Redefining Cancer: A Unified Framework for Predicting, Preventing, and Stabilizing Malignancy
Abstract
For decades, cancer biology has grappled with the paradox of diverse cancers exhibiting similar hallmark behaviors and the persistent challenge of therapeutic resistance. This paper defines cancer as an entropic process—a system where mutation-driven disorder competes with repair mechanisms. By formalizing DNA entropy as a quantifiable metric, we establish a predictive model for cancer progression.
This framework explains how hallmark behaviors predictably emerge from corrupted genetic instructions and why resistance arises when therapies target downstream effects rather than root causes. By identifying DNA repair as a fundamental intervention point, it offers testable predictions about cancer progression and strategies to mitigate entropy accumulation. Bridging theoretical innovation with modern technologies such as CRISPR, AI-driven genomic analysis, and molecular monitoring, this framework provides a comprehensive foundation for advancing cancer research and developing durable therapeutic strategies.