Related Experiment Video
Updated: Oct 4, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Identification of key genes involved in tamoxifen-resistant breast cancer using bioinformatics analysis
Xiaopeng Wang1,2,3, Shixia Wang1,2,3
1Department of Outpatient and Emergency, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Background:
The purpose of the present study was to investigate the molecular mechanisms of tamoxifen resistance in breast cancer and to identify potential targets for antitamoxifen resistance.
Methods:
Differentially expressed genes (DEGs) in tamoxifen-resistant and tamoxifen-sensitive breast cancer cells were assessed using the GSE67916 dataset acquired from the Gene Expression Omnibus database. Gene ontology (GO) and pathway enrichment analyses were applied to investigate the functions and pathways of the DEGs. Subsequently, the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and subnetworks were further analyzed by Molecular Complex Detection (MCODE). The PPI network and subnetworks were visualized using Cytoscape software.
Results:
In total, 438 DEGs were identified, of which 300 were upregulated and 138 were downregulated. The DEGs were significantly enriched in the protein binding, cellular response to estradiol stimulus, and immune response GO terms while the most significant pathways included the mitogen-activated protein kinase (MAPK) signaling pathway in cancer. The PPI network of DEGs was constructed with 288 nodes and 629 edges, and 2 subnetworks were screened out from the entire network.
Conclusions:
A number of significant hub DEGs were identified based on their degree of connectivity in the PPI network, , included MAPK1 (node degree 36), ESR1 (node degree 27), SMARCA4 (node degree 27), RANBP2 (node degree 25), and PRKCA (node degree 21). These critical hub genes were found to be related to tamoxifen resistance in breast cancer. The results of this study further the understanding of tamoxifen resistance at the molecular level and identify potential therapeutic targets for tamoxifen-resistant breast cancer.
Insights
This study identifies key genes involved in tamoxifen resistance in breast cancer, revealing potential therapeutic targets. Understanding these molecular mechanisms is crucial for developing new treatments for tamoxifen-resistant breast cancer.
Area of Science:
- Genomics and Molecular Biology
- Cancer Research
- Bioinformatics
Background:
- Tamoxifen resistance is a significant challenge in breast cancer treatment.
- Understanding the molecular basis of resistance is crucial for improving patient outcomes.
Purpose of the Study:
- To investigate the molecular mechanisms underlying tamoxifen resistance in breast cancer.
- To identify potential therapeutic targets for overcoming tamoxifen resistance.
Main Methods:
- Analysis of differentially expressed genes (DEGs) in tamoxifen-resistant versus sensitive breast cancer cells using the GSE67916 dataset.
- Gene Ontology (GO) and pathway enrichment analyses to determine DEG functions and associated pathways.
- Construction and analysis of a protein-protein interaction (PPI) network using STRING and MCODE, visualized with Cytoscape.
Main Results:
- Identified 438 DEGs (300 upregulated, 138 downregulated).
- DEGs were significantly enriched in protein binding, cellular response to estradiol stimulus, and immune response pathways.
- The mitogen-activated protein kinase (MAPK) signaling pathway was notably implicated.
Conclusions:
- Identified key hub differentially expressed genes (DEGs) including MAPK1, ESR1, SMARCA4, RANBP2, and PRKCA, crucial for tamoxifen resistance.
- These findings enhance the understanding of tamoxifen resistance at the molecular level.
- Potential therapeutic targets for tamoxifen-resistant breast cancer were identified.
