Evidence map›Paper›PMID 38779678›Full record

ArticleFrontiers in immunology2024

Mathematical modeling of the synergistic interplay of radiotherapy and immunotherapy in anti-cancer treatments.

Paolo Castorina, Filippo Castiglione, Gianluca Ferini, Stefano Forte, Emanuele Martorana, Dario Giuffrida

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

6 authors.

Paolo CastorinaGenomics and molecular oncology unit, Istituto Oncologico del Mediterraneo, Viagrande, Italy.
Filippo CastiglioneBiotech Research Center, Technology Innovation Institute, Abu Dhabi, United Arab Emirates.
Gianluca FeriniRadiotherapy Unit, REM Radioterapia, Viagrande, Italy.
Stefano ForteGenomics and molecular oncology unit, Istituto Oncologico del Mediterraneo, Viagrande, Italy.
Emanuele MartoranaGenomics and molecular oncology unit, Istituto Oncologico del Mediterraneo, Viagrande, Italy.
Dario GiuffridaGenomics and molecular oncology unit, Istituto Oncologico del Mediterraneo, Viagrande, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: While radiotherapy has long been recognized for its ability to directly ablate cancer cells through necrosis or apoptosis, radiotherapy-induced abscopal effect suggests that its impact extends beyond local tumor destruction thanks to immune response. Cellular proliferation and necrosis have been extensively studied using mathematical models that simulate tumor growth, such as Gompertz law, and the radiation effects, such as the linear-quadratic model. However, the effectiveness of radiotherapy-induced immune responses may vary among patients due to individual differences in radiation sensitivity and other factors. Methods: We present a novel macroscopic approach designed to quantitatively analyze the intricate dynamics governing the interactions among the immune system, radiotherapy, and tumor progression. Building upon previous research demonstrating the synergistic effects of radiotherapy and immunotherapy in cancer treatment, we provide a comprehensive mathematical framework for understanding the underlying mechanisms driving these interactions. Results: Our method leverages macroscopic observations and mathematical modeling to capture the overarching dynamics of this interplay, offering valuable insights for optimizing cancer treatment strategies. One shows that Gompertz law can describe therapy effects with two effective parameters. This result permits quantitative data analyses, which give useful indications for the disease progression and clinical decisions. Discussion: Through validation against diverse data sets from the literature, we demonstrate the reliability and versatility of our approach in predicting the time evolution of the disease and assessing the potential efficacy of radiotherapy-immunotherapy combinations. This further supports the promising potential of the abscopal effect, suggesting that in select cases, depending on tumor size, it may confer full efficacy to radiotherapy.

Indexed as

ImmunotherapyNeoplasmsCombined Modality TherapyHumansModels, TheoreticalRadiotherapyabscopal effectGompertz lawimmune responseimmunotherapymathematical modelingradiotherapy

Identifiers

PMID38779678
PMCPMC11109403

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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.