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Competing endogenous RNA network and prognostic nomograms for hepatocellular carcinoma patients who underwent R0 resection
Author(s) -
Li Yuntong,
Ma Bingfen,
Yin Zhenyu,
Liu Pingguo,
Liu Jianming,
Li Jie,
Wang Fuqiang,
Chen Huimin
Publication year - 2019
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.28634
Subject(s) - nomogram , competing endogenous rna , microrna , hepatocellular carcinoma , concordance , proportional hazards model , rna , oncology , messenger rna , long non coding rna , medicine , biology , gene , genetics
The prognosis of hepatocellular carcinoma (HCC) after R0 resection is unsatisfactory due to the high rate of recurrence. In this study, we investigated the recurrence‐related RNAs and the underlying mechanism. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data and clinical information of 247 patients who underwent R0 resection patients with HCC were obtained from The Cancer Genome Atlas. Comparing the 1‐year recurrence group ( n = 56) with the nonrecurrence group ( n = 60), we detected 34 differentially expressed lncRNAs (DElncRNAs), five DEmiRNAs, and 216 DEmRNAs. Of these, three DElncRNAs, hsa‐mir‐150‐5p, and 11 DEmRNAs were selected for constructing the competing endogenous RNA (ceRNA) network. Next, two nomogram models were constructed based separately on the lncRNAs and mRNAs that were further selected by Cox and least absolute shrinkage and selection operator regression analysis. The two nomogram models that showed a high prediction accuracy for disease‐free survival with the concordance indexes at 0.725 and 0.639. Further functional enrichment analysis of DEmRNAs showed that the mRNAs in the ceRNA network and nomogram models were associated with immune pathways. Hence, we constructed a hsa‐mir‐150‐5p‐centric ceRNA network and two effective nomogram prognostic models, and the related RNAs may be useful as potential biomarkers for predicting recurrence in patients with HCC.