Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Feb 24, 2024; 15(2): 243-270
Published online Feb 24, 2024. doi: 10.5306/wjco.v15.i2.243
Identification of immune cell-related prognostic genes characterized by a distinct microenvironment in hepatocellular carcinoma
Meng-Ting Li, Kai-Feng Zheng, Yi-Er Qiu
Meng-Ting Li, Kai-Feng Zheng, Yi-Er Qiu, Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Ningbo 315000, Zhejiang Province, China
Author contributions: Li MT contributed to writing-original draft; Zheng KF contributed to writing-reviewing and editing; Qiu YE contributed to supervision.
Institutional review board statement: Our research was conducted based on public datasets, and no human subjects were involved in this research. Thus, there is no need to obtain approval by the institutional review board.
Informed consent statement: Our research was conducted based on public datasets, and no human subjects were involved in this research. Thus, there is no need to obtain informed consent.
Conflict-of-interest statement: All the authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data sharing statement: The data sets supporting the results of this article are all included in the article.
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: Meng-Ting Li, MD, PhD, Doctor, Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, No. 251 Baizhang East Road, Ningbo 315000, Zhejiang Province, China. limengting1992@foxmail.com
Received: October 18, 2023
Peer-review started: October 18, 2023
First decision: November 17, 2023
Revised: December 4, 2023
Accepted: January 11, 2024
Article in press: January 11, 2024
Published online: February 24, 2024
Processing time: 125 Days and 2.8 Hours
Abstract
BACKGROUND

The development and progression of hepatocellular carcinoma (HCC) have been reported to be associated with immune-related genes and the tumor microenvironment. Nevertheless, there are not enough prognostic biomarkers and models available for clinical use. Based on seven prognostic genes, this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment (TME).

AIM

To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.

METHODS

We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression. The relative analysis of tumor mutation burden (TMB), TME cell infiltration, immune checkpoints, immune therapy, and functional pathways was also performed based on prognostic genes.

RESULTS

Seven prognostic genes were identified for signature construction. Survival receiver operating characteristic curve analysis showed the good performance of survival prediction. TMB could be regarded as an independent factor in HCC survival prediction. There was a significant difference in stromal score, immune score, and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model. Several immune checkpoints, including VTCN1 and TNFSF9, were found to be associated with the seven prognostic genes and risk score. Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies. Potential pathways, such as cell cycle regulation and metabolism of some amino acids, were also identified and analyzed.

CONCLUSION

The novel seven-gene (CYTH3, ENG, HTRA3, PDZD4, SAMD14, PGF, and PLN) prognostic model showed high predictive efficiency. The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC, which might be worthy of clinical application.

Keywords: Hepatocellular carcinoma; Prognostic model; Weighted gene coexpression network analysis; Microenvironment; Chemotherapy

Core Tip: In this work, we focused on establishing a prognostic survival model with seven prognostic genes to predict overall survival in patients with hepatocellular carcinoma (HCC) and revealing the tumor microenvironment based on intersecting genes of The Cancer Genome Atlas and The Cancer Genome Atlas datasets. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of HCC.