Biomarkers for cancer diagnosis, prognosis, and treatment response: Breast Cancer as a model - Alhussain, Ali Hassan; Alquwayi, Waseem Ali; Alameer Alkuwaiti, Yasser Abdrab; Almehainy, Ahmed Mohammed; Alqahtani, Bakr Mansour (International journal of health sciences, 2018)
Background: The management of invasive breast cancer presents significant challenges, particularly in determining which patients should receive adjuvant chemotherapy. Prognostic and predictive biomarkers play crucial roles in tailoring treatment decisions to individual patients. Aim: This article aims to explore the utility of both traditional and molecular biomarkers in optimizing therapeutic strategies for patients with newly diagnosed breast cancer. Methods: A comprehensive review was conducted to analyze traditional prognostic factors, including lymph node involvement, tumor size, and tumor grade, alongside emerging molecular biomarkers like Oncotype DX, MammaPrint, and others. Results: Traditional factors remain pivotal in breast cancer management, despite the emergence of molecular tests. Notably, lymph node status, tumor size, and tumor grade continue to correlate with patient outcomes. Investigational biomarkers, including circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), are currently under evaluation for their prognostic capabilities. The Oncotype DX assay, which assesses gene expression to predict recurrence risk, has demonstrated substantial impact on clinical decision-making, leading to reduced chemotherapy use in specific patient populations. Conclusion: The integration of both traditional and molecular biomarkers is essential for personalized breast cancer management. Ongoing research is crucial for validating the clinical utility of newer biomarkers, ultimately enhancing treatment decision-making processes.