已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues

作者
Yongsheng Xiao,Lei Guo,Yinsheng Wang
出处
期刊:Molecular & Cellular Proteomics [Elsevier BV]
卷期号:13 (4): 1065-1075 被引量:54
标识
DOI:10.1074/mcp.m113.036905
摘要

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy.

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
刚刚
1秒前
完美世界应助来时冬至采纳,获得10
1秒前
钟钟钟钟发布了新的文献求助10
3秒前
2hi完成签到,获得积分10
5秒前
无语的巨人完成签到 ,获得积分10
6秒前
小yang完成签到,获得积分10
7秒前
7秒前
7秒前
西瓜大王发布了新的文献求助10
13秒前
111发布了新的文献求助20
13秒前
山东人在南京完成签到 ,获得积分10
14秒前
一只大嵩鼠完成签到 ,获得积分10
17秒前
渔渔完成签到 ,获得积分10
19秒前
19秒前
19秒前
ming2026应助科研通管家采纳,获得10
20秒前
21秒前
23秒前
搜集达人应助wztin采纳,获得10
23秒前
23秒前
qq发布了新的文献求助10
25秒前
25秒前
Nole应助gjww采纳,获得10
26秒前
红豆完成签到 ,获得积分10
26秒前
小蘑菇应助如意的洋葱采纳,获得10
27秒前
等意送汝发布了新的文献求助10
27秒前
dearkay发布了新的文献求助10
27秒前
从容的乐松完成签到,获得积分10
29秒前
30秒前
Alice发布了新的文献求助10
32秒前
沐风完成签到,获得积分20
32秒前
斯文败类应助等意送汝采纳,获得10
32秒前
34秒前
35秒前
粗心的烨伟完成签到,获得积分10
35秒前
假装有昵称完成签到 ,获得积分10
37秒前
日且完成签到,获得积分10
37秒前
38秒前
wztin发布了新的文献求助10
39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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7633181
求助须知:如何正确求助?哪些是违规求助? 9207513
关于积分的说明 19747471
捐赠科研通 7202092
什么是DOI,文献DOI怎么找? 3274916
关于科研通互助平台的介绍 2436834
邀请新用户注册赠送积分活动 2271747