↓ Skip to main content

Impact of deleterious passenger mutations on cancer progression

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, February 2013
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
5 news outlets
blogs
1 blog
twitter
20 X users
facebook
1 Facebook page

Citations

dimensions_citation
280 Dimensions

Readers on

mendeley
438 Mendeley
citeulike
6 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Impact of deleterious passenger mutations on cancer progression
Published in
Proceedings of the National Academy of Sciences of the United States of America, February 2013
DOI 10.1073/pnas.1213968110
Pubmed ID
Authors

Christopher D. McFarland, Kirill S. Korolev, Gregory V. Kryukov, Shamil R. Sunyaev, Leonid A. Mirny

Abstract

Cancer progression is driven by the accumulation of a small number of genetic alterations. However, these few driver alterations reside in a cancer genome alongside tens of thousands of additional mutations termed passengers. Passengers are widely believed to have no role in cancer, yet many passengers fall within protein-coding genes and other functional elements that can have potentially deleterious effects on cancer cells. Here we investigate the potential of moderately deleterious passengers to accumulate and alter the course of neoplastic progression. Our approach combines evolutionary simulations of cancer progression with an analysis of cancer sequencing data. From simulations, we find that passengers accumulate and largely evade natural selection during progression. Although individually weak, the collective burden of passengers alters the course of progression, leading to several oncological phenomena that are hard to explain with a traditional driver-centric view. We then tested the predictions of our model using cancer genomics data and confirmed that many passengers are likely damaging and have largely evaded negative selection. Finally, we use our model to explore cancer treatments that exploit the load of passengers by either (i) increasing the mutation rate or (ii) exacerbating their deleterious effects. Though both approaches lead to cancer regression, the latter is a more effective therapy. Our results suggest a unique framework for understanding cancer progression as a balance of driver and passenger mutations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 438 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 15 3%
Germany 4 <1%
France 4 <1%
Spain 4 <1%
Canada 3 <1%
Denmark 2 <1%
United Kingdom 2 <1%
Netherlands 2 <1%
Korea, Republic of 1 <1%
Other 4 <1%
Unknown 397 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 127 29%
Researcher 89 20%
Student > Master 40 9%
Student > Bachelor 37 8%
Student > Postgraduate 23 5%
Other 72 16%
Unknown 50 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 159 36%
Biochemistry, Genetics and Molecular Biology 102 23%
Medicine and Dentistry 38 9%
Physics and Astronomy 17 4%
Computer Science 16 4%
Other 41 9%
Unknown 65 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 55. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 May 2023.
All research outputs
#745,250
of 24,739,153 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#12,454
of 101,711 outputs
Outputs of similar age
#6,032
of 293,770 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#93
of 1,016 outputs
Altmetric has tracked 24,739,153 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 101,711 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.8. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 293,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 1,016 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.