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. 2020 Aug;9(16):5719-5730.
doi: 10.1002/cam4.3275. Epub 2020 Jul 6.

A prognostic model composed of four long noncoding RNAs predicts the overall survival of Asian patients with hepatocellular carcinoma

Xuefeng Gu  1   2 , Hongbo Li  3 , Ling Sha  4 , Wei Zhao  1   2
Affiliations

A prognostic model composed of four long noncoding RNAs predicts the overall survival of Asian patients with hepatocellular carcinoma

Xuefeng Gu et al. Cancer Med. 2020 Aug.

Abstract

Based on accumulating evidence, long noncoding RNAs (lncRNAs) are potential biomarkers and therapeutic targets for many diseases, including tumors. In this study, we consulted The Cancer Genome Atlas (TCGA) database to explore the functions and modulatory mechanisms of lncRNAs as competing endogenous RNAs (ceRNAs) in hepatocellular carcinoma (HCC) in Asian patients and constructed a risk scoring system composed of four lncRNAs (SNHG1, STEAP3-AS1, RUSC1-AS1, and SNHG3) to predict the outcomes of Asian patients with HCC. The prognostic value of this risk model was validated in the internal validation cohort (n = 157). The stratified survival analysis revealed good performance for the risk model in stratifying clinical features. According to the Cox proportional hazard regression analysis, the four-lncRNA risk model is an independent prognostic model for Asian patients with HCC. Finally, we developed a nomogram that integrates prognostic signals and other clinical information to predict 1-, 3-, and 5-year overall survival rates. In conclusion, the prognostic lncRNAs identified in our study exerted potential biological effects on the development of HCC. The risk scoring model based on four lncRNAs may be an effective classification tool for assessing the prognosis of Asian patients with HCC.

Keywords: TCGA; ceRNA; hepatocellular carcinoma; lncRNA; overall survival; risk score.

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Conflict of interest statement

The authors have declared that no competing interest exists.

Figures

FIGURE 1
FIGURE 1
Specific lncRNA‐related ceRNA network and characteristics of the constituent lncRNAs in Asian patients with HCC. The volcano plot shows the expression profiles of mRNAs (A), lncRNAs (B), and miRNAs (C). Red dots indicate upregulated RNAs, and green dots indicate downregulated RNAs. ceRNA: competing endogenous RNA, HCC: hepatocellular carcinoma, lncRNA: long noncoding RNA, miRNA: microRNA
FIGURE 2
FIGURE 2
Heatmaps of differentially expressed RNAs in different samples: A, mRNAs, B, lncRNAs, and C, miRNAs. The y‐axis represents RNAs and the x‐axis represents patient samples; red denotes upregulation and green denotes downregulation
FIGURE 3
FIGURE 3
The ceRNA network in Asian patients with HCC. A, Venn diagram of DEmRNAs involved in the ceRNA network. B, The ceRNA network of lncRNAs‐miRNAs‐mRNAs involved in HCC. Ellipses represent lncRNAs, rectangles represent miRNAs, and octagons represent mRNAs. The nodes highlighted in red and blue indicate up‐ and downregulation, respectively. DEmRNAs: differentially expressed mRNAs
FIGURE 4
FIGURE 4
Enrichment analysis of DEmRNAs involved in the ceRNA network. A, The top 10 significantly enriched pathways identified in the DEmRNA GO enrichment analysis. B, Significantly enriched KEGG pathways of DERNAs (FDR <0.05). DEmRNA: differentially expressed mRNA, GO: gene ontology, KEGG: Kyoto Encyclopedia of Genes and Genomes, FDR: false discovery rate.
FIGURE 5
FIGURE 5
Construction of a four‐lncRNA risk model for Asian patients with HCC. A, Distribution of lncRNA risk scores for 157 Asian patients with HCC. B, Survival status of each patient. C, Heatmap showing the expression of the four lncRNAs corresponding to each of the above samples. Red: high expression; green: low expression. D, Kaplan‐Meier analysis of the OS of Asian patients with HCC using the risk scores based on the four characteristic lncRNAs. E, Analysis of the predicted survival based on the time‐dependent ROC curve for the prognostic model. F, Analysis of the Kaplan‐Meier curve for the four‐lncRNA prognostic model risk scores in the internal validation cohort to validate the OS of Asian patients with HCC. G, Analysis of time‐dependent ROC curves for survival predicted by the prognostic model and verified in the internal validation cohort. OS: overall survival, ROC: receiver operating characteristic.
FIGURE 6
FIGURE 6
Confirmation and development of the lncRNA risk scoring system using a TCGA cohort. Analysis of Kaplan‐Meier curves for OS values of the subgroups of Asian patients with HCC using the four‐lncRNA risk model, including (A) TNM I + II phase, (B) TNM III + IV phase, (C) histology G1 + G2 phase, (D) histology G3 + G4 phase, (E) ECOG = 0, (F) ECOG ≥ 1, (G) without HBV, (H) with HBV, (I) alcohol consumption (no) , (K) AFP≤ 20 ng/mL, (M) no vascular invasion, and (N) vascular invasion. No significant difference in Asian patients with a history of alcohol consumption (J) or an AFP> 20 ng/ml (L) (all P > 0.05). P values were determined using the log‐rank test. TCGA: The Cancer Genome Atlas, R: residual tumor, ECOG: Eastern Cooperative Oncology Group, HBV: hepatitis B virus, AFP: Alpha‐fetoprotein
FIGURE 7
FIGURE 7
Univariate and multivariate Cox regression analyses of Asian patients with HCC
FIGURE 8
FIGURE 8
Establishment of a nomogram for predicting the OS of Asian patients with HCC. (A) Nomogram used to predict the 1‐, 3‐, and 5‐year survival rates of Asian patients with HCC. Total points were calculated by adding the corresponding points for each individual covariate included in the scale. Then, 1‐, 3‐, and 5‐year survival rates were obtained by directly converting the total points. Calibration chart of the nomogram used to predict the (C) 1‐, (D) 3‐, and (E) 5‐year OS rates. The predicted probability and actual probability of OS are plotted on the x‐ and y‐axes, respectively
FIGURE 9
FIGURE 9
Flow chart of the bioinformatics analysis
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