.ConclusionA regulatory lncRNA-miRNA-mRNA ceRNA network was successfully constructed and 24 prognostic biomarkers were identified for PCPG patients. These findings may contribute toward a better understanding of the biological mechanism of tumorigenesis and enable further evaluation of the prognosis of patients with PCPG.

Project description:Globally, non-small cell lung cancer (NSCLC) is the most common malignancy and its prognosis remains poor because of the lack of reliable early diagnostic biomarkers. The competitive endogenous RNA (ceRNA) network plays an important role in the tumorigenesis and prognosis of NSCLC. Tumor immune microenvironment (TIME) is valuable for predicting the response to immunotherapy and determining the prognosis of NSCLC patients. To understand the TIME-related ceRNA network, the RNA profiling datasets from the Genotype-Tissue Expression and The Cancer Genome Atlas databases were analyzed to identify the mRNAs, microRNAs, and lncRNAs associated with the differentially expressed genes. Weighted gene co-expression network analysis revealed that the brown module of mRNAs and the turquoise module of lncRNAs were the most important. Interactions among microRNAs, lncRNAs, and mRNAs were prognosticated using miRcode, miRDB, TargetScan, miRTarBase, and starBase databases. A prognostic model consisting of 13 mRNAs was established using univariate and multivariate Cox regression analyses and validated by the receiver operating characteristic (ROC) curve. The 22 immune infiltrating cell types were analyzed using the CIBERSORT algorithm, and results showed that the high-risk score of this model was related to poor prognosis and an immunosuppressive TIME. A lncRNA-miRNA-mRNA ceRNA network that included 69 differentially expressed lncRNAs (DElncRNAs) was constructed based on the five mRNAs obtained from the prognostic model. ROC survival analysis further showed that the seven DElncRNAs had a substantial prognostic value for the overall survival (OS) in NSCLC patients; the area under the curve was 0.65. In addition, the high-risk group showed drug resistance to several chemotherapeutic and targeted drugs including cisplatin, paclitaxel, docetaxel, gemcitabine, and gefitinib. The differential expression of five mRNAs and seven lncRNAs in the ceRNA network was supported by the results of the HPA database and RT-qPCR analyses. This comprehensive analysis of a ceRNA network identified a set of biomarkers for prognosis and TIME prediction in NSCLC.

Dataset Information

Comprehensive analysis of the long non-coding RNA-associated competitive endogenous RNA network reveals novel prognostic biomarkers in Wilms' tumor.

Publications

Comprehensive analysis of the long non-coding RNA-associated competitive endogenous RNA network reveals novel prognostic biomarkers in Wilms' tumor.

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