Comprehensive analysis of a novel lncRNA profile reveals potential prognostic biomarkers in clear cell renal cell carcinoma

Liu, Tong; Sui, Jing; Zhang, Yan; Zhang, Xiaomei; Wu, Wenjuan; Yang, Sheng; Xu, Siyi; Hong, Wan; Peng, Hui; Ye, Lihong; Pu, Yue‐Pu; Liang, Geyu

doi:10.3892/or.2018.6540

Cited by 13 publications

(16 citation statements)

References 35 publications

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“…The present findings suggested that the 10 DElncRNAs of the optimal combination may be involved in the pathogenesis of ccRCC. Among the 10 DElncRNAs, COL18A1-AS1 ( 68 , 69 ), TCL6 ( 70 ) and TFAP2A-AS1 ( 71 ) are associated with a worse survival of patients with ccRCC, in accordance with the results of the present study. Furthermore, ELOVL2-AS1, LINC00189, LINC00470, LINC00896 and MIR205HG may be associated with tumors other than ccRCC.…”

Section: Discussionsupporting

confidence: 92%

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma

Dang

Wang

et al. 2020

Oncol Lett

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Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of RCC; however, prognostic prediction tools for ccRCC are scant. Developing mRNA or long non-coding RNA (lncRNA)-based risk assessment tools may improve the prognosis in patients with ccRCC. RNA-sequencing and prognostic data from patients with ccRCC were downloaded from The Cancer Genome Atlas and the European Bioinformatics Institute Array database at the National Center for Biotechnology Information. Differentially expressed (DE) RNAs (DERs) and prognostic DERs were screened between less favorable and favorable prognoses using the limma package in R 3.4.1, and analyzed using univariate and multivariate Cox regression analyses, respectively. Risk score models were constructed using optimal combinations of DEmRNAs and DElncRNAs identified using the Least Absolute Shrinkage And Selection Operator Cox regression model of the penalized package. Associations between risk score models and overall survival time were evaluated. Independent prognostic clinical factors were screened using univariate and multivariate Cox regression analyses, and nomogram models were constructed. Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using the clusterProfiler package in R3.4.1. A total of 451 DERs were identified, including 404 mRNAs and 47 lncRNAs, between less favorable and favorable prognoses, and 269 DERs, including 233 mRNAs and 36 lncRNAs, were identified as independent prognostic factors. Optimal combinations including 10 DEmRNAs or 10 DElncRNAs were screened using four risk score models based on the status or expression levels of the 10 DEmRNAs or 10 DElncRNAs. The model based on the expression levels of the 10 DEmRNAs had the highest prognostic power. These prognostic DEmRNAs may be involved in biological processes associated with the inflammatory response, complement and coagulation cascades and neuroactive ligand-receptor interaction pathways. The present validated risk assessment tool based on the expression levels of these 10 DEmRNAs may help to identify patients with ccRCC at a high risk of mortality. These 10 DEmRNAs in optimal combinations may serve as prognostic biomarkers and help to elucidate the pathogenesis of ccRCC.

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Section: Discussionsupporting

confidence: 92%

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma

Dang

Wang

et al. 2020

Oncol Lett

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“…In 2018, Liu et al published a paper on a novel lncRNA profile reveals potential prognostic biomarkers in clear cell renal cell carcinoma. The expression profile of 1801 lncRNAs of ccRCC patients was obtained using TCGA RNASeqv2 system [39]. To enable a comprehensive understanding of lncRNAs in ccRCC, the present study mined high-throughput TCGA data from 530 patients and analyzed 13,198 lncRNAs.…”

Section: Discussionmentioning

confidence: 99%

Prognosis of clear cell renal cell carcinoma (ccRCC) based on a six-lncRNA-based risk score: an investigation based on RNA-sequencing data

Zeng¹,

Lü²,

Liang³

et al. 2019

J Transl Med

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Background The scientific understanding of long non-coding RNAs (lncRNAs) has improved in recent decades. Nevertheless, there has been little research into the role that lncRNAs play in clear cell renal cell carcinoma (ccRCC). More lncRNAs are assumed to influence the progression of ccRCC via their own molecular mechanisms. Methods This study investigated the prognostic significance of differentially expressed lncRNAs by mining high-throughput lncRNA-sequencing data from The Cancer Genome Atlas (TCGA) containing 13,198 lncRNAs from 539 patients. Differentially expressed lncRNAs were assessed using the R packages edgeR and DESeq. The prognostic significance of lncRNAs was measured using univariate Cox proportional hazards regression. ccRCC patients were then categorized into high- and low-score cohorts based on the cumulative distribution curve inflection point the of risk score, which was generated by the multivariate Cox regression model. Samples from the TCGA dataset were divided into training and validation subsets to verify the prognostic risk model. Bioinformatics methods, gene set enrichment analysis, and protein–protein interaction networks, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were subsequently used. Results It was found that the risk score based on 6 novel lncRNAs (CTA-384D8.35, CTD-2263F21.1, LINC01510, RP11-352G9.1, RP11-395B7.2, RP11-426C22.4) exhibited superior prognostic value for ccRCC. Moreover, we categorized the cases into two groups (high-risk and low-risk), and also examined related pathways and genetic differences between them. Kaplan–Meier curves indicated that the median survival time of patients in the high-risk group was 73.5 months, much shorter than that of the low-risk group (112.6 months; P < 0.05). Furthermore, the risk score predicted the 5-year survival of all 539 ccRCC patients (AUC at 5 years, 0.683; concordance index [C-index], 0.853; 95% CI 0.817–0.889). The training set and validation set also showed similar performance (AUC at 5 years, 0.649 and 0.681, respectively; C-index, 0.822 and 0.891; 95% CI 0.774–0.870 and 0.844–0.938). Conclusions The results of this study can be applied to analyzing various prognostic factors, leading to new possibilities for clinical diagnosis and prognosis of ccRCC.

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“…LINC00202 is one of the lncRNAs associated with overall survival (OS) time in patients with renal cancer (Liu et al, 2018). To investigate if LINC00202 functions in RB, we first examined this lncRNA expression in RB tissues by qRT-PCR.…”

Section: Linc00202 Is Up-regulated In Rb and High Linc00202 Expressiomentioning

confidence: 99%

“…LINC00202 is a lncRNA related to poor prognosis in RB. It has been reported that it is also associated with overall survival (OS) time in patients with renal cancer (Liu et al, 2018). However, the biological functions of LINC00202 have not been clarified.…”

Section: Introductionmentioning

confidence: 99%

Long Noncoding RNA LINC00202 Promotes Tumor Progression by Sponging miR-3619-5p in Retinoblastoma

Yan

et al. 2019

Cell Struct. Funct.

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Retinoblastoma (RB) is the most common intraocular malignancy in childhood, and the prognosis in the advanced RB is poor. It is urgent to find novel therapeutic targets. Long noncoding RNAs (lncRNAs) have critical functions in cancer progression, and lncRNA LINC00202 is found associated with poor prognosis in RB. However, the functions of LINC00202 in RB remain unclear. We employed qRT-PCR and immunoblot to detect the expression levels of mRNAs and proteins, respectively. Cell proliferation was determined by CCK-8 assay and colony formation assay. Transwell assays were applied to evaluate the cell abilities of migration and invasion. Luciferase reporter assay was applied to examine RNA stability, and RNA pulldown assays were used to detect interaction between lncRNA and microRNA (miRNA). LINC00202 expression in RB tissues is higher than that in the paired adjacent normal tissues, which has correlation with poor prognosis in RB. RB cell proliferation, migration and invasion were weakened by LINC00202 depletion, but enhanced by LINC00202 overexpression. MiR-3619-5p was identified to directly bind and mediate LINC00202-promoted RB progression, meanwhile, miR-3619-5p directly regulated expression of an oncongene, RIN1. Moreover, RIN1 knockdown completely blocked miR-3619-5p-enhanced RB progression. In summary, high LINC00202 levels are correlated with poor prognosis in RB, and it promotes RB progression by sponging miR-3619-5p and therefore up-regulating RIN1 expression.

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Comprehensive analysis of a novel lncRNA profile reveals potential prognostic biomarkers in clear cell renal cell carcinoma

Cited by 13 publications

References 35 publications

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma

Prognosis of clear cell renal cell carcinoma (ccRCC) based on a six-lncRNA-based risk score: an investigation based on RNA-sequencing data

Long Noncoding RNA LINC00202 Promotes Tumor Progression by Sponging miR-3619-5p in Retinoblastoma

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