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Mutational processes shape the landscape of TP53 mutations in human cancer

Overview of attention for article published in Nature Genetics, September 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Citations

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Title
Mutational processes shape the landscape of TP53 mutations in human cancer
Published in
Nature Genetics, September 2018
DOI 10.1038/s41588-018-0204-y
Pubmed ID
Authors

Andrew O. Giacomelli, Xiaoping Yang, Robert E. Lintner, James M. McFarland, Marc Duby, Jaegil Kim, Thomas P. Howard, David Y. Takeda, Seav Huong Ly, Eejung Kim, Hugh S. Gannon, Brian Hurhula, Ted Sharpe, Amy Goodale, Briana Fritchman, Scott Steelman, Francisca Vazquez, Aviad Tsherniak, Andrew J. Aguirre, John G. Doench, Federica Piccioni, Charles W. M. Roberts, Matthew Meyerson, Gad Getz, Cory M. Johannessen, David E. Root, William C. Hahn

Abstract

Unlike most tumor suppressor genes, the most common genetic alterations in tumor protein p53 (TP53) are missense mutations1,2. Mutant p53 protein is often abundantly expressed in cancers and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models3-8. To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53 wild-type and null cell lines. We found that loss or dominant-negative inhibition of wild-type p53 function reliably enhanced cellular fitness. By integrating these data with the Catalog of Somatic Mutations in Cancer (COSMIC) mutational signatures database9,10, we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 160 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 425 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 425 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 86 20%
Researcher 72 17%
Student > Bachelor 39 9%
Student > Master 30 7%
Student > Doctoral Student 20 5%
Other 53 12%
Unknown 125 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 129 30%
Agricultural and Biological Sciences 68 16%
Medicine and Dentistry 54 13%
Computer Science 10 2%
Immunology and Microbiology 7 2%
Other 30 7%
Unknown 127 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 93. 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 16 September 2021.
All research outputs
#455,588
of 25,402,528 outputs
Outputs from Nature Genetics
#923
of 7,579 outputs
Outputs of similar age
#9,803
of 351,043 outputs
Outputs of similar age from Nature Genetics
#26
of 81 outputs
Altmetric has tracked 25,402,528 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,579 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.0. 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 351,043 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 81 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.