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Author Spotlight: Exploring Salidroside's Molecular Mechanisms in Breast Cancer Treatment
Published on: June 9, 2023
Transcriptome Profiling Analysis of Breast Cancer Cell MCF-7 Treated by Sesamol
Jiafa Wu1, Dongping Luo2, Jiayun Xu2
1School of Food and Bioengineering, Henan University of Science and Technology, Luoyang, People's Republic of China.
Background:
Breast cancer is a highly malignant tumor that affects a large number of women worldwide. Sesamol, a natural compound, has been shown to exhibit inhibitory effects on various tumors, including breast cancer. However, the underlying mechanism of its action has not been fully explored. In this study, we aimed to investigate the effect of sesamol on the transcriptome of MCF-7 breast cancer cells, in order to better understand its potential as an anti-cancer agent.
Methods:
The transcriptome profiles of MCF-7 breast cancer cells treated with sesamol were analyzed using Illumina deep-sequencing. The differentially expressed genes (DEGs) between the control and sesamol-treated groups were identified, and GO and KEGG pathway analyses of these DEGs were conducted using ClueGO. Protein-protein interaction (PPI) network of DEGs was mapped on STRING database and visualized by Cytoscape software. Hub genes in the network were screened by Cytohubba plugin of Cytoscape. Prognostic values of hub genes were analyses by the online Kaplan-Meier plotter and validated by qRT-PCR in MCF-7 cells.
Results:
The results of the study showed that sesamol treatment had a significant effect on the transcriptome of MCF-7 cells, with a total of 351 DEGs identified. Functional enrichment analyses of DEGs revealed their involvement in extracellular matrix (ECM) remodeling, fatty acid metabolism and monocyte chemotaxis. The protein-protein interaction (PPI) network analysis of DEGs resulted in the identification of 10 hub genes, namely IGF2, MMP1, MSLN, CXCL10, WT1, ITGAL, PLD1, MME, TWIST1, and FOXA2. Survival analysis showed that MMP1 and ITGAL were significantly associated with overall survival (OS) and recovery-free survival (RFS) in breast cancer patients.
Conclusion:
Sesamol may play important roles in extracellular matrix (ECM) remodeling, fatty acid metabolism and cell cycle of MCF-7.
Insights
Sesamol impacts breast cancer cell gene expression, affecting extracellular matrix remodeling and fatty acid metabolism. Key genes like MMP1 and ITGAL show prognostic value for patient survival.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Breast cancer is a prevalent malignancy in women globally.
- Sesamol, a natural compound, demonstrates anti-cancer properties.
- The precise molecular mechanisms of sesamol's action in breast cancer remain unclear.
Purpose of the Study:
- To investigate the impact of sesamol on the transcriptome of MCF-7 breast cancer cells.
- To elucidate the molecular pathways affected by sesamol treatment.
- To identify potential therapeutic targets and biomarkers for breast cancer.
Main Methods:
- Transcriptome profiling using Illumina deep-sequencing.
- Differential gene expression analysis and functional enrichment (GO, KEGG) via ClueGO.
- Protein-protein interaction network construction (STRING, Cytoscape) and hub gene identification.
- Prognostic analysis of hub genes using Kaplan-Meier plotter and qRT-PCR validation.
Main Results:
- Sesamol significantly altered the transcriptome of MCF-7 cells, identifying 351 differentially expressed genes (DEGs).
- Enriched pathways include extracellular matrix (ECM) remodeling, fatty acid metabolism, and monocyte chemotaxis.
- Ten hub genes were identified, including MMP1 and ITGAL, which were significantly associated with overall survival and recovery-free survival in breast cancer patients.
Conclusions:
- Sesamol influences key biological processes in breast cancer cells, including ECM remodeling, fatty acid metabolism, and cell cycle.
- MMP1 and ITGAL emerge as potential prognostic biomarkers for breast cancer patients.
- Further research into sesamol's mechanisms could lead to novel breast cancer therapies.
