Dynamic Homeostatic Control Architecture (DHCA) and Healthy Cellular Dynamic Identity (HCDI): A Healthy-First, Dynamics-Based Framework for Pan-Cancer Malignancy Recognition and Conditional Therapeutic Targeting
Dynamic Homeostatic Control Architecture (DHCA) and Healthy Cellular Dynamic Identity (HCDI) present a healthy-first, falsification-driven computational framework aimed at developing a generalizable approach to pan-cancer malignancy recognition and, ultimately, conditional therapeutic targeting. Rather than searching for a universal cancer-specific molecular signature, the framework defines context-dependent healthy cellular dynamics and evaluates malignancy through persistent, context-inappropriate, and autonomous failures of homeostatic control. The framework was evaluated using public human transcriptomic datasets through healthy-only dynamic modeling, frozen challenge analyses, hard-negative testing, and explicit falsification experiments. The results reject simpler approaches based on a universal healthy centroid, static transcriptomic abnormality, or persistence alone. They support context-dependent healthy dynamic trajectories and demonstrate measurable persistence and response/coupling behavior, while showing that recovery must be defined as return to an allowed context-appropriate healthy trajectory rather than a single baseline state. The final computational audit supports the core healthy-first dynamic architecture while identifying recovery and, particularly, autonomy as remaining requirements for full validation. The long-term objective is a biologically implementable pan-cancer recognition system capable of selectively identifying malignant control failure while preserving legitimate healthy states, ultimately enabling conditional therapeutic targeting. This work represents a computational proof-of-concept and falsifiable research framework. It does not constitute a validated clinical diagnostic, universal pan-cancer classifier, demonstrated cancer treatment, or cure. Version 1.0 — Final Computational Audit.
Authors
- AQEEL RAJA (ORCID: https://orcid.org/0009-0007-2051-6644)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-08-31
- DOI
- https://doi.org/10.5281/zenodo.22188929
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00