An absolute human stemness index associated with oncogenic dedifferentiation

索引(排版) 增殖指数 生物 癌症研究 癌症 干细胞 遗传学 免疫组织化学 计算机科学 免疫学 万维网
作者
Hailong Zheng,Kai Song,Yelin Fu,Tianyi You,Jing Yang,Wenbing Guo,Kai Wang,Liangliang Jin,Yunyan Gu,Lishuang Qi,Wenyuan Zhao
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:22 (2): 2151-2160 被引量:21
标识
DOI:10.1093/bib/bbz174
摘要

Abstract The progression of cancer is accompanied by the acquisition of stemness features. Many stemness evaluation methods based on transcriptional profiles have been presented to reveal the relationship between stemness and cancer. However, instead of absolute stemness index values—the values with certain range—these methods gave the values without range, which makes them unable to intuitively evaluate the stemness. Besides, these indices were based on the absolute expression values of genes, which were found to be seriously influenced by batch effects and the composition of samples in the dataset. Recently, we have showed that the signatures based on the relative expression orderings (REOs) of gene pairs within a sample were highly robust against these factors, which makes that the REO-based signatures have been stably applied in the evaluations of the continuous scores with certain range. Here, we provided an absolute REO-based stemness index to evaluate the stemness. We found that this stemness index had higher correlation with the culture time of the differentiated stem cells than the previous stemness index. When applied to the cancer and normal tissue samples, the stemness index showed its significant difference between cancers and normal tissues and its ability to reveal the intratumor heterogeneity at stemness level. Importantly, higher stemness index was associated with poorer prognosis and greater oncogenic dedifferentiation reflected by histological grade. All results showed the capability of the REO-based stemness index to assist the assignment of tumor grade and its potential therapeutic and diagnostic implications.
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
2秒前
zzzyyyuuu完成签到 ,获得积分10
6秒前
脑洞疼应助naturehome采纳,获得10
7秒前
7秒前
caisongliang发布了新的文献求助10
7秒前
8秒前
Ywl关注了科研通微信公众号
8秒前
9秒前
122发布了新的文献求助10
12秒前
河马完成签到,获得积分10
12秒前
林林完成签到,获得积分10
14秒前
16秒前
沉默凌雪关注了科研通微信公众号
17秒前
dajiejie完成签到 ,获得积分10
17秒前
彼得大帝发布了新的文献求助10
17秒前
万能图书馆应助122采纳,获得10
18秒前
19秒前
灯火完成签到,获得积分10
19秒前
小松松发布了新的文献求助10
22秒前
日月完成签到,获得积分10
23秒前
大宝完成签到,获得积分10
24秒前
25秒前
杨茉发布了新的文献求助10
25秒前
26秒前
maya完成签到,获得积分10
27秒前
12发布了新的文献求助10
28秒前
28秒前
29秒前
仁爱的尔蓝完成签到 ,获得积分10
29秒前
终陌完成签到,获得积分10
31秒前
33秒前
盛夏完成签到,获得积分10
34秒前
终陌发布了新的文献求助10
34秒前
周雪妍发布了新的文献求助10
35秒前
naturehome发布了新的文献求助10
35秒前
36秒前
36秒前
赫连人杰完成签到,获得积分10
41秒前
JRod发布了新的文献求助10
41秒前
YOUNG-M发布了新的文献求助10
42秒前
高分求助中
请在求助之前详细阅读求助说明!!!! 20000
One Man Talking: Selected Essays of Shao Xunmei, 1929–1939 1000
Yuwu Song, Biographical Dictionary of the People's Republic of China 700
[Lambert-Eaton syndrome without calcium channel autoantibodies] 520
Pressing the Fight: Print, Propaganda, and the Cold War 500
Bernd Ziesemer - Maos deutscher Topagent: Wie China die Bundesrepublik eroberte 500
The Three Stars Each: The Astrolabes and Related Texts 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2470623
求助须知:如何正确求助?哪些是违规求助? 2137423
关于积分的说明 5446309
捐赠科研通 1861574
什么是DOI,文献DOI怎么找? 925783
版权声明 562721
科研通“疑难数据库(出版商)”最低求助积分说明 495235