ArticleBiology direct2016
Systematic analysis of somatic mutations driving cancer: uncovering functional protein regions in disease development.
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.
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.
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.
Who cites it
10 citing papers in PubMed.
- Discovery and Characterization of Linear Motif Mediated Protein-Protein Complexes.Advances in experimental medicine and biology · 2024Article
- DisCanVis: Visualizing integrated structural and functional annotations to better understand the effect of cancer mutations located within disordered proteins.Protein science : a publication of the Protein Society · 2023Article
- A novel ferroptosis-related gene prognostic index for prognosis and response to immunotherapy in patients with prostate cancer.Frontiers in endocrinology · 2022Article
- Mutations of Intrinsically Disordered Protein Regions Can Drive Cancer but Lack Therapeutic Strategies.Biomolecules · 2021Article
- Distribution of disease-causing germline mutations in coiled-coils implies an important role of their N-terminal region.Scientific reports · 2020Article
- Ancient Evolutionary Origin of Intrinsically Disordered Cancer Risk Regions.Biomolecules · 2020Article
- Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy.Experimental dermatology · 2020Article
- DisProt: intrinsic protein disorder annotation in 2020.Nucleic acids research · 2020Article
- Prediction of protein disorder based on IUPred.Protein science : a publication of the Protein Society · 2018Article
- Comparison of algorithms for the detection of cancer drivers at subgene resolution.Nature methods · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.