Evidence map›Paper›PMID 28013235›Full record

ArticleBriefings in bioinformatics2018

Kinase impact assessment in the landscape of fusion genes that retain kinase domains: a pan-cancer study.

Pora Kim, Peilin Jia, Zhongming Zhao

Open access · bronzeAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2018. 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
0.4field-weighted citation impact, top 33% 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, 34 citations in OpenAlex.

  1. Article
  2. Genes · 2025
    Review
  3. CCDC6-RET fusion protein regulates Ras/MAPK signaling through the fusion- GRB2-SHC1 signal niche.Proceedings of the National Academy of Sciences of the United States of America · 2024
    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.

Pora KimCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Peilin JiaCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
The University of Texas Health Science Center at Houston · US

Funding

Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
Mapping the Genetic Architecture of Complex Disease via RNA-seq and GWAS DataR01LM011177 · NLM · VANDERBILT UNIVERSITY · PI ZHAO, ZHONGMING · 2012 to 2014
$1.0M
MicroRNA and Transcription Factor Co-regulation in CancerR21CA196508 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHAO, ZHONGMING · 2016 to 2017
$368k
NCI NIH HHS R21 CA196508NLM NIH HHS R01 LM011177NLM NIH HHS R01 LM012806
6 · The paper itself

Abstract

Assessing the impact of kinase in gene fusion is essential for both identifying driver fusion genes (FGs) and developing molecular targeted therapies. Kinase domain retention is a crucial factor in kinase fusion genes (KFGs), but such a systematic investigation has not been done yet. To this end, we analyzed kinase domain retention (KDR) status in chimeric protein sequences of 914 KFGs covering 312 kinases across 13 major cancer types. Based on 171 kinase domain-retained KFGs including 101 kinases, we studied their recurrence, kinase groups, fusion partners, exon-based expression depth, short DNA motifs around the break points and networks. Our results, such as more KDR than 5'-kinase fusion genes, combinatorial effects between 3'-KDR kinases and their 5'-partners and a signal transduction-specific DNA sequence motif in the break point intronic sequences, supported positive selection on 3'-kinase fusion genes in cancer. We introduced a degree-of-frequency (DoF) score to measure the possible number of KFGs of a kinase. Interestingly, kinases with high DoF scores tended to undergo strong gene expression alteration at the break points. Furthermore, our KDR gene fusion network analysis revealed six of the seven kinases with the highest DoF scores (ALK, BRAF, MET, NTRK1, NTRK3 and RET) were all observed in thyroid carcinoma. Finally, we summarized common features of 'effective' (highly recurrent) kinases in gene fusions such as expression alteration at break point, redundant usage in multiple cancer types and 3'-location tendency. Collectively, our findings are useful for prioritizing driver kinases and FGs and provided insights into KFGs' clinical implications.

Indexed as

Oncogene FusionHumansNeoplasmsOncogene Proteins, FusionProtein DomainsProtein-Tyrosine KinasesReceptor Protein-Tyrosine KinasesOncogene Proteins, FusionProtein-Tyrosine KinasesReceptor Protein-Tyrosine Kinases

Identifiers

PMID28013235
PMCPMC5952959
OpenAlexW2564216510

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.