Integrated High-throughput Transcriptomic Data Identifies Survivin as a Potential Breast Cancer Therapeutic Biomarker

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</i> (survivin), MMP11, S100P, RARA</i>, and the most downregulated genes were ADIPOQ, LEP, CFD, PCK1</i> and HBA2</i>. Transcriptomic and molecular pathway analyses identified BIRC5</i>/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; biomarkers; docking; pathway analysis; survivin; transcriptomics.