Long noncoding RNA LINC00460 promotes carcinogenesis via sponging miR‐613 in papillary thyroid carcinoma

Li, Feng; Yang, Bin; Tang, Xiaodi

doi:10.1002/jcp.27799

Cited by 28 publications

(34 citation statements)

References 20 publications

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“…LINC00460, located on chromosome 13q33.2. has been shown to be up-regulated in cancers such as non-small cell lung cancer, esophageal squamous cell carcinoma, nasopharyngeal carcinoma, and thyroid carcinoma [46][47][48][49]. It can promote the migration and invasion of non-small cell lung cancer cells, induce epithelial-mesenchymal transition, and inhibit the growth of esophageal squamous cell carcinoma cells by regulating cell proliferation and apoptosis.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic biomarkers in lung adenocarcinoma based on aberrant lncRNA–miRNA–mRNA networks and Cox regression models

Yao

Zhang

et al. 2020

Bioscience Reports

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Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide, and its underlying mechanism remains unclear. Accumulating evidence has highlighted that long non-coding RNA (lncRNA) acts as competitive endogenous RNA (ceRNA) and plays an important role in the occurrence and development of LUAD. Here, we comprehensively analyzed and provided an overview of the lncRNAs, miRNAs, and mRNAs associated with LUAD from The Cancer Genome Atlas (TCGA) database. Then, differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA) were used to construct a lncRNA–miRNA–mRNA regulatory network according to interaction information from miRcode, TargetScan, miRTarBase, and miRDB. Finally, the RNAs of the network were analyzed for survival and submitted for Cox regression analysis to construct prognostic indicators. A total of 1123 DElncRNAs, 95 DEmiRNAs, and 2296 DEmRNAs were identified (|log2FoldChange| (FC) > 2 and false discovery rate (FDR) or adjusted P value < 0.01). The ceRNA network was established based on this and included 102 lncRNAs, 19 miRNAs, and 33 mRNAs. The DEmRNAs in the ceRNA network were found to be enriched in various cancer-related biological processes and pathways. We detected 22 lncRNAs, 12 mRNAs, and 1 miRNA in the ceRNA network that were significantly associated with the overall survival of patients with LUAD (P < 0.05). We established three prognostic prediction models and calculated the area under the 1,3,5-year curve (AUC) values of lncRNA, mRNA, and miRNA, respectively. Among them, the prognostic index (PI) of lncRNA showed good predictive ability which was 0.737, 0.702 and 0.671 respectively, and eight lncRNAs can be used as candidate prognostic biomarkers for LUAD. In conclusion, our study provides a new perspective on the prognosis and diagnosis of LUAD on a genome-wide basis, and develops independent prognostic biomarkers for LUAD.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognostic biomarkers in lung adenocarcinoma based on aberrant lncRNA–miRNA–mRNA networks and Cox regression models

Yao

Zhang

et al. 2020

Bioscience Reports

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“…Among the three lncRNAs in the LPM, LINC00460 is the most studied oncogenic lncRNA. On a large scale of cancer types, LINC00460 functions as a competing endogenous RNA, sponging multiple miRNAs, indicating that it plays a vital role in promoting tumor cell proliferation, migration, and invasion [36][37][38]. However, a rare study has explored the role of LINC00460 in KIRC, so this was the first study which found that high expression of LINC00460 is linked to poor prognosis in patients with KIRC.…”

Section: Discussionmentioning

confidence: 99%

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

Hu¹,

Zeng

2020

Preprint

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Background: Lone 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) located in 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 3 insight into the prognostic biomarkers and therapeutic targets of KIRC. BackgroundKidney Renal Clear Cell Carcinoma (KIRC), the most common and aggressive malignant subtype of renal cell carcinoma, has a poor prognosis and high mortality in an advanced stage due to the lack of useful biomarkers and treatments [1]. Currently, 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. Despite these treatments, about 50% of KIRC patients develop metastases, and the 5-year survival rate of these patients is still lower than 10% [2]. Therefore, the identification of u...

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“…It promotes the occurrence of NPC by regulating the miR-149-5p/IL6 signaling pathway (18), which is compatible with our ndings. However, the speci c function and mechanism of Linc00460 remain unclear, and previous studies have shown that the up-regulation of Linc00460 expression is closely related to TNM stage and lymph node metastasis (19), which indicates that similar to other lncRNAs, Linc00460 may act by regulating cell proliferation and migration in PTC tissues, and involves the regulation of cell cycle in the mechanism of regulating proliferation.…”

Section: Discussionmentioning

confidence: 99%

lncRNA-miRNA-mRNA ceRNA Network in Thyroid Carcinoma from The Cancer Genome Atlas

Mo¹,

Jiang²,

Wang³

et al. 2020

Preprint

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Increasing evidence indicates that the competitive endogenous RNA (ceRNA) hypothesis, that is, long non-coding RNA (LncRNA) can competitively bind microRNA (miRNA) through miRNA response elements to affect the expression of target RNA, and dysregulation of LncRNA expression plays a key role in tumor progression. The papillary thyroid carcinoma that we studied is the most significant pathological type of thyroid cancer, but its ceRNA network has not been extensively evaluated. We analyzed level-3 data from RNA-Seq of 58 para-carcinoma tissues and 501 patients with primary papillary thyroid carcinoma (PTC) using the DEseq software package and downloaded clinical information from The Cancer Genome Atlas (TCGA) to find potential biomarkers or therapeutic targets. As a result, 149 differential miRNAs were selected, including 117 up -regulated, 32 down-regulated, and 3099 differential mRNAs, including 1976 up-regulated, 1123 down-regulated, and 434 differential lncRNAs, including 331 up-regulated and 103 down-regulated (Fold Change > 2, P < 0.05). The interactions between these differentially expressed RNA groups constitute the ceRNA network of PTC. Moreover, we used the microde database to predict the miRNAs that may be acted by the above screened differential lncRNAs and intersected with the selected miRNAs, and further predicted the target genes of the intersecting miRNAs by TargetScan, miRTarBase and miRDB, and intersected with the selected mRNAs. From the constructed ceRNA network we can see that Linc00460 may cause the invasion and metastasis of PTC by competitively inhibiting hsa-mir-150 and upregulating the expression of its downstream target gene EREG. Our study identified a series of lncRNAs associated with PTC progression and prognosis, and this complex ceRNA interaction network provides guidance for better understanding of the molecular mechanisms of PTC and can be used as an effective diagnostic tool for PTC invasion, metastasis and prognosis. Kaplan-Meier analysis of the differentially expressed RNAs associated with PTC pathogenesis confirmed that the lncRNAs AC097717.1, C20orf203, EMX2OS were potentially associated with the prognosis of PTC (P<0.05).

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Long noncoding RNA LINC00460 promotes carcinogenesis via sponging miR‐613 in papillary thyroid carcinoma

Cited by 28 publications

References 20 publications

Comprehensive analysis of prognostic biomarkers in lung adenocarcinoma based on aberrant lncRNA–miRNA–mRNA networks and Cox regression models

Comprehensive analysis of prognostic biomarkers in lung adenocarcinoma based on aberrant lncRNA–miRNA–mRNA networks and Cox regression models

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

lncRNA-miRNA-mRNA ceRNA Network in Thyroid Carcinoma from The Cancer Genome Atlas

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