Evidence map›Paper›PMID 38167455›Full record

ArticleScientific reports2024

Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis.

Ruiqi Zhang, Weilin Zhao, Xingyao Zhu, Yuhua Liu, Qi Ding, Caiyun Yang, Hong Zou

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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
2.3field-weighted citation impact, top 14% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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

7 authors at 3 institutions in 1 country.

Ruiqi Zhang *Department of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang, 832002, China.
Weilin Zhao *Department of Pathology, Taihe Hospital, Hubei University of Medicine, Hubei, 442000, China.
Xingyao ZhuDepartment of Pathology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang, 310009, China.
Yuhua LiuDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang, 832002, China.
Qi DingDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang, 832002, China.
Caiyun YangDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of Medicine, Xinjiang, 832002, China.
Hong ZouDepartment of Pathology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang, 310009, China. zouhong@zju.edu.cn.
Shihezi University · CNSecond Affiliated Hospital of Zhejiang University · CNHubei University of Medicine · CN

Funding

the International Cooperation Project of Xinjiang Production and Construction Corps of China 2019BC001the National Natural Science Foundation of China 81660411, 81460383
6 · The paper itself

Abstract

Diagnosing low-grade and high-grade endometrial stromal sarcoma (LG-ESS and HG-ESS) is a challenge. This study aimed to identify biomarkers. 22 ESS cases were analyzed using Illumina microarrays. Differentially expressed genes (DEGs) were identified via Limma. DEGs were analyzed with String and Cytoscape. Core genes were enriched with GO and KEGG, their pan-cancer implications and immune aspects were studied. 413 DEGs were found by exome sequencing, 2174 by GSE85383 microarray. 36 common genes were identified by Venn analysis, and 10 core genes including RBFOX1, PCDH7, FAT1 were selected. Core gene GO enrichment included cell adhesion, T cell proliferation, and KEGG focused on related pathways. Expression was evaluated across 34 cancers, identifying immune DEGs IGF1 and AVPR1A. Identifying the DEGs not only helps improve our understanding of LG-ESS, HG-ESS but also promises to be potential biomarkers for differential diagnosis between LG-ESS and HG-ESS and new therapeutic targets.

Indexed as

Endometrial NeoplasmsSarcoma, Endometrial StromalBiomarkers, TumorComputational BiologyFemaleGene Expression ProfilingHumansBiomarkers, Tumor

Identifiers

PMID38167455
PMCPMC10761685
OpenAlexW4390502095

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.