Single‐cell combined with transcriptome sequencing to explore the molecular mechanism of cell communication in idiopathic pulmonary fibrosis

特发性肺纤维化 生物 转录组 列线图 免疫系统 基因 机制(生物学) HMGA2型 计算生物学 癌症研究 生物信息学 免疫学 医学 基因表达 遗传学 肿瘤科 小RNA 内科学 认识论 哲学
作者
Minggao Zhu,Yu-Hu Yi,Kui Jiang,Yongzhi Liang,Lijun Li,Feng Zhang,X. Long Zheng,Haiyan Yin
出处
期刊:Journal of Cellular and Molecular Medicine [Wiley]
卷期号:28 (12) 被引量:2
标识
DOI:10.1111/jcmm.18499
摘要

Abstract Idiopathic pulmonary fibrosis (IPF) is a common, chronic, and progressive lung disease that severely impacts human health and survival. However, the intricate molecular underpinnings of IPF remains elusive. This study aims to delve into the nuanced molecular interplay of cellular interactions in IPF, thereby laying the groundwork for innovative therapeutic approaches in the clinical field of IPF. Sophisticated bioinformatics methods were employed to identify crucial biomarkers essential for the progression of IPF. The GSE122960 single‐cell dataset was obtained from the Gene Expression Omnibus (GEO) compendium, and intercellular communication potentialities were scrutinized via CellChat. The random survival forest paradigm was established using the GSE70866 dataset. Quintessential genes were selected through Kaplan–Meier (KM) curves, while immune infiltration examinations, functional enrichment critiques and nomogram paradigms were inaugurated. Analysis of intercellular communication revealed an intimate potential connections between macrophages and various cell types, pinpointing five cardinal genes influencing the trajectory and prognosis of IPF. The nomogram paradigm, sculpted from these seminal genes, exhibits superior predictive prowess. Our research meticulously identified five critical genes, confirming their intimate association with the prognosis, immune infiltration and transcriptional governance of IPF. Interestingly, we discerned these genes' engagement with the EPITHELIAL_MESENCHYMAL_TRANSITION signalling pathway, which may enhance our understanding of the molecular complexity of IPF.
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
bittersugar发布了新的文献求助10
1秒前
Ava应助朴素从安采纳,获得10
1秒前
1秒前
1秒前
moon发布了新的文献求助20
2秒前
3秒前
3秒前
3秒前
5秒前
情怀应助超帅发夹采纳,获得10
5秒前
5秒前
风清扬发布了新的文献求助10
5秒前
飞逝的快乐时光完成签到 ,获得积分10
6秒前
Doublemorning关注了科研通微信公众号
6秒前
123完成签到,获得积分10
6秒前
哈哈一笑发布了新的文献求助10
6秒前
韩豆乐发布了新的文献求助10
6秒前
ding应助kinn采纳,获得20
7秒前
mao完成签到 ,获得积分10
7秒前
7秒前
邱琳完成签到,获得积分10
7秒前
1曲发布了新的文献求助20
8秒前
8秒前
猪皮恶人发布了新的文献求助10
8秒前
8秒前
Lainey发布了新的文献求助30
8秒前
整齐的伊完成签到,获得积分10
8秒前
lll发布了新的文献求助10
9秒前
小L同学完成签到,获得积分20
9秒前
9秒前
9秒前
Lazarus发布了新的文献求助10
11秒前
凡平完成签到,获得积分10
11秒前
gtrf发布了新的文献求助10
11秒前
秀丽的紫文完成签到,获得积分10
11秒前
宇心完成签到,获得积分10
11秒前
善学以致用应助且听风呤采纳,获得10
12秒前
九九发布了新的文献求助10
12秒前
任性孤容发布了新的文献求助10
13秒前
Lucas应助niuma采纳,获得30
13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
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Digital Twins of Advanced Materials Processing 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6041258
求助须知:如何正确求助?哪些是违规求助? 7780313
关于积分的说明 16233688
捐赠科研通 5187272
什么是DOI,文献DOI怎么找? 2775741
邀请新用户注册赠送积分活动 1758854
关于科研通互助平台的介绍 1642332