Evidence map›Paper›PMID 27150584›Full record

ArticleBiology direct2016

Systematic analysis of somatic mutations driving cancer: uncovering functional protein regions in disease development.

Bálint Mészáros, András Zeke, Attila Reményi, István Simon, Zsuzsanna Dosztányi

Abstract read
In one paragraph

Article in Biology direct, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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  9. Prediction of protein disorder based on IUPred.Protein science : a publication of the Protein Society · 2018
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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

5 authors.

Bálint MészárosInstitute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, 2 Magyar Tudósok krt, Budapest, H-1117, Hungary. meszaros.balint@ttk.mta.hu.
András ZekeLendület Protein Interaction Group, Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, 2 Magyar Tudósok krt, Budapest, H-1117, Hungary.
Attila ReményiLendület Protein Interaction Group, Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, 2 Magyar Tudósok krt, Budapest, H-1117, Hungary.
István SimonInstitute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, 2 Magyar Tudósok krt, Budapest, H-1117, Hungary.
Zsuzsanna DosztányiMTA-ELTE Lendület Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, 11/c Pázmány Péter stny, Budapest, H-1117, Hungary. dosztanyi@caesar.elte.hu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent advances in sequencing technologies enable the large-scale identification of genes that are affected by various genetic alterations in cancer. However, understanding tumor development requires insights into how these changes cause altered protein function and impaired network regulation in general and/or in specific cancer types.

resultsIn this work we present a novel method called iSiMPRe that identifies regions that are significantly enriched in somatic mutations and short in-frame insertions or deletions (indels). Applying this unbiased method to the complete human proteome, by using data enriched through various cancer genome projects, we identified around 500 protein regions which could be linked to one or more of 27 distinct cancer types. These regions covered the majority of known cancer genes, surprisingly even tumor suppressors. Additionally, iSiMPRe also identified novel genes and regions that have not yet been associated with cancer.

conclusionsWhile local somatic mutations correspond to only a subset of genetic variations that can lead to cancer, our systematic analyses revealed that they represent an accompanying feature of most cancer driver genes regardless of the primary mechanism by which they are perturbed during tumorigenesis. These results indicate that the accumulation of local somatic mutations can be used to pinpoint genes responsible for cancer formation and can also help to understand the effect of cancer mutations at the level of functional modules in a broad range of cancer driver genes. REVIEWERS: This article was reviewed by Sándor Pongor, Michael Gromiha and Zoltán Gáspári.

Indexed as

GenomicsMutationHumansNeoplasmsCancerDeletionDriver geneInsertionMissense mutationProtein functional modulesSomatic mutation

Identifiers

PMID27150584
PMCPMC4858844

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Registered trials

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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.