Evidence map›Paper›PMID 41256596›Full record

ArticlebioRxiv : the preprint server for biology2025

Regulatory network and spatial modeling reveal cooperative mechanisms of resistance and immune escape in ER+ breast cancer.

Yijia Fan, Sarthak Sahoo, Mohit K Jolly, Jason T George

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yijia FanDepartment of Biomedical Engineering, Texas A&M University, Houston, TX, USA.
Sarthak SahooDepartment of Bioengineering, Indian Institute of Science, Bengaluru, India.
Mohit K JollyDepartment of Bioengineering, Indian Institute of Science, Bengaluru, India.
Jason T GeorgeDepartment of Biomedical Engineering, Texas A&M University, Houston, TX, USA.ORCID 0000-0002-8248-2888

Funding

Quantifying phenotypic adaptation of biological systems in dynamic environmentsR35GM155458 · NIGMS · TEXAS ENGINEERING EXPERIMENT STATION · PI Jason George · 2024 to 2026
$1.1M
NIGMS NIH HHS R35 GM155458
6 · The paper itself

Abstract

Despite significant progress, the treatment of estrogen receptor-positive (ER+) breast cancer remains clinically challenging due to reversible drug resistance and immune evasion. Drug resistance often arises as cells undergo a dynamic epithelial-to-mesenchymal transition (EMT), while elevated PD-L1 levels contribute to immune escape. While these phenotypic features can variably co-occur, the impact of co-occurrence on the availability of synergistic treatment strategies remains unknown. To investigate their interplay, we constructed an ER-EMT-PD-L1 gene regulatory network and simulated these networks as coupled ordinary differential equations with biologically informed parameters, to generate steady-state expression profiles. Our study revealed that the relevant overarching network generated antagonistic epithelial and mesenchymal modules, capable of producing monostable, bistable, and tristable dynamics. We further examined the link between phenotypes and immune evasion by quantifying average PD-L1 expression, and found that epithelial-sensitive states consistently exhibited low PD-L1. In contrast, hybrid- and mesenchymal-resistant states were associated with high PD-L1, highlighting a strong coupling between EMT, resistance, and immune evasion. Extending on these network-level insights, we further used a spatially explicit agent-based model seeded with GRN-derived phenotypes to probe tumor behavior under therapeutic pressure. Simulations revealed that tumor escape required co-occurrence of therapy resistance, motility, and immune suppression, with plasticity and multistability further promoting adaptive persistence. Lastly, we identified combination therapies predicted to constrain malignant diversification and enhanced immune accessibility. Taken together, our modeling work links regulatory dynamics with tumor-level adaptation and underscores potential strategies to therapeutically reprogram cell states toward sensitivity.

Indexed as

Agent-based modelCombination therapyEMTER+ breast cancerGene regulatory networkTumor plasticity

Identifiers

PMID41256596
PMCPMC12621902

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.