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Breast cancer is the most prevalent cancer among women in the United States, representing ~30% of all new female cancer cases annually. For the year 2024, it is estimated that 310,720 new instances of invasive breast cancer will be diagnosed, and breast cancer will be responsible for over 42,000 deaths among women. Today, despite the availability of numerous treatments for breast cancer and its symptoms, most cancer-related deaths result from metastasis for which there is no treatment. This emphasizes the importance of early detection and treatment of breast cancer before it spreads. For initial detection and staging of breast cancer, clinicians routinely employ mammography and ultrasonography, which, while effective for broad screening, have limitations in sensitivity and specificity. Advanced biomarkers could significantly enhance the precision of early detection, enable more accurate monitoring of disease evolution, and facilitate the development of personalized treatment plans tailored to the specific molecular profile of each tumor. This would not only improve therapeutic outcomes, but also help in avoiding overtreatment and the associated side effects, thereby improving the quality of life for patients. Thus, the pursuit of novel biomarkers, potentially encompassing metabolomic and lipidomic signatures, is essential for advancing breast cancer diagnosis and treatment. In this brief review, we will provide an overview of the current translational potential of metabolic and lipidomic biomarkers for predicting breast cancer prognosis and response to therapy.
Carmona et al. (Mon,) studied this question.