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.

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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
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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

AQEEL RAJA
Zenodo (CERN European Organization for Nuclear Research)
Single-cell and spatial transcriptomics
article

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

AQEEL RAJA
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 17%
Single-cell and spatial transcriptomics
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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 — AQEEL RAJA · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS