Qiu XT, Song YC, Liu J, Wang ZM, Niu X, He J. Identification of an immune-related gene-based signature to predict prognosis of patients with gastric cancer. World J Gastrointest Oncol 2020; 12(8): 857-876 [PMID: 32879664 DOI: 10.4251/wjgo.v12.i8.857]
Corresponding Author of This Article
Jing He, MD, PhD, Professor, Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9, Jinsui Road, Guangzhou 510623, Guangdong Province, China. hejing198374@gmail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Basic Study
Open-Access Policy of This Article
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/
Xiang-Ting Qiu, Jian Liu, Zhen-Min Wang, Department of Clinical Laboratory, Linyi Central Hospital, Linyi 276400, Shandong Province, China
Yu-Cui Song, Department of Operating Room, Linyi Central Hospital, Linyi 276400, Shandong Province, China
Xing Niu, Second Clinical College, Shengjing Hospital Affiliated to China Medical University, Shenyang 110004, Liaoning Province, China
Jing He, Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, Guangdong Province, China
Author contributions: He J and Niu X conceived and designed the study; Qiu XT and Song YC conducted most of the experiments and data analyses, and wrote the manuscript; Liu J and Wang ZM participated in collecting the data and helped to draft the manuscript; all authors reviewed and approved the manuscript.
Conflict-of-interest statement: The authors declare that they no conflicts of interest.
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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Jing He, MD, PhD, Professor, Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9, Jinsui Road, Guangzhou 510623, Guangdong Province, China. hejing198374@gmail.com
Received: February 10, 2020 Peer-review started: February 10, 2020 First decision: March 24, 2020 Revised: April 6, 2020 Accepted: June 17, 2020 Article in press: June 17, 2020 Published online: August 15, 2020
ARTICLE HIGHLIGHTS
Research background
Gastric cancer (GC) is the most commonly diagnosed malignancy worldwide. Increasing evidence suggests that it is necessary to further explore genetic and immunological characteristics of GC.
Research motivation
The prognosis of GC is closely related to the crosstalk between immune cells and tumor cells. Nevertheless, the role of immune-related genes in predicting GC patients’ prognosis has not yet been elucidated.
Research objectives
In this study, we aimed to construct an immune-related gene signature for accurately predicting the prognosis of patients with GC.
Research methods
Cox univariate survival analysis was performed to screen survival-related immune-related genes (IRGs). Differentially expressed survival-related IRGs were considered as hub IRGs. Hub IRGs were selected to conduct a prognostic signature. Receiver operating characteristic (ROC) curve analysis was performed to evaluate its prognostic performance. The correlation of the signature with clinical features and tumor-infiltrating immune cells was analyzed.
Research results
Our study constructed a prognostic signature consisting of ten hub IRGs (including S100A12, DEFB126, KAL1, APOH, CGB5, GRP, GLP2R, LGR6, PTGER3, and CTLA4), and it could be an independent prognostic predictor for GC. Furthermore, it was significantly associated with immune cell infiltration (especially macrophages).
Research conclusions
We have proposed an immune-related prognostic signature for GC, which may possess prognostic value as a prediction tool for identification of patients who will benefit from immunotherapy.
Research perspectives
The prognostic signature could help develop treatment strategies for patients with GC in the future.
