Predictive oncology represents a rapidly evolving field that combines genomics, biomarker science, artificial intelligence, and precision medicine to improve cancer prediction, diagnosis, treatment selection, and long-term patient management. By integrating large-scale molecular datasets with advanced computational models, researchers and clinicians can identify disease-associated biological patterns, estimate individual risk profiles, and support highly personalized therapeutic strategies that account for the unique molecular characteristics of each patient and tumor type. Cancer develops through the progressive accumulation of genomic alterations that disrupt normal cellular regulation and promote uncontrolled growth, survival, and adaptation. Critical tumor suppressor genes such as TP53 function as central guardians of genomic integrity by coordinating DNA repair, cell cycle control, apoptosis, and stress-response pathways, making their molecular status highly informative f...