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
伯赏人杰发布了新的文献求助10
1秒前
2秒前
2秒前
冬冬完成签到,获得积分10
3秒前
kisaki完成签到 ,获得积分10
4秒前
8秒前
听听发布了新的文献求助10
9秒前
10秒前
13秒前
清秀尔竹发布了新的文献求助10
14秒前
nicewink发布了新的文献求助10
15秒前
15秒前
16秒前
量子星尘发布了新的文献求助10
16秒前
FashionBoy应助不辣的皮特采纳,获得10
16秒前
我是老大应助务实的大神采纳,获得10
17秒前
17秒前
18秒前
orixero应助拉长的乐瑶采纳,获得10
18秒前
18秒前
tiantan521发布了新的文献求助10
18秒前
19秒前
千跃举报崔风机求助涉嫌违规
20秒前
20秒前
20秒前
Nature完成签到,获得积分10
21秒前
英姑应助piso采纳,获得10
21秒前
21秒前
21秒前
Danish完成签到,获得积分10
21秒前
高高初柔发布了新的文献求助10
22秒前
23秒前
娟娟发布了新的文献求助30
23秒前
希望天下0贩的0应助nicewink采纳,获得10
23秒前
23秒前
24秒前
多喝水发布了新的文献求助10
24秒前
lay发布了新的文献求助10
24秒前
26秒前
26秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
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 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3959759
求助须知:如何正确求助?哪些是违规求助? 3506016
关于积分的说明 11127457
捐赠科研通 3237969
什么是DOI,文献DOI怎么找? 1789411
邀请新用户注册赠送积分活动 871741
科研通“疑难数据库(出版商)”最低求助积分说明 803019