Abstract

Breast cancer remains one of the most prevalent malignancies worldwide and continues to represent a major cause of cancer￾related morbidity and mortality. In recent years, advances in high-throughput omics technologies, particularly genomics,
transcriptomics, and proteomics, have substantially transformed our understanding of breast cancer biology. Transcriptomic
analyses provide detailed insights into gene expression dynamics and regulatory mechanisms, whereas proteomic approaches
elucidate protein abundance, post-translational modifications, and interaction networks, together enabling a systems-level
characterization of disease processes. These integrative approaches have significantly contributed to the identification of robust
biomarkers for early detection, prognosis, and therapeutic stratification. Furthermore, the convergence of multi-omics data has
facilitated the development of composite biomarker signatures and precision-based therapeutic strategies, effectively bridging
the gap between molecular insights and clinical translation. Despite these advances, several challenges remain, including
the complexity of data integration, high operational costs, and limited accessibility to advanced analytical platforms, which
collectively constrain their routine implementation in clinical settings. Nevertheless, the integration of omics technologies with
advanced bioinformatics frameworks continues to accelerate the discovery of novel biomarkers and actionable therapeutic
targets, thereby driving the evolution of personalized medicine. This review provides a comprehensive overview of genomic,
transcriptomic, and proteomic approaches in breast cancer, with particular emphasis on their roles in biomarker discovery and
therapeutic development, as well as the critical contribution of bioinformatics tools in enhancing data interpretation and clinical
applicability