Evidence map›Paper›PMID 40760079›Full record

ArticleScientific reports2025

Predicting head and neck cancer response to radiotherapy with a chemokine-based model.

Jinzhi Lai, Rongfu Huang, Jingshan Huang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Review
  3. 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

3 authors.

Jinzhi LaiDepartment of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
Rongfu HuangDepartment of Clinical Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China. Rongf_Huang@126.com.
Jingshan HuangDepartment of General Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China. jingshan_huang@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiotherapy resistance remains a major challenge in Head and neck squamous cell carcinoma (HNSCC) treatment. This study aimed to develop a chemokine-based model for predicting radiosensitivity in HNSCC using a retrospective analysis of 432 patients from the TCGA database. We identified a model incorporating CXCL2, CCL28, and CCR8 expression that effectively stratified patients into radiosensitive (RS) and radioresistant (RR) groups. Patients in the RS group demonstrated significantly improved overall survival (OS) with radiotherapy, whereas this prognostic advantage was not observed in the non-radiotherapy group. Notably, patients within the RS group with high PD-L1 expression exhibited even better OS and increased immune infiltration, indicating a synergistic relationship between radiosensitivity and PD-L1 expression. Further analyses revealed enrichment of immune-related pathways and higher effector immune cell abundance in the RS group, suggesting greater potential for immunotherapy response. Corroborating these findings, analysis of the GSE40020 cohort showed significant upregulation of CCL28 in patients with complete response compared to those with post-treatment failure. In vitro experiments using radiosensitive and radioresistant Tongue squamous cell carcinoma (TSCC) cell lines validated the association between chemokine gene expression and radiosensitivity. Our model provides a valuable tool for identifying HNSCC patients who may benefit from combined treatment strategies incorporating synergistic anti-tumor agents.

Indexed as

ChemokinesHead and Neck NeoplasmsRadiation ToleranceSquamous Cell Carcinoma of Head and NeckAgedB7-H1 AntigenCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisRetrospective StudiesB7-H1 AntigenChemokines

Identifiers

PMID40760079
PMCPMC12322276

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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.