The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We identified 391 out of the 622 curated COSMIC cancer-related and AML-related genes located inside the altered TADs in at least one sample, and more than 100 are recurrent across multiple samples (Extended Data Fig. 3b)4,24,25.”
From Subtype-specific 3D genome alteration in acute myeloid leukaemia (2022) · cites this paper as [24]
Experimental — accuracy not yet measuredIn the citing paper
“four interact with or signal through KRAS16,38 or are known oncogenes or tumor suppressors39: TP53, RNF43, MAP2K4, and RBM10”
From The origins and genetic interactions of KRAS mutations are allele- and tissue-specific (2021) · cites this paper as [39]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Hanahan, D., & Weinberg, R. A. (2000) · Cell · doi:10.1016/s0092-8674(00)81683-9 · Cited by 29,219
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
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
Cited by
Sorted by citations
Items 801–900 of 998
Sorel, N., Díaz-Pascual, F., Bessot, B., Sadek, H., Mollet, C., Chouteau, M., Zahn, M., Gil-Fariña, I., Tajer, P., van Eggermond, M. C. J. A., et al. (2024) · Biomedicines · doi:10.3390/biomedicines12071495 · Cited by 6
Learning to estimate sample-specific transcriptional networks for 7,000 tumors
Ellington, C. N., Lengerich, B. J., Watkins, T. B. K., Yang, J., Adduri, A., Mahbub, S., Xiao, H., Kellis, M., & Xing, E. P. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2411930122 · Cited by 7
Cancer gene identification from RNA variant allelic frequencies using RVdriver
Black, J. R., Jones, T. P., Martínez‐Ruiz, C., Litovchenko, M., Puttick, C., Swanton, C., & McGranahan, N. (2025) · Genome biology · doi:10.1186/s13059-025-03557-y · Cited by 8
Loss of Integrase Interactor 1 (INI1) Expression in a Subset of Differentiated Thyroid Cancer
Ho, K.-C., Lee, J.-J., Lin, C., Leung, C.-H., & Cheng, S. (2020) · Diagnostics · doi:10.3390/diagnostics10050280 · Cited by 6
Anandanadarajah, N., Chu, C. H., & Loganantharaj, R. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104323 · Cited by 7
Assembling Disease Networks From Causal Interaction Resources
Cesareni, G., Sacco, F., & Perfetto, L. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.694468 · Cited by 6
Prediction of Disease Genes Based on Stage-Specific Gene Regulatory Networks in Breast Cancer
Fan, L., Hou, J., & Qin, G. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.717557 · Cited by 6
Vergani, E., Frigerio, S., Dugo, M., Devecchi, A., Feltrin, E., Cecco, L. D., Vallacchi, V., Cossa, M., Guardo, L. D., Manoukian, S., et al. (2021) · Genes · doi:10.3390/genes12091440 · Cited by 7
Huang, Y.-T., Hsu, Y., Chen, Y., & Shen, M.-R. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.762387 · Cited by 6
Zhang, T., Zhang, S., Zhang, S.-Y., & Ma, Q. (2022) · Methods · doi:10.1016/j.ymeth.2022.03.008 · Cited by 6
Wang, C., Wallerman, O., Arendt, M. L., Sundström, E., Karlsson, Å., Nordin, J., Mäkeläinen, S., Pielberg, G., Hanson, J., Ohlsson, Å., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.02.185108 · Cited by 6
Genetic variants for head size share genes and pathways with cancerPreprint
Knol, M. J., Poot, R. A., Evans, T. E., Satizábal, C. L., Mishra, A., der Auwera, S. V., Duperron, M., Jian, X., Hostettler, I. C., van Dam-Nolen, D. H. K., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.15.191114 · Cited by 6
Boot, A., Ng, A. W. T., Chong, F. T., Ho, S.-C., Yu, W., Tan, D. S.-W., Iyer, N. G., & Rozen, S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/368753 · Cited by 6
Variable efficiency of nonsense-mediated mRNA decay across human tissues, tumors and individualsPreprint
Palou-Márquez, G., & Supek, F. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.29.582778 · Cited by 6
Gnanapragasam, A., Kirbizakis, E., Li, A., White, K. H., Mortenson, K. L., de Moura, J. C., Jawhar, W., Yan, Y., Falter, R., Russett, C. S., et al. (2024) · Cancer Research · doi:10.1158/0008-5472.can-23-2397 · Cited by 5
EXaCT-2: an augmented and customizable oncology-focused whole exome sequencing platform
Waltman, P., Chandra, P., Eng, K. W., Wilkes, D. C., Park, H. H., Pabón-Peña, C., Delpe, P., Bhinder, B., Manohar, J., Kane, T., et al. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01390-5 · Cited by 4
Pan-Cancer Upregulation of the FOXM1 Transcription Factor
Pozzobon, D., Bellezza, A., & Giorgi, F. M. (2025) · Genes · doi:10.3390/genes16010056 · Cited by 5
Zeeshan, S., Dalal, B., Arauz, R. F., Zingone, A., Harris, C. C., Khiabanian, H., Pine, S. R., & Ryan, B. M. (2025) · Oncogene · doi:10.1038/s41388-024-03267-y · Cited by 5
Gong, T., Jiang, J., Uthayopas, K., Bornman, R. M. S., Gheybi, K., Stricker, P. D., Weischenfeldt, J., Mutambirwa, S. B. A., Jaratlerdsiri, W., & Hayes, V. M. (2025) · Nature Communications · doi:10.1038/s41467-025-57312-9 · Cited by 7
Kim, S., Kim, G.-H., Park, J. H., Lee, K.-H., Koh, J., Kim, T. Y., Lee, D.-W., Kim, Y., Kim, S., Park, S. Y., et al. (2025) · Breast Cancer Research · doi:10.1186/s13058-025-02032-7 · Cited by 5
Russell, C. B., Vettermann, C., Agarwal, S., Witt, E., Clark, W. T., Arens, J., Fronza, R., Obrochta, K. M., Kasprzyk, T., Robinson, T. M., et al. (2025) · Human Gene Therapy · doi:10.1089/hum.2024.236 · Cited by 5
Intraline genomic heterogeneity of the triple-negative breast cancer MDA-MB-231-luc-GFP cell line
Varela, N., Estévez‐Gómez, N., Fernández-Santiago, C., Tomás, L., Pérez, M., García‐Souto, D., Pasantes, J. J., Piñeiro, R., Alves, J. M., & Posada, D. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.06.033 · Cited by 6
Passenger mutations link cellular origin and transcriptional identity in human lung adenocarcinomas
Panja, S., Mantri, P., Johnson, K. E., Andrade-Martínez, J. S., Yang, S., Deshpande, A. S., Tian, H., Beg, S., Ohara, K., Leal, A., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02418-5 · Cited by 5
Temporal trends in evidence supporting novel drug target discovery
Falaguera, M. J., McDonagh, E. M., Ochoa, D., Rusina, P. V., Roldán‐Romero, J. M., Hulcoop, D. G., Leach, A. R., & Dunham, I. (2025) · Nature Communications · doi:10.1038/s41467-025-67180-y · Cited by 7
Self-citationElHarouni, D., Hernansaiz-Ballesteros, R. D., Peterziel, H., Balasubramanian, G. P., Previti, C., Schramm, K., Blattner-Johnson, M., Kabbe, R., Jones, B. C., Oppermann, S., et al. (2025) · Cancer Research · doi:10.1158/0008-5472.can-24-1938 · Cited by 7
Zhang, X., Zhang, Y., Liu, X., Liu, C., Liu, Y., He, Y., Qiu, Y., Sun, L., Hu, J., Gao, Y., et al. (2025) · Cell · doi:10.1016/j.cell.2025.11.037 · Cited by 7
Genome-wide detection of human 5′ UTR variants that impact protein translation
Chaldebas, M., Ponsin, K., Bohlen, J., Conil, C., Mourelatos, H. A., Stenson, P. D., Cooper, D. N., Abel, L., Casanova, J., Cobat, A., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.02.020 · Cited by 6
DIOPT: the DRSC Integrative Ortholog Prediction Tool, 2026 update
Hu, Y., Comjean, A., Gao, C., Veal, A., Yamamoto, S., Mohr, S. E., & Perrimon, N. (2026) · Genetics · doi:10.1093/genetics/iyag194 · Cited by 5
A computational approach to generate highly conserved gene co-expression networks with RNA-seq data
Arshad, Z., & McDonald, J. F. (2022) · STAR Protocols · doi:10.1016/j.xpro.2022.101432 · Cited by 5
Zulkifli, N. D., & Zulkifle, N. (2023) · Genomics & Informatics · doi:10.5808/gi.23003 · Cited by 5
The utility of liquid biopsy in clinical genetic diagnosis of cancer and monogenic mosaic disorders
Hallermayr, A., Keßler, T., Steinke‐Lange, V., Heitzer, E., Holinski‐Feder, E., & Speicher, M. R. (2023) · Medizinische Genetik · doi:10.1515/medgen-2023-2066 · Cited by 5
Araki, R., Suga, T., Hoki, Y., Imadome, K., Sunayama, M., Kamimura, S., Fujita, M., & Abe, M. (2024) · Nature Communications · doi:10.1038/s41467-024-49335-5 · Cited by 6
Choi, Y., Choi, S. A., Koh, E. J., Yun, I., Park, S. H., Jeon, S., Kim, Y., Park, S., Woo, D., Phi, J. H., et al. (2024) · Acta Neuropathologica Communications · doi:10.1186/s40478-024-01814-y · Cited by 5
Cho, H.-M., Choe, S.-H., Lee, J.-R., Park, H., Ko, M.-G., Lee, Y.-J., Lee, H.-Y., Park, S. H., Park, S.-J., Kim, Y., et al. (2024) · npj Aging · doi:10.1038/s41514-024-00158-0 · Cited by 5
CIBRA identifies genomic alterations with a system-wide impact on tumor biology
Lakbir, S., Buranelli, C., Meijer, G. A., Heringa, J., Fijneman, R. J. A., & Abeln, S. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae384 · Cited by 5
He, J., Perera, D., Wen, W., Ping, J., Li, Q., Lyu, L., Chen, Z., Shu, X., Long, J., Cai, Q., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1035 · Cited by 8
Stricker, E., Peckham‐Gregory, E. C., Lai, S. Y., Sandulache, V. C., & Scheurer, M. E. (2024) · Microorganisms · doi:10.3390/microorganisms12122435 · Cited by 5
Cancer Relevance of Human Genes
Qing, T., Mohsen, H., Cannataro, V. L., Marczyk, M., Rozenblit, M., Foldi, J., Murray, M. T., Townsend, J. P., Kluger, Y., Gerstein, M., et al. (2022) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djac068 · Cited by 5
SNPs Ability to Influence Disease Risk: Breaking the Silence on Synonymous Mutations in Cancer
Herreros, E., Janssens, X., Pepe, D., & Keersmaecker, K. D. (2022) · Springer eBooks · doi:10.1007/978-3-031-05616-1_5 · Cited by 5
Multivariate Bayesian structured variable selection for pharmacogenomic studies
Zhao, Z. Q., Banterle, M., Lewin, A., & Zucknick, M. (2023) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1093/jrsssc/qlad102 · Cited by 5
DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network
Huang, Y., Zhou, S., Liu, H., Zhou, X., Yuan, M., Hou, F., Chen, S., Chen, J., Wang, L., & Jiang, W. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad066 · Cited by 5
The Clinical Significance of Genetic Variation in Ovarian Cancer
Ban, D., Housley, S. N., & McDonald, J. F. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241310823 · Cited by 5
Actionable loss of SLF2 drives B‐cell lymphomagenesis and impairs the DNA damage response
Zhang, L., Wirth, M., Patra, U., Stroh, J., Isaakidis, K., Rieger, L., Kossatz, S., Milanovic, M., Zang, C., Demel, U. M., et al. (2023) · EMBO Molecular Medicine · doi:10.15252/emmm.202216431 · Cited by 5
Tudose, C., Bond, J., & Ryan, C. J. (2023) · NAR Cancer · doi:10.1093/narcan/zcad056 · Cited by 5
The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations
Cui, H., Srinivasan, S., Gao, Z., & Korkin, D. (2023) · Biomolecules · doi:10.3390/biom14010040 · Cited by 5
Long Intergenic Non-Coding RNAs of Human Chromosome 18: Focus on Cancers
Ershov, P. V., Yablokov, E. O., Mezentsev, Y. V., & Ivanov, A. S. (2024) · Biomedicines · doi:10.3390/biomedicines12030544 · Cited by 5
Childhood cancer mutagenesis caused by transposase-derived PGBD5
Yamada, M., Keller, R. R., Gutierrez, R. L., Cameron, D., Suzuki, H., Sanghrajka, R. M., Vaynshteyn, J., Gerwin, J. N., Maura, F., Hooper, W. F., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn4649 · Cited by 6
Han, Z., Yao, L., Fang, Y., Chen, S., Lian, R., Yao, Y., Chen, H., Ji, X., Yu, W., Wang, Z., et al. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1361603 · Cited by 5
Germline susceptibility from broad genomic profiling of pediatric brain cancers
Mardis, E. R., Potter, S. L. P., Schieffer, K. M., Varga, E. A., Mathew, M. T., Costello, H. M., Wheeler, G., Kelly, B., Miller, K. E., Garfinkle, E. A. R., et al. (2024) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdae099 · Cited by 5
Ong, S. S., Ho, P. J., Khng, A. J., Tan, B. K. T., Tan, Q. T., Tan, E. Y., Tan, S.-M., Putti, T. C., Lim, S. H., Tang, E. L. S., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25169058 · Cited by 6
Shatara, M., Schieffer, K. M., Melas, M., Varga, E. A., Thomas, D., Bucknor, B. A., Costello, H. M., Wheeler, G., Kelly, B., Miller, K. E., et al. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1453309 · Cited by 5
Repo, P. E., Jakkula, E., Hiltunen, J., Putkuri, H., Staskiewicz, A., Järvinen, R., Täll, M., Raivio, V., Al‐Jamal, R. T., Kivelä, T., et al. (2024) · Pigment Cell & Melanoma Research · doi:10.1111/pcmr.13198 · Cited by 5
Kenny, P. A. (2019) · F1000Research · doi:10.12688/f1000research.19541.2 · Cited by 5
Unveiling potential anticancer drugs through in silico drug repurposing approaches
S, H. S. G. N., Prasanna, V. L., Pai, R. R., Jos, S. M., Murthy, M. K., & Saraswathy, G. R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819668-7.00004-x · Cited by 5
Kelman, G., Brandes, N., & Michal Linial, B. (2020) · Cancer Research · doi:10.1158/0008-5472.can-20-3147 · Cited by 5
Unger, K., Fleischmann, D. F., Ruf, V., Felsberg, J., Piehlmaier, D., Samaga, D., Heß, J., Suresh, M. P., Mittelbronn, M. G. A., Lauber, K., et al. (2020) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdaa137 · Cited by 5
Ülgen, E., Can, Ö., Bilgüvar, K., Akyerli, C. B., Yüksel, Ş., Danyeli, A. E., Sezerman, O. U., Yakicier, M. C., Pamir, M. N., & Özduman, K. (2021) · BMC Medical Genomics · doi:10.1186/s12920-021-00904-3 · Cited by 5
Differential chromatin accessibility landscape of gain-of-function mutant p53 tumours
Dhaka, B., & Sabarinathan, R. (2021) · BMC Cancer · doi:10.1186/s12885-021-08362-x · Cited by 5
Nieboer, M. M., Nguyen, L., & de Ridder, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-93917-y · Cited by 5
An Unbiased Functional Genetics Screen Identifies Rare Activating ERBB4 Mutations
Chakroborty, D., Ojala, V. K., Knittle, A. M., Drexler, J., Tamirat, M. Z., Ruzicka, R., Bosch, K., Woertl, J., Schmittner, S., Elo, L. L., et al. (2022) · Cancer Research Communications · doi:10.1158/2767-9764.crc-21-0021 · Cited by 6
Prostanoid Signaling in Cancers: Expression and Regulation Patterns of Enzymes and Receptors
Ershov, P. V., Yablokov, E. O., Kaluzhskiy, L. A., Mezentsev, Y. V., & Ivanov, A. S. (2022) · Biology · doi:10.3390/biology11040590 · Cited by 6
Larios‐Serrato, V., Martínez‐Ezquerro, J. D., Valdez‐Salazar, H.-A., Torres, J., Camorlinga‐Ponce, M., Piña‐Sánchez, P., & Tachiquín, M. E. R. (2022) · Molecular Medicine Reports · doi:10.3892/mmr.2022.12707 · Cited by 5
Brain somatic mutations as RNA therapeutic targets in neurological disorders
Lee, S., & Lee, J. H. (2022) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14786 · Cited by 5
A genetic map of the chromatin regulators to drug response in cancer cells
Chen, B., Li, P., Liu, M., Liu, K., Zou, M., Geng, Y., Zhuang, S., Xu, H., Wang, L., Chen, T., et al. (2022) · Journal of Translational Medicine · doi:10.1186/s12967-022-03651-w · Cited by 5
Accurate Prediction of Cancer Prognosis by Exploiting Patient-Specific Cancer Driver Genes
Lee, S., Jung, H., Park, J., & Ahn, J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24076445 · Cited by 5
Sakthikumar, S., Facista, S. J., Whitley, D. B., Byron, S. A., Ahmed, Z. A., Warrier, M., Zhu, Z., Chon, E., Banovich, K., Haworth, D., et al. (2023) · Veterinary and Comparative Oncology · doi:10.1111/vco.12911 · Cited by 5
Maya‐González, C., Wessman, S., Lagerstedt‐Robinson, K., Taylan, F., Tesi, B., Kuchinskaya, E., McCluggage, W. G., Poluha, A., Holm, S., Nergårdh, R., et al. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1172565 · Cited by 5
Song, S., Koh, Y., Kim, S., Lee, S. M., Kim, H. U., Ko, J. M., Lee, S., Yoon, S., & Park, S. (2023) · Genome Medicine · doi:10.1186/s13073-023-01252-w · Cited by 5
Supervised prediction of aging-related genes from a context-specific protein interaction subnetwork
Li, Q., & Milenković, T. (2019) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm47256.2019.8983063 · Cited by 4
Mutation hotspots may not be drug targets
Carter, H. K. (2019) · Science · doi:10.1126/science.aax9108 · Cited by 5
Ianevski, A., Giri, A. K., & Aittokallio, T. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/812131 · Cited by 5
Perera, Y., González, A., & Perez, R. (2021) · Preprints.org · doi:10.20944/preprints202102.0234.v1 · Cited by 5
Wieder, N., D’Souza, E. N., Martin-Geary, A. C., Lassen, F. H., Talbot-Martin, J., Fernandes, M., Chothani, S. P., Rackham, O. J. L., Schäfer, S., Aspden, J. L., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.15.540809 · Cited by 5
Variability of mutational signatures is a footprint of carcinogensPreprint
Morrison, M. L., Mangé, L., Senkin, S., Rosenberg, N. A., Foll, M., Fernandez‐Cuesta, L., & Alcala, N. (2023) · medRxiv · doi:10.1101/2023.11.23.23298821 · Cited by 5
Peng, S., Jia, K., Peng, M., Chen, Y., Lin, A., Luo, P., Wang, J., Wang, Y., & Bai, Y. (2025) · International Journal of Surgery · doi:10.1097/js9.0000000000002526 · Cited by 4
Eleveld, T. F., Ylstra, B., & Looijenga, L. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf689 · Cited by 4
Collignon, C., Hansen, T. H., Hercus, C., Ruzinova, M. B., Guépin, G. R., Bonmati, C., Rubio, M., Feugier, P., Gaudfrin, M., Sartelet, H., et al. (2025) · Blood Cancer Journal · doi:10.1038/s41408-025-01345-2 · Cited by 4
Isolated oral CD30+/CD4+ CAR+ T cell lymphoma in long-term remission after radiotherapy
Bezerra, E. D., Lupu, L., de Lima, M., Pfaller, L., Neal, A., Hajizadeh, N. R., Zhao, Q., Beibel, M., Chung, C. T. ‐., Lemmens, M., et al. (2025) · Molecular Therapy · doi:10.1016/j.ymthe.2025.08.043 · Cited by 4
Zhang, H., del Barrio, J. L. A., Miguel, M. P. D., & Alió, J. L. (2025) · Experimental Eye Research · doi:10.1016/j.exer.2025.110631 · Cited by 4
Integrated multi-optosis model for pan-cancer candidate biomarker and therapy target discovery
de Souza, E. R., Nogueira, H. A. C., Francisco, R. D. S., Garcia, A. B., & Medina‐Acosta, E. (2025) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2025.1630518 · Cited by 5
Zhang, P., Liu, D., Yu, T., Zhang, Y., Zhong, L. X., Ouyang, X., Qin, X., & Dong, L. (2025) · Clinical and Translational Medicine · doi:10.1002/ctm2.70517 · Cited by 4
Chromatin landscape and epigenetic heterogeneity of acute myeloid leukaemia
Ochi, Y., Liew-Littorin, M., Nannya, Y., Bengtzén, S., Piauger, B., Deneberg, S., Jädersten, M., Lazarević, V., Cammenga, J., Robelius, A., et al. (2026) · Nature · doi:10.1038/s41586-026-10703-4 · Cited by 5
Urzúa-Traslaviña, C. G., van Lieshout, T., Boulogne, F., Domanegg, K., Zidan, M., Bakker, O. B., Claringbould, A., de Ridder, J., Zwart, W. T., Westra, H.-J., et al. (2024) · BMC Medical Genomics · doi:10.1186/s12920-024-01941-4 · Cited by 4
Genome-wide association studies are enriched for interacting genes
Nguyen, P., Coetzee, S. G., Silacheva, I., & Hazelett, D. J. (2025) · BioData Mining · doi:10.1186/s13040-024-00421-w · Cited by 4
Yu, J., Cha, J., Koh, G., & Lee, I. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3002702 · Cited by 7
Wang, H., Zhang, Y., Li, W., Wei, Z., Wang, Z., & Yang, M. (2025) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2025.102534 · Cited by 4
Xu, X., Wang, S., Zhou, H., Tan, Q., Lang, Z., Zhu, Y., Yuan, H. S., Wu, Z., Zhu, L., Hu, K., et al. (2025) · Oncogene · doi:10.1038/s41388-025-03338-8 · Cited by 4
Huang, C., Chao, A., Lin, C., Rozen, S., Chao, A.-S., Chang, C.-B., Tung, H., Wu, R., & Lai, C. (2025) · BMC Cancer · doi:10.1186/s12885-025-15053-4 · Cited by 4
Anglada-Girotto, M., Miravet‐Verde, S., & Serrano, L. G. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf855 · Cited by 4
Li, Q., Song, Q., Chen, Z., Choi, J.-Y., Moreno, V. R., Ping, J., Wen, W., Li, C., Shu, X., Yan, J., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.11.008 · Cited by 4
Menezes, K., Atanesyan, L., Sherborne, A. L., Steenkamer, M., Clemens, I., Savola, S. P., & Kaiser, M. (2020) · Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2020.06.007 · Cited by 4
El cáncer de pulmón de células no pequeñas en la era de la medicina de precisión
Rivas, S., & Armisén, R. (2022) · Revista Médica Clínica Las Condes · doi:10.1016/j.rmclc.2022.01.001 · Cited by 4
Bernal, A. M. C., Pham, V., Li, X., Liu, L., Li, J., & Le, T. D. (2022) · Briefings in Functional Genomics · doi:10.1093/bfgp/elac030 · Cited by 4
Wild animals as an underused treasure trove for studying the genetics of cancer
Sepp, T., & Giraudeau, M. (2022) · BioEssays · doi:10.1002/bies.202200188 · Cited by 6
MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles
Santamarina, M., Iglesias, J. B., Bramsen, J. B., Fuentes-Losada, M., Caneiro-Gómez, F. J., Vázquez-Bueno, J. Á., Lázare‐Iglesias, H., Fernández-Díaz, N., Sánchez-Rivadulla, L., Betancor, Y. Z., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106127 · Cited by 4
Multi-View Kernel Learning for Identification of Disease Genes
Shah, E. J., & Maji, P. (2023) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2023.3247033 · Cited by 4
Striker, S. S., Wilferd, S. F., Lewis, E. M., O’Connor, S. A., & Plaisier, C. L. (2022) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100442 · Cited by 4
Kim, J., Park, M., Baek, G. W., Kim, J.-I., Kwon, E., Kang, B., Kim, J., & Kang, H. J. (2023) · Molecular Therapy — Oncolytics · doi:10.1016/j.omto.2023.05.004 · Cited by 5
Hotspot propensity across mutational processes
Arnedo-Pac, C., Muiños, F., González-Pérez, A., & López-Bigas, N. (2023) · Molecular Systems Biology · doi:10.1038/s44320-023-00001-w · Cited by 6
Metadata
- 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
- Published
- 2018-10-06
- Volume
- 18
- Issue
- 11
- Pages
- 696-705
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review