Abstract
Background: Breast cancer is the leading cause of cancer-related mortality among women worldwide. Advanced stages are usually obstinate with chemotherapy, resulting in a poor prognosis; however, they are treatable if diagnosed early.
Objective: Identifying biomarkers that can detect cancer early or have therapeutic significance is imperative.
Methods: Herein, a comprehensive bioinformatics-based transcriptomics study of breast cancer for identifying differentially expressed genes (DEGs), followed by a screening of potential compounds by molecular docking, was performed. Genome-wide mRNA expression data of breast cancer patients (n=248) and controls (n=65) were retrieved from the GEO database for meta-analysis. Statistically significant DEGs were used for enrichment analysis based on ingenuity pathway analysis and protein-protein network analysis.
Results: A total of 3096 unique DEGs (965 up-regulated and 2131 down-regulated) were mapped as biologically relevant. The most upregulated genes were COL10A1, COL11A1, TOP2A, BIRC5 (survivin), MMP11, S100P, RARA, and the most downregulated genes were ADIPOQ, LEP, CFD, PCK1 and HBA2. Transcriptomic and molecular pathway analyses identified BIRC5/survivin as a significant DEG. Kinetochore metaphase signaling is recognized as a prominent dysregulated canonical pathway. Protein-protein interaction study revealed that KIF2C, KIF20A, KIF23, CDCA8, AURKA, AURKB, INCENP, CDK1, BUB1 and CENPA are BIRC5-associated proteins. Molecular docking was performed to exhibit binding interactions with multiple natural ligands.
Conclusion: BIRC5 is a promising predictive marker and a potential therapeutic target in breast cancer. Further large-scale studies are required to correlate the significance of BIRC5 in breast cancer, leading to a step toward the clinical translation of novel diagnostic and therapeutic options.
Keywords: Breast cancer, transcriptomics, biomarkers, docking, pathway analysis, survivin.
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