---
title: "Agent-based 3D model of non-genetic adaptation in tumors under electrical, mechanical, and hypoxic"
id: "biorxiv-15-an-agent-based-3d-model-of-non-genetic-adaptation-in-cancer-tissues-under"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-15-an-agent-based-3d-model-of-non-genetic-adaptation-in-cancer-tissues-under"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.08.31.748266v1?rss=1"
published_at: "2026-09-02T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Agent-based 3D model of non-genetic adaptation in tumors under electrical, mechanical, and hypoxic
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-15-an-agent-based-3d-model-of-non-genetic-adaptation-in-cancer-tissues-under
- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.08.31.748266v1?rss=1)
- **Published At:** 2026-09-02T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The study presents an **agent-based model** of 3D tumor tissue that integrates vascular oxygen supply, an externally imposed electric field, mechanical crowding and compression cues, phenotype transitions, cell growth, mitosis, death, and inheritance of adaptive memory. - The model focuses on **non-genetic adaptation**, i.e., phenotype changes that do not require new mutations, and how multiple physical stresses combine to shape adaptive dynamics in spatially organized tumor tissue. - Simulated tumors follow a three-stage trajectory: onset of necrosis, a transient collapse of live mass, and partial regrowth with progressive accumulation of adapted cells. - Continuous electrical stimulation reduces live tumor mass in a dose-dependent manner while substantially increasing the fraction of adapted cells; the final necrotic burden changes less markedly. - Mechanical conditions strongly condition the response to electrical forcing; mechanics both reshape adaptive capacity and are reshaped by it in the simulations. - Pulsed electrical stimulation shows that both field amplitude and temporal scheduling jointly determine memory phenomena, phenotypic diversification, and recovery of growth in the model. - Coupling local oxygen availability, **mechanical constraints**, **electrical forcing**, and history-dependent phenotype transitions can produce distinct tissue-level patterns of phenotypic heterogeneity. - The model suggests that both stimulus magnitude and temporal protocol (history of physical stress) are important determinants of adaptive dynamics in spatially organized tumor models. - Data and code are available from the authors’ repository (GitHub link provided in the source).
## Clinical Analysis & Structured Key Points
An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress | bioRxiv Skip to main content New Results An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress Joao F. Gil , Nathalia Pinehiro , View ORCID Profile Saverio Gentile , View ORCID Profile Gil Goncalves , View ORCID Profile Rosalia Moreddu doi: https://doi.org/10.64898/2026.08.31.748266 Joao F. Gil 1 University of Aveiro, Aveiro, Portugal; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nathalia Pinehiro 2 Medical University of South Carolina, Charleston, USA; Find this author on Google Scholar Find this author on PubMed Search for this author on this site Saverio Gentile 2 Medical University of South Carolina, Charleston, USA; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Saverio Gentile Gil Goncalves 1 University of Aveiro, Aveiro, Portugal; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Gil Goncalves Rosalia Moreddu 3 University of Southampton Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rosalia Moreddu For correspondence: rosalia.moreddu{at}eng.ox.ac.uk Abstract Info/History Metrics Data/Code Preview PDF Abstract Non-genetic adaptation enables cancer cells to alter their phenotype under stress without requiring new mutations. However, the mechanisms by which electrical, mechanical, and hypoxic cues combine to shape this process in 3D tissues remain poorly understood. This work presents an agent-based tumor model that integrates vascular oxygen supply, a globally imposed electric field, mechanically mediated crowding and compression cues, phenotype transitions, cell growth, mitosis, death, and inheritance of adaptive memory across division. The simulated tumors exhibit a three-stage trajectory consisting of necrosis onset, transient collapse of live mass, and partial regrowth accompanied by progressive accumulation of adapted cells. Continuous electrical stimulation produces a dose-dependent reduction in live mass while markedly increasing the adapted fraction, with comparatively limited changes in final necrotic burden. This response is strongly conditioned by mechanics and reshapes (and is reshaped by) adaptive capacity. Pulsed stimulation further shows that, in the model, electric field amplitude and temporal schedule jointly determine memory phenomena, phenotypic diversification, and growth recovery. These results show that coupling local oxygen availability, mechanical constraints, electrical forcing, and history-dependent phenotype transitions can generate distinct tissue-level patterns of phenotypic heterogeneity. Both stimulus magnitude and temporal protocol influenced the resulting population structure, suggesting that the history of physical stress may be an important determinant of adaptive dynamics in spatially organized tumor models. Competing Interest Statement The authors have declared no competing interest. Footnotes https://github.com/moreddurosalia-code/Electromechanical-Adaptation-Modeling Copyright The copyright holder has placed this preprint in the Public Domain. It is no longer restricted by copyright. Anyone can legally share, reuse, remix, or adapt this material for any purpose without crediting the original authors. Back to top Previous Next Posted September 02, 2026. Download PDF Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress Joao F. Gil , Nathalia Pinehiro , Saverio Gentile , Gil Goncalves , Rosalia Moreddu bioRxiv 2026.08.31.748266; doi: https://doi.org/10.64898/2026.08.31.748266 Share This Article: Copy Citation Tools An agent-based 3D model of non-genetic adaptation in cancer tissues under electrical, mechanical, and hypoxic stress Joao F. Gil , Nathalia Pinehiro , Saverio Gentile , Gil Goncalves , Rosalia Moreddu bioRxiv 2026.08.31.748266; doi: https://doi.org/10.64898/2026.08.31.748266 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Areas All Articles Animal Behavior and Cognition (7953) Biochemistry (18602) Bioengineering (14744) Bioinformatics (44050) Biophysics (22431) Cancer Biology (19557) Cell Biology (26708) Clinical Trials (138) Developmental Biology (13874) Ecology (20842) Epidemiology (2067) Evolutionary Biology (25267) Genetics (16084) Genomics (23365) Immunology (18560) Microbiology (42156) Molecular Biology (17924) Neuroscience (92702) Paleontology (693) Pathology (2964) Pharmacology and Toxicology (5054) Physiology (8040) Plant Biology (15881) Scientific Communication and Education (2090) Synthetic Biology (4532) Systems Biology (10168) Zoology (2371)
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