Related Experiment Video
Updated: Oct 6, 2025
Author Spotlight: Unveiling the Role of TMOD3 in Platinum Resistance and Immune Infiltration in Ovarian Cancer
Published on: August 2, 2024
Comprehensive Analysis of Tripterine Anti-Ovarian Cancer Effects Using Weighted Gene Co-Expression Network Analysis
Xi Long1, Leping Liu1,2, Qinyu Zhao3
1College of Medicine, Hunan University of Traditional Chinese Medicine, Changsha, Hunan, China (mainland).
Abstract:
BACKGROUND Ovarian cancer has the highest mortality of gynecological cancers worldwide. The aim of this study was to identify the role of tripterine against ovarian cancer. MATERIAL AND METHODS GSE18520 and GSE12470 data sets were downloaded from the GEO database. WGCNA was used to analyze gene modules and hub genes related to ovarian cancer. These hub genes were intersected with tripterine targets, and GO and KEGG enrichment analyses were performed. HPA and GEPIA determined the expression of tripterine anti-ovarian hub genes in tumor tissues. Kaplan-Meier plotter was used to explore the role of hub genes in ovarian cancer prognosis. AutoDock was used to conduct molecular docking of tripterine and hub genes to observe whether the combination was stable. RESULTS By differential analysis of gene expression and the construction of WGCNA co-expression network, 5 hub genes, ARHGAP11A, MUC1, HBB, RUNX1T1, and FUT8, were screened by module gene screening. Seven biological processes and 20 KEGG-related pathways were obtained by gene enrichment. The expression of tripterine anti-ovarian hub genes ARHGAP11A, MUC1, and FUT8 were obtained by HPA and GEPIA. Using Kaplan-Meier plotter, the survival of ovarian cancer was negatively correlated with ARHGAP11A, MUC1, and FUT8. Molecular docking showed the combination of tripterine and FUT8 was most stable, having the greatest potential role. CONCLUSIONS Tripterine may be involved in megakaryocyte development and platelet production through potential genes ARHGAP11A, MUC1, HBB, RUNX1T1, and FUT8 and may have an anti-ovarian cancer effect in immune factors signaling, transporting and exchanging oxygen pathways, and autophagy pathways, through these 5 key genes.
Insights
Tripterine shows potential against ovarian cancer by targeting key genes like ARHGAP11A, MUC1, and FUT8. These genes are linked to cancer progression and patient survival, with FUT8 showing a stable interaction with tripterine.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Ovarian cancer presents a significant global mortality challenge among gynecological malignancies.
- Identifying novel therapeutic targets and agents is crucial for improving patient outcomes.
Purpose of the Study:
- To investigate the potential anti-ovarian cancer role of tripterine.
- To identify key genes and pathways modulated by tripterine in ovarian cancer.
Main Methods:
- Utilized gene expression datasets (GSE18520, GSE12470) and Weighted Gene Co-expression Network Analysis (WGCNA) to identify hub genes.
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.
- Validated gene expression and prognostic significance using Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), and Kaplan-Meier plotter.
- Assessed drug-target interactions via molecular docking (AutoDock).
Main Results:
- Identified five hub genes (ARHGAP11A, MUC1, HBB, RUNX1T1, FUT8) associated with ovarian cancer.
- Enrichment analyses revealed involvement in seven biological processes and 20 KEGG pathways.
- ARHGAP11A, MUC1, and FUT8 expression correlated negatively with ovarian cancer survival.
- Molecular docking indicated a stable interaction between tripterine and FUT8.
Conclusions:
- Tripterine may exert anti-ovarian cancer effects by influencing megakaryocyte development and platelet production via the identified hub genes.
- Potential mechanisms involve immune signaling, oxygen transport/exchange, and autophagy pathways.
- FUT8 emerges as a promising direct target for tripterine in ovarian cancer therapy.
More Related Videos
09:08Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
13:18Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
Published on: March 3, 2023