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Transcriptional Profiling of Breast Cancer Metastases Identifies Liver Metastasis–Selective Genes Associated with Adverse Outcome in Luminal A Primary Breast Cancer

Overview of attention for article published in Clinical Cancer Research, August 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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6 tweeters

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2 Mendeley
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Title
Transcriptional Profiling of Breast Cancer Metastases Identifies Liver Metastasis–Selective Genes Associated with Adverse Outcome in Luminal A Primary Breast Cancer
Published in
Clinical Cancer Research, August 2015
DOI 10.1158/1078-0432.ccr-15-0487
Pubmed ID
Authors

Siker Kimbung, Ida Johansson, Anna Danielsson, Srinivas Veerla, Suzanne Egyhazi Brage, Marianne Frostvik Stolt, Lambert Skoog, Lena Carlsson, Zakaria Einbeigi, Elisabet Lidbrink, Barbro Kristina Linderholm, Niklas Loman, Per Malmström, Martin Söderberg, Thomas M. Walz, Mårten Fernö, Thomas Hatschek, Ingrid A Hedenfalk

Abstract

The complete molecular basis of the organ-specificity of metastasis is elusive. This study aimed to provide an independent characterization of the transcriptional landscape of breast cancer metastases with the specific objective to identify liver metastasis-selective genes of prognostic importance following primary tumor diagnosis. A cohort of 304 women with advanced breast cancer was studied. Associations between the site of recurrence and clinico-pathological features were investigated. Fine-needle aspirates of metastases (n=91) were subjected to whole genome transcriptional profiling. Liver metastasis-selective genes were identified by significance analysis of microarray (SAM) analyses and independently validated in external datasets. Finally, the prognostic relevance of the liver metastasis-selective genes in primary breast cancer was tested. Liver relapse was associated with estrogen receptor (ER) expression (P=0.002), luminal B subtype (P=0.01), and was prognostic for an inferior post-relapse survival (P=0.01). The major variation in the transcriptional landscape of metastases was also associated with ER expression and molecular subtype. However, liver metastases displayed unique transcriptional fingerprints, characterized by down-regulation of extracellular matrix (i.e. stromal) genes. Importantly, we identified a 17-gene liver metastasis-selective signature, which was significantly and independently prognostic for shorter relapse-free (P<0.001) and overall (P=0.001) survival in ER positive tumors. Remarkably, this signature remained independently prognostic for shorter relapse-free survival (P=0.001) among luminal A tumors. Extracellular matrix (stromal) genes can be used to partition breast cancer by site of relapse and may be used to further refine prognostication in ER positive primary breast cancer.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 50%
Unknown 1 50%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 100%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 50%
Medicine and Dentistry 1 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 04 January 2016.
All research outputs
#1,425,199
of 6,905,088 outputs
Outputs from Clinical Cancer Research
#1,060
of 4,868 outputs
Outputs of similar age
#56,183
of 223,195 outputs
Outputs of similar age from Clinical Cancer Research
#47
of 162 outputs
Altmetric has tracked 6,905,088 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,868 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 77% 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 223,195 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 162 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 70% of its contemporaries.