Abstract
Hepatocellular carcinoma (HCC) is one of the most common types of malignancy and is associated with high mortality. Prior research suggests that long non-coding RNAs (lncRNAs) play a crucial role in the development of HCC. Therefore, it is necessary to identify lncRNA-associated therapeutic biomarkers to improve the accuracy of HCC prognosis. Transcriptomic data of HCC obtained from The Cancer Genome Atlas (TCGA) database were used in the present study. Differentially expressed RNAs (DERNAs), including 74 lncRNAs, 16 miRNAs, and 35 mRNAs, were identified using bioinformatics analysis. The DERNAs were subsequently used to reconstruct a competing endogenous RNA (ceRNA) network. A lncRNA signature was revealed using Cox regression analysis, including LINC00200, MIR137HG, LINC00462, AP002478.1, and HTR2A-AS1. Kaplan-Meier plot demonstrated that the lncRNA signature is highly accurate in discriminating high- and low-risk patients (P < 0.05). The area under curve (AUC) value exceeded 0.7 in both training and validation cohort, suggesting a high prognostic potential of the signature. Furthermore, multivariate Cox regression analysis indicated that both the TNM stage and the lncRNA signature could serve as independent prognostic factors for HCC (P < 0.05). Then, a nomogram comprising the TNM stage and the lncRNA signature was determined to raise the accuracy in predicting the survival of HCC patients. In the present study, we have introduced a ceRNA network that could contribute to provide a new insight into the identification of potential regulation mechanisms for the development of HCC. The five-lncRNA signature could serve as a reliable biosignature for HCC prognosis, while the nomogram possesses strong potential in clinical applications.
Highlights
Liver cancer is one of the most common types of malignancy, with 841,080 new cases and 781,631 cancer deaths being reported globally in 2018 (Bray et al, 2018)
The RNA sequencing (RNA-seq) data (FPKM, Fragment Per Kilobase of transcript per Million mapped reads) and the corresponding clinical information of 376 hepatocellular carcinoma (HCC) patients were downloaded from the The Cancer Genome Atlas (TCGA) database1
To elucidate the potential regulatory mechanism governing competing endogenous RNA (ceRNA) in HCC, we established a ceRNA network for HCC based on the ceRNA hypothesis
Summary
Liver cancer is one of the most common types of malignancy, with 841,080 new cases and 781,631 cancer deaths being reported globally in 2018 (Bray et al, 2018). In the United States, the death rates of liver are the fastest growing ones in comparison to other cancer (Islami et al, 2017). It is estimated that 42,030 new cases of liver cancer will be diagnosed in 2019 causing 31780 deaths in United States (Siegel et al, 2019). The major histology phenotype (approximately 80%) of liver cancer is hepatocellular carcinoma (HCC) accounting for more than 80% of liver cancer cases worldwide (McGlynn et al, 2015; Yang et al, 2019). It is urgently important to identify novel biomarkers that can more accurately prognose the outcomes of the disease to optimize the clinical management of HCC patients (Bruix et al, 2016)
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