Evidence map›Paper›PMID 28743916›Full record

ArticleScientific reports2017

Analysis of somatic mutations across the kinome reveals loss-of-function mutations in multiple cancer types.

Runjun D Kumar, Ron Bose

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Therapeutic advances of targeting receptor tyrosine kinases in cancer.Signal transduction and targeted therapy · 2024
    Review
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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

2 authors.

Runjun D KumarDivision of Oncology, Department of Medicine, Washington University School of Medicine, 660S Euclid Ave, St. Louis, MO, 63110, USA.
Ron BoseDivision of Oncology, Department of Medicine, Washington University School of Medicine, 660S Euclid Ave, St. Louis, MO, 63110, USA. rbose@dom.wustl.edu.

Funding

CIHR DFS-134967
6 · The paper itself

Abstract

In this study we use somatic cancer mutations to identify important functional residues within sets of related genes. We focus on protein kinases, a superfamily of phosphotransferases that share homologous sequences and structural motifs and have many connections to cancer. We develop several statistical tests for identifying Significantly Mutated Positions (SMPs), which are positions in an alignment with mutations that show signs of selection. We apply our methods to 21,917 mutations that map to the alignment of human kinases and identify 23 SMPs. SMPs occur throughout the alignment, with many in the important A-loop region, and others spread between the N and C lobes of the kinase domain. Since mutations are pooled across the superfamily, these positions may be important to many protein kinases. We select eleven mutations from these positions for functional validation. All eleven mutations cause a reduction or loss of function in the affected kinase. The tested mutations are from four genes, including two tumor suppressors (TGFBR1 and CHEK2) and two oncogenes (KDR and ERBB2). They also represent multiple cancer types, and include both recurrent and non-recurrent events. Many of these mutations warrant further investigation as potential cancer drivers.

Indexed as

Loss of Function MutationAnimalsCheckpoint Kinase 2Databases, GeneticErb-b2 Receptor Tyrosine KinasesHumansMiceNeoplasmsNIH 3T3 CellsPhosphotransferasesReceptor, Transforming Growth Factor-beta Type IReproducibility of ResultsVascular Endothelial Growth Factor Receptor-2Checkpoint Kinase 2CHEK2 protein, humanERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesKDR protein, humanPhosphotransferasesReceptor, Transforming Growth Factor-beta Type ITGFBR1 protein, humanVascular Endothelial Growth Factor Receptor-2

Identifiers

PMID28743916
PMCPMC5527104

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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.