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Cell-lineage heterogeneity and driver mutation recurrence in pre-invasive breast neoplasia

Overview of attention for article published in Genome Medicine, April 2015
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
twitter
8 X users
facebook
1 Facebook page

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
40 Mendeley
citeulike
3 CiteULike
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Title
Cell-lineage heterogeneity and driver mutation recurrence in pre-invasive breast neoplasia
Published in
Genome Medicine, April 2015
DOI 10.1186/s13073-015-0146-2
Pubmed ID
Authors

Ziming Weng, Noah Spies, Shirley X Zhu, Daniel E Newburger, Dorna Kashef-Haghighi, Serafim Batzoglou, Arend Sidow, Robert B West

Abstract

All cells in an individual are related to one another by a bifurcating lineage tree, in which each node is an ancestral cell that divided into two, each branch connects two nodes, and the root is the zygote. When a somatic mutation occurs in an ancestral cell, all its descendants carry the mutation, which can then serve as a lineage marker for the phylogenetic reconstruction of tumor progression. Using this concept, we investigate cell lineage relationships and genetic heterogeneity of pre-invasive neoplasias compared to invasive carcinomas. We deeply sequenced over a thousand phylogenetically informative somatic variants in 66 morphologically independent samples from six patients that represent a spectrum of normal, early neoplasia, carcinoma in situ, and invasive carcinoma. For each patient, we obtained a highly resolved lineage tree that establishes the phylogenetic relationships among the pre-invasive lesions and with the invasive carcinoma. The trees reveal lineage heterogeneity of pre-invasive lesions, both within the same lesion, and between histologically similar ones. On the basis of the lineage trees, we identified a large number of independent recurrences of PIK3CA H1047 mutations in separate lesions in four of the six patients, often separate from the diagnostic carcinoma. Our analyses demonstrate that multi-sample phylogenetic inference provides insights on the origin of driver mutations, lineage heterogeneity of neoplastic proliferations, and the relationship of genomically aberrant neoplasias with the primary tumors. PIK3CA driver mutations may be comparatively benign inducers of cellular proliferation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 28%
Student > Ph. D. Student 6 15%
Student > Master 4 10%
Student > Postgraduate 3 8%
Other 2 5%
Other 6 15%
Unknown 8 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 28%
Biochemistry, Genetics and Molecular Biology 6 15%
Computer Science 5 13%
Medicine and Dentistry 4 10%
Engineering 2 5%
Other 3 8%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 47. 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 June 2015.
All research outputs
#749,229
of 22,797,621 outputs
Outputs from Genome Medicine
#146
of 1,440 outputs
Outputs of similar age
#10,345
of 264,944 outputs
Outputs of similar age from Genome Medicine
#1
of 25 outputs
Altmetric has tracked 22,797,621 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,440 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.6. This one has done well, scoring higher than 89% 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 264,944 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 96% of its contemporaries.
We're also able to compare this research output to 25 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 96% of its contemporaries.