Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment

生物 转录组 计算生物学 人类遗传学 钥匙(锁) 进化生物学 遗传学 基因 基因表达 生态学
作者
Boxi Kang,J. Camps,Biao Fan,Hongpeng Jiang,Mahmoud M. Ibrahim,Xueda Hu,Shishang Qin,Dennis Kirchhoff,Derek Y. Chiang,Shan Wang,Yingjiang Ye,Zhanlong Shen,Zhaode Bu,Zemin Zhang,Helge G. Roider
出处
期刊:Genome Biology [Springer Nature]
卷期号:23 (1) 被引量:52
标识
DOI:10.1186/s13059-022-02828-2
摘要

Abstract Background The tumor microenvironment (TME) has been shown to strongly influence treatment outcome for cancer patients in various indications and to influence the overall survival. However, the cells forming the TME in gastric cancer have not been extensively characterized. Results We combine bulk and single-cell RNA sequencing from tumors and matched normal tissue of 24 treatment-naïve GC patients to better understand which cell types and transcriptional programs are associated with malignant transformation of the stomach. Clustering 96,623 cells of non-epithelial origin reveals 81 well-defined TME cell types. We find that activated fibroblasts and endothelial cells are most prominently overrepresented in tumors. Intercellular network reconstruction and survival analysis of an independent cohort imply the importance of these cell types together with immunosuppressive myeloid cell subsets and regulatory T cells in establishing an immunosuppressive microenvironment that correlates with worsened prognosis and lack of response in anti-PD1-treated patients. In contrast, we find a subset of IFNγ activated T cells and HLA-II expressing macrophages that are linked to treatment response and increased overall survival. Conclusions Our gastric cancer single-cell TME compendium together with the matched bulk transcriptome data provides a unique resource for the identification of new potential biomarkers for patient stratification. This study helps further to elucidate the mechanism of gastric cancer and provides insights for therapy.

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
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
顾矜应助爱撒娇的西装采纳,获得10
3秒前
薄荷心完成签到 ,获得积分10
4秒前
Rita发布了新的文献求助10
5秒前
光亮的天真完成签到 ,获得积分10
7秒前
刘丰发布了新的文献求助10
9秒前
吕嫣娆完成签到 ,获得积分10
9秒前
hala安胖胖完成签到 ,获得积分10
11秒前
13秒前
15秒前
Max7完成签到,获得积分10
15秒前
zzy完成签到,获得积分10
17秒前
18秒前
elodie发布了新的文献求助30
18秒前
oqura完成签到 ,获得积分10
19秒前
lchenbio发布了新的文献求助10
20秒前
21秒前
Remon发布了新的文献求助10
23秒前
24秒前
25秒前
ALITAOZI发布了新的文献求助10
25秒前
肥波爱吃鱼完成签到,获得积分10
28秒前
yuuki发布了新的文献求助10
29秒前
lchenbio完成签到,获得积分10
29秒前
殁177发布了新的文献求助10
30秒前
抹茶肥肠完成签到,获得积分10
36秒前
elodie完成签到,获得积分10
36秒前
阡陌完成签到,获得积分10
38秒前
百川完成签到,获得积分10
38秒前
FashionBoy应助CALCULATING采纳,获得10
41秒前
王富贵完成签到,获得积分10
47秒前
123发布了新的文献求助10
49秒前
隐形曼青应助shangtaomao采纳,获得10
54秒前
57秒前
江海完成签到 ,获得积分10
59秒前
1分钟前
demo完成签到,获得积分10
1分钟前
糖_发布了新的文献求助10
1分钟前
王子杰完成签到,获得积分20
1分钟前
1分钟前
123完成签到,获得积分10
1分钟前
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
Les Mantodea de guyane 2500
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Competency Based Human Resource Management 500
How to Develop Robust Scale-up Strategies for Complex Injectable Dosage Forms 450
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5863892
求助须知:如何正确求助?哪些是违规求助? 6396113
关于积分的说明 15649873
捐赠科研通 4978032
什么是DOI,文献DOI怎么找? 2685236
邀请新用户注册赠送积分活动 1628313
关于科研通互助平台的介绍 1586018