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Assessing breast cancer cell lines as tumour models by comparison of mRNA expression profiles

Overview of attention for article published in Breast Cancer Research, August 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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9 X users

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Title
Assessing breast cancer cell lines as tumour models by comparison of mRNA expression profiles
Published in
Breast Cancer Research, August 2015
DOI 10.1186/s13058-015-0613-0
Pubmed ID
Authors

Krista Marie Vincent, Scott D. Findlay, Lynne Marie Postovit

Abstract

Breast cancer researchers use cell lines to model myriad phenomena ranging from DNA repair to cancer stem cell phenotypes. Though appropriate, and even requisite, for many studies, the suitability of cell lines as tumour models has come into question owing to possibilities of tissue culture artefacts and clonal selection. These issues are compounded by the inability of cancer cells grown in isolation to fully model the in situ tumour environment, which also contains a plethora of non-tumour cell types. It is thus important to understand similarities and differences between cancer cell lines and the tumours that they represent so that the optimal tumour models can be chosen to answer specific research questions. In the present study, we compared the RNA-sequencing transcriptomes of a collection of breast cancer cell lines to transcriptomes obtained from hundreds of tumours using The Cancer Genome Atlas. Tumour purity was accounted for by analysis of stromal and immune scores using the ESTIMATE algorithm so that differences likely resulting from non-tumour cells could be accounted for. We found the transcriptional characteristics of breast cancer cell lines to mirror those of the tumours. We identified basal and luminal cell lines that are most transcriptionally similar to their respective breast tumours. Our comparison of expression profiles revealed pronounced differences between breast cancer cell lines and tumours, which could largely be attributed to the absence of stromal and immune components in cell culture. A focus on the Wnt pathway revealed the transcriptional downregulation or absence of several secreted Wnt antagonists in culture. Gene set enrichment analysis suggests that cancer cell lines have enhanced proliferation and glycolysis independent of stromal and immune contributions compared with breast cancer cells in situ. This study demonstrates that many of the differences between breast cancer cell lines and tumours are due to the absence of stromal and immune components in vitro. Hence, extra precautions should be taken when modelling extracellular proteins in vitro. The specific differences discovered emphasize the importance of choosing an appropriate model for each research question.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 2%
United States 1 1%
Brazil 1 1%
Unknown 95 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 21%
Researcher 17 17%
Student > Master 12 12%
Student > Bachelor 6 6%
Student > Doctoral Student 5 5%
Other 21 21%
Unknown 17 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 30%
Agricultural and Biological Sciences 23 23%
Medicine and Dentistry 7 7%
Computer Science 5 5%
Engineering 4 4%
Other 7 7%
Unknown 23 23%
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 22 April 2016.
All research outputs
#7,119,031
of 25,373,627 outputs
Outputs from Breast Cancer Research
#818
of 2,052 outputs
Outputs of similar age
#77,133
of 277,478 outputs
Outputs of similar age from Breast Cancer Research
#20
of 42 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,052 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has gotten more attention than average, scoring higher than 60% 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 277,478 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 42 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 52% of its contemporaries.