Gene Expression Signatures as Biomarkers of Tumour Hypoxia

缺氧(环境) 基因表达 基因 基因表达谱 生物标志物 医学 癌症研究 放射治疗 肿瘤缺氧 生物信息学 计算生物学 生物 内科学 遗传学 有机化学 化学 氧气
作者
Benjamin Harris,Alessandro Barberis,Catharine West,Francesca M. Buffa
出处
期刊:Clinical Oncology [Elsevier]
卷期号:27 (10): 547-560 被引量:105
标识
DOI:10.1016/j.clon.2015.07.004
摘要

Hypoxia is a feature of most solid tumours and is associated with a poor prognosis. The hypoxic environment can reduce the efficacy of radiotherapy and some chemotherapeutics, and has been investigated extensively as a therapeutic target. The clinical use of hypoxia-targeting treatment will benefit from the development of a biomarker to assess tumour hypoxia. There are several possible techniques that measure either the level of oxygen or the tumour molecular response to hypoxia. The latter includes gene expression profiling, which measures the transcriptional response of a tumour to its hypoxic microenvironment. A systematic review identified 32 published hypoxia gene expression signatures. The methods used for their derivation varied, but are broadly classified as: (i) identifying genes with significantly higher or lower expression in cancer cells cultured under hypoxic versus normoxic conditions; (ii) using either previously characterised hypoxia-regulated genes/biomarkers to define hypoxic tumours and then identifying other genes that are over- or under-expressed in the hypoxic tumours. Both generated gene signatures useful in furthering our understanding of hypoxia biology. However, signatures derived using the second method seem to be superior in terms of providing prognostic information. Here we summarise all 32 published hypoxia signatures, discuss their commonalities and differences, and highlight their strengths and limitations. This review also highlights the importance of reproducibility and gene annotation, which must be accounted for to transfer signatures robustly for clinical application as biomarkers.
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
当时只道是寻常完成签到,获得积分10
刚刚
北风完成签到,获得积分10
刚刚
李健应助温暖的定格采纳,获得10
刚刚
1秒前
酷波er应助义气代梅采纳,获得10
1秒前
1秒前
李健应助顺顺采纳,获得10
1秒前
开心的大娘完成签到,获得积分10
1秒前
牛牛完成签到,获得积分10
2秒前
下载文章即可完成签到,获得积分10
2秒前
秋海棠完成签到,获得积分10
2秒前
yifan92完成签到,获得积分10
3秒前
liam完成签到,获得积分10
4秒前
haliw完成签到,获得积分10
4秒前
志豪发布了新的文献求助10
4秒前
关山完成签到,获得积分10
4秒前
5秒前
牛不可完成签到,获得积分10
5秒前
13633501455完成签到,获得积分10
5秒前
wsg完成签到,获得积分10
5秒前
奥斯卡发布了新的文献求助10
6秒前
whisper完成签到,获得积分10
6秒前
勤奋帅帅完成签到,获得积分10
7秒前
paopao发布了新的文献求助10
8秒前
panpan完成签到 ,获得积分10
8秒前
李L完成签到,获得积分10
8秒前
迅速思萱完成签到,获得积分10
8秒前
sunny心晴完成签到 ,获得积分10
8秒前
9秒前
春锅锅完成签到,获得积分10
9秒前
9秒前
9秒前
三三四完成签到,获得积分10
11秒前
研友_LN7x6n完成签到,获得积分10
11秒前
popo完成签到,获得积分10
11秒前
11秒前
小林太郎应助Wendygogogo采纳,获得30
12秒前
天天快乐应助tesla采纳,获得10
12秒前
三三完成签到,获得积分10
12秒前
早早发论文完成签到,获得积分10
12秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 800
Conference Record, IAS Annual Meeting 1977 610
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
白土三平研究 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3556011
求助须知:如何正确求助?哪些是违规求助? 3131566
关于积分的说明 9392042
捐赠科研通 2831431
什么是DOI,文献DOI怎么找? 1556440
邀请新用户注册赠送积分活动 726584
科研通“疑难数据库(出版商)”最低求助积分说明 715910