Guest Editors
Dr. Rashid Sayyid
Email: rksayyid@gmail.com
Affiliation: Department of Urology, University of Arizona, Banner Medical Center, Tuscon, USA
Homepage:
Research Interests: clinically localized and advanced prostate cancer, perioperative outcomes with open and minimally invasive pelvic surgery, biomarker risk stratification in localized and advanced urologic malignancies, health services research, clinical implementation science and evidence synthesis
Summary
This Special Issue will focus on the integration of biomarkers and risk stratification tools to guide treatment decision-making across urologic malignancies, including prostate, bladder, and kidney cancers. While therapeutic selection has traditionally relied on clinicopathologic features, these approaches incompletely capture biologic heterogeneity and often fail to accurately identify patients at the highest risk of progression, metastasis, or disease-specific mortality.
Recent advances in molecular profiling, including genomic alterations (e.g., homologous recombination repair mutations), transcriptomic classifiers, circulating biomarkers, and advanced imaging modalities such as PSMA PET, have expanded opportunities for biomarker-guided care. In parallel, improved risk stratification frameworks—incorporating clinical, pathologic, and biologic data—are increasingly used to identify patients who may benefit from treatment intensification or, conversely, de-escalation strategies.
This Special Issue will highlight contemporary evidence supporting biomarker-guided and risk-adapted treatment approaches across disease states. Topics will include identification of high-risk populations for therapeutic intensification, biomarker-informed selection for targeted and immune-based therapies, perioperative risk stratification, and emerging technologies such as spatial transcriptomics and artificial intelligence–enabled predictive modeling.
Through original research, state-of-the-art reviews, and expert perspectives, this issue aims to define practical and clinically actionable frameworks for integrating biomarkers and risk stratification into personalized care pathways in urologic oncology.
Keywords
biomarkers, urologic malignancies, risk stratification
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