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In silico saturation mutagenesis of cancer genes

Ferran Muiños, Francisco Martinez-Jimenez, Oriol Pich, Abel Gonzalez-Perez, Nuria Lopez-Bigas
doi: https://doi.org/10.1101/2020.06.03.130211
Ferran Muiños
1Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
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Francisco Martinez-Jimenez
1Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
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Oriol Pich
1Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
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Abel Gonzalez-Perez
1Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
2Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
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  • For correspondence: abel.gonzalez@irbbarcelona.org nuria.lopez@irbbarcelona.org
Nuria Lopez-Bigas
1Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
2Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
3Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
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  • For correspondence: abel.gonzalez@irbbarcelona.org nuria.lopez@irbbarcelona.org
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Summary

Extensive bioinformatics analysis of datasets of tumor somatic mutations data have revealed the presence of some 500-600 cancer driver genes. The identification of all potential driver mutations affecting cancer genes is essential to implement precision cancer medicine and to understand the interplay of mutation probability and selection in tumor development. Here, we present an in silico saturation mutagenesis approach to identify all driver mutations in 568 cancer genes across 66 tumor types. For most cancer genes the mutation probability across tissues --underpinned by active mutational processes-- influences which driver variants have been observed, although this differs significantly between tumor suppressor and oncogenes. The role of selection is apparent in some of the latter, the observed and unobserved driver mutations of which are equally likely to occur. The number of potential driver mutations in a cancer gene roughly determines how many mutations are available for detection across newly sequenced tumors.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • We have reformatted figures to leave more space on top of the page so that it doesn't overlap with the text introduced by biorxiv.

  • https://www.intogen.org/boostdm

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 09, 2020.
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In silico saturation mutagenesis of cancer genes
Ferran Muiños, Francisco Martinez-Jimenez, Oriol Pich, Abel Gonzalez-Perez, Nuria Lopez-Bigas
bioRxiv 2020.06.03.130211; doi: https://doi.org/10.1101/2020.06.03.130211
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In silico saturation mutagenesis of cancer genes
Ferran Muiños, Francisco Martinez-Jimenez, Oriol Pich, Abel Gonzalez-Perez, Nuria Lopez-Bigas
bioRxiv 2020.06.03.130211; doi: https://doi.org/10.1101/2020.06.03.130211

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