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High-Content Monitoring of Drug Effects in a 3D Spheroid Model

Overview of attention for article published in Frontiers in oncology, December 2017
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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1 news outlet
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1 X user

Citations

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129 Dimensions

Readers on

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326 Mendeley
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Title
High-Content Monitoring of Drug Effects in a 3D Spheroid Model
Published in
Frontiers in oncology, December 2017
DOI 10.3389/fonc.2017.00293
Pubmed ID
Authors

Frédérique Mittler, Patricia Obeïd, Anastasia V. Rulina, Vincent Haguet, Xavier Gidrol, Maxim Y. Balakirev

Abstract

A recent decline in the discovery of novel medications challenges the widespread use of 2D monolayer cell assays in the drug discovery process. As a result, the need for more appropriate cellular models of human physiology and disease has renewed the interest in spheroid 3D culture as a pertinent model for drug screening. However, despite technological progress that has significantly simplified spheroid production and analysis, the seeming complexity of the 3D approach has delayed its adoption in many laboratories. The present report demonstrates that the use of a spheroid model may be straightforward and can provide information that is not directly available with a standard 2D approach. We describe a cost-efficient method that allows for the production of an array of uniform spheroids, their staining with vital dyes, real-time monitoring of drug effects, and an ATP-endpoint assay, all in the same 96-well U-bottom plate. To demonstrate the method performance, we analyzed the effect of the preclinical anticancer drug MLN4924 on spheroids formed by VCaP and LNCaP prostate cancer cells. The drug has different outcomes in these cell lines, varying from cell cycle arrest and protective dormancy to senescence and apoptosis. We demonstrate that by using high-content analysis of spheroid arrays, the effect of the drug can be described as a series of EC50 values that clearly dissect the cytostatic and cytotoxic drug actions. The method was further evaluated using four standard cancer chemotherapeutics with different mechanisms of action, and the effect of each drug is described as a unique multi-EC50 diagram. Once fully validated in a wider range of conditions, this method could be particularly valuable for phenotype-based drug discovery.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 326 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 326 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 16%
Researcher 47 14%
Student > Master 41 13%
Student > Bachelor 33 10%
Student > Postgraduate 13 4%
Other 36 11%
Unknown 103 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 82 25%
Agricultural and Biological Sciences 32 10%
Engineering 22 7%
Pharmacology, Toxicology and Pharmaceutical Science 16 5%
Medicine and Dentistry 13 4%
Other 43 13%
Unknown 118 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 June 2023.
All research outputs
#3,411,404
of 26,160,558 outputs
Outputs from Frontiers in oncology
#975
of 22,911 outputs
Outputs of similar age
#69,313
of 450,214 outputs
Outputs of similar age from Frontiers in oncology
#6
of 85 outputs
Altmetric has tracked 26,160,558 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 22,911 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 95% 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 450,214 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 84% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.