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The stepwise evolution of the exome during acquisition of docetaxel resistance in breast cancer cells

Overview of attention for article published in BMC Genomics, June 2016
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

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5 tweeters

Citations

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15 Dimensions

Readers on

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59 Mendeley
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Title
The stepwise evolution of the exome during acquisition of docetaxel resistance in breast cancer cells
Published in
BMC Genomics, June 2016
DOI 10.1186/s12864-016-2749-4
Pubmed ID
Authors

Stine Ninel Hansen, Natasja Spring Ehlers, Shida Zhu, Mathilde Borg Houlberg Thomsen, Rikke Linnemann Nielsen, Dongbing Liu, Guangbiao Wang, Yong Hou, Xiuqing Zhang, Xun Xu, Lars Bolund, Huanming Yang, Jun Wang, Jose Moreira, Henrik J Ditzel, Nils Brünner, Anne-Sofie Schrohl, Jan Stenvang, Ramneek Gupta

Abstract

Resistance to taxane-based therapy in breast cancer patients is a major clinical problem that may be addressed through insight of the genomic alterations leading to taxane resistance in breast cancer cells. In the current study we used whole exome sequencing to discover somatic genomic alterations, evolving across evolutionary stages during the acquisition of docetaxel resistance in breast cancer cell lines. Two human breast cancer in vitro models (MCF-7 and MDA-MB-231) of the step-wise acquisition of docetaxel resistance were developed by exposing cells to 18 gradually increasing concentrations of docetaxel. Whole exome sequencing performed at five successive stages during this process was used to identify single point mutational events, insertions/deletions and copy number alterations associated with the acquisition of docetaxel resistance. Acquired coding variation undergoing positive selection and harboring characteristics likely to be functional were further prioritized using network-based approaches. A number of genomic changes were found to be undergoing evolutionary selection, some of which were likely to be functional. Of the five stages of progression toward resistance, most resistance relevant genomic variation appeared to arise midway towards fully resistant cells corresponding to passage 31 (5 nM docetaxel) for MDA-MB-231 and passage 16 (1.2 nM docetaxel) for MCF-7, and where the cells also exhibited a period of reduced growth rate or arrest, respectively. MCF-7 cell acquired several copy number gains on chromosome 7, including ABC transporter genes, including ABCB1 and ABCB4, as well as DMTF1, CLDN12, CROT, and SRI. For MDA-MB-231 numerous copy number losses on chromosome X involving more than 30 genes was observed. Of these genes, CASK, POLA1, PRDX4, MED14 and PIGA were highly prioritized by the applied network-based gene ranking approach. At higher docetaxel concentration MCF-7 subclones exhibited a copy number loss in E2F4, and the gene encoding this important transcription factor was down-regulated in MCF-7 resistant cells. Our study of the evolution of acquired docetaxel resistance identified several genomic changes that might explain development of docetaxel resistance. Interestingly, the most relevant resistance-associated changes appeared to originate midway through the evolution towards fully resistant cell lines. Our data suggest that no single genomic event sufficiently predicts resistance to docetaxel, but require genomic alterations affecting multiple pathways that in concert establish the final resistance stage.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Belgium 1 2%
Canada 1 2%
Unknown 56 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 16 27%
Student > Ph. D. Student 10 17%
Researcher 9 15%
Professor > Associate Professor 5 8%
Professor 5 8%
Other 8 14%
Unknown 6 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 47%
Agricultural and Biological Sciences 10 17%
Medicine and Dentistry 5 8%
Engineering 3 5%
Computer Science 2 3%
Other 2 3%
Unknown 9 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 June 2016.
All research outputs
#3,251,484
of 7,879,571 outputs
Outputs from BMC Genomics
#2,381
of 5,660 outputs
Outputs of similar age
#101,442
of 268,688 outputs
Outputs of similar age from BMC Genomics
#85
of 181 outputs
Altmetric has tracked 7,879,571 research outputs across all sources so far. This one has received more attention than most of these and is in the 58th percentile.
So far Altmetric has tracked 5,660 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 55% 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 268,688 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 61% of its contemporaries.
We're also able to compare this research output to 181 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.