Tumor-derived Endothelial Cell: Important Etiological Factors in Endometriosis

子宫内膜异位症 血管生成 癌症研究 新生血管 细胞 生物 医学 内科学 遗传学
作者
Yishan Dong,Ming Zhang,Jun Ouyang,Wenbai Zhou,Bin Yu
出处
期刊:Archives of Medical Research [Elsevier BV]
卷期号:54 (7): 102891-102891 被引量:2
标识
DOI:10.1016/j.arcmed.2023.102891
摘要

Endometriosis (EMS) is a very complex disease with high heterogeneity. Recently, single-cell RNA sequencing (scRNA-seq) has been applied to comprehensively characterize cellular heterogeneity. Here, we built a new transcriptomic profile of EMS cellular signatures. Three women diagnosed with endometriosis were recruited. Their fresh eutopic endometrium (EM) and ectopic endometrium (EC) tissues were sampled during surgery. ScRNA-seq was performed on 10x Genomics Chromium. Thirty cell clusters were identified as more than ten different cell types using cell type-specific marker genes. Re-clustering analysis revealed five subtypes of endothelial cells (ECs). Compared to EM, the proportion of tumor-derived ECs (IGFBP3+) was significantly increased in EC (43.8 vs. 16.0%). 63 differentially expressed genes (DEGs) between tumor-derived ECs and normal ECs were enriched in “angiogenesis”, such as EFNB2, DLL4, and THSD7A. Subsequently, 114 retrospective EMS cases were included in clinical validation studies of EFNB2. It was co-expressed with PECAM1 and IGFBP3 and significantly increased in EC. Meanwhile, the recurrence rate of women with EFNB2++ expression was significantly higher than that of EFNB2+ cases (p <0.05). The significant increase in tumor-derived ECs characterized by neovascularization may be an important pathological feature of EMS. In addition, EFNB2 plays an important role and is closely related to the recurrence of EMS.
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
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
刚刚
橙橙发布了新的文献求助10
刚刚
NexusExplorer应助研友_LJGmvn采纳,获得10
刚刚
NIU完成签到,获得积分10
1秒前
1秒前
乔滴滴发布了新的文献求助10
1秒前
GDROSE发布了新的文献求助10
1秒前
Jasper应助淡淡念柏采纳,获得20
2秒前
马汉仓发布了新的文献求助10
2秒前
刘广进完成签到 ,获得积分10
3秒前
3秒前
3秒前
3秒前
4秒前
灼灼完成签到 ,获得积分10
4秒前
刀剑完成签到,获得积分20
4秒前
大漠谣发布了新的文献求助10
4秒前
心灵美砖头完成签到,获得积分0
5秒前
6秒前
123发布了新的文献求助10
6秒前
6秒前
xinyeeast发布了新的文献求助10
6秒前
6秒前
刘广进关注了科研通微信公众号
6秒前
刀剑发布了新的文献求助10
7秒前
v0id应助CaseyMelkus采纳,获得10
7秒前
8秒前
11发布了新的文献求助10
8秒前
8秒前
研友_VZG7GZ应助谢西瓜采纳,获得10
8秒前
8秒前
9秒前
科研通AI6.4应助大力迎曼采纳,获得10
9秒前
9秒前
9秒前
社会王完成签到,获得积分10
9秒前
含蓄向雁完成签到,获得积分10
9秒前
小肉包脸完成签到 ,获得积分10
10秒前
10秒前
10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
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7767525
求助须知:如何正确求助?哪些是违规求助? 9311083
关于积分的说明 20321775
捐赠科研通 7352505
什么是DOI,文献DOI怎么找? 3315412
关于科研通互助平台的介绍 2464693
邀请新用户注册赠送积分活动 2330053