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LINC00461 affects the survival of patients with renal cell carcinoma by acting as a competing endogenous RNA for microRNA?942.

ABSTRACT: The present study aimed to investigate the potential mechanisms of human miR?942 in the sunitinib?resistance of renal cell carcinoma (RCC). A sunitinib?resistant OS?RC?2 cell line was established by continuous exposure to increasing concentrations of sunitinib for ~12 weeks. The expression levels of four miRNAs were determined by reverse transcription?quantitative (RT?q)PCR. miR?942 mimics were transfected into OS?RC?2 cells and RNA sequencing was performed on the miR?942? and negative control?transfected cells. Downregulated genes, including those of long non?coding RNAs (lncRNAs) and mRNAs, were identified. The target genes of miR?942 were predicted, followed by protein?protein interaction network construction and functional enrichment analyses of miR?942 target genes. In addition, RCC RNA?seq and miRNA?seq data were downloaded from The Cancer Genome Atlas (TCGA) database. The contributions of lncRNA and/or mRNAs to survival prediction were assessed and a competing endogenous RNA (ceRNA) network consisting of miR?942, lncRNA and mRNAs was constructed. The expression levels of LINC00461, miR?942, spalt?like transcription factor 1 (SALL1), methionyl aminopeptidase 1 (METAP1) and DDB1 and CUL4 associated factor 1 (DCAF11) were verified using RT?qPCR. The role of LINC00461 in cell viability was detected by MTT assay. The expression level of miR?942 was significantly increased in sunitinib?resistant cells. A total of seven lncRNAs and 155 mRNAs were predicted as target genes of miR?942 in the miR?942 mimic?treated samples, compared with the mimic control?treated group. These potential target genes were significantly associated with 'protein binding', 'TNF?? signaling pathway', 'negative transcriptional regulation' and 'RNA binding'. Through the integrated analysis of RNA?sequencing and TCGA data, an miR?942?related ceRNA network, which was predicted to significantly affect the survival of patients with RCC, was constructed. The expression levels of lncRNA LINC00461 and the genes SALL1, METAP1, and DCAF11 were further verified. The viability of OS?RC?2 cells was decreased following co?transfection with miR?942 mimics and LINC00641 siRNA, and was comparable to that of wild type OS?RC?2 cells (P>0.05). Therefore, lncRNA LINC00461 may act as an miR?942 ceRNA, and affect the survival of patients with RCC by regulating the expression of SALL1, METAP1 and DCAF11.

SUBMITTER: Chen Y

PROVIDER: S-EPMC6775798 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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LINC00461 affects the survival of patients with renal cell carcinoma by acting as a competing endogenous RNA for microRNA‑942.

Chen Yicheng Y He Jinkui J Su Changju C Wang Huan H Chen Yuanlei Y Guo Wenhao W Li Yining Y Ding Guoqing G

Oncology reports 20190912 5

The present study aimed to investigate the potential mechanisms of human miR‑942 in the sunitinib‑resistance of renal cell carcinoma (RCC). A sunitinib‑resistant OS‑RC‑2 cell line was established by continuous exposure to increasing concentrations of sunitinib for ~12 weeks. The expression levels of four miRNAs were determined by reverse transcription‑quantitative (RT‑q)PCR. miR‑942 mimics were transfected into OS‑RC‑2 cells and RNA sequencing was performed on the miR‑942‑ and negative control‑t ...[more]

PMID: 31545458

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Project description:Background:Cell autophagy has been proposed to be involved in drug resistance therapy. However, how the long non-coding RNA (lncRNA) reduces risks of drug resistance in renal cancer (RC) cells needs a thorough inquiry. This study was assigned to probe the effect and mechanism of HOTAIR on sunitinib resistance of RC. Methods:Clinical RC tissues and para-carcinoma tissues were obtained to detect the expressions of miR-17-5p, HOTAIR and Beclin1. Sunitinib-resistant cells (786-O-R and ACHN-R) were constructed using parental RC cells (786-O and ACHN). The resistance of 786-O-R and ACHN-R cells to sunitinib was examined. Western blot and qRT-PCR were assayed to obtain the expressions of miR-17-5p, HOTAIR and Beclin1. The effects of HOTAIR knockdown or miR-17-5p overexpression/knockdown on cell autophagy and sunitinib resistance were measured by MDC staining, immunofluorescence and Western blot. The sensitivity of RC cells to sunitinib and change in cell clone formation after sunitinib treatment were assessed by CCK-8 assay and colony formation assay, respectively. The relationships among HOTAIR, miR-17-5p and Beclin1 were verified by dual-luciferase reporter gene and RIP assay. The role of HOTAIR knockdown in sunitinib resistance was verified in nude mice. Results:HOTAIR expression in sunitinib-resistant cells is higher than that in parental cells. Knockdown of HOTAIR in sunitinib-resistant cells lead to refrained sunitinib resistance and cell autophagy both in vivo and in vitro. Activation of autophagy could raise resistance to sunitinib in RC cells, while inhibition of autophagy could improve the sensitivity of sunitinib-resistant cells to sunitinib. HOTAIR could compete with miR-17-5p to regulate Beclin1 expression. Knockdown of miR-17-5p in parental cells increases cell resistant to sunitinib, and overexpression of miR-17-5p in sunitinib-resistant cells increases cell sensitive to sunitinib. Conclusion:HOTAIR negatively targets miR-17-5p to activate Beclin1-mediated cell autophagy, thereby enhancing sunitinib resistance in RC cells.

Project description:The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA‑sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE‑miRNAs), long non‑coding RNAs (DE‑lncRNAs) and genes (DEGs). Subsequently, lncRNA‑miRNA, miRNA‑gene (that is, miRNA‑mRNA) and gene‑gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA‑mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE‑lncRNAs, 917 DEGs and 30 DE‑miRNAs were screened. The miRNA‑mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand‑receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine‑cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA‑206 and kallikrein‑related peptidase 10 were nodes in the ceRNA regulatory network of the selected feature gene, and they may serve import roles in the development of PTC.

Dataset Information

LINC00461 affects the survival of patients with renal cell carcinoma by acting as a competing endogenous RNA for microRNA?942.

Publications

LINC00461 affects the survival of patients with renal cell carcinoma by acting as a competing endogenous RNA for microRNA‑942.

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