Plasma RNA sequencing of extracellular RNAs reveals potential biomarkers for non-small cell lung cancer

肺癌 癌变 核糖核酸 小桶 细胞外 生物 癌症 基因 生物标志物 基因表达 癌症研究 血浆 基因本体论 计算生物学 分子生物学 肿瘤科 医学 内科学 遗传学 生物化学
作者
Liujing Wang,Jun Wang,Erteng Jia,Zhiyu Liu,Qinyu Ge,Xiangwei Zhao
出处
期刊:Clinical Biochemistry [Elsevier]
卷期号:83: 65-73 被引量:11
标识
DOI:10.1016/j.clinbiochem.2020.06.004
摘要

Lung cancer is one of the most common malignancies, and it has extremely high incidence and mortality rates. Although there have been many studies focused on lung cancer biomarkers, few have reported the extracellular RNA profiles of lung cancer. In this study, we used RNA-seq technology to analyze extracellular RNAs in low volume peripheral blood plasma; we compared the differentially expressed genes from the plasma of non-small cell lung cancer (NSCLC) patients with that of healthy controls. We used RNA-seq technology and bioinformatics to analyze the extracellular RNA (exRNA) sequences of 12 human plasma samples (500 μl per sample), 6 from NSCLC patients and 6 from healthy controls. Subsequently, we used gene ontology (GO) enrichment, KEGG analysis and coexpression experiments to compare the differentially expressed genes (DEGs) and identify tumor biomarkers that were highly correlated with NSCLC. These DEGs were further verified by quantitative PCR. Approximately 20 million clean reads were produced for each plasma sample; 50–80% of the reads aligned to the human references, and hundreds of thousands of reads were counted in each plasma sample. In addition, a total of 640 genes (368 upregulated and 272 downregulated) were differentially expressed between NSCLC plasma and normal plasma. Further, we identified 7 key DEGs that are highly correlated with lung tumorigenesis: COX1, COX2, COX3, ND1, ND2, ND4L, and ATP6. exRNA-seq from a small amount (400–500 μl) of plasma opens new possibilities for exploring lung cancer biomarkers in the plasma.
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
大幅提高文件上传限制,最高150M (2024-4-1)

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
1秒前
科研通AI2S应助科研通管家采纳,获得10
2秒前
隐形曼青应助科研通管家采纳,获得10
2秒前
完美世界应助科研通管家采纳,获得10
2秒前
小二郎应助科研通管家采纳,获得10
2秒前
礼礼应助科研通管家采纳,获得30
2秒前
上官若男应助科研通管家采纳,获得10
2秒前
wanci应助科研通管家采纳,获得10
2秒前
打打应助科研通管家采纳,获得10
2秒前
乐乐应助科研通管家采纳,获得10
2秒前
852应助科研通管家采纳,获得10
2秒前
苹果柜子应助科研通管家采纳,获得20
3秒前
科研通AI2S应助科研通管家采纳,获得10
3秒前
3秒前
ZYQ发布了新的文献求助10
3秒前
4秒前
zqxu完成签到,获得积分10
5秒前
6秒前
凹凸先森应助OCTOPUS采纳,获得10
6秒前
险胜应助OCTOPUS采纳,获得10
6秒前
明明完成签到,获得积分10
7秒前
NA发布了新的文献求助10
11秒前
11秒前
山橘月发布了新的文献求助10
11秒前
猪猪hero发布了新的文献求助20
15秒前
Rforoeverad发布了新的文献求助30
16秒前
斯文的茹嫣完成签到,获得积分10
16秒前
DXiao完成签到,获得积分10
16秒前
16秒前
无私的电灯胆完成签到,获得积分10
17秒前
香蕉觅云应助苗条寒梦采纳,获得10
17秒前
Monica发布了新的文献求助10
17秒前
19秒前
StandardR发布了新的文献求助10
19秒前
笑笑发布了新的文献求助30
20秒前
遇见飞儿完成签到,获得积分10
20秒前
20秒前
可爱的石头完成签到,获得积分10
23秒前
书竹完成签到,获得积分10
23秒前
Yacon发布了新的文献求助10
25秒前
高分求助中
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger Heßler, Claudia, Rud 1000
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 1000
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Autoregulatory progressive resistance exercise: linear versus a velocity-based flexible model 500
Spatial Political Economy: Uneven Development and the Production of Nature in Chile 400
Research on managing groups and teams 300
热门求助领域 (近24小时)
化学 医学 生物 材料科学 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 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3329637
求助须知:如何正确求助?哪些是违规求助? 2959215
关于积分的说明 8594828
捐赠科研通 2637692
什么是DOI,文献DOI怎么找? 1443719
科研通“疑难数据库(出版商)”最低求助积分说明 668843
邀请新用户注册赠送积分活动 656278