The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The mutational landscape of phosphorylation signaling in cancer
Open accessAbstract
Somatic mutations in cancer genomes include drivers that provide selective advantages to tumor cells and passengers present due to genome instability. Discovery of pan-cancer drivers will help characterize biological systems important in multiple cancers and lead to development of better therapies. Driver genes are most often identified by their recurrent mutations across tumor samples. However, some mutations are more important for protein function than others. Thus considering the location of mutations with respect to functional protein sites can predict their mechanisms of action and improve the sensitivity of driver gene detection. Protein phosphorylation is a post-translational modification central to cancer biology and treatment and frequently altered by driver mutations. Here we used our ActiveDriver method to analyze known phosphorylation sites mutated by single nucleotide variants (SNVs) in The Cancer Genome Atlas Research Network (TCGA) pan-cancer dataset of 3,185 genomes and 12 cancer types. Phosphorylation-related SNVs (pSNVs) occur in ~90% of tumors, show increased conservation and functional mutation impact compared to other protein-coding mutations and are enriched in cancer genes and pathways. Gene-centric analysis found 150 known and candidate cancer genes with significant pSNV recurrence. Using a novel computational method, we predict that 29% of these mutations directly abolish phosphorylation or modify kinase target sites to rewire signaling pathways. This analysis shows that incorporation of information about protein signaling sites will improve computational pipelines for variant function prediction.
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A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
The cancer genome atlas pan-cancer analysis project
The Cancer Genome Atlas Research Network, Weinstein, J. N., Collisson, E. A., Mills, G. B., Shaw, K. R. M., Ozenberger, B. A., Ellrott, K., Shmulevich, I., Sander, C., & Stuart, J. M. (2013) · Nature Genetics · doi:10.1038/ng.2764 · Cited by 9,092
Comprehensive molecular characterization of human colon and rectal cancer
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11252 · Cited by 8,499
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Comprehensive genomic characterization defines human glioblastoma genes and core pathways
The Cancer Genome Atlas Research Network (2008) · Nature · doi:10.1038/nature07385 · Cited by 7,735
Improved survival with vemurafenib in melanoma with BRAF V600E mutation
Chapman, P. B., Hauschild, A., Robert, C., Haanen, J. B., Ascierto, P., Larkin, J., Dummer, R., Garbe, C., Testori, A., Maio, M., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1103782 · Cited by 7,720
Kumar, P., Henikoff, S., & Ng, P. C. (2009) · Nature Protocols · doi:10.1038/nprot.2009.86 · Cited by 6,521
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature · doi:10.1038/nature10983 · Cited by 6,097
Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
The Cancer Genome Atlas Research Network (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1301689 · Cited by 5,078
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Self-citationComprehensive identification of mutational cancer driver genes across 12 tumor types
Tamborero, D., Gonzalez-Perez, A., Perez-Llamas, C., Deu-Pons, J., Kandoth, C., Reimand, J., Lawrence, M. S., Getz, G., Bader, G. D., Ding, L., et al. (2013) · Scientific Reports · doi:10.1038/srep02650 · Cited by 484
Self-citationDriver and Passenger Mutations in Cancer
Pon, J. R., & Marra, M. A. (2015) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-012414-040312 · Cited by 355
Solleder, M., Guillaume, P., Racle, J., Michaux, J., Pak, H.-S., Müller, M., Coukos, G., Bassani-Sternberg, M., & Gfeller, D. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001641 · Cited by 68
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“In contrast, phosphorylation sites are primarily found in disordered regions [18].”
BackgroundSelf-citation
Metadata
- Authors
- Reimand, J., Wagih, O., & Bader, G. D.
- Venue
- Scientific Reports
- Published
- 2013-10-02
- Volume
- 3
- Issue
- 1
- Pages
- 2651-2651
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W1982564236
- Cited by
- 162
- References
- 18
- FWCI
- 6.21
- Type
- journal article
- Language
- en
- Open access
- gold
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