Evidence map›Paper›PMID 24520089›Full record

ArticleMolecular & cellular proteomics : MCP2014

A targeted quantitative proteomics strategy for global kinome profiling of cancer cells and tissues.

Yongsheng Xiao, Lei Guo, Yinsheng Wang

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.9field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 53 citations in OpenAlex.

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  13. Molecular Targeted Therapy Approach to Musculoskeletal Tumors.Techniques in orthopaedics (Rockville, Md.) · 2018
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  19. Proteomic Findings in Melanoma.Journal of proteomics & bioinformatics · 2016
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Yongsheng XiaoDepartment of Chemistry and.
Lei Guo
Yinsheng Wang
University of California, Riverside · US

Funding

Chemistry and Biology of DNA CarboxyalkylationR01DK082779 · NIDDK · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI WANG, YINSHENG · 2009 to 2016
$3.0M
NIDDK NIH HHS R01 DK082779
6 · The paper itself

Abstract

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.

Indexed as

Adenosine TriphosphateCell Line, TumorChromatography, LiquidHeLa CellsHumansIsotope LabelingLung NeoplasmsMass SpectrometryMelanomaMolecular ProbesPhosphotransferasesProtein Kinase InhibitorsProteomicsReproducibility of ResultsAdenosine TriphosphateMolecular ProbesPhosphotransferasesProtein Kinase Inhibitors

Identifiers

PMID24520089
PMCPMC3977184
OpenAlexW2148691504

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.