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Noninvasive Identification and Monitoring of Cancer Mutations by Targeted Deep Sequencing of Plasma DNA

Overview of attention for article published in Science Translational Medicine, May 2012
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
9 news outlets
blogs
5 blogs
twitter
41 tweeters
patent
61 patents
weibo
1 weibo user
facebook
1 Facebook page
wikipedia
2 Wikipedia pages
reddit
2 Redditors

Citations

dimensions_citation
958 Dimensions

Readers on

mendeley
1063 Mendeley
citeulike
10 CiteULike
Title
Noninvasive Identification and Monitoring of Cancer Mutations by Targeted Deep Sequencing of Plasma DNA
Published in
Science Translational Medicine, May 2012
DOI 10.1126/scitranslmed.3003726
Pubmed ID
Authors

Tim Forshew, Muhammed Murtaza, Christine Parkinson, Davina Gale, Dana W. Y. Tsui, Fiona Kaper, Sarah-Jane Dawson, Anna M. Piskorz, Mercedes Jimenez-Linan, David Bentley, James Hadfield, Andrew P. May, Carlos Caldas, James D. Brenton, Nitzan Rosenfeld

Abstract

Plasma of cancer patients contains cell-free tumor DNA that carries information on tumor mutations and tumor burden. Individual mutations have been probed using allele-specific assays, but sequencing of entire genes to detect cancer mutations in circulating DNA has not been demonstrated. We developed a method for tagged-amplicon deep sequencing (TAm-Seq) and screened 5995 genomic bases for low-frequency mutations. Using this method, we identified cancer mutations present in circulating DNA at allele frequencies as low as 2%, with sensitivity and specificity of >97%. We identified mutations throughout the tumor suppressor gene TP53 in circulating DNA from 46 plasma samples of advanced ovarian cancer patients. We demonstrated use of TAm-Seq to noninvasively identify the origin of metastatic relapse in a patient with multiple primary tumors. In another case, we identified in plasma an EGFR mutation not found in an initial ovarian biopsy. We further used TAm-Seq to monitor tumor dynamics, and tracked 10 concomitant mutations in plasma of a metastatic breast cancer patient over 16 months. This low-cost, high-throughput method could facilitate analysis of circulating DNA as a noninvasive "liquid biopsy" for personalized cancer genomics.

Twitter Demographics

The data shown below were collected from the profiles of 41 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,063 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 1%
United Kingdom 13 1%
Korea, Republic of 3 <1%
Norway 3 <1%
Netherlands 2 <1%
Ireland 2 <1%
Argentina 2 <1%
Japan 2 <1%
Canada 2 <1%
Other 8 <1%
Unknown 1013 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 302 28%
Student > Ph. D. Student 203 19%
Other 96 9%
Student > Master 87 8%
Student > Bachelor 81 8%
Other 166 16%
Unknown 128 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 329 31%
Medicine and Dentistry 233 22%
Biochemistry, Genetics and Molecular Biology 231 22%
Engineering 22 2%
Computer Science 19 2%
Other 71 7%
Unknown 158 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 132. 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 03 May 2022.
All research outputs
#228,946
of 21,110,276 outputs
Outputs from Science Translational Medicine
#715
of 4,899 outputs
Outputs of similar age
#1,020
of 142,700 outputs
Outputs of similar age from Science Translational Medicine
#7
of 91 outputs
Altmetric has tracked 21,110,276 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 4,899 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 76.6. This one has done well, scoring higher than 85% 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 142,700 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 99% of its contemporaries.
We're also able to compare this research output to 91 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 92% of its contemporaries.