Basic Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Mar 21, 2024; 30(11): 1609-1620
Published online Mar 21, 2024. doi: 10.3748/wjg.v30.i11.1609
Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication
Jun-Tao Li, Hong-Mei Zhang, Wei Wang, Dong-Qing Wei
Jun-Tao Li, Hong-Mei Zhang, College of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, Henan Province, China
Wei Wang, College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, Henan Province, China
Dong-Qing Wei, State Key Laboratory of Microbial Metabolism, and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
Co-corresponding authors: Hong-Mei Zhang and Dong-Qing Wei.
Author contributions: Zhang HM and Wei DQ contributed equally to this work and should be considered co-corresponding authors. Li JT and Zhang HM conceived this study and implemented the experiments; Li JT and Wang W collected and preprocessed the data; Zhang HM and Wei DQ drafted and revised the manuscript.
Supported by Scientific and Technological Project of Henan Province, No. 212102210140.
Institutional review board statement: This study doesn’t involve any human subjects.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this 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: Hong-Mei Zhang, MPhil, Master’s Student, College of Mathematics and Information Science, Henan Normal University, Jianshe East Road, Xinxiang 453007, Henan Province, China. zhanghmmail@163.com
Received: December 13, 2023
Peer-review started: December 13, 2023
First decision: December 27, 2023
Revised: January 9, 2024
Accepted: March 4, 2024
Article in press: March 4, 2024
Published online: March 21, 2024
Core Tip

Core Tip: In this study, CellChat was employed to infer cell-cell communication, thereby selecting highly active cell groups in immune-related pathways on single-cell RNA-sequencing data. Highly active immune cells were identified by intersecting these groups with B and T cells. Subsequently, significantly differentially expressed genes between highly active immune cells and the remaining cells were incorporated into the Lasso regression model. Ultimately, incorporating genes selected more than 5 times in 10 Lasso regression experiments into a multivariable Cox regression model, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified to construct a gene signature.