Advancements in point-of-care diagnostics for breast cancer: Biomarkers, metabolomics, and biosensor technologies

Breast cancer is one of the most prevalent and fatal malignancies globally, necessitating immediate and legitimate detection for fruitful treatment outcomes. Traditional diagnostic techniques employed for breast cancer detection, like mammography, biopsy, magnetic resonance imaging (MRI), and positron emission tomography (PET) scans, are associated with inherent limitations including invasiveness, high cost, limited accessibility, and challenges in detecting the disease at its earliest stages. This review explores advancements in point-of-care (POC) diagnostic technologies for breast cancer, highlighting the role of specific biomarkers, metabolomic studies, and innovative biosensor technologies. Biomarkers such as CA15–3, HER2, BRCA1/2, and circulating tumor DNA (ctDNA) have revolutionized detection accuracy, while metabolomic profiling offers insights into cancer-specific metabolic signatures. The integration of artificial intelligence (AI) in POC diagnostics has enhanced data analysis and predictive capabilities, streamlining personalized treatment approaches. Biosensors, particularly gold nanoparticle-based biosensors, demonstrate exceptional sensitivity, specificity, and rapid response times, making them promising tools for real-time breast cancer detection. This review presents an elaborate and comprehensive understanding of point-of-care diagnostics for breast cancer and emphasises on the potential of these cutting-edge technologies in transforming breast cancer diagnosis and improving patient outcomes in resource-limited settings. Unlike traditional reviews, this study emphasises the clinical translation potential for resource-limited settings, particularly addressing healthcare challenges in developing countries like India, where POC technologies can provide economical, accessible, and effective diagnostic solutions that reduce dependency on expensive centralized laboratory facilities.