Abstract

BackgroundLong 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.MethodsDifferentially 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.ResultsA 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.ConclusionThis 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.

Highlights

  • Long noncoding RNA is generally identified as competing endogenous RNA 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

  • Construction of the competing endogenous RNA (ceRNA) network Considering the nuclear-cytoplasmic localization of Long noncoding RNA (lncRNA) plays a vital role in its molecular function, we firstly confirmed the subcellular localization of the 2015 DElncRNAs by utilizing the lncATLAS database, and excluded 385 DElncRNAs which were located only in

  • Though many effective treatments have been developed for KIRC, the unsatisfied survival rate and intolerant of chemotherapy make it an emerging need for new therapeutic targets and prognostic biomarkers to improve the clinical outcomes of KIRC patients in the future [39]

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Summary

Introduction

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. There is a multitude of established treatments for KIRC, such as surgical resection, nonspecific immune approach, targeted therapy against vascular endothelial growth factor, and novel immunotherapy agents. The commonly used clinical prognostic markers of KIRC include the pathological grade system and tumor node metastasis (TNM) stage, microvascular invasion, tumor necrosis, and invasion of the collecting system [3]. These clinicopathological risk factors exhibit valuable but insufficient prediction of prognosis and estimation for subsets of KIRC patients. The identification of useful prognostic biomarkers and therapeutic targets is urgingly needed to predict more accurately and improve the outcome of KIRC patients

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