A Unified Framework for Understanding Pathological State Transitions Through Regulatory Informational Collapse and Evolutionary Fallback Mechanisms

Abstract Despite decades of progress in molecular oncology, the fundamental question of how a normal cell transitions into a pathological state remains incompletely answered. Traditional models emphasize somatic mutations, genomic instability, and clonal expansion. While these mechanisms are undoubtedly important, they do not fully explain phenomena such as field cancerization, spontaneous regression, therapy resistance, and the convergent evolution of similar phenotypic traits across diverse cancer types. This paper presents NOAH6, a comprehensive theoretical framework that integrates recent advances in systems biology, evolutionary medicine, information theory, and molecular oncology. The model proposes that pathological state transitions arise not primarily from mutational events but from a progressive regulatory informational collapse – a gradual degradation of the capacity of higher-order control systems to reliably distinguish homeostatic from pathological signals. Building on the NOAH6 hierarchical architecture (R0–R5 macro, R0'–R5' micro), the framework introduces three interconnected concepts: 1. Regulatory Informational Collapse – the progressive degradation of signal quality at receptor modules (R0'–R1') due to camouflage, contradictory signals, and chronic noise, leading to loss of discriminative capacity in cellular decision-making centers (R3'). 2. Epigenetic Latency – the condition-dependent reversible silencing of regulatory pathways, creating a "memory" of stress that limits future regulatory options without requiring permanent genetic change. 3. Evolutionary Fallback – the reversion to ancient, evolutionarily conserved survival programs (the "ancestral algorithm") when higher-order regulatory control is lost, representing a default state of cellular autonomy. The model explains why diverse pathological entities (cancer, chronic inflammation, viral persistence, parasitic infection) converge on similar adaptive behaviors, why identical therapeutic interventions produce heterogeneous responses, and why Pₛtate becomes progressively more stable over time. The framework generates falsifiable predictions and proposes a staged experimental validation strategy. Key addition: The model explicitly describes five mechanisms through which tumors propagate pathological regulatory states to surrounding healthy tissue without requiring physical spread of tumor cells, explaining field cancerization, pre-metastatic niche formation, and therapy resistance.