| _version_ | 1866901100808896512 |
|---|---|
| author | Morris, Jamie |
| author_facet | Morris, Jamie |
| contents | <p>Conventional cancer therapies rely predominantly on maximum tolerated dose strategies that impose strong selective pressures on heterogeneous tumor populations. While often producing rapid tumor regression, these approaches systematically favor the emergence of resistant clones, leading to predictable relapse and treatment failure. This reflects a fundamental mismatch between static treatment paradigms and cancer’s evolutionary nature.</p> <p>This work presents the Evolutionary Neutrality Framework, a systems-based strategy that reframes cancer management from eradication to controlled equilibrium. Drawing on evolutionary biology, population genetics, tumor metabolism, and systems theory, the framework aims to suppress clonal sweeps by flattening fitness differentials between tumor subpopulations and maintaining tumors within a bounded regime of effective neutrality (fitness ≈ 1.0). By reducing directional selection rather than maximizing cytotoxicity, the approach seeks to preserve immune competence, constrain mutation-driven escape, and enable durable disease control.</p> <p>Three equilibrium-based therapeutic strategies are defined: (i) a Frozen State characterized by growth arrest, (ii) a Homeostatic Pulse strategy employing controlled oscillation to prevent adaptation, and (iii) a Gentle Decline strategy in which fitness is gradually reduced over extended time horizons. Computational simulations demonstrate that neutrality-based strategies prevent clonal dominance and resistance emergence observed under aggressive monotherapy, particularly when combined with preserved immune surveillance.</p> <p>The framework is translated into a concrete clinical implementation for pancreatic ductal adenocarcinoma (PDAC), a malignancy marked by profound metabolic dependency, clonal heterogeneity, and resistance to conventional therapy. Using clinically available metabolic modulators targeting glucose, glutamine, and lactate utilization, the proposed approach is designed to flatten selective gradients while maintaining host physiological stability. A fully specified Phase I/II adaptive clinical trial protocol (IMPALA) is included, incorporating longitudinal liquid biopsy, advanced metabolic imaging, immune profiling, and quality-of-life assessment to empirically test the framework.</p> <p>This document is presented as a research framework and trial-enabling protocol, not as clinical guidance, and makes no claims of clinical efficacy. It is intended to support hypothesis testing, regulatory dialogue, and collaborative development. By aligning therapeutic strategy with evolutionary reality, the Evolutionary Neutrality Framework establishes a platform for durable cancer management and a broader shift toward treating malignancy as a dynamic biological system rather than a static target.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18072423 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Evolutionary Neutrality Framework: A Systems-Based Strategy for Durable Cancer Control Morris, Jamie <p>Conventional cancer therapies rely predominantly on maximum tolerated dose strategies that impose strong selective pressures on heterogeneous tumor populations. While often producing rapid tumor regression, these approaches systematically favor the emergence of resistant clones, leading to predictable relapse and treatment failure. This reflects a fundamental mismatch between static treatment paradigms and cancer’s evolutionary nature.</p> <p>This work presents the Evolutionary Neutrality Framework, a systems-based strategy that reframes cancer management from eradication to controlled equilibrium. Drawing on evolutionary biology, population genetics, tumor metabolism, and systems theory, the framework aims to suppress clonal sweeps by flattening fitness differentials between tumor subpopulations and maintaining tumors within a bounded regime of effective neutrality (fitness ≈ 1.0). By reducing directional selection rather than maximizing cytotoxicity, the approach seeks to preserve immune competence, constrain mutation-driven escape, and enable durable disease control.</p> <p>Three equilibrium-based therapeutic strategies are defined: (i) a Frozen State characterized by growth arrest, (ii) a Homeostatic Pulse strategy employing controlled oscillation to prevent adaptation, and (iii) a Gentle Decline strategy in which fitness is gradually reduced over extended time horizons. Computational simulations demonstrate that neutrality-based strategies prevent clonal dominance and resistance emergence observed under aggressive monotherapy, particularly when combined with preserved immune surveillance.</p> <p>The framework is translated into a concrete clinical implementation for pancreatic ductal adenocarcinoma (PDAC), a malignancy marked by profound metabolic dependency, clonal heterogeneity, and resistance to conventional therapy. Using clinically available metabolic modulators targeting glucose, glutamine, and lactate utilization, the proposed approach is designed to flatten selective gradients while maintaining host physiological stability. A fully specified Phase I/II adaptive clinical trial protocol (IMPALA) is included, incorporating longitudinal liquid biopsy, advanced metabolic imaging, immune profiling, and quality-of-life assessment to empirically test the framework.</p> <p>This document is presented as a research framework and trial-enabling protocol, not as clinical guidance, and makes no claims of clinical efficacy. It is intended to support hypothesis testing, regulatory dialogue, and collaborative development. By aligning therapeutic strategy with evolutionary reality, the Evolutionary Neutrality Framework establishes a platform for durable cancer management and a broader shift toward treating malignancy as a dynamic biological system rather than a static target.</p> |
| title | The Evolutionary Neutrality Framework: A Systems-Based Strategy for Durable Cancer Control |
| url | https://doi.org/10.5281/zenodo.18072423 |