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Collateral sensitivity networks reveal evolutionary instability and novel treatment strategies in ALK mutated non-small cell lung cancer

Overview of attention for article published in Scientific Reports, April 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
6 news outlets
blogs
4 blogs
twitter
59 X users
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
87 Dimensions

Readers on

mendeley
89 Mendeley
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Title
Collateral sensitivity networks reveal evolutionary instability and novel treatment strategies in ALK mutated non-small cell lung cancer
Published in
Scientific Reports, April 2017
DOI 10.1038/s41598-017-00791-8
Pubmed ID
Authors

Andrew Dhawan, Daniel Nichol, Fumi Kinose, Mohamed E. Abazeed, Andriy Marusyk, Eric B. Haura, Jacob G. Scott

Abstract

Drug resistance remains an elusive problem in cancer therapy, particularly for novel targeted therapies. Much work is focused upon the development of an arsenal of targeted therapies, towards oncogenic driver genes such as ALK-EML4, to overcome the inevitable resistance that develops over time. Currently, after failure of first line ALK TKI therapy, another ALK TKI is administered, though collateral sensitivity is not considered. To address this, we evolved resistance in an ALK rearranged non-small cell lung cancer line (H3122) to a panel of 4 ALK TKIs, and performed a collateral sensitivity analysis. All ALK inhibitor resistant cell lines displayed significant cross-resistance to all other ALK inhibitors. We then evaluated ALK-inhibitor sensitivities after drug holidays of varying length (1-21 days), and observed dynamic patterns of resistance. This unpredictability led us to an expanded search for treatment options, where we tested 6 further anti-cancer agents for collateral sensitivity among resistant cells, uncovering possibilities for further treatment, including cross-sensitivity to standard cytotoxic therapies, as well as Hsp90 inhibitors. Taken together, these results imply that resistance to targeted therapy in non-small cell lung cancer is highly dynamic, and also one where there are many opportunities to re-establish sensitivities where there was once resistance. Drug resistance in cancer inevitably emerges during treatment; particularly with novel targeted therapies, designed to inhibit specific molecules. A clinically-relevant example of this phenomenon occurs in ALK-positive non-small cell lung cancer, where targeted therapies are used to inhibit the ALK-EML4 fusion protein. A potential solution to this may lie in finding drug sensitivities in the resistant population, termed collateral sensitivities, and then using these as second-line agents. This study shows how the evolution of resistance in ALK-positive lung cancer is a dynamic process through time, one in which patterns of drug resistance and collateral sensitivity change substantially, and therefore one where temporal regimens, such as drug cycling and drug holidays may have great benefit.

X Demographics

X Demographics

The data shown below were collected from the profiles of 59 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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 28%
Researcher 14 16%
Student > Bachelor 12 13%
Student > Doctoral Student 5 6%
Professor > Associate Professor 5 6%
Other 15 17%
Unknown 13 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 21%
Biochemistry, Genetics and Molecular Biology 16 18%
Medicine and Dentistry 16 18%
Mathematics 5 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Other 12 13%
Unknown 17 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 99. 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 03 November 2022.
All research outputs
#429,435
of 25,539,438 outputs
Outputs from Scientific Reports
#4,763
of 141,623 outputs
Outputs of similar age
#8,917
of 323,822 outputs
Outputs of similar age from Scientific Reports
#156
of 4,114 outputs
Altmetric has tracked 25,539,438 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 141,623 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one has done particularly well, scoring higher than 96% 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 323,822 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 4,114 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 96% of its contemporaries.