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Integrated Expression Analysis May Support Serine/Threonine Kinases as Common Hub Genes in Breast Cancer
Mohammad Soleiman Ekhtiyari1, Mostafa Ghaderi-Zefrehei2, Zahra Mogharari3
1Division of Biochemistry, Faculty of Veterinary Medicine, University of Tabriz, Tabriz, Iran.
Iranian Journal of Medical Sciences
|October 29, 2025
Summary
Five key breast cancer genes (NEK2, MELK, PLK1, AURKB, CHEK1) were identified as potential therapeutic targets. Higher expression of these genes correlates with poorer patient survival, highlighting their role in breast cancer progression.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Breast cancer (BC) is a leading cause of cancer-related deaths in women globally.
- Identifying novel molecular targets is crucial for developing effective BC therapies.
Purpose of the Study:
- To conduct a large-scale transcriptomic analysis to identify key genes involved in breast cancer pathophysiology.
- To identify potential therapeutic targets for breast cancer treatment.
Main Methods:
- Utilized transcriptomic data from NCBI GEO and TCGA databases (microarray and RNA-Seq).
- Identified differentially expressed genes (DEGs) and constructed gene co-expression networks using WGCNA.
- Identified hub genes using STRING and MCODE, followed by Gene Ontology enrichment analysis.
Main Results:
- Identified two regulatory modules, one with 85 genes in cancer and another with 474 genes in control tissues.
- Discovered a cluster of 29 cancer-related genes, including five hub genes: NEK2, MELK, PLK1, AURKB, and CHEK1.
- Found that elevated expression of these five hub genes is associated with decreased overall survival in breast cancer patients (P<0.001), with Hazard Ratios ranging from 1.41 to 1.77.
Conclusions:
- The identified hub genes (NEK2, MELK, PLK1, AURKB, CHEK1) are significantly associated with poorer patient survival in breast cancer.
- These genes play a critical role in breast cancer pathophysiology and represent potential targets for monitoring and therapeutic intervention.
Keywords:
Breast neoplasms (D001943)Computational biology (D057180)Gene regulatory networks (D059687)Molecular modeling (D052199)Mortality (D009020)Neoplasm proteins (D009369)Protein-serine-threonine kinases (D051685)More Related Videos
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