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Genomic aberrations in young and elderly  breast cancer patients

Overview of attention for article published in BMC Medicine, October 2015
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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 (92nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

1 news outlet
1 blog
13 tweeters
1 Google+ user


51 Dimensions

Readers on

71 Mendeley
1 CiteULike
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Genomic aberrations in young and elderly  breast cancer patients
Published in
BMC Medicine, October 2015
DOI 10.1186/s12916-015-0504-3
Pubmed ID

Hatem A. Azim, Bastien Nguyen, Sylvain Brohée, Gabriele Zoppoli, Christos Sotiriou


Age at breast cancer diagnosis is a known prognostic factor. Previously, several groups including ours have shown that young age at diagnosis is associated with higher prevalence of basal-like tumors and aggressive tumor phenotypes. Yet the impact of age at diagnosis on the genomic landscape of breast cancer remains unclear. In this study, we examined the pattern of somatic mutations, chromosomal copy number variations (CNVs) and transcriptomic profiles in young and elderly breast cancer patients. Analyses were performed on The Cancer Genome Atlas (TCGA) dataset. Patients with metastatic disease at diagnosis, classified as normal-like by PAM50 or had missing clinical information were excluded. Young patients were defined as ≤45 years of age, while elderly patients were those ≥70 years of age at breast cancer diagnosis. The remaining patients were classified as "intermediate". We evaluated the association between age at diagnosis and somatic mutations, CNV and gene expression in a logistic regression model adjusting for tumor size, nodal status, histology and breast cancer subtype. All analyses were corrected for multiple testing using the Benjamini-Hochberg approach. In this study, 125, 486 and 169 patients were ≤45, 46-69 and ≥70 years of age, respectively. Older patients had more somatic mutations (n = 44 versus 35 versus 31; P = 0.0009) and more CNVs, especially in ductal tumors (P = 0.02). Eleven mutations were independently associated with age at diagnosis, of which only GATA3 was associated with young age (15.2 % versus 8.2 % versus 9 %; P = 0.003). Only two CNV events were independently associated with age, with more chr18p losses in older patients and more chr6q27 deletions in younger ones. Younger age at diagnosis was associated with higher expression of gene signatures related to proliferation, stem cell features and endocrine resistance. Age adds a layer of biological complexity beyond breast cancer molecular subtypes, classic pathological and clinical variables, worthy of further consideration in future drug development as we seek to refine therapeutic strategies in the era of personalized medicine.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Uruguay 1 1%
Slovenia 1 1%
Unknown 69 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Student > Master 13 18%
Student > Ph. D. Student 9 13%
Student > Bachelor 9 13%
Other 5 7%
Other 9 13%
Unknown 10 14%
Readers by discipline Count As %
Medicine and Dentistry 25 35%
Biochemistry, Genetics and Molecular Biology 12 17%
Agricultural and Biological Sciences 11 15%
Computer Science 3 4%
Nursing and Health Professions 2 3%
Other 5 7%
Unknown 13 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 December 2015.
All research outputs
of 13,604,914 outputs
Outputs from BMC Medicine
of 2,153 outputs
Outputs of similar age
of 282,515 outputs
Outputs of similar age from BMC Medicine
of 297 outputs
Altmetric has tracked 13,604,914 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,153 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.0. This one has gotten more attention than average, scoring higher than 70% 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 282,515 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 92% of its contemporaries.
We're also able to compare this research output to 297 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 63% of its contemporaries.