Premium
Screening of significant biomarkers related with prognosis of liver cancer by lncRNA‐associated ceRNAs analysis
Author(s) -
He Jiefeng,
Zhao Haichao,
Deng Dongfeng,
Wang Yadong,
Zhang Xiao,
Zhao Haoliang,
Xu Zongquan
Publication year - 2020
Publication title -
journal of cellular physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 174
eISSN - 1097-4652
pISSN - 0021-9541
DOI - 10.1002/jcp.29151
Subject(s) - competing endogenous rna , nomogram , proportional hazards model , biology , long non coding rna , oncology , liver cancer , gene , cancer , medicine , multivariate analysis , survival analysis , bioinformatics , rna , genetics
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.