Background: Hepatocellular carcinoma (HCC) is a common type of cancer with a high
mortality rate and is usually detected at the middle or late stage, missing the optimal treatment period.
The current study aims to identify potential long non-coding RNA (lncRNAs) biomarkers that
contribute to the diagnosis and prognosis of HCC.
Methods: The differentially expressed lncRNAs (DElncRNAs) in HCC patients were detected
from the Cancer Genome Atlas (TCGA) dataset. LncRNAs signature was screened by LASSO regression,
univariate, and multivariate Cox regression. The models for predicting diagnosis and
prognosis were established, respectively. The prognostic model was evaluated by Kaplan-Meier
survival curve receiver operating characteristic (ROC) curve and stratified analysis. The diagnostic
model was validated by ROC. The lncRNAs signature was further demonstrated by functional enrichment
Results: We found the 13-lncRNAs signature that had a good performance in predicting prognosis
and could help to improve the value of diagnosis. In the training set, testing set, and entire cohort,
the low-risk group had longer survival than the high-risk group (median OS: 3124 vs. 649 days,
2456 vs. 770 days and 3124 vs. 755 days). It performed well in 1-, 3-, and 5-year survival prediction.
13-lncRNAs-based risk score, age, and race were good predictors of prognosis. The AUC of
diagnosis was 0.9487, 0.9265, and 0.9376, respectively. Meanwhile, the 13-lncRNAs were involved
in important pathways, including the cell cycle and multiple metabolic pathways.
Conclusion: In our study, the 13-lncRNAs signature may be a potential marker for the prognosis
of HCC and improve the diagnosis.