Basic Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Feb 15, 2024; 16(2): 493-513
Published online Feb 15, 2024. doi: 10.4251/wjgo.v16.i2.493
Identification of anti-gastric cancer effects and molecular mechanisms of resveratrol: From network pharmacology and bioinformatics to experimental validation
Ying-Qian Ma, Ming Zhang, Zhen-Hua Sun, Hong-Yue Tang, Ying Wang, Jiang-Xue Liu, Zhan-Xue Zhang, Chao Wang
Ying-Qian Ma, Ming Zhang, Zhen-Hua Sun, Department of Oncology, Hebei General Hospital, Shijiazhuang 050051, Hebei Province, China
Ying-Qian Ma, Ying Wang, Jiang-Xue Liu, School of Graduate Studies, Hebei Medical University, Shijiazhuang 050017, Hebei Province, China
Hong-Yue Tang, Chao Wang, Clinical Medical Research Center, Hebei General Hospital, Shijiazhuang 050051, Hebei Province, China
Zhan-Xue Zhang, Department of Gastrointestinal Surgery, Second Hospital of Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Author contributions: Zhang M and Wang C designed the research and supervised the project; Ma YQ and Sun ZH performed network pharmacology analysis and molecular docking; Wang Y and Tang HY performed bioinformatics analysis; Ma YQ and Liu JX performed the experiments, analyzed the data and wrote the paper; Zhang M, Zhang ZX and Wang C revised the paper; all authors approved the final version of the article.
Supported by Natural Science Foundation of Hebei Province, No. H2018307071; Traditional Chinese Medicine Research Plan Project in Hebei Province, No. 2022122; and Hebei Provincial Science and Technology Program, No. 17397763D.
Conflict-of-interest statement: All other authors have nothing to disclose.
Data sharing statement: No additional data are available.
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: Ming Zhang, MD, Chief Physician, Department of Oncology, Hebei General Hospital, No. 348 Heping West Road, Xinhua District, Shijiazhuang 050051, Hebei Province, China. zhangming096@163.com
Received: November 9, 2023
Peer-review started: November 9, 2023
First decision: November 23, 2023
Revised: December 5, 2023
Accepted: January 12, 2024
Article in press: January 12, 2024
Published online: February 15, 2024
Processing time: 84 Days and 16.6 Hours
ARTICLE HIGHLIGHTS
Research background

Gastric cancer (GC) is a malignant tumor of digestive tract with high incidence and mortality. The treatment of GC is more difficult due to its characteristics such as rapid invasive growth, difficulties in personalized medication and high risk of recurrence. Resveratrol, as a traditional Chinese medicine (TCM) monomer, plays an outstanding anticancer role in a variety of cancers.

Research motivation

In this study, network pharmacology, bioinformatics, molecular docking technology and experimental verification were used to explore the important effects and key targets of resveratrol in anti-GC. This discovery is of great clinical significance for identifying potential novel biomarkers and therapeutic targets for GC treatment.

Research objectives

The main objective of this study was to explore the mechanism of resveratrol based on network analysis. In this study, through network analysis and in vitro experiments, we verified the anti-cancer effects of resveratrol on GC cells, including inhibiting proliferation, invasion and migration, inducing cycle arrest and apoptosis, as well as important action targets. Our results suggested that resveratrol has a great clinical value as an anti-GC drug, providing a new direction for the drug treatment of GC.

Research methods

Network pharmacology, bioinformatics, molecular docking technology and experiments were used in this study. These methods utilize biological networks to mechanically link drugs and diseases, comprehensively elucidate the roles and molecular mechanisms of resveratrol in GC.

Research results

In the research, FBJ murine osteosarcoma viral oncogene homolog (FOS) and matrix metallopeptidase 9 (MMP9) were screened as the most important targets of resveratrol against GC by using multiple biological information databases. The experiments verified the anti-GC effect of resveratrol by targeting FOS and MMP9. These findings provide a scientific basis for GC treatment of resveratrol, and also provide a new method for the study of the mechanism of TCM monomer or compound in the diseases However, the pathways which may play critical roles in the anti-GC effect of resveratrol have not been fully validated and should be further studied.

Research conclusions

In the research, the key biotargets and biological effects of resveratrol against GC were explored by molecular network analysis and experimental verification for the first time.

Research perspectives

Development and validation of biomarkers for classifying and treating diseases through bioinformatics and machine learning.