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Published in: Cancer Cell International 1/2020

Open Access 01-12-2020 | Primary research

Identification of a three-long noncoding RNA prognostic model involved competitive endogenous RNA in kidney renal clear cell carcinoma

Authors: Di Zhang, Song Zeng, Xiaopeng Hu

Published in: Cancer Cell International | Issue 1/2020

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Abstract

Background

Long noncoding RNA (lncRNA) is generally identified as competing endogenous RNA (ceRNA) that plays a vital role in the pathogenesis of kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma with poor prognosis and unclear pathogenesis. This study established a novel ceRNA network and thus identified a three-lncRNA prognostic model in KIRC patients.

Methods

Differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) database. The lncATLAS was applied to determine the differentially expressed lncRNAs (DElncRNAs) of the cytoplasm. The miRcode, miRDB, miRTarBase, and TargetScan databases were utilized to predict the interactions of DElncRNAs, DEmiRNAs, and DEmRNAs. Cytoscape was used to construct the ceRNA network. Then, a lncRNA prognostic model (LPM) was constructed based on ceRNA-related lncRNA that was significantly related to overall survival (OS), and its predictive ability was evaluated. Moreover, an LPM-based nomogram model was constructed. The significantly different expression of genes in the LPM was validated in an independent clinical cohort (N = 21) by quantitative RT-PCR.

Results

A novel ceRNA regulatory network, including 73 lncRNAs, 8 miRNAs, and 21 mRNAs was constructed. Functional enrichment analysis indicated that integral components of membrane and PI3K–Akt signaling pathway represented the most significant GO terms and pathway, respectively. The LPM established based on three lncRNAs (MIAT, LINC00460, and LINC00443) of great prognostic value from the ceRNA network was proven to be independent of conventional clinical parameters to differentiate patients with low or high risk of poor survival, with the AUC of 1-, 5- and 10-year OS were 0.723, 0.714 and 0.826 respectively. Furthermore, the nomogram showed a better predictive value in KIRC patients than individual prognostic parameters. The expression of MIAT and LINC00460 was significantly upregulated in the KIRC samples, while the expression of LINC00443 was significantly downregulated compared with the adjacent normal samples in the clinical cohort, TCGA, and GTEx.

Conclusion

This LPM based on three-lncRNA could serve as an independent prognostic factor with a tremendous predictive ability for KIRC patients, and the identified novel ceRNA network may provide insight into the prognostic biomarkers and therapeutic targets of KIRC.
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Literature
2.
go back to reference Barata PC. Treatment of renal cell carcinoma: current status and future directions. CA Cancer J Clin. 2017;67:507–24.CrossRefPubMed Barata PC. Treatment of renal cell carcinoma: current status and future directions. CA Cancer J Clin. 2017;67:507–24.CrossRefPubMed
4.
29.
go back to reference Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4(5):P3.CrossRefPubMed Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4(5):P3.CrossRefPubMed
Metadata
Title
Identification of a three-long noncoding RNA prognostic model involved competitive endogenous RNA in kidney renal clear cell carcinoma
Authors
Di Zhang
Song Zeng
Xiaopeng Hu
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2020
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-020-01423-4

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