Evidence map›Paper›PMID 39586899›Full record

ArticleTheory in biosciences = Theorie in den Biowissenschaften2025

Mathematical model of tumor immune microenvironment with application to the combined therapy targeting the PD-1/PD-L1 pathway and IL-10 cytokine antibody.

Zixin Zhang, Xiyin Liang, Jianyong Qin, Jinzhi Lei

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Article in Theory in biosciences = Theorie in den Biowissenschaften, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

4 authors.

Zixin ZhangSchool of Mathematical Sciences, Center for Applied Mathematics, Tiangong University, Tianjin, 300387, China.
Xiyin LiangSchool of Mathematical Sciences, Center for Applied Mathematics, Tiangong University, Tianjin, 300387, China.
Jianyong QinLiwan Central Hospital of Guangzhou, Liwan Road 35, Guangzhou, 510170, China.
Jinzhi LeiSchool of Mathematical Sciences, Center for Applied Mathematics, Tiangong University, Tianjin, 300387, China. jzlei@tiangong.edu.cn.

Funding

National Natural Science Foundation of China 12331018
6 · The paper itself

Abstract

The tumor microenvironment constitutes a complex system shaped by the intricate interactions among tumor cells, immune cells, and cytokines. Within this environment, the interplay between immune cells and cytokines is crucial in influencing tumor growth and progression. Despite advancements in clinical tumor immunotherapy, there remains a gap in comprehensive simulations of tumor immune responses, particularly regarding cytokine-driven processes. This study aims to address this gap by investigating the regulatory interactions among tumor cells, immune cells, and cytokines to simulate the complexities of tumor immunotherapy. We develop a comprehensive modeling and computational framework incorporating PD-1 inhibitors and interleukin-10 (IL-10) antibodies. Through detailed mathematical analysis, we elucidate the impact of changes in the immune microenvironment on tumor cells number. Our findings highlight the significant therapeutic effect of anti-PD-1 and IL-10 inhibitors, with increased drug dosage correlating with a reduction in tumor burden. Furthermore, combination therapy demonstrates a marked extension of survival with reduced dosages compared to monotherapy. Based on model simulations, we proposed prognostic predictions by assessing the microenvironmental status before treatment. The findings indicate a promising method for enhancing treatment effectiveness and offering potential advantages to patients receiving tumor immunotherapy.

Indexed as

B7-H1 AntigenInterleukin-10NeoplasmsProgrammed Cell Death 1 ReceptorTumor MicroenvironmentComputer SimulationHumansImmune Checkpoint InhibitorsImmunotherapyModels, BiologicalModels, TheoreticalSignal TransductionB7-H1 AntigenCD274 protein, humanIL10 protein, humanImmune Checkpoint InhibitorsInterleukin-10PDCD1 protein, humanProgrammed Cell Death 1 ReceptorCytokinesImmunotherapyMathematical modelPD-1/PD-L1Tumor immunity

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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.