Clinical and Translational Research
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
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
ARTICLE HIGHLIGHTS
Research background

the interactions between solitary metabolic features and the surrounding complex tumor environment characterize cancer. fatty acids are the essential components of diverse types of lipids, which are crucial mediators in energy metabolism and signal transduction. Although various molecules have been identified in gastric cancer (GC) metastasis, uncovering novel links between fatty acids and the tumor environment is necessary to comprehensively understand gastric cancer.

Research motivation

we constructed a novel prognostic risk model for GC based on fatty acid metastasis (FAM) -related genes. We examined the mechanisms underlying FAM in GC, the relationship between the risk of GC and tumor microenvironment characteristics, and treatment strategies for GC.

Research objectives

we want to construct novel links between fatty acids and the tumor environment to contribute to accurate diagnosis, prognosis prediction, and recurrence risk and metastasis assessments in patients with GC.

Research methods

Data download and analysis; Detection of differentially expressed genes and functional enrichment analysis between normal and cancer samples; Establishment and validation of prognostic risk model; Principal component analysis and gene set variation analysis; Construction of protein-protein interaction network

Research results

Functional analysis of FAM-related genes between normal and cancer samples from TCGA database; Construction and validation of the prognostic risk model in GC; Correlation between risk model score and clinical features; Establishment of predictive nomogram in patients with GC; A FAM-related model predicting response to chemotherapy and GSVA in high- and low-risk groups; Immune differences between high- and low-risk groups; Functional enrichment analysis of FAM-related DEGs in the low- and high-risk score groups based on protein-protein interaction.

Research conclusions

A fatty acid risk score model to assess the intact fatty acid features in GC was constructed. This risk model combined with clinicopathological characteristics, prognosis, chemotherapy sensitivity, and immune cell function.

Research perspectives

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.