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In patients with metastatic breast cancer the identification of circulating tumor cells in epithelial-to-mesenchymal transition is associated with a poor prognosis

Overview of attention for article published in Breast Cancer Research, March 2016
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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 (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
18 tweeters
facebook
1 Facebook page

Citations

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95 Dimensions

Readers on

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117 Mendeley
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Title
In patients with metastatic breast cancer the identification of circulating tumor cells in epithelial-to-mesenchymal transition is associated with a poor prognosis
Published in
Breast Cancer Research, March 2016
DOI 10.1186/s13058-016-0687-3
Pubmed ID
Authors

Michela Bulfoni, Lorenzo Gerratana, Fabio Del Ben, Stefania Marzinotto, Marisa Sorrentino, Matteo Turetta, Giacinto Scoles, Barbara Toffoletto, Miriam Isola, Carlo Alberto Beltrami, Carla Di Loreto, Antonio Paolo Beltrami, Fabio Puglisi, Daniela Cesselli

Abstract

Although recent models suggest that the detection of Circulating Tumor Cells (CTC) in epithelial-to-mesenchymal transition (EM CTC) might be related to disease progression in metastatic breast cancer (MBC) patients, current detection methods are not efficient in identifying this subpopulation of cells. Furthermore, the possible association of EM CTC with both clinicopathological features and prognosis of MBC patients has still to be demonstrated. Aims of this study were: first, to optimize a DEPArray-based protocol meant to identify, quantify and sort single, viable EM CTC and, subsequently, to test the association of EM CTC frequency with clinical data. This prospective observational study enrolled 56 MBC patients regardless of the line of treatment. Blood samples, depleted of CD45(pos) leukocytes, were stained with an antibody cocktail recognizing both epithelial and mesenchymal markers. Four CD45(neg) cell subpopulations were identified: cells expressing only epithelial markers (E CTC), cells co-expressing epithelial and mesenchymal markers (EM CTC), cells expressing only mesenchymal markers (MES) and cells negative for every tested marker (NEG). CTC subpopulations were quantified as both absolute cell count and relative frequency. The association of CTC subpopulations with clinicopathological features, progression free survival (PFS), and overall survival (OS) was explored by Wilcoxon-Mann-Whitney test and Univariate Cox Regression Analysis, respectively. By employing the DEPArray-based strategy, we were able to assess the presence of cells pertaining to the above-described classes in every MBC patient. We observed a significant association between specific CD45(neg) subpopulations and tumor subtypes (e.g. NEG and triple negative), proliferation (NEG and Ki67 expression) and sites of metastatic spread (e.g. E CTC and bone; NEG and brain). Importantly, the fraction of CD45(neg) cells co-expressing epithelial and mesenchymal markers (EM CTC) was significantly associated with poorer PFS and OS, computed, this latter, both from the diagnosis of a stage IV disease and from the initial CTC assessment. This study suggests the importance of dissecting the heterogeneity of CTC in MBC. Precise characterization of CTC could help in estimating both metastatization pattern and outcome, driving clinical decision-making and surveillance strategies.

Twitter Demographics

The data shown below were collected from the profiles of 18 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 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 <1%
Unknown 116 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 16%
Student > Ph. D. Student 18 15%
Student > Master 17 15%
Student > Bachelor 13 11%
Student > Doctoral Student 9 8%
Other 17 15%
Unknown 24 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 24%
Medicine and Dentistry 23 20%
Agricultural and Biological Sciences 13 11%
Engineering 8 7%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 11 9%
Unknown 30 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 19 November 2018.
All research outputs
#2,215,887
of 16,578,610 outputs
Outputs from Breast Cancer Research
#323
of 1,698 outputs
Outputs of similar age
#46,015
of 268,545 outputs
Outputs of similar age from Breast Cancer Research
#6
of 15 outputs
Altmetric has tracked 16,578,610 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,698 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 81% 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 268,545 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 82% of its contemporaries.
We're also able to compare this research output to 15 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 66% of its contemporaries.