Evidence map›Paper›PMID 27175787›Full record

ArticleGenome medicine2016

Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer.

Soumil Narayan, Gary D Bader, Jüri Reimand

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
4.2field-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

33 citing papers in PubMed, 54 citations in OpenAlex.

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  6. ER-associated degradation ligase HRD1 links ER stress to DNA damage repair by modulating the activity of DNA-PKcs.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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.

Soumil NarayanThe Donnelly Centre, University of Toronto, Toronto, Canada.
Gary D BaderThe Donnelly Centre, University of Toronto, Toronto, Canada. Gary.Bader@utoronto.ca.
Jüri ReimandThe Donnelly Centre, University of Toronto, Toronto, Canada. Juri.Reimand@utoronto.ca.
University of Toronto · CA

Funding

TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

backgroundDiscovery of cancer drivers is a major goal of cancer research. Driver genes and pathways are often predicted using mutation frequency, assuming that statistically significant recurrence of specific somatic mutations across independent samples indicates their importance in cancer. However, many mutations, including known cancer drivers, are not observed at high frequency. Fortunately, abundant information is available about functional "active sites" in proteins that can be integrated with mutations to predict cancer driver genes, even based on low frequency mutations. Further, considering active site information predicts detailed biochemical mechanisms impacted by the mutations. Post-translational modifications (PTMs) are active sites that are regulatory switches in proteins and pathways. We analyzed acetylation and ubiquitination, two important PTM types often involved in chromatin organization and protein degradation, to find proteins that are significantly affected by tumor somatic mutations.

methodsWe performed computational analyses of acetylation and ubiquitination sites in a pan-cancer dataset of 3200 tumor samples from The Cancer Genome Atlas (TCGA). These analyses were targeted at different levels of biological organization including individual genes, pathway annotated gene sets, and protein-protein interaction networks.

resultsAcetylation and ubiquitination site mutations are enriched in cancer with significantly stronger evolutionary conservation and accumulation in protein domains. Gene-focused analysis with the ActiveDriver method reveals significant co-occurrences of acetylation and ubiquitination PTMs and mutation hotspots in known oncoproteins (TP53, AKT1, IDH1) and highlights candidate cancer driver genes with PTM-related mechanisms (e.g. several histone proteins and the splicing factor SF3B1). Pathway analysis shows that PTM mutations in acetylation and ubiquitination sites accumulate in cancer-related processes such as cell cycle, apoptosis, chromatin regulation, and metabolism. Integrated mutation analysis of clinical information and protein interaction networks suggests that many PTM-specific mutations associate with decreased patient survival.

conclusionsMutation analysis of acetylation and ubiquitination PTM sites reveals their importance in cancer. As PTM networks are increasingly mapped and related enzymes are often druggable, deeper investigation of specific associated mutations may lead to the discovery of treatment-relevant cellular mechanisms.

Indexed as

Mutation RateProtein Processing, Post-TranslationalAcetylationComputational BiologyDatabases, GeneticGene Regulatory NetworksGenetic Predisposition to DiseaseHumansMutationNeoplasm ProteinsNeoplasmsProtein Interaction MapsSurvival AnalysisUbiquitinationNeoplasm Proteins

Identifiers

PMID27175787
PMCPMC4864925
OpenAlexW2352710988

What OpenQuestion holds

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LicenceCC BY
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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.