Cited by 1,597Cancer Genomics and DiagnosticsGenomics and Rare DiseasesChromatin Remodeling and Cancer

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The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers

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Sondka, Zbyslaw, Bamford, Sally, Cole, Charlotte G., Ward, Sari A., Dunham, Ian, Forbes, Simon A.·2018·Nature Reviews Cancer

DOI 10.1038/s41568-018-0060-1PMC PMC6450507

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Abstract

The Catalogue of Somatic Mutations in Cancer (COSMIC) Cancer Gene Census (CGC) is an expert-curated description of the genes driving human cancer that is used as a standard in cancer genetics across basic research, medical reporting and pharmaceutical development. After a major expansion and complete re-evaluation, the 2018 CGC describes in detail the effect of 719 cancer-driving genes. The recent expansion includes functional and mechanistic descriptions of how each gene contributes to disease generation in terms of the key cancer hallmarks and the impact of mutations on gene and protein function. These functional characteristics depict the extraordinary complexity of cancer biology and suggest multiple cancer-related functions for many genes, which are often highly tissue-dependent or tumour stage-dependent. The 2018 CGC encompasses a second tier, describing an expanding list of genes (currently 145) from more recent cancer studies that show supportive but less detailed indications of a role in cancer.

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Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
The hallmarks of cancer
Hanahan, D., & Weinberg, R. A. (2000) · Cell · doi:10.1016/s0092-8674(00)81683-9 · Cited by 29,219
Cancer Genome Landscapes
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
Mutation and cancer: statistical study of retinoblastoma
Knudson, A. G. (1971) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.68.4.820 · Cited by 7,612
Cancer-associated IDH1 mutations produce 2-hydroxyglutarate
Dang, L., White, D. W., Gross, S., Bennett, B. D., Bittinger, M. A., Driggers, E. M., Fantin, V. R., Jang, H. G., Jin, S., Keenan, M. C., et al. (2009) · Nature · doi:10.1038/nature08617 · Cited by 4,154
A census of human cancer genes
Futreal, P. A., Coin, L., Marshall, M., Down, T., Hubbard, T., Wooster, R., Rahman, N., & Stratton, M. R. (2004) · Nature Reviews Cancer · doi:10.1038/nrc1299 · Cited by 3,184
Inhibition of Mutated, Activated BRAF in Metastatic Melanoma
Flaherty, K. T., Puzanov, I., Kim, K. B., Ribas, A., McArthur, G. A., Sosman, J. A., O'Dwyer, P. J., Lee, R. J., Grippo, J. F., Nolop, K., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1002011 · Cited by 3,103
Processing of primary microRNAs by the Microprocessor complex
Denli, A. M., Tops, B. B. J., Plasterk, R. H. A., Ketting, R. F., & Hannon, G. J. (2004) · Nature · doi:10.1038/nature03049 · Cited by 2,784
Wnt signaling in cancer
Zhan, T., Rindtorff, N., & Boutros, M. (2017) · Oncogene · doi:10.1038/onc.2016.304 · Cited by 2,626
The mutational landscape of lethal castration-resistant prostate cancer
Grasso, C. S., Wu, Y.-M., Robinson, D. R., Cao, X., Dhanasekaran, S. M., Khan, A. P., Quist, M. J., Jing, X., Lonigro, R. J., Brenner, J. C., et al. (2012) · Nature · doi:10.1038/nature11125 · Cited by 2,517

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Liu, H., Yuan, M., Mitra, R., Zhou, X., Min, L., Lei, W., Zhou, S., Huang, Y. L., Hou, F., Eischen, C. M., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01119-6 · Cited by 35
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Konda, P., Garinet, S., Allen, E. M. V., & Viswanathan, S. R. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112978 · Cited by 36
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Tanaka, A., Ogawa, M., Zhou, Y., Namba, K., Hendrickson, R. C., Miele, M. M., Li, Z., Klimstra, D. S., Buckley, P. G., Gulcher, J. R., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113810 · Cited by 37
Systematically Characterizing A-to-I RNA Editing Neoantigens in Cancer
Zhou, C., Wei, Z., Zhang, L., Yang, Z., & Liu, Q. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.593989 · Cited by 36
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Supper, E., Rudat, S., Iyer, V., Droop, A., Wong, K., Spinella, J.-F., Thomas, P., Sauvageau, G., Adams, D. J., & Wong, C. C. (2021) · Nature Communications · doi:10.1038/s41467-021-22750-8 · Cited by 33
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Jurmeister, P. S., Wrede, N., Hoffmann, I., Vollbrecht, C., Heim, D., Hummel, M., Wolkenstein, P., Koch, I., Heynol, V., Schmitt, W., et al. (2021) · The Journal of Pathology · doi:10.1002/path.5808 · Cited by 33
3D genomic analysis reveals novel enhancer-hijacking caused by complex structural alterations that drive oncogene overexpression
Mortenson, K. L., Dawes, C., Wilson, E. R., Patchen, N. E., Johnson, H. E., Gertz, J., Bailey, S. D., Yang, J., Varley, K. E., & Zhang, X. (2024) · Nature Communications · doi:10.1038/s41467-024-50387-w · Cited by 35
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Chahal, C. A. A., Alahdab, F., Asatryan, B., Addison, D., Aung, N., Chung, M. K., Denaxas, S., Dunn, J., Hall, J. L., Pamir, N., et al. (2025) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.124.004624 · Cited by 35
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Carrot‐Zhang, J., Yao, X., Devarakonda, S. H. K., Deshpande, A. S., Damrauer, J. S., Silva, T. C., Wong, C. K., Choi, H. Y., Felau, I., Robertson, A. G., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.108707 · Cited by 30
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Cells with cancer‐associated mutations overtake our tissues as we age
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Lenoir, W. F., Morgado, M. C., DeWeirdt, P. C., McLaughlin, M. E., Griffith, A. L., Sangree, A. K., Feeley, M. N., Anvar, N. E., Kim, E., Bertolet, L. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26867-8 · Cited by 31
Oncogenic fusion proteins and their role in three-dimensional chromatin structure, phase separation, and cancer
Quiroga, I. Y., Ahn, J. H., Wang, G. G., & Phanstiel, D. H. (2022) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2022.101901 · Cited by 32
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Chen, J., Shen, S., Li, Y., Fan, J., Xiong, S., Xu, J., Zhu, C., Lin, L., Dong, X., Duan, W., et al. (2022) · EBioMedicine · doi:10.1016/j.ebiom.2022.104007 · Cited by 32
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Synonymous mutations promote tumorigenesis by disrupting m6A-dependent mRNA metabolism
Lan, Y., Xia, Z., Shao, Q., Lin, P., Lu, J., Xiao, X., Zheng, M., Chen, D., Dou, Y., & Xie, Q. (2025) · Cell · doi:10.1016/j.cell.2025.01.026 · Cited by 36
Features of increased malignancy in eosinophilic clear cell renal cell carcinoma
Nilsson, H., Lindgren, D., Axelson, H., Brueffer, C., Saal, L. H., Lundgren, J., & Johansson, M. (2020) · The Journal of Pathology · doi:10.1002/path.5532 · Cited by 32
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Sentís, I., González, S., Genescà, E., García‐Hernández, V., Muiños, F., González‐Gil, C., López‐Arribillaga, E., González, J., Fernández‐Ibarrondo, L., Mularoni, L., et al. (2020) · Genome biology · doi:10.1186/s13059-020-02192-z · Cited by 35
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Vancura, A., Lanzós, A., Bosch-Guiteras, N., Esteban, M. T., Gutierrez, A. H., Haefliger, S., & Johnson, R. (2021) · NAR Cancer · doi:10.1093/narcan/zcab013 · Cited by 34
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Arshad, Z., & McDonald, J. F. (2021) · iScience · doi:10.1016/j.isci.2021.103522 · Cited by 31
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Barreiro, R., Sabbaga, J., Rossi, B. M., Achatz, M. I., Bettoni, F., Camargo, A. A., Asprino, P. F., & Galante, P. A. F. (2021) · The Journal of Pathology · doi:10.1002/path.5829 · Cited by 33
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Schick, M., Zhang, L., Maurer, S., Maurer, H. C., Isaakidis, K., Schneider, L., Patra, U., Schunck, K., Rohleder, E., Hofstetter, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-021-27704-8 · Cited by 31
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Zhang, J., Pei, J., Durham, J., Bos, T., & Cong, Q. (2022) · Protein Science · doi:10.1002/pro.4479 · Cited by 31
Transcriptional immune suppression and up-regulation of double-stranded DNA damage and repair repertoires in ecDNA-containing tumors
Lin, M. S., Jo, S., Luebeck, J., Chang, H. Y., Wu, S., Mischel, P. S., & Bafna, V. (2023) · eLife · doi:10.7554/elife.88895 · Cited by 37
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Noberini, R., Restellini, C., Savoia, E. O., Raimondi, F., Ghiani, L., Jodice, M. G., Bertalot, G., Bonizzi, G., Capra, M. C., Maffini, F. A., et al. (2019) · Cancers · doi:10.3390/cancers11050723 · Cited by 29
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López‐Cortés, A., Paz‐y‐Miño, C., Guerrero, S. X., Jaramillo-Koupermann, G., Cáceres, Á. L., Intriago-Baldeón, D. P., García-Cárdenas, J. M., Guevara‐Ramírez, P., Armendáriz‐Castillo, I., Leone, P., et al. (2019) · The Pharmacogenomics Journal · doi:10.1038/s41397-019-0102-4 · Cited by 29
FACT-seq: profiling histone modifications in formalin-fixed paraffin-embedded samples with low cell numbers
Zhao, L., Xing, P., Polavarapu, V. K., Zhao, M., Valero-Martínez, B., Dang, Y., Maturi, N., Mathot, L., Neves, I., Yildirim, I., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab813 · Cited by 26

Authors: Sondka, Z., Bamford, S., Cole, C. G., Ward, S. A., Dunham, I., & Forbes, S. A.
Affiliations: Wellcome Sanger Institute (GB)
European Bioinformatics Institute (GB)
ORCID: Dunham, Ian
Venue: Nature Reviews Cancer
Publisher: Springer Science and Business Media LLC
Published: 2018-10-06
Volume: 18
Issue: 11
Pages: 696-705
ISSN: 1474-175X (ISSN-L)
1474-1768
DOI: 10.1038/s41568-018-0060-1
PMC: PMC6450507
OpenAlex: W2894573839
Cited by: 1,597
References: 102
Citations by year: 2026: 125 · 2025: 227 · 2024: 242 · 2023: 239 · 2022: 260 · 2021: 250 · 2020: 167 · 2019: 75 · 2018: 8
FWCI: 13.23
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature reviews. Cancer (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: Wellcome Trust
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords: somatic mutations, cancer genetics, gene function, cancer hallmarks, expert curation, cancer genomics
MeSH terms: Humans, Mutation, Neoplasms, Censuses

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The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers

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