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Catalog of driver mutations (2016.5)

This database contains the results of the driver analysis performed by the Cancer Genome Interpreter across 6,792 exomes of a pan-cancer cohort of 28 tumor types. Validated oncogenic mutations are identified according to the state-of-the-art clinical and experimental data, whereas the effect of the mutations of unknown significance is predicted by the OncodriveMUT method.


Citation
Tamborero D., Rubio-Perez C., Deu-Pons J., Schroeder M., Vivancos A., Rovira A., Tusquets I, Albanell J., Rodon J., Tabernero J., Dienstmann R., Gonzalez-Perez A. and Lopez-Bigas N. Cancer Genome Interpreter identifies driver and actionable alterations. Manuscript in preparation


Cancer Drivers Database (2014.12)

This database contains information on the genes identified as drivers in Rubio-Perez and Tamborero et al. (2015). It contains information on driver identification at mutational, CNA and gene fusion level. Additional ancillary information about the role and major clonality of drivers is also included. A table is also provided with the list of datasets used for mutational driver identification.


Citation
Rubio-Perez, C., Tamborero, D., Schroeder, MP., Antolín, AA., Deu-Pons,J., Perez-Llamas, C., Mestres, J., Gonzalez-Perez, A., Lopez-Bigas, N. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals novel targeting opportunities. Cancer Cell 27 (2015), pp. 382-396


Cancer Drivers Actionability Database (2014.12)

This database contains data on the interactions with therapeutic agents an driver genes contained in Cancer Drivers Database (2014.12). It characterizes the interacting therapeutic agents in terms of clinical phase and cancer prescription, among other features. Additionally, it contains ancillary information on specific genomic alterations associated to drug effectiveness which are FDA approved or clinically being tested together with data on other genomic alterations known to be responsible of drug primary resistance.


Citation
Rubio-Perez, C., Tamborero, D., Schroeder, MP., Antolín, AA., Deu-Pons,J., Perez-Llamas, C., Mestres, J., Gonzalez-Perez, A., Lopez-Bigas, N. In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals novel targeting opportunities. Cancer Cell 27 (2015), pp. 382-396




Previous releases

TCGA pan-cancer12 high confidence drivers (2013)

This file lists the High Confidence Drivers identified as part of the pan-cancer12 initiative, published in the paper Comprehensive identification of mutational cancer driver genes across 12 tumor types" Scientific Reports 3:2650, 2013, doi:10.1038/srep02650


Cancer driver database (2013)

Mutations, genes and pathways involved in tumorigenesis across 4,623 cancer genomes/exomes from 13 cancer sites.

IntOGen-mutations identifies cancer drivers across tumor types. Nature Methods 10, 2013, doi:10.1038/nmeth.2642


Intogen Arrays (2010)

Genes and pathways affected by expression and copy number changes in tumors across projects and cancer types.

Gundem G, Perez-Llamas C, Jene-Sanz A, Kedzierska A, Islam A, Deu-Pons J, Furney S and Lopez-Bigas N. IntOGen: Integration and data-mining of multidimensional oncogenomic data, Nature Methods 7, 92-93, 2010, doi:10.1038/nmeth0210-92.