Open AccessIntegrated analysis of long noncoding RNA associated‐competing endogenous RNA as prognostic biomarkers in clear cell renal carcinoma
Author(s) -
Yin Hang,
Wang Xiaoyuan,
Zhang Xue,
Wang Yan,
Zeng Yangyang,
Xiong Yudi,
Li Tianqi,
Lin Rongjie,
Zhou Qian,
Ling Huan,
Zhou Fuxiang,
Zhou Yunfeng
Publication year - 2018
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/cas.13778
Subject(s) - rna , biology , messenger rna , gene expression , long non coding rna , competing endogenous rna , non coding rna , microbiology and biotechnology , gene , cancer research , computational biology , genetics
Clear cell renal cell carcinoma (cc RCC ) is one of the most common malignant carcinomas and its molecular mechanisms remain unclear. Long noncoding RNA (lnc RNA ) could bind sites of mi RNA which affect the expression of mRNA according to the competing endogenous (ce RNA ) theory. The aim of the present study was to construct a ce RNA network and to identify key lnc RNA to predict survival prognosis. We identified differentially expressed mRNA , lnc RNA and mi RNA between tumor tissues and normal tissues from The Cancer Genome Atlas database. Then, using bioinformatics tools, we explored the connection of 89 lnc RNA , 10 mi RNA and 22 mRNA , and we constructed the ce RNA network. Furthermore, we analyzed the functions and pathways of 22 differentially expressed mRNA . Then, univariate and multivariate Cox regression analyses of these 89 lnc RNA and overall survival were explored. Nine lnc RNA were finally screened out in the training group. The patients were divided into high‐risk and low‐risk groups according to the 9 lnc RNA and low‐risk scores having better clinical overall survival ( P < .01). Furthermore, the receiver operating characteristic curve demonstrates the predicted role of the 9 lnc RNA . The 9‐lnc RNA signature was successfully proved in the testing group and the entire group. Finally, multivariate Cox regression analysis and stratification analysis further proved that the 9‐lnc RNA signature was an independent factor to predict survival. In summary, the present study provides a deeper understanding of the lnc RNA ‐related ce RNA network in cc RCC and suggests that the 9‐lnc RNA signature could serve as an independent biomarker to predict survival in cc RCC patients.