Fu Y, Wang B, Fu P, Zhang L, Bao Y, Gao ZZ. Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications. World J Clin Cases 2023; 11(20): 4800-4813 [PMID: 37583992 DOI: 10.12998/wjcc.v11.i20.4800]
Corresponding Author of This Article
Zhen-Zhen Gao, MD, PhD, Director, Doctor, Department of Clinical Oncology, The Second affiliated hospital of Jiaxing University, No. 1518 Huancheng Road, Jiaxing 314000, Zhejiang Province, China. gaozhenzhen@zjxu.edu.cn
Research Domain of This Article
Gastroenterology & Hepatology
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/
World J Clin Cases. Jul 16, 2023; 11(20): 4800-4813 Published online Jul 16, 2023. doi: 10.12998/wjcc.v11.i20.4800
Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications
Yu Fu, Bin Wang, Peng Fu, Lei Zhang, Yi Bao, Zhen-Zhen Gao
Yu Fu, Bin Wang, Department of General Practice Medicine, The Second affiliated hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
Peng Fu, Department of Orthopeadic Oncology, The Second Affiliated Hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
Lei Zhang, Yi Bao, Zhen-Zhen Gao, Department of Clinical Oncology, The Second affiliated hospital of Jiaxing University, Jiaxing 314000, Zhejiang Province, China
Author contributions: Fu Y was responsible for the data collection and manuscript preparation; Gao ZZ and Zhang L were responsible for data analysis and manuscript; Fu P was responsible for data analysis; Bao Y was responsible for manuscript preparation.
Institutional review board statement: All analyses were based on publicly available online datasets; thus, no ethical approval and patient consent were required.
Informed consent statement: All analyses were based on publicly available online datasets; thus, no informed consent statements were applied.
Conflict-of-interest statement: All the authors have no conflict of interest related to the manuscript.
Data sharing statement: The original anonymous dataset is available on request from the corresponding author at sophiever0112@163.com.
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: Zhen-Zhen Gao, MD, PhD, Director, Doctor, Department of Clinical Oncology, The Second affiliated hospital of Jiaxing University, No. 1518 Huancheng Road, Jiaxing 314000, Zhejiang Province, China. gaozhenzhen@zjxu.edu.cn
Received: March 22, 2023 Peer-review started: March 22, 2023 First decision: April 11, 2023 Revised: April 23, 2023 Accepted: May 19, 2023 Article in press: May 19, 2023 Published online: July 16, 2023
Abstract
BACKGROUND
The prognosis of gastric cancer is extremely poor. Metabolic reprogramming involving lipids has been associated with cancer occurrence and progression.
AIM
To illustrate fatty acid metabolic mechanisms in gastric cancer, detect core genes, develop a prognostic model, and provide treatment options.
METHODS
Raw data from The Cancer Genome Atlas and Gene Expression Omnibus databases were collected and analyzed. Differentially expressed fatty acid metabolism genes were identified and incorporated into a risk model based on least absolute shrinkage and selection operator regression analysis. Then, patients from The Cancer Genome Atlas were assigned to high- and low-risk cohorts according to the mean value of the risk score as the threshold, which was verified in the Gene Expression Omnibus database. Relationships between chemotherapeutic sensitivity and tumor microenvironment features were assessed.
RESULTS
An integrated evaluation was performed in this study. Fatty acid metabolism-related genes were used to construct the risk model. Patients classified into the high-risk cohort were considered to be resistant to chemotherapy based on results of the “pRRophetic” R package. Patients in the high-risk cohort were associated with type I/II interferon activation, increased inflammation level, immune cell infiltration, and tumor immune dysfunction based on the exclusion algorithm, indicating the potential benefit of immunotherapy in these patients.
CONCLUSION
We constructed a fatty acid-related risk score model to assess the comprehensive fatty acid features in gastric cancer and validated its vital role in prognosis, chemotherapy sensitivity, and immunotherapy.
Core Tip: We established a prognostic risk model using data collected from The Cancer Genome Atlas database, explored the function of the risk model, and identified the relationship between the risk model and clinical features. The findings of our study provide innovative therapeutic options in clinical practice.
