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Discovery of cancer driver genes based on nucleotide context

Felix Dietlein, Donate Weghorn, Amaro Taylor-Weiner, André Richters, Brendan Reardon, David Liu, Eric S. Lander, View ORCID ProfileEliezer M. Van Allen, Shamil R. Sunyaev
doi: https://doi.org/10.1101/485292
Felix Dietlein
1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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Donate Weghorn
3Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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Amaro Taylor-Weiner
1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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André Richters
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
5Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Brendan Reardon
1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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David Liu
1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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Eric S. Lander
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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Eliezer M. Van Allen
1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA
2Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, 02142, USA
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  • ORCID record for Eliezer M. Van Allen
Shamil R. Sunyaev
3Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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Abstract

Many cancer genomes contain large numbers of somatic mutations, but few of these mutations drive tumor development. Current approaches to identify cancer driver genes are largely based on mutational recurrence, i.e. they search for genes with an increased number of nonsynonymous mutations relative to the local background mutation rate. Multiple studies have noted that the sensitivity of recurrence-based methods is limited in tumors with high background mutation rates, because passenger mutations dilute their statistical power. Here, we observe that passenger mutations tend to occur in characteristic nucleotide sequence contexts, while driver mutations follow a different distribution pattern determined by the location of functionally relevant genomic positions along the protein-coding sequence. To discover new cancer genes, we searched for genes with an excess of mutations in unusual nucleotide contexts that deviate from the characteristic context around passenger mutations. By applying this statistical framework to whole-exome sequencing data from 12,004 tumors, we discovered a long tail of novel candidate cancer genes with mutation frequencies as low as 1% and functional supporting evidence. Our results show that considering both the number and the nucleotide context around mutations helps identify novel cancer driver genes, particularly in tumors with high background mutation rates.

Footnotes

  • ↵7 These authors jointly supervised this work: Eliezer M. Van Allen, Shamil R. Sunyaev.

  • ↵* email: ssunyaev{at}rics.bwh.harvard.edu; EliezerM_VanAllen{at}dfci.harvard.edu; Felix_Dietlein{at}dfci.harvard.edu

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 December 04, 2018.
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Discovery of cancer driver genes based on nucleotide context
Felix Dietlein, Donate Weghorn, Amaro Taylor-Weiner, André Richters, Brendan Reardon, David Liu, Eric S. Lander, Eliezer M. Van Allen, Shamil R. Sunyaev
bioRxiv 485292; doi: https://doi.org/10.1101/485292
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Discovery of cancer driver genes based on nucleotide context
Felix Dietlein, Donate Weghorn, Amaro Taylor-Weiner, André Richters, Brendan Reardon, David Liu, Eric S. Lander, Eliezer M. Van Allen, Shamil R. Sunyaev
bioRxiv 485292; doi: https://doi.org/10.1101/485292

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