Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

被引:36
作者
He, Jiefeng [1 ]
Zhao, Haichao [1 ]
Deng, Dongfeng [2 ]
Wang, Yadong [2 ]
Zhang, Xiao [2 ]
Zhao, Haoliang [1 ]
Xu, Zongquan [2 ]
机构
[1] Shanxi Med Univ, Shanxi Dayi Hosp, Dept Gen Surg, 99 Longcheng St, Taiyuan 030032, Shanxi, Peoples R China
[2] Henan Univ, Zhengzhou Univ, Peoples Hosp, Henan Prov Peoples Hosp,Dept Hepatobilliary Pancr, 7 Weiwu Rd, Zhengzhou 450003, Henan, Peoples R China
基金
中国国家自然科学基金;
关键词
biomarker; competing endogenous RNAs; gene signature; liver cancer; prognosis; LONG NONCODING RNA; EXPRESSION; GENES; PROLIFERATION; PREDICTION; CARCINOMA; PACKAGE; EDGER;
D O I
10.1002/jcp.29151
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.
引用
收藏
页码:2464 / 2477
页数:14
相关论文
共 54 条
[1]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[2]   Nomograms in oncology: more than meets the eye [J].
Balachandran, Vinod P. ;
Gonen, Mithat ;
Smith, J. Joshua ;
DeMatteo, Ronald P. .
LANCET ONCOLOGY, 2015, 16 (04) :E173-E180
[3]  
Barrett T, 2005, NUCLEIC ACIDS RES, V33, pD562
[4]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[5]   Genetic Variation in Aldo-Keto Reductase 1D1 (AKR1D1) Affects the Expression and Activity of Multiple Cytochrome P450s [J].
Chaudhry, Amarjit S. ;
Thirumaran, Ranjit K. ;
Yasuda, Kazuto ;
Yang, Xia ;
Fan, Yiping ;
Strom, Stephen C. ;
Schuetz, Erin G. .
DRUG METABOLISM AND DISPOSITION, 2013, 41 (08) :1538-1547
[6]   PPAR signaling pathway may be an important predictor of breast cancer response to neoadjuvant chemotherapy [J].
Chen, Y. Z. ;
Xue, J. Y. ;
Chen, C. M. ;
Yang, B. L. ;
Xu, Q. H. ;
Wu, F. ;
Liu, F. ;
Ye, X. ;
Meng, X. ;
Liu, G. Y. ;
Shen, Z. Z. ;
Shao, Z. M. ;
Wu, J. .
CANCER CHEMOTHERAPY AND PHARMACOLOGY, 2012, 70 (05) :637-644
[7]   Targeting the cell division cycle in cancer: CDK and cell cycle checkpoint kinase inhibitors [J].
Collins, I ;
Garrett, MD .
CURRENT OPINION IN PHARMACOLOGY, 2005, 5 (04) :366-373
[8]   InCeDB: Database of Human Long Noncoding RNA Acting as Competing Endogenous RNA [J].
Das, Shaoli ;
Ghosal, Suman ;
Sen, Rituparno ;
Chakrabarti, Jayprokas .
PLOS ONE, 2014, 9 (06)
[9]   Survival of patients with invasive cervical cancer in French Guiana, 2003-2008 [J].
Douine, Maylis ;
Roue, Tristan ;
Fior, Angela ;
Adenis, Antoine ;
Thomas, Nadia ;
Nacher, Mathieu .
INTERNATIONAL JOURNAL OF GYNECOLOGY & OBSTETRICS, 2014, 125 (02) :166-167
[10]   miRWalk2.0: a comprehensive atlas of microRNA-target interactions [J].
Dweep, Harsh ;
Gretz, Norbert .
NATURE METHODS, 2015, 12 (08) :697-697