Identification of unique long non-coding RNAs as putative biomarkers for chromophobe renal cell carcinoma

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Item Type:	Article
Title:	Identification of unique long non-coding RNAs as putative biomarkers for chromophobe renal cell carcinoma
Creators Name:	Wu, G., Xia, P., Yan, S., Chen, D., Xie, L. and Fan, G.
Abstract:	AIM: To investigate whether long non-coding RNAs (lncRNAs) can be utilized as molecular biomarkers in predicting the occurrence and progression of chromophobe renal cell carcinoma. METHODS & RESULTS: Genetic and related clinical traits of chromophobe renal cell carcinoma were downloaded from the Cancer Genome Atlas and used to construct modules using weighted gene coexpression network analysis. In total, 44,889 genes were allocated into 21 coexpression modules depending on intergenic correlation. Among them, the green module was the most significant key module identified by module-trait correlation calculations (R(2) = 0.43 and p = 4e-04). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that genes in the green module were enriched in many pathways. Coexpression, protein-protein interaction networks, screening for differentially expressed genes, and survival analysis were used to select hub lncRNAs. Five hub lncRNAs (TTK, CENPE, KIF2C, BUB1, and RAD51AP1) were selected out. CONCLUSION: Our findings suggest that the five lncRNAs may act as potential biomarkers for chromophobe renal cell carcinoma progression and prognosis.
Keywords:	Bioinformatics, Biomarker, Chromophobe Renal Cell Carcinoma, Differentially Expressed Genes, Hub Gene, Long Non-Coding RNA, The Cancer Genome Atlas, Weighted Gene Coexpression Network Analysis
Source:	Personalized Medicine
ISSN:	1741-0541
Publisher:	Future Medicine
Volume:	18
Number:	1
Page Range:	9-19
Date:	January 2021
Official Publication:	https://doi.org/10.2217/pme-2020-0020
PubMed:	View item in PubMed

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