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MutSigCVsyn: Identification of Thirty Synonymous Cancer Drivers

View ORCID ProfileYiyun Rao, Nabeel Ahmed, Justin Pritchard, View ORCID ProfileEdward O’Brien
doi: https://doi.org/10.1101/2022.01.16.476507
Yiyun Rao
1Huck Institute of the Life Sciences, Pennsylvania State University, University Park, 16802, Pennsylvania, USA
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Nabeel Ahmed
1Huck Institute of the Life Sciences, Pennsylvania State University, University Park, 16802, Pennsylvania, USA
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Justin Pritchard
2Department of Biomedical Engineering, Pennsylvania State University, University Park, 16802, Pennsylvania, USA
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  • For correspondence: jrp94@psu.edu epo2@psu.edu
Edward O’Brien
3Department of Chemistry, Pennsylvania State University, University Park, 16802, Pennsylvania, USA
4Institute for Computational and Data Sciences, Pennsylvania State University, University Park, 16802, Pennsylvania, USA
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  • For correspondence: jrp94@psu.edu epo2@psu.edu
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Abstract

Synonymous mutations, which change only the DNA sequence but not the encoded protein sequence, can affect protein structure and function, mRNA maturation, and mRNA half-lives. The possibility that synonymous mutations can act as cancer drivers has been explored in several recent studies. However, none of these studies control for all three levels (patient, histology, and gene) of mutational heterogeneity that are known to affect the accurate identification of non-synonymous cancer drivers. Here, we create an algorithm, MutSigCVsyn, an adaptation of MutSigCV, to identify synonymous cancer drivers based on a novel non-coding background model that takes into account the mutational heterogeneity across these levels. Examining 2,572 PCAWG cancer whole-genome sequences, MutSigCVsyn identifies 30 novel synonymous drivers that include mutations in promising candidates like BCL-2. By bringing the best practices in non-synonymous driver identification to the analysis of synonymous drivers, these are promising candidates for future experimental study.

Competing Interest Statement

The authors have declared no competing interest.

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 January 18, 2022.
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MutSigCVsyn: Identification of Thirty Synonymous Cancer Drivers
Yiyun Rao, Nabeel Ahmed, Justin Pritchard, Edward O’Brien
bioRxiv 2022.01.16.476507; doi: https://doi.org/10.1101/2022.01.16.476507
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MutSigCVsyn: Identification of Thirty Synonymous Cancer Drivers
Yiyun Rao, Nabeel Ahmed, Justin Pritchard, Edward O’Brien
bioRxiv 2022.01.16.476507; doi: https://doi.org/10.1101/2022.01.16.476507

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