Evidence map›Paper›PMID 41560673›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Immune Predictors of Radiotherapy Outcomes in Cervical Cancer.

Linghao Wang, Jie Zhu, Zequn Ding, Zhiyuan Xie, Xingchen Liu, Feihong Zhang, Xiaojun Liu, Yan Zhang, Haiyan Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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. Article
  2. Review
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.

Linghao WangMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Jie ZhuDepartment of Obstetrics and Gynecology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Zequn DingMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Zhiyuan XieMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xingchen LiuMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Feihong ZhangMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xiaojun LiuDepartment of Gynecology and Obstetrics, The Second Affiliated Hospital of Naval Medical University, Shanghai, China.
Yan ZhangMed-X Research Institute & School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0001-5612-1387
Haiyan ChenDepartment of radiation oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0001-8874-1302

Funding

Fundamental Research Funds for the Central Universities YG2023ZD06National Key Research and Development Program of China 2023YFA1800700National Key Research and Development Program of China 2023YFA1800702National Key Research and Development Program of China 2023YFC1404100National Key Research and Development Program of China 2023YFC1404102National Natural Science Foundation of China 81903129National Natural Science Foundation of China ‪81972670‬Renji hospital RJTJ25-MS-002Shanghai Shenkang Hospital Development Center SHDC12024121
6 · The paper itself

Abstract

The immune microenvironment influences the sensitivity of patients to radiotherapy (RT), yet determinants of therapeutic resistance remain elusive. This study integrates single-cell transcriptomics and machine learning to delineate immune predictors of RT outcomes. Comprehensive analysis reveals reduced epithelial cell numbers, accompanied by enhanced apoptosis, complement activation, and inflammatory responses. RT triggers macrophage accumulation, particularly an RT-responsive M1-like HSPA1B+ subset with elevated antigen-presenting capacity. While T and NK cell cytotoxicity increases, their exhaustion markers (e.g., PDCD1, TIGIT) are exacerbated. CellChat analysis identifies robust epithelial-myeloid crosstalk mediated by the C3/C3AR1 axis. In murine models, C3AR1 antagonism diminishes RT efficacy, impairing macrophage infiltration and M1 polarization. Leveraging 25 single-cell-derived immune features, an 8-feature multilayer perceptron model: Cervical Cancer Radiotherapy Immune-Response Model (CCRTIM) is developed. CCRTIM robustly predicts prognosis (AUC = 0.76) and exhibits risk stratification. These findings unveil dynamic immune remodeling post-RT and establish actionable biomarkers for precision radiotherapy strategies.

Indexed as

Tumor MicroenvironmentUterine Cervical NeoplasmsAnimalsFemaleHumansMachine LearningMacrophagesMicePrognosisTreatment Outcomecervical cancercomplement pathwaysmachine learningmacrophage polarizationradiotherapy outcomes

Identifiers

PMID41560673
PMCPMC13042687

What OpenQuestion holds

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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.