Evidence map›Paper›PMID 40296809›Full record

ArticleMathematical biosciences and engineering : MBE2025

Mathematical modeling of the synergetic effect between radiotherapy and immunotherapy.

Yixun Xing, Casey Moore, Debabrata Saha, Dan Nguyen, MaryLena Bleile, Xun Jia, Robert Timmerman, Hao Peng, Steve Jiang

Abstract read
In one paragraph

Article in Mathematical biosciences and engineering : MBE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

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

9 authors.

Yixun XingMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Casey MooreDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Debabrata SahaDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Dan NguyenMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
MaryLena BleileMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Xun JiaMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Robert TimmermanDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Hao PengMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Steve JiangMedical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

Funding

Human-like automated radiotherapy treatment planning via imitation learningR01CA254377 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN, JIANG, STEVE BIN · 2021 to 2025
$2.9M
Artificial Intelligence-Based Quality Assurance for Online Adaptive RadiotherapyR01CA258987 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Steve Bin Jiang, Dan Nguyen · 2022 to 2026
$2.8M
Intelligent treatment planning for cancer radiotherapyR01CA237269 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI JIA, XUN, JIANG, STEVE BIN · 2019 to 2023
$2.5M
NCI NIH HHS R01 CA237269NCI NIH HHS R01 CA254377NCI NIH HHS R01 CA258987
6 · The paper itself

Abstract

The synergy between radiotherapy and immunotherapy plays a pivotal role in enhancing tumor control and treatment outcomes. To explore the underlying mechanisms of synergy, we investigated a novel treatment approach known as personalized ultra-fractionated stereotactic adaptive radiation (PULSAR) therapy, which emphasizes the impact of radiation timing. Unlike conventional daily treatments, PULSAR delivers high-dose radiation in spaced intervals over weeks or months, enabling tumors to adapt and potentially enhancing synergy with immunotherapy. Drawing on insights from small-animal radiation studies, we developed a discrete-time model based on multiple difference equations to elucidate the temporal dynamics of tumor control driven by both radiation and the adaptive immune response. By accounting for the migration and infiltration of T cells within the tumor microenvironment, we established a quantitative link between radiation therapy and immunotherapy. Model parameters were estimated using a simulated annealing algorithm applied to training data, and our model achieved high accuracy for the test data with a root mean square error of 287 mm

Indexed as

ImmunotherapyNeoplasmsAdaptive ImmunityAlgorithmsAnimalsCombined Modality TherapyComputer SimulationDose Fractionation, RadiationHumansMiceModels, TheoreticalRadiosurgeryT-LymphocytesTumor Microenvironmentimmunotherapymathematical modelingpersonalized ultra-fractionated stereotactic adaptive radiation therapy (PULSAR)T cell infiltrationT cell migration

Identifiers

PMID40296809
PMCPMC12822734

What OpenQuestion holds

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Registered trials

None linked

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.