Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Mar 15, 2024; 16(3): 945-967
Published online Mar 15, 2024. doi: 10.4251/wjgo.v16.i3.945
Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients
Jia-Li Hu, Mei-Jin Huang, Halike Halina, Kun Qiao, Zhi-Yuan Wang, Jia-Jie Lu, Cheng-Liang Yin, Feng Gao
Jia-Li Hu, Halike Halina, Kun Qiao, Zhi-Yuan Wang, Jia-Jie Lu, Feng Gao, Department of Gastroenterology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi 830001, Xinjiang Uygur Autonomous Region, China
Jia-Li Hu, Halike Halina, Kun Qiao, Zhi-Yuan Wang, Jia-Jie Lu, Feng Gao, Xinjiang Clinical Research Center for Digestive Disease, Urumqi 830001, Xinjiang Uygur Autonomous Region, China
Mei-Jin Huang, Department of Oncology, 920th Hospital of PLA Joint Logistics Support Force, Kunming 650032, Yunnan Province, China
Cheng-Liang Yin, Faculty of Medicine, Macau University of Science and Technology, Macau 999078, China
Co-first authors: Jia-Li Hu and Mei-Jin Huang.
Co-corresponding authors: Cheng-Liang Yin and Feng Gao.
Author contributions: Gao F and Yin CL designed the article; Hu JL and Huang MJ collected and evaluated the data, and wrote the first draft of the manuscript; All authors reviewed the manuscript, contributed to the interpretation of the results, read and approved the final version of the manuscript.
Institutional review board statement: This study is based on the public database and does not require ethical approval.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.
Data sharing statement: The data were downloaded from the Gene Expression Omnibus (GEO) cohort.
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: Feng Gao, PhD, Adjunct Associate Professor, Department of Gastroenterology, People’s Hospital of Xinjiang Uygur Autonomous Region, No. 91 Tianchi Road, Tianshan District, Urumqi 830001, Xinjiang Uygur Autonomous Region, China. xjgf@sina.com
Received: November 25, 2023
Peer-review started: November 25, 2023
First decision: December 7, 2023
Revised: December 25, 2023
Accepted: January 30, 2024
Article in press: January 30, 2024
Published online: March 15, 2024
Processing time: 108 Days and 2.9 Hours
ARTICLE HIGHLIGHTS
Research background

Gastric cancer (GC) is a highly aggressive malignancy with a heterogeneous nature, which makes prognosis prediction and treatment determination difficult. Inflammation is now recognized as one of the hallmarks of cancer and plays an important role in the aetiology and continued growth of tumours. Inflammation also affects the prognosis of GC patients. Recent reports suggest that a number of inflammatory-related biomarkers are useful for predicting tumour prognosis.

Research motivation

The importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear.

Research objectives

We established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.

Research methods

We downloaded the mRNA expression profiles and corresponding clinical data of patients with GC from a public database. Then, we constructed a prognostic signature comprising three differentially expressed genes (DEGs) related to the inflammatory response. We employed univariate and multivariate Cox regression analyses to evaluate the prognosis of patients with GC from the GEO cohort independently and validated the stability and reliability of the findings. Furthermore, we analysed the associations between prognostic gene expression and immune infiltrate types and between prognostic gene expression and chemotherapeutic sensitivity.

Research results

A prognostic model consisting of three inflammatory-related genes (MRPS17, GUF1, and PDK4) was constructed. Independent prognostic analysis revealed that the risk score was a separate prognostic factor in GC patients. According to the risk score, GC patients were stratified into high- and low-risk groups, and patients in the high-risk group had significantly worse prognoses according to age, sex, TNM stage and Lauren type. Consensus clustering identified three subtypes of inflammation that could predict GC prognosis more accurately than traditional grading and staging. Finally, the study revealed that patients in the low-risk group were more sensitive to certain drugs than were those in the high-risk group, indicating a link between inflammation-related genes and drug sensitivity.

Research conclusions

We identified a novel signature consisting of three inflammatory response-related genes that could precisely predict the prognosis of patients with GC. However, the specific underlying mechanism of inflammatory response-related genes and tumour immunity in GC is still unclear and deserves further study. Taken together, our work will help shed light on the role of these genes in tumorigenesis, particularly in the areas of immune response, tumour microenvironment and drug resistance, which are critical for the development of personalized cancer therapies.

Research perspectives

We believe that this powerful prognostic signature could help improve the risk stratification of GC patients, provide a more effective assessment for clinical management and provide new therapeutic targets for the treatment of these patients.