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An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Overview of attention for article published in Genome Biology (Online Edition), January 2007
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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 (88th percentile)

Mentioned by

news
1 news outlet
patent
2 patents

Citations

dimensions_citation
409 Dimensions

Readers on

mendeley
268 Mendeley
citeulike
2 CiteULike
connotea
2 Connotea
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Title
An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer
Published in
Genome Biology (Online Edition), January 2007
DOI 10.1186/gb-2007-8-8-r157
Pubmed ID
Authors

Andrew E Teschendorff, Ahmad Miremadi, Sarah E Pinder, Ian O Ellis, Carlos Caldas

Abstract

Estrogen receptor (ER)-negative breast cancer specimens are predominantly of high grade, have frequent p53 mutations, and are broadly divided into HER2-positive and basal subtypes. Although ER-negative disease has overall worse prognosis than does ER-positive breast cancer, not all ER-negative breast cancer patients have poor clinical outcome. Reliable identification of ER-negative tumors that have a good prognosis is not yet possible. We apply a recently proposed feature selection method in an integrative analysis of three major microarray expression datasets to identify molecular subclasses and prognostic markers in ER-negative breast cancer. We find a subclass of basal tumors, characterized by over-expression of immune response genes, which has a better prognosis than the rest of ER-negative breast cancers. Moreover, we show that, in contrast to ER-positive tumours, the majority of prognostic markers in ER-negative breast cancer are over-expressed in the good prognosis group and are associated with activation of complement and immune response pathways. Specifically, we identify an immune response related seven-gene module and show that downregulation of this module confers greater risk for distant metastasis (hazard ratio 2.02, 95% confidence interval 1.2-3.4; P = 0.009), independent of lymph node status and lymphocytic infiltration. Furthermore, we validate the immune response module using two additional independent datasets. We show that ER-negative basal breast cancer is a heterogeneous disease with at least four main subtypes. Furthermore, we show that the heterogeneity in clinical outcome of ER-negative breast cancer is related to the variability in expression levels of complement and immune response pathway genes, independent of lymphocytic infiltration.

Mendeley readers

The data shown below were compiled from readership statistics for 268 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 1%
France 2 <1%
United States 2 <1%
Brazil 1 <1%
Spain 1 <1%
Argentina 1 <1%
Unknown 257 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 72 27%
Researcher 56 21%
Student > Master 28 10%
Professor > Associate Professor 16 6%
Student > Bachelor 16 6%
Other 48 18%
Unknown 32 12%
Readers by discipline Count As %
Medicine and Dentistry 76 28%
Agricultural and Biological Sciences 64 24%
Biochemistry, Genetics and Molecular Biology 57 21%
Computer Science 10 4%
Immunology and Microbiology 7 3%
Other 22 8%
Unknown 32 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 April 2018.
All research outputs
#1,677,066
of 17,359,532 outputs
Outputs from Genome Biology (Online Edition)
#1,575
of 3,593 outputs
Outputs of similar age
#38,440
of 350,650 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 17,359,532 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,593 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has gotten more attention than average, scoring higher than 55% 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 350,650 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 88% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them