Basic Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Nov 15, 2019; 11(11): 983-997
Published online Nov 15, 2019. doi: 10.4251/wjgo.v11.i11.983
Eight key long non-coding RNAs predict hepatitis virus positive hepatocellular carcinoma as prognostic targets
Zi-Lin Huang, Wang Li, Qi-Feng Chen, Pei-Hong Wu, Lu-Jun Shen
Zi-Lin Huang, Wang Li, Qi-Feng Chen, Pei-Hong Wu, Lu-Jun Shen, Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong Province, China
Zi-Lin Huang, Wang Li, Qi-Feng Chen, Pei-Hong Wu, Lu-Jun Shen, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China
Author contributions: Huang ZL, Li W, and Chen QF contributed equally to this work; Huang ZL, Li W, and Chen QF contributed to study conceptualization; Chen QF contributed to the methodology; Wu PH contributed to software; Chen QF, Huang ZL, and Li W contributed to data validation; Chen QF, Wu PH, Huang ZL, and Shen LJ analyzed the data and contributed to manuscript writing and editing; Chen QF and Li W contributed to manuscript drafting; Chen QF contributed to visualization and supervised the final paper.
Institutional review board statement: Not applicable, because the data were publicly available.
Institutional animal care and use committee statement: Not applicable, because no animal was used in the present study.
Conflict-of-interest statement: The authors deny any conflict of interest.
Data sharing statement: The data used in this manuscript are accessible through: https://portal.gdc.cancer.gov/
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Qi-Feng Chen, MD, Doctor, Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center, 651 East Dongfeng Road, Yuexiu District, Guangzhou 510060, Guangdong Province, China. ch_peaks@126.com
Telephone: +86-15626062848 Fax: +86-20-87343392
Received: March 27, 2019
Peer-review started: March 28, 2019
First decision: April 15, 2019
Revised: July 26, 2019
Accepted: September 12, 2019
Article in press: September 12, 2019
Published online: November 15, 2019
Processing time: 233 Days and 22.6 Hours
Abstract
BACKGROUND

Hepatitis B virus, together with hepatitis C virus, has been recognized as the leading causes of hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) have been suggested in increasing studies to be the potential prognostic factors for HCC. However, the role of combined application of lncRNAs in estimating overall survival (OS) for hepatitis virus positive HCC (VHCC) is uncertain.

AIM

To construct an lncRNA signature related to the OS of VHCC patients to enhance the accuracy of prognosis prediction.

METHODS

The expression patterns of lncRNAs, as well as related clinical data were collected from 149 VHCC patients from The Cancer Genome Atlas database. The R package was adopted to obtain the differentially expressed lncRNAs (DElncRNAs). LncRNAs significantly associated with OS were screened by means of univariate Cox regression analysis, so as to construct a least absolute shrinkage and selection operator (LASSO) model. Subsequently, the constructed lncRNA signature was developed and validated. Afterwards, the prognostic nomogram was established, which combined the as-established lncRNA signature as well as the clinical features. Meanwhile, subgroup analysis stratified by the virus type was also performed. Finally, the above-mentioned lncRNAs were enriched to corresponding pathways according to the markedly co-expressed genes.

RESULTS

A total of 1420 DElncRNAs were identified, among which 406 were significant in univariate Cox regression analysis. LASSO regression confirmed 8 out of the 406 lncRNAs, including AC005722.2, AC107959.3, AL353803.1, AL589182.1, AP000844.2, AP002478.1, FLJ36000, and NPSR1-AS1. Then, the prognostic risk score was calculated. Our results displayed a significant association between the risk model and the OS of VHCC [hazard ratio = 1.94, 95% confidence interval (CI): 1.61-2.34, log-rank P = 2e-10]. The inference tree suggested that the established lncRNA signature was useful in the risk stratification of VHCC. Furthermore, a nomogram was plotted, and the concordance index of internal validation was 0.763 (95%CI: 0.700-0.826). Moreover, the subgroup analysis regarding etiology confirmed this risk model. In addition, the Wnt signaling pathway, angiogenesis, the p53 pathway, and the PI3 kinase pathway were the remarkably enriched pathways.

CONCLUSION

An eight-lncRNA signature has been established to predict the prognosis for VHCC, which contributes to providing a novel foundation for the targeted therapy of VHCC.

Keywords: Long non-coding RNAs; Hepatitis virus; Hepatocellular carcinoma; Prognostic signature; Least absolute shrinkage and selection operator

Core tip: The existing long non-coding RNA (lncRNA) signatures for prognosis prediction are still controversial and need to be optimized for hepatocellular carcinoma (HCC). Typically, there is less knowledge concerning the lncRNA signature for hepatitis virus positive HCC (VHCC). As a result, this study was carried out to construct a robust lncRNA signature to predict the prognosis for VHCC. Typically, the eight-lncRNA signature constructed in this study displayed a potent potential to predict the prognosis of VHCC, which might contribute to risk stratification, and provide the individualized clinical suggestion for an individual case.