AUTHOR=Li Wang , Chen Qi-Feng , Huang Tao , Wu Peihong , Shen Lujun , Huang Zi-Lin 

TITLE=Identification and Validation of a Prognostic lncRNA Signature for Hepatocellular Carcinoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 10 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.00780

DOI=10.3389/fonc.2020.00780

ISSN=2234-943X

ABSTRACT=Background: As suggested in increasing studies, lncRNAs, the long non-coding RNAs, can serve as the potential cancer prognostic factors. However, the role of lncRNAs combinations in estimating overall survival (OS) for hepatocellular carcinoma (HCC) remains to be elucidated. This study aimed to construct a potent lncRNA signature related to the OS for HCC, so as to enhance the predicting accuracy of prognosis.
Methods: The expression patterns of lncRNAs, together with related clinical data of 371 HCC patients were obtained base on The Cancer Genome Atlas (TCGA). Besides, the differentially expressed lncRNAs (DElncRNAs) were acquired through comparing tumor with normal samples. In addition, lncRNAs displaying significant association with OS were screened through univariate Cox regression analysis based on the least absolute shrinkage and selection operator (LASSO) algorithm. Afterwards, all cases were classified as validation or training group at the ratio of 3:7. Then, the constructed lncRNA signature had been developed and validated. Additionally, gene set enrichment analysis (GSEA) of the lncRNA model risk score was also conducted.
Results: A total of 1292 DElncRNAs were identified, among which, 172 were significant in univariate Cox regression analysis. In the training group (n=263), LASSO regression analysis confirmed 11 out of the 172 DElncRNAs, including AC010547.1, AC010280.2, AC015712.7, GACAT3, AC079466.1, AC089983.1, AC051618.1, AL121721.1, LINC01747, LINC01517, and AC008750.3. Afterwards, the prognostic risk score was calculated. The constructed risk model showed significant correlation with HCC OS, with the log-rank P-value of 8.489e-9 and the hazard ratio (HR) of 3.648 (95% confidence interval [CI]: 2.238-5.945). At the same time, the area under the curve (AUC) for this lncRNA model was up to 0.846. Furthermore, this risk model was confirmed in the validation group (n=108) and the entire cohort. Moreover, pathways related to the lncRNA model risk score were confirmed by GSEA.
Conclusion: The lncRNA signature is established in this study to predict the prognosis for HCC, which offers novel clinical evidence to targeted HCC treatment.