Establishment of a diagnostic model of endometriosis based on disulfidptosis‐related genes

基因 接收机工作特性 计算生物学 免疫系统 医学 诊断模型 基因表达 支持向量机 基因表达谱 生物信息学 遗传学 生物 人工智能 免疫学 数据挖掘 计算机科学 内科学
作者
Hong-yan Shi,Caixia Zhou,Y Zhao
出处
期刊:Journal of Obstetrics and Gynaecology Research [Wiley]
卷期号:50 (7): 1201-1207
标识
DOI:10.1111/jog.15945
摘要

Abstract Objectives We aimed to establish a diagnostic model of endometriosis (EM) based on disulfidptosis‐related genes (DRGs). Materials and Methods The mRNA expression data of EM were downloaded from the gene expression omnibus database and subjected to differential analysis, and co‐expression analysis was performed based on 10 disulfidptosis genes to acquire DRGs. The differentially expressed DRGs were subjected to biofunctional analysis. Lasso analysis and support vector machine‐recursive feature elimination (SVM‐RFE) analysis were employed to extract the intersection of feature genes as biomarkers, and the diagnostic values of biomarkers for EM were evaluated based on receiver operating characteristic curves. The correlations between biomarkers and the immune microenvironment were assessed by Pearson analysis of biomarkers and immune cell infiltration levels. Results Transforming growth factor β stimulated protein clone 22 domain family member 4 (TSC22D4), and F‐box/SPRY domain‐containing protein 1 (FBXO45) worked as the diagnostic classifiers in EM, with an obvious decrease in FBXO45 expression and an evident increase in TSC22D4 expression. The areas under the curves of FBXO45 and TSC22D4 were 0.752 and 0.706, respectively, and the area of FBXO45 combined with TSC22D4 reached 0.865, suggesting that TSC22D4 and FBXO45 had high predictive values. The diagnostic markers were closely correlated with immune cell infiltration. Conclusion The diagnostic markers constructed based on disulfidptosis are good predictors for EM, which have close correlations with EM.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
挡住所有坏运气888完成签到,获得积分10
1秒前
汉堡包应助JESSE采纳,获得10
3秒前
Lucas应助mmmi采纳,获得10
4秒前
LEI完成签到,获得积分20
5秒前
6秒前
ZPQ发布了新的文献求助10
7秒前
7秒前
wil35完成签到,获得积分10
8秒前
归陌完成签到 ,获得积分10
9秒前
10秒前
qiqi完成签到,获得积分20
10秒前
SSY完成签到,获得积分10
11秒前
12秒前
大马哥完成签到 ,获得积分0
12秒前
小方发布了新的文献求助10
12秒前
13秒前
wxj完成签到,获得积分20
13秒前
汉堡包应助白日焰火采纳,获得10
13秒前
orixero应助科研通管家采纳,获得10
14秒前
Jasper应助科研通管家采纳,获得10
14秒前
汉堡包应助科研通管家采纳,获得10
14秒前
科研通AI2S应助科研通管家采纳,获得10
14秒前
李健应助科研通管家采纳,获得10
14秒前
科研通AI6应助科研通管家采纳,获得20
14秒前
JamesPei应助科研通管家采纳,获得10
14秒前
段盼兰应助科研通管家采纳,获得20
14秒前
上官若男应助科研通管家采纳,获得10
15秒前
所所应助科研通管家采纳,获得10
15秒前
科研通AI6应助科研通管家采纳,获得10
15秒前
Orange应助科研通管家采纳,获得10
15秒前
深情安青应助科研通管家采纳,获得10
15秒前
Ava应助科研通管家采纳,获得10
15秒前
Hello应助科研通管家采纳,获得10
15秒前
天天快乐应助科研通管家采纳,获得10
15秒前
科研通AI6应助科研通管家采纳,获得10
15秒前
优雅听枫应助科研通管家采纳,获得10
15秒前
英姑应助科研通管家采纳,获得10
15秒前
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.).. Frederic G. Reamer 1070
Alloy Phase Diagrams 1000
Introduction to Early Childhood Education 1000
2025-2031年中国兽用抗生素行业发展深度调研与未来趋势报告 1000
List of 1,091 Public Pension Profiles by Region 891
Historical Dictionary of British Intelligence (2014 / 2nd EDITION!) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5424683
求助须知:如何正确求助?哪些是违规求助? 4539082
关于积分的说明 14165073
捐赠科研通 4456131
什么是DOI,文献DOI怎么找? 2444042
邀请新用户注册赠送积分活动 1435140
关于科研通互助平台的介绍 1412483