Evidence map›Paper›PMID 40166070›Full record

ArticleFrontiers in medicine2025

Identification of immune characteristic biomarkers and therapeutic targets in cuproptosis for rheumatoid arthritis by integrated bioinformatics analysis and single-cell RNA sequencing analysis.

Xianbin Li, Xueli Zhang, Tao Liu, Guodao Zhang, Dan Chen, Suxian Lin

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

6 authors.

Xianbin LiSchool of Computer and Big Data Science, Jiujiang University, Jiujiang, China.
Xueli ZhangDepartment of Medical Technology, Zhengzhou Railway Vocational and Technical College, Zhengzhou, China.
Tao LiuSchool of Computer and Big Data Science, Jiujiang University, Jiujiang, China.
Guodao ZhangDepartment of Digital Media Technology, Hangzhou Dianzi University, Hangzhou, China.
Dan ChenDepartment of Rheumatology, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, China.
Suxian LinDepartment of Rheumatology, Wenzhou People's Hospital, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Rheumatoid arthritis (RA) is a chronic autoimmune disorder intricately liked with inflammation. Cuproptosis, an emerging type of cell death, has been implicated in the initiation and development of RA. However, the exact alterations in the expression and biological function of cuproptosis-related genes (CRGs) in RA remain poorly understood. Therefore, our study aims to elucidate the potential association between CRGs and RA, with the goal of identifying novel biomarkers for the treatment and prognosis of RA. Methods: In this study, we identified ten differentially expressed cuproptosis-related genes (DE-CRGs) between patients with RA and controls. Through comprehensive functional enrichment and protein-protein interaction (PPI) network analysis, we explored the functional roles of the DE-CRGs. Additionally, we investigated the correlation between DE-CRGs and immune infiltration, immune factors, diagnostic efficacy, and potential therapeutic drugs. Results: Leveraging single-cell RNA sequencing data, we conducted a detailed analysis to elucidate alterations in various cell clusters associated with RA. Our study unveiled a significant association between DE-CRGs and diverse biological functions, as well as potential drug candidates. Discussion: These findings provide crucial insights into the involvement of DE-CRGs in the pathogenesis of RA and shed light on potential therapeutic strategies.

Indexed as

cuproptosisimmune infiltrationrheumatoid arthritissingle-cell RNAtherapeutic drugs

Identifiers

PMID40166070
PMCPMC11955502

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.