Hu JL, Huang MJ, Halina H, Qiao K, Wang ZY, Lu JJ, Yin CL, Gao F. Identification of a novel inflammatory-related gene signature to evaluate the prognosis of gastric cancer patients. World J Gastrointest Oncol 2024; 16(3): 945-967 [PMID: 38577477 DOI: 10.4251/wjgo.v16.i3.945]
Corresponding Author of This Article
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
Research Domain of This Article
Medicine, General & Internal
Article-Type of This Article
Clinical and Translational Research
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/
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
Abstract
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. However, the importance of inflammatory-related biomarkers in predicting the prognosis of GC patients is still unclear.
AIM
To investigate inflammatory-related biomarkers in predicting the prognosis of GC patients.
METHODS
In this study, the mRNA expression profiles and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) database (GSE66229). An inflammatory-related gene prognostic signature model was constructed using the least absolute shrinkage and selection operator Cox regression model based on the GEO database. GC patients from the GSE26253 cohort were used for validation. Univariate and multivariate Cox analyses were used to determine the independent prognostic factors, and a prognostic nomogram was established. The calibration curve and the area under the curve based on receiver operating characteristic analysis were utilized to evaluate the predictive value of the nomogram. The decision curve analysis results were plotted to quantify and assess the clinical value of the nomogram. Gene set enrichment analysis was performed to explore the potential regulatory pathways involved. The relationship between tumour immune infiltration status and risk score was analysed via Tumour Immune Estimation Resource and CIBERSORT. Finally, we analysed the association between risk score and patient sensitivity to commonly used chemotherapy and targeted therapy agents.
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.
CONCLUSION
In conclusion, we established a novel three-gene prognostic signature that may be useful for predicting the prognosis and personalizing treatment decisions of GC patients.
Core Tip: Our study identified a novel signature consisting of three inflammatory response-related genes that could precisely predict the prognosis of patients with gastric cancer (GC). The specific underlying mechanism of inflammatory response related genes and tumor immunity in GC is still unclear, which deserves further study. Taken together, our work will help shed light on their role in tumorgenesis, particularly in the areas of immune response, tumor microenvironment and drug resistance, which are critical for the development of personalized cancer therapies.
