| Title |
Biomarker and competing endogenous RNA potential of tumor-specific long noncoding RNA in chromophobe renal cell carcinoma
|
|---|---|
| Published in |
OncoTargets and therapy, October 2016
|
| DOI | 10.2147/ott.s116392 |
| Pubmed ID | |
| Authors |
Hai-Tao He, Mu Xu, Ye Kuang, Xiao-Yun Han, Ming-Qi Wang, Qing Yang |
| Abstract |
Accumulating evidence suggests long noncoding RNAs (lncRNAs) play important roles in the initiation and progression of cancers. However, their functions in chromophobe renal cell carcinoma (chRCC) are not fully understood. We analyzed the expression profiles of lncRNA, microRNA, and protein-coding RNA, along with the clinical information of 59 primary chRCC patients collected from The Cancer Genome Atlas database to identify lncRNA biomarkers for prognosis. We also constructed an lncRNA-microRNA-mRNA coexpression network (competitive endogenous RNAs network) by bioinformational approach. One hundred and forty-two lncRNAs were found to be differentially expressed between the cancer and normal tissues (fold change ≥1.5, P<0.001). Among them, 12 lncRNAs were also differentially expressed with the corresponding clinical characteristics (fold change ≥1.5, P<0.01). Besides, 7 lncRNAs (COL18A1-AS, BRE-AS1, SNHG7, TMEM51-AS1, C21orf62-AS1, LINC00336, and LINC00882) were identified to be significantly correlated with overall survival (log-rank P<0.05). A competitive endogenous RNA network in chRCC containing 16 lncRNAs, 18 miRNAs, and 168 protein-coding RNAs was constructed. Our results identified specific lncRNAs associated with chRCC progression and prognosis, and presented competing endogenous RNA potential of lncRNAs in the tumor. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 4% |
| Unknown | 23 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 25% |
| Student > Bachelor | 5 | 21% |
| Student > Doctoral Student | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Student > Master | 3 | 13% |
| Other | 2 | 8% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 38% |
| Agricultural and Biological Sciences | 5 | 21% |
| Medicine and Dentistry | 3 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Chemical Engineering | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 3 | 13% |
Attention Score in Context
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#22,759,452
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Outputs from OncoTargets and therapy
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Outputs of similar age from OncoTargets and therapy
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