Evidence map›Paper›PMID 21151926›Full record

ArticlePloS one2010

Analysis of kinase gene expression patterns across 5681 human tissue samples reveals functional genomic taxonomy of the kinome.

Sami Kilpinen, Kalle Ojala, Olli Kallioniemi

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

24 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
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  6. CFI-402257, a TTK inhibitor, effectively suppresses hepatocellular carcinoma.Proceedings of the National Academy of Sciences of the United States of America · 2022
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  12. Nuclear Receptor Corepressor 1 Expression and Output Declines with Prostate Cancer Progression.Clinical cancer research : an official journal of the American Association for Cancer Research · 2016
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  15. Article
  16. Article
  17. Article
  18. INPP4B suppresses prostate cancer cell invasion.Cell communication and signaling : CCS · 2014
    Article
  19. Review
  20. Article
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 2 institutions in 1 country.

Sami KilpinenInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. sami.k.kilpinen@helsinki.fi
Kalle Ojala
Olli Kallioniemi
University of Helsinki · FIInstitute for Molecular Medicine Finland · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kinases play key roles in cell signaling and represent major targets for drug development, but the regulation of their activation and their associations with health and disease have not been systematically analyzed. Here, we carried out a bioinformatic analysis of the expression levels of 459 human kinase genes in 5681 samples consisting of 44 healthy and 55 malignant human tissues. Defining the tissues where the kinase genes were transcriptionally active led to a functional genomic taxonomy of the kinome and a classification of human tissues and disease types based on the similarity of their kinome gene expression. The co-expression network around each of the kinase genes was defined in order to determine the functional context, i.e. the biological processes that were active in the cells and tissues where the kinase gene was expressed. Strong associations for individual kinases were found for mitosis (69 genes, including AURKA and BUB1), cell cycle control (73 genes, including PLK1 and AURKB), DNA repair (49 genes, including CHEK1 and ATR), immune response (72 genes, including MATK), neuronal (131 genes, including PRKCE) and muscular (72 genes, including MYLK2) functions. We then analyzed which kinase genes gain or lose transcriptional activity in the development of prostate and lung cancers and elucidated the functional associations of individual cancer associated kinase genes. In summary, we report here a systematic classification of kinases based on the bioinformatic analysis of their expression in human tissues and diseases, as well as grouping of tissues and tumor types according to the similarity of their kinome transcription.

Indexed as

Gene Expression ProfilingGene Expression Regulation, EnzymologicCell CycleComputational BiologyDatabases, GeneticErb-b2 Receptor Tyrosine KinasesGene Expression RegulationGene Expression Regulation, NeoplasticGenome, HumanGenomicsHumansNeoplasmsSignal TransductionTranscription, GeneticErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID21151926
PMCPMC2997066
OpenAlexW2080326459

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.