Analysis of immunogenic cell death in atherosclerosis based on scRNA-seq and bulk RNA-seq data

小桶 RNA序列 药物数据库 基因表达谱 计算生物学 转录组 生物 基因 基因表达 遗传学 药品 药理学
作者
Zemin Tian,Xinyang Li,Delong Jiang
出处
期刊:International Immunopharmacology [Elsevier BV]
卷期号:119: 110130-110130 被引量:8
标识
DOI:10.1016/j.intimp.2023.110130
摘要

Regulated cell death plays a very important role in atherosclerosis (AS). Despite a large number of studies, there is a lack of literature on immunogenic cell death (ICD) in AS. Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define involved cells and determine their transcriptomic characteristics. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, CIBERSORT, ESTIMATE and ssGSEA (Gene Set Enrichment Analysis), consensus clustering analysis, random forest (RF), Decision Curve Analysis (DCA), and the Drug-Gene Interaction and DrugBank databases were applied for bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO). mDCs and CTLs correlated obviously with AS occurrence and development (k2(mDCs) = 48.333, P < 0.001; k2(CTL) = 130.56, P < 0.001). In total, 21 differentially expressed genes were obtained for the bulk transcriptome; KEGG enrichment analysis results were similar to those for differentially expressed genes in endothelial cells. Eleven genes with a gene importance score > 1.5 were obtained in the training set and validated in the test set, resulting in 8 differentially expressed genes for ICD. A model to predict occurrence of AS and 56 drugs that may be used to treat AS were obtained with these 8 genes. Immunogenic cell death occurs mainly in endothelial cells in AS. ICD maintains chronic inflammation in AS and plays a crucial role in its occurrence and development. ICD related genes may become drug-targeted genes for AS treatment.
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
豆⑧发布了新的文献求助10
刚刚
苗条元柏完成签到,获得积分10
刚刚
惠_____发布了新的文献求助10
刚刚
可靠幼旋完成签到,获得积分10
刚刚
超级无敌幸运星完成签到,获得积分10
1秒前
Daisy完成签到,获得积分10
1秒前
cc发布了新的文献求助10
1秒前
2秒前
yyyyds完成签到 ,获得积分10
2秒前
核桃应助潇湘雪月采纳,获得60
2秒前
Nole应助dg_fisher采纳,获得10
2秒前
好名字完成签到,获得积分10
3秒前
1111发布了新的文献求助10
3秒前
tamo发布了新的文献求助10
3秒前
无尘泪发布了新的文献求助10
3秒前
丑角苏完成签到,获得积分10
3秒前
美满诗槐完成签到,获得积分10
4秒前
wys2493完成签到,获得积分10
4秒前
科研人完成签到,获得积分10
4秒前
专注代芙应助嘻嘻采纳,获得10
4秒前
苹果枣豆完成签到,获得积分10
5秒前
5秒前
醉熏的朋友完成签到 ,获得积分10
5秒前
学渣一枚完成签到,获得积分10
5秒前
小红发布了新的文献求助10
5秒前
6秒前
酒儿完成签到 ,获得积分10
6秒前
英俊的铭应助木南采纳,获得10
6秒前
合适的凡完成签到,获得积分10
7秒前
侯小然发布了新的文献求助10
7秒前
1111完成签到,获得积分10
7秒前
Ying完成签到,获得积分10
7秒前
唱拉拉完成签到,获得积分10
7秒前
cc完成签到,获得积分10
8秒前
ZHUJIANJIAN完成签到,获得积分20
8秒前
8秒前
反复回响发布了新的文献求助30
9秒前
健壮书包发布了新的文献求助10
9秒前
10秒前
ccboom完成签到,获得积分10
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
Römisch-Germanische Forschungen 1000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7606942
求助须知:如何正确求助?哪些是违规求助? 9182850
关于积分的说明 19668159
捐赠科研通 7181222
什么是DOI,文献DOI怎么找? 3269710
关于科研通互助平台的介绍 2433567
邀请新用户注册赠送积分活动 2263977