Basic Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Oct 15, 2022; 14(10): 1981-2003
Published online Oct 15, 2022. doi: 10.4251/wjgo.v14.i10.1981
Cuproptosis-related long non-coding RNAs model that effectively predicts prognosis in hepatocellular carcinoma
En-Min Huang, Ning Ma, Tao Ma, Jun-Yi Zhou, Wei-Sheng Yang, Chuang-Xiong Liu, Ze-Hui Hou, Shuang Chen, Zhen Zong, Bing Zeng, Ying-Ru Li, Tai-Cheng Zhou
En-Min Huang, Ning Ma, Tao Ma, Wei-Sheng Yang, Chuang-Xiong Liu, Ze-Hui Hou, Shuang Chen, Bing Zeng, Ying-Ru Li, Tai-Cheng Zhou, Department of Gastroenterological Surgery and Hernia Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China
En-Min Huang, Ning Ma, Tao Ma, Jun-Yi Zhou, Wei-Sheng Yang, Chuang-Xiong Liu, Ze-Hui Hou, Shuang Chen, Bing Zeng, Ying-Ru Li, Tai-Cheng Zhou, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China
Jun-Yi Zhou, Department of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, Guangdong Province, China
Zhen Zong, Department of Gastroenterological Surgery, The Second Affiliated Hospital, Nanchang University, Nanchang 330006, Jiangxi Province, China
Author contributions: Zhou TC, Li YR, Zeng B, Zong Z, and Chen S conceived the study and its design, and provided administrative support; Huang EM, Ma N, and Ma T were involved in data analyses and wrote, reviewed, and edited the manuscript; Zhou JY, Yang WS, Liu CX, and Hou ZH contributed data analysis and reviewed the manuscript; all authors read and approved the final manuscript, and contributed to the article and approved the submitted version for publication.
Supported by the National Key Clinical Discipline, the Basic and Applied Basic Research Fund Project of Guangdong Province, No. 2021A1515410004 and No. 2019A1515011200; National Natural Science Foundation of China, No. 81973858 and No. 82172790; and Science and Technology Plan Project of Qingyuan City, No. 2019A028.
Institutional review board statement: The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Since the present study is a bioinformatics work that did not involve animal or human specimens, there is no requirement for ethical permission from our institution or an ethics number.
Conflict-of-interest statement: There are no conflicts of interest to report.
Data sharing statement: Publicly available datasets were analyzed in this study. These data can be found here: https://portal.gdc.cancer.gov/repository. Technical appendix, statistical code, and dataset available from the corresponding author at zhoutch3@mail.sysu.edu.cn.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Tai-Cheng Zhou, MD, PhD, Associate Professor, Doctor, Surgeon, Surgical Oncologist, Department of Gastroenterological Surgery and Hernia Center, The Sixth Affiliated Hospital, Sun Yat-sen University, No. 26 Erheng Road, Yuancun, Guangzhou 510655, Guangdong Province, China. zhoutch3@mail.sysu.edu.cn
Received: June 24, 2022
Peer-review started: June 24, 2022
First decision: July 18, 2022
Revised: July 29, 2022
Accepted: August 17, 2022
Article in press: August 17, 2022
Published online: October 15, 2022
Processing time: 112 Days and 6.8 Hours
Abstract
BACKGROUND

Cuproptosis has recently been considered a novel form of programmed cell death. To date, long-chain non-coding RNAs (lncRNAs) crucial to the regulation of this process remain unelucidated.

AIM

To identify lncRNAs linked to cuproptosis in order to estimate patients' prognoses for hepatocellular carcinoma (HCC).

METHODS

Using RNA sequence data from The Cancer Genome Atlas Live Hepatocellular Carcinoma (TCGA-LIHC), a co-expression network of cuproptosis-related genes and lncRNAs was constructed. For HCC prognosis, we developed a cuproptosis-related lncRNA signature (CupRLSig) using univariate Cox, lasso, and multivariate Cox regression analyses. Kaplan-Meier analysis was used to compare overall survival among high- and low-risk groups stratified by median CupRLSig risk score. Furthermore, comparisons of functional annotation, immune infiltration, somatic mutation, tumor mutation burden (TMB), and pharmacologic options were made between high- and low-risk groups.

RESULTS

Three hundred and forty-three patients with complete follow-up data were recruited in the analysis. Pearson correlation analysis identified 157 cuproptosis-related lncRNAs related to 14 cuproptosis genes. Next, we divided the TCGA-LIHC sample into a training set and a validation set. In univariate Cox regression analysis, 27 LncRNAs with prognostic value were identified in the training set. After lasso regression, the multivariate Cox regression model determined the identified risk equation as follows: Risk score = (0.2659 × PICSAR expression) + (0.4374 × FOXD2-AS1 expression) + (-0.3467 × AP001065.1 expression). The CupRLSig high-risk group was associated with poor overall survival (hazard ratio = 1.162, 95%CI = 1.063-1.270; P < 0.001) after the patients were divided into two groups depending upon their median risk score. Model accuracy was further supported by receiver operating characteristic and principal component analysis as well as the validation set. The area under the curve of 0.741 was found to be a better predictor of HCC prognosis as compared to other clinicopathological variables. Mutation analysis revealed that high-risk combinations with high TMB carried worse prognoses (median survival of 30 mo vs 102 mo of low-risk combinations with low TMB group). The low-risk group had more activated natural killer cells (NK cells, P = 0.032 by Wilcoxon rank sum test) and fewer regulatory T cells (Tregs, P = 0.021) infiltration than the high-risk group. This finding could explain why the low-risk group has a better prognosis. Interestingly, when checkpoint gene expression (CD276, CTLA-4, and PDCD-1) and tumor immune dysfunction and rejection (TIDE) scores are considered, high-risk patients may respond better to immunotherapy. Finally, most drugs commonly used in preclinical and clinical systemic therapy for HCC, such as 5-fluorouracil, gemcitabine, paclitaxel, imatinib, sunitinib, rapamycin, and XL-184 (cabozantinib), were found to be more efficacious in the low-risk group; erlotinib, an exception, was more efficacious in the high-risk group.

CONCLUSION

The lncRNA signature, CupRLSig, constructed in this study is valuable in prognostic estimation of HCC. Importantly, CupRLSig also predicts the level of immune infiltration and potential efficacy of tumor immunotherapy.

Keywords: Hepatocellular carcinoma; Cuproptosis; Long-chain non-coding RNAs; Prognosis; Tumor microenvironment; Immunotherapy

Core Tip: Factors crucial to the regulation of cuproptosis remain unelucidated. Using transcriptome data from The Cancer Genome Atlas (TCGA-LIHC), we developed a cuproptosis- and prognosis-related long-chain non-coding RNAs signature (CupRLSig) for hepatocellular carcinoma. The high-risk group identified by CupRLSig was associated with poorer overall survival and progression-free survival. Less activation of natural killer cells and more infiltration of regulatory T cells in the high-risk group may explain the worse outcomes. Interestingly, based on checkpoint gene expression (CD276, CTLA-4, and PDCD-1) and tumor immune dysfunction and rejection, high-risk patients may respond better to immunotherapy.