The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Predicting the functional impact of protein mutations: application to cancer genomics
Open accessAbstract
As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations ('drivers'). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.
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Cites
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Comprehensive genomic characterization defines human glioblastoma genes and core pathways
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Cancer-associated IDH1 mutations produce 2-hydroxyglutarate
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Somatic mutations affect key pathways in lung adenocarcinoma
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“Therefore we tested the FI score on data obtained from experimental studies of the functional impact of TP53 mutations as collected in the IARC TP53 database (55).”
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Exomic Sequencing Identifies PALB2 as a Pancreatic Cancer Susceptibility Gene
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Cited by
Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0095 · Cited by 17,455
Self-citationIntegrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Gao, J., Aksoy, B. A., Dogrusoz, U., Dresdner, G., Gross, B., Sumer, S. O., Sun, Y., Jacobsen, A., Sinha, R., Larsson, E., et al. (2013) · Science Signaling · doi:10.1126/scisignal.2004088 · Cited by 15,160
Self-citationComprehensive genomic characterization of squamous cell lung cancers
The Cancer Genome Atlas Research Network (2012) · Nature · doi:10.1038/nature11404 · Cited by 3,994
REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants
Ioannidis, N. M., Rothstein, J. H., Pejaver, V., Middha, S., McDonnell, S. K., Baheti, S., Musolf, A., Li, Q., Holzinger, E., Karyadi, D., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.08.016 · Cited by 2,908
Predicting the Functional Effect of Amino Acid Substitutions and Indels
Choi, Y., Sims, G. E., Murphy, S., Miller, J. R., & Chan, A. P. (2012) · PLoS ONE · doi:10.1371/journal.pone.0046688 · Cited by 2,890
Metadata
- Authors
- Reva, B., Antipin, Y., & Sander, C.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-07-03
- Volume
- 39
- Issue
- 17
- Pages
- e118-e118
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2111326065
- Cited by
- 2,002
- References
- 10
- FWCI
- 40.93
- Type
- journal article
- Language
- en
- Open access
- gold
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