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Passenger mutations in more than 2,500 cancer genomes: overall molecular functional impact and consequences

The dichotomous model of “drivers” and “passengers” in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAW...

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Main Authors: Kumar, Sushant (Author) , Warrell, Jonathan (Author) , Li, Shantao (Author) , McGillivray, Patrick D. (Author) , Meyerson, William (Author) , Salichos, Leonidas (Author) , Harmanci, Arif (Author) , Martinez-Fundichely, Alexander (Author) , Chan, Calvin Wing Yiu (Author) , Nielsen, Morten Muhlig (Author) , Lochovsky, Lucas (Author) , Zhang, Yan (Author) , Li, Xiaotong (Author) , Lou, Shaoke (Author) , Pedersen, Jakob Skou (Author) , Herrmann, Carl (Author) , Getz, Gad (Author) , Khurana, Ekta (Author) , Gerstein, Mark B. (Author)
Format: Article (Journal)
Language:English
Published: 20 February 2020
In: Cell
Year: 2020, Volume: 180, Issue: 5, Pages: 915-927,e1-e16
ISSN:1097-4172
DOI:10.1016/j.cell.2020.01.032
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.cell.2020.01.032
Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0092867420301136
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Author Notes:Sushant Kumar, Jonathan Warrell, Shantao Li, Patrick D. McGillivray, William Meyerson, Leonidas Salichos, Arif Harmanci, Alexander Martinez-Fundichely, Calvin W.Y. Chan, Morten Muhlig Nielsen, Lucas Lochovsky, Yan Zhang, Xiaotong Li, Shaoke Lou, Jakob Skou Pedersen, Carl Herrmann, Gad Getz, Ekta Khurana, and Mark B. Gerstein
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Summary:The dichotomous model of “drivers” and “passengers” in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that—in addition to the dichotomy of high- and low-impact variants—there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (∼12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.
Item Description:Gesehen am 11.05.2020
Physical Description:Online Resource
ISSN:1097-4172
DOI:10.1016/j.cell.2020.01.032

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