Evidence map›Paper›PMID 40291456›Full record

ArticleJournal of inflammation research2025

Identification and Experimental Validation of PANoptosis-Related Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics Analysis.

Dongguang Wang, Yifan Yuan, Xiang Tong, Lian Wang, Jibo Sun, Shijie Zhang, Sitong Liu, Huatian Gan, Hong Fan

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of inflammation research, 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

The trial behind it

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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

9 authors.

Dongguang Wang *Department of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Yifan Yuan *Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Xiang TongDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Lian WangDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Jibo SunDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Shijie ZhangDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Sitong LiuDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Huatian GanCenter of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Hong FanDepartment of Respiratory and Critical Care Medicine, and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: To identify the molecular signature of differentially expressed genes (DEGs) associated with PANoptosis in idiopathic pulmonary fibrosis (IPF) and to interpret their immune landscape and cellular distribution characteristics. Methods and Results: We acquired two IPF datasets from the Gene Expression Omnibus (GEO) database to identify PANoptosis-related DGEs (PAN-DEGs), initially identifying thirty PAN-DEGs. Utilizing machine learning algorithms, we established a five-gene PANoptosis-related signature comprising IGF1, GPX3, GADD45β, SMAD7, and TIMP3, each demonstrating robust diagnostic performance. The expression of these hub genes was subsequently validated using a third GEO dataset and a bleomycin-induced pulmonary fibrosis model. Immune infiltration analysis revealed a close association of these genes with various immune cells, and single-cell RNA sequencing indicated significant expression changes in diverse pulmonary cell types, particularly endothelial cells and fibroblasts. Conclusion: We identified and validated a PANoptosis-related gene signature in IPF, providing insights into their immune infiltration and potential cellular distribution. Further research is necessary to elucidate the biological functions and mechanisms of these genes in the pathogenesis of IPF.

Indexed as

bioinformatics analysisdifferentially expressed genesidiopathic pulmonary fibrosisPANoptosis

Identifiers

PMID40291456
PMCPMC12034268

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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.