Journal of Cancer Therapeutics and Immunotherapy

ABSTRACT

Breast cancer, a complex and heterogeneous disease driven by genetic mutations in breast tissue cells, remains a leading cause of cancer-related mortality among women globally. A mutational signature can reveal the genomic landscape and history of breast cancer as it reflects the cumulative effect of various mutational processes that operate in cancer cells. This review provides an overview of the concept and classification of mutational signatures and discusses their clinical implications for breast cancer. We highlight how mutational signatures can provide insights into the therapeutic strategies, prognostic indicators, resistance mechanisms, and evolution of mutational signatures during treatment. Besides, we explore the potential applications of mutational signatures in personalized medicine for breast cancer, such as their integration with genomic profiling, prediction of treatment response, monitoring of treatment progression, and tailoring of therapeutic regimens based on signature analysis. We also address the challenges and limitations that need to be overcome before mutational signatures can be fully exploited for clinical benefit, such as the technical issues of data interpretation and standardization, the clinical translation of signature-based biomarkers, the exploration of emerging mutational signatures, and the longitudinal study of signature evolution. Future directions in mutational signature research encompass the exploration of emerging signatures, longitudinal studies to capture signature evolution, and the application of artificial intelligence to enhance signature detection and interpretation. While challenges remain, mutational signatures in breast cancer stand as a powerful tool that can revolutionize diagnosis and treatment, ultimately advancing our understanding and management of this complex disease.

Article History

KEYWORDS

1. Mutational signatures
2. Cancer diagnosis
3. Personalized medicine
4. Artificial intelligence
5. Prognosis
6. Therapeutics
7. Biomarkers