Dependence of artesunate on long noncoding RNA‐RP11 to inhibit epithelial‐mesenchymal transition of hepatocellular carcinoma

2018 ◽  
Vol 120 (4) ◽  
pp. 6026-6034 ◽  
Author(s):  
Wu Jing ◽  
Hu Dong ◽  
Mu Min ◽  
Zhao Runpeng ◽  
Xu Xuewei ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Epithelial Mesenchymal Transition ◽  
Mesenchymal Transition

scholarly journals Long noncoding RNA CPS1-IT1 suppresses the metastasis of hepatocellular carcinoma by regulating HIF-1α activity and inhibiting epithelial-mesenchymal transition

Oncotarget ◽  
2016 ◽  
Vol 7 (28) ◽  
pp. 43588-43603 ◽  
Author(s):  
Tong-Hong Wang ◽  
Cheng-Chia Yu ◽  
Yong-Shiang Lin ◽  
Tse-Ching Chen ◽  
Chau-Ting Yeh ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Epithelial Mesenchymal Transition ◽  
Mesenchymal Transition

scholarly journals An epithelial–mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Hang Tong ◽  
Tinghao Li ◽  
Shun Gao ◽  
Hubin Yin ◽  
Honghao Cao ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Epithelial Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Functional Enrichment ◽  
Diagnostic Efficacy ◽  
Mesenchymal Transition

Abstract Bladder cancer is a common malignant tumour worldwide. Epithelial–mesenchymal transition (EMT)-related biomarkers can be used for early diagnosis and prognosis of cancer patients. To explore, accurate prediction models are essential to the diagnosis and treatment for bladder cancer. In the present study, an EMT-related long noncoding RNA (lncRNA) model was developed to predict the prognosis of patients with bladder cancer. Firstly, the EMT-related lncRNAs were identified by Pearson correlation analysis, and a prognostic EMT-related lncRNA signature was constructed through univariate and multivariate Cox regression analyses. Then, the diagnostic efficacy and the clinically predictive capacity of the signature were assessed. Finally, Gene set enrichment analysis (GSEA) and functional enrichment analysis were carried out with bioinformatics. An EMT-related lncRNA signature consisting of TTC28-AS1, LINC02446, AL662844.4, AC105942.1, AL049840.3, SNHG26, USP30-AS1, PSMB8-AS1, AL031775.1, AC073534.1, U62317.2, C5orf56, AJ271736.1, and AL139385.1 was constructed. The diagnostic efficacy of the signature was evaluated by the time-dependent receiver-operating characteristic (ROC) curves, in which all the values of the area under the ROC (AUC) were more than 0.73. A nomogram established by integrating clinical variables and the risk score confirmed that the signature had a good clinically predict capacity. GSEA analysis revealed that some cancer-related and EMT-related pathways were enriched in high-risk groups, while immune-related pathways were enriched in low-risk groups. Functional enrichment analysis showed that EMT was associated with abundant GO terms or signaling pathways. In short, our research showed that the 14 EMT-related lncRNA signature may predict the prognosis and progression of patients with bladder cancer.

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