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A novel method for downstream characterization of breast cancer circulating tumor cells following CellSearch isolation

Overview of attention for article published in Journal of Translational Medicine, April 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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3 X users
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1 patent

Citations

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41 Mendeley
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Title
A novel method for downstream characterization of breast cancer circulating tumor cells following CellSearch isolation
Published in
Journal of Translational Medicine, April 2015
DOI 10.1186/s12967-015-0493-1
Pubmed ID
Authors

Henrik Frithiof, Charlotte Welinder, Anna-Maria Larsson, Lisa Rydén, Kristina Aaltonen

Abstract

Enumeration of circulating tumor cells (CTCs) obtained from minimally invasive blood samples has been well established as a valuable monitoring tool in metastatic and early breast cancer, as well as in several other cancer types. The gold standard technology for detecting CTCs in blood against a backdrop of millions of leukocytes is the FDA-approved CellSearch system (Janssen Diagnostics), which relies on EpCAM-based immunomagnetic separation. Secondary characterization of these cells could enable treatment selection based on specific targets in these cells, as well as providing a real time window into the metastatic process and offering unique insights into tumor heterogeneity. The objective of this study was to develop a method for downstream characterization of CTCs following isolation with the CellSearch system. An in vitro CTC model system focusing on clinically useful treatment predictive biomarkers in breast cancer, specifically the estrogen receptor α (ERα) and the human epidermal growth factor receptor 2 (HER2), was established using healthy donor blood spiked with breast cancer cell lines MCF7 (ERα(+)/HER2(-)) and SKBr3 (ERα(-)/HER2(+)). Following CTC isolation by CellSearch, the captured CTCs were further enriched and fixed on a microscope slide using the in-house-developed CTC-DropMount technique. The recovery rate of CTCs after CellSearch Profile analysis and CTC-DropMount was 87%. A selective and consistent triple-immunostaining protocol was optimized. Cells positive for DAPI, cytokeratin (CK) 8, 18 and 19, but negative for the leukocyte-specific marker CD45, were classified as CTCs and subsequently analyzed for ERα and HER2 expression. The method was verified in breast cancer patient samples, thus demonstrating its clinical relevance. Our results show that it is possible to ascertain the status of important predictive biomarkers expressed in breast cancer CTCs using the newly developed CTC-DropMount technique. Downstream characterization of multiple biomarkers using a standard fluorescence microscope demonstrates that important clinical and biological information may be obtained from a single patient blood sample following either CellSearch epithelial or profile analyses. Clinical Trials NCT01322893.

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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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 2%
Unknown 40 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 17%
Researcher 6 15%
Student > Bachelor 4 10%
Other 4 10%
Student > Master 4 10%
Other 8 20%
Unknown 8 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 22%
Medicine and Dentistry 9 22%
Biochemistry, Genetics and Molecular Biology 8 20%
Engineering 4 10%
Computer Science 1 2%
Other 2 5%
Unknown 8 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 December 2019.
All research outputs
#6,100,020
of 22,800,560 outputs
Outputs from Journal of Translational Medicine
#917
of 3,990 outputs
Outputs of similar age
#72,055
of 265,398 outputs
Outputs of similar age from Journal of Translational Medicine
#19
of 88 outputs
Altmetric has tracked 22,800,560 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 3,990 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 76% 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 265,398 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 72% of its contemporaries.
We're also able to compare this research output to 88 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.