Evidence map›Paper›PMID 40939764›Full record

ArticleMathematical biosciences2025

Employing nullclines to balance treatment efficacy and neurotoxicity for sustained tumor control.

Lois C Okereke, Ernesto A B F Lima, Anna G Sorace, Thomas E Yankeelov

Abstract read
In one paragraph

Article in Mathematical biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lois C OkerekeOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA. Electronic address: lois.okereke@austin.utexas.edu.
Ernesto A B F LimaOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA; Texas Advanced Computing Center, Austin, Texas 78757, USA.
Anna G SoraceDepartment of Radiology, University of Alabama at Birmingham, Birmingham, Alabama 35233, USA; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama 35233, USA; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, Alabama 35233, USA.
Thomas E YankeelovOden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA; Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas 78712, USA; Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA; Department of Diagnostic Medicine, The University of Texas at Austin, Austin, Texas 78712, USA; Department of Imaging Physics, MD Anderson Cancer Center, Houston, Texas 77030, USA.

Funding

Using label-free Raman microscopy to predict therapeutic resistance of TNBC cellsU01CA253540 · NCI · UNIVERSITY OF TEXAS AT AUSTIN · PI BROCK, AMY, YANKEELOV, THOMAS E · 2020 to 2024
$2.1M
Personalizing immunotherapy in HER2+ breast cancer through quantitative imagingR01CA240589 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SORACE, ANNA C · 2020 to 2023
$1.6M
Mathematical modeling and molecular imaging to maximize response while minimizing toxicities from systemic therapies in preclinical models of breast cancerR01CA276540 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SORACE, ANNA C, YANKEELOV, THOMAS E · 2023 to 2025
$1.4M
NCI NIH HHS R01 CA240589NCI NIH HHS R01 CA276540NCI NIH HHS U01 CA253540
6 · The paper itself

Abstract

There is increasing interest in identifying therapeutic regimens capable of maintaining tumor burden within well-defined size boundaries with constraints on the amount and frequency of drugs on a patient-specific basis. We have developed coupled systems of ordinary differential equations (ODEs) capturing the temporal dynamics of tumor burden, treatment effects due to cytotoxic drugs, and neurotoxicity. The models account for tumor cell proliferation and phenotypic heterogeneity, drug availability due to continuous or impulsive drug delivery, drug-induced apoptosis and microglia activation. We utilize nullclines of the system to derive effective dose ranges that stabilize tumor burden and mitigate neurotoxicity. Our results generate bounded treatment regimens that can be validated in the experimental setting. We found that for tumors with a proliferation saturation index (i.e., pre-treatment volume to carrying capacity ratio) between 0.10 and 0.30, containing the tumor in the sense of RECIST can yield up to a 51.8% reduction in drug concentration when compared with regimens designed for tumor eradication. In silico experiments using data from a breast cancer study demonstrate that the nullcline-derived treatments maintained stable disease in the tumors with neurotoxicity maintained below the desired threshold. The methodology developed in this study provides a theoretical formalism to potentially explain several preclinical and clinical observations indicating that low dose therapy can stabilize tumor growth and result in an enhanced quality of life. Importantly, our model identified quantitative biologic indices that can offer practical guidance to the design of personalized regimens that balance treatment efficacy and toxicity.

Indexed as

Antineoplastic AgentsNeoplasmsNeurotoxicity SyndromesComputer SimulationHumansPrecision MedicineTreatment InterruptionTumor BurdenAntineoplastic AgentsLow-dose metronomic TherapyMicroglia activationOptimal therapeutic regimenTumor stability analysis

Identifiers

PMID40939764
PMCPMC13595847

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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.