Evidence map›Paper›PMID 38165493›Full record

ArticleDiscover oncology2024

Exploring the relationship between immune heterogeneity characteristic genes of rheumatoid arthritis and acute myeloid leukemia.

Chengzhi Jiang, Wenjuan Jiang, Pengtao Liu, Wenxue Sun, Wenjie Teng

Open access · goldAbstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
7.1field-weighted citation impact, top 3% of its field
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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. CD4Combinatorial chemistry & high throughput screening · 2026
    Article
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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

5 authors at 1 institution in 1 country.

Chengzhi JiangSchool of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Wenjuan JiangQingdao Municipal Hospital (Group), Qingdao, Shandong, 266000, People's Republic of China.
Pengtao LiuComputer Teaching and Research Office, Shandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Wenxue SunSchool of Public Health, Shandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China.
Wenjie TengComputer Teaching and Research Office, Shandong Second Medical University, Weifang, Shandong, 261053, People's Republic of China. wfteng@wfmc.edu.cn.
Qingdao Municipal Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeople with autoimmune diseases are prone to cancer, and there is a close relationship between rheumatoid arthritis (RA) and acute myeloid leukemia (AML). The bone marrow (BM) is affected throughout the course of RA, with a variety of hematologic involvement. Hopes are pinned on rheumatoid arthritis research to obtain BM biomarkers for AML.

methodsSynovial transcriptome sequencing data for RA and osteoarthritis (OA), and single-cell sequencing data for RA and controls were obtained from the GEO database.Bone marrow sequencing data for AML patients and normal subjects were obtained from the UCSC Xena database. The final immune heterogeneity characteristics of RA were determined through ssGSEA analysis, gene differential expression analysis, fuzzy c-means clustering algorithm, and XGboost algorithm. Random Ferns classifiers (RFs) are used to identify new bone marrow markers for AML.

resultsSELL, PTPRC, IL7R, CCR7, and KLRB1 were able to distinguish leukemia cells from normal cells well, with AUC values higher than 0.970.

conclusionGenes characterizing the immune heterogeneity of RA are associated with AML, and KLRBA may be a potential target for AML treatment.

Indexed as

Acute myeloid leukemiaBiomarkersMachine learningTherapeutic target

Identifiers

PMID38165493
PMCPMC10761643
OpenAlexW4390508153

What OpenQuestion holds

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LicenceCC BY
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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.