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Characterizing the heterogeneity of triple-negative breast cancers using microdissected normal ductal epithelium and RNA-sequencing

Overview of attention for article published in Breast Cancer Research and Treatment, November 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

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3 X users
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3 patents
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3 Facebook pages

Citations

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49 Mendeley
Title
Characterizing the heterogeneity of triple-negative breast cancers using microdissected normal ductal epithelium and RNA-sequencing
Published in
Breast Cancer Research and Treatment, November 2013
DOI 10.1007/s10549-013-2780-y
Pubmed ID
Authors

Milan Radovich, Susan E. Clare, Rutuja Atale, Ivanesa Pardo, Bradley A. Hancock, Jeffrey P. Solzak, Nawal Kassem, Theresa Mathieson, Anna Maria V. Storniolo, Connie Rufenbarger, Heather A. Lillemoe, Rachel J. Blosser, Mi Ran Choi, Candice A. Sauder, Diane Doxey, Jill E. Henry, Eric E. Hilligoss, Onur Sakarya, Fiona C. Hyland, Matthew Hickenbotham, Jin Zhu, Jarret Glasscock, Sunil Badve, Mircea Ivan, Yunlong Liu, George W. Sledge, Bryan P. Schneider

Abstract

Triple-negative breast cancers (TNBCs) are a heterogeneous set of tumors defined by an absence of actionable therapeutic targets (ER, PR, and HER-2). Microdissected normal ductal epithelium from healthy volunteers represents a novel comparator to reveal insights into TNBC heterogeneity and to inform drug development. Using RNA-sequencing data from our institution and The Cancer Genome Atlas (TCGA) we compared the transcriptomes of 94 TNBCs, 20 microdissected normal breast tissues from healthy volunteers from the Susan G. Komen for the Cure Tissue Bank, and 10 histologically normal tissues adjacent to tumor. Pathway analysis comparing TNBCs to optimized normal controls of microdissected normal epithelium versus classic controls composed of adjacent normal tissue revealed distinct molecular signatures. Differential gene expression of TNBC compared with normal comparators demonstrated important findings for TNBC-specific clinical trials testing targeted agents; lack of over-expression for negative studies and over-expression in studies with drug activity. Next, by comparing each individual TNBC to the set of microdissected normals, we demonstrate that TNBC heterogeneity is attributable to transcriptional chaos, is associated with non-silent DNA mutational load, and explains transcriptional heterogeneity in addition to known molecular subtypes. Finally, chaos analysis identified 146 core genes dysregulated in >90 % of TNBCs revealing an over-expressed central network. In conclusion, use of microdissected normal ductal epithelium from healthy volunteers enables an optimized approach for studying TNBC and uncovers biological heterogeneity mediated by transcriptional chaos.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 48 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 9 18%
Professor 6 12%
Student > Bachelor 5 10%
Other 4 8%
Other 8 16%
Unknown 7 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 29%
Medicine and Dentistry 11 22%
Biochemistry, Genetics and Molecular Biology 9 18%
Computer Science 2 4%
Nursing and Health Professions 1 2%
Other 6 12%
Unknown 6 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 10 November 2016.
All research outputs
#3,556,030
of 22,733,113 outputs
Outputs from Breast Cancer Research and Treatment
#633
of 4,649 outputs
Outputs of similar age
#42,432
of 306,996 outputs
Outputs of similar age from Breast Cancer Research and Treatment
#16
of 71 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,649 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has done well, scoring higher than 86% 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 306,996 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 71 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.