Evidence map›Paper›PMID 41171428›Full record

ArticleHepatology communications2025

Integrated analysis identifies CD276 in fibroblasts as a malignancy predictor and regulator of neutrophil infiltration in hepatoblastoma.

Miao Ding, Guoqing Zhu, Tianshu Chen, Jiabei Zhu, Siwei Mao, Xiaochen Tang, Han Wu, Ni Zhen, Fenyong Sun, Qiuhui Pan and 1 more

Abstract read
In one paragraph

Article in Hepatology communications, 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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Single-cell and spatial transcriptomics reveal an arachidonic acid-related cellular atlas in lung adenocarcinoma.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
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4 · The record

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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

11 authors.

Miao DingDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.ORCID 0000-0001-8674-2731
Guoqing ZhuDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Tianshu ChenDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Jiabei ZhuDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Siwei MaoDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Xiaochen TangDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Han WuDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Ni ZhenDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.
Fenyong SunDepartment of Clinical Laboratory, Shanghai Tenth People's Hospital of Tongji University, Shanghai, China.
Qiuhui PanDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.ORCID 0000-0001-7386-2590
Ji MaDepartment of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China.ORCID 0000-0001-6904-5360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatoblastoma is the most prevalent liver cancer in children. Immunotherapy targeting immune checkpoint molecules has become pivotal in various cancer treatments. However, the clinical significance of immune checkpoint ligands in hepatoblastoma remains largely unclear due to various challenges. This study sought to first characterize the expression profile of the immune checkpoint ligand CD276 in hepatoblastoma and assess its potential as a predictor of malignant characteristics and regulator of neutrophil infiltration.

methodsUnivariable and multivariable logistic regression analyses were performed to evaluate the clinical significance of immune checkpoint ligands in the bulk RNA-seq dataset and develop a novel predictive model for malignancy. Furthermore, single-cell RNA sequencing (scRNA-seq), immunohistochemistry (IHC), deconvolution analysis, and correlation analysis were employed to characterize the expression pattern of CD276 and explore its influence on the tumor immune microenvironment.

resultsThe bulk RNA-seq analysis revealed CD276 transcript levels were significantly elevated in hepatoblastoma tissues, especially in patients with more aggressive malignant phenotypes. Furthermore, we developed a predictive model based on a risk score and constructed a user-friendly nomogram to predict patient metastasis by integrating CD276 levels with clinical features. Both scRNA-seq and multiplex immunohistochemistry (mIHC) analyses confirmed that CD276 is highly expressed, predominantly in cancer-associated fibroblasts. Our results also demonstrated that CD276 levels correlate with immune infiltration in hepatoblastoma, and that CD276 regulates CXCL2 to modulate neutrophil infiltration, suggesting a potential mechanism underlying the role of CD276 in hepatoblastoma malignancy. In addition, we validated that CD276 in cancer-associated fibroblasts promotes hepatoblastoma growth in mice.

conclusionsOur findings highlight the critical role of CD276 in hepatoblastoma malignancy, potentially providing novel insights and therapeutic targets for the development of combinatorial immunotherapy strategies for this disease.

Indexed as

B7 AntigensCancer-Associated FibroblastsHepatoblastomaLiver NeoplasmsNeutrophil InfiltrationAnimalsBiomarkers, TumorFemaleHumansMaleMiceNomogramsTumor MicroenvironmentB7 AntigensBiomarkers, Tumorbulk RNA-seqCD276fibroblastslogistic regression analysisscRNA-seq

Identifiers

PMID41171428
PMCPMC12577996

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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.