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Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells*

Overview of attention for article published in Molecular and Cellular Proteomics, September 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 3,221)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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8 news outlets
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19 X users

Citations

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18 Dimensions

Readers on

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26 Mendeley
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Title
Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells*
Published in
Molecular and Cellular Proteomics, September 2018
DOI 10.1074/mcp.ra118.000713
Pubmed ID
Authors

Claudia Ctortecka, Vinayak Palve, Brent M Kuenzi, Bin Fang, Natalia J Sumi, Victoria Izumi, Silvia Novakova, Fumi Kinose, Lily L Remsing Rix, Eric B Haura, John Matthew Koomen, Uwe Rix

Abstract

Lung cancer is associated with high prevalence and mortality, and despite significant successes with targeted drugs in genomically defined subsets of lung cancer and immunotherapy, the majority of patients currently does not benefit from these therapies. Through a targeted drug screen, we found the recently approved multi-kinase inhibitor midostaurin to have potent activity in several lung cancer cells independent of its intended target, PKC, or a specific genomic marker. To determine the underlying mechanism of action we applied a layered functional proteomics approach and a new data integration method. Using chemical proteomics, we identified multiple midostaurin kinase targets in these cells. Network-based integration of these targets with quantitative tyrosine and global phosphoproteomics data using protein-protein interactions from the STRING database suggested multiple targets are relevant for the mode of action of midostaurin. Subsequent functional validation using RNA interference and selective small molecule probes showed that simultaneous inhibition of TBK1, PDPK1 and AURKA was required to elicit midostaurin's cellular effects. Immunoblot analysis of downstream signaling nodes showed that combined inhibition of these targets altered PI3K/AKT and cell cycle signaling pathways that in part converged on PLK1. Furthermore, rational combination of midostaurin with the potent PLK1 inhibitor BI2536 elicited strong synergy. Our results demonstrate that combination of complementary functional proteomics approaches and subsequent network-based data integration can reveal novel insight into the complex mode of action of multi-kinase inhibitors, actionable targets for drug discovery and cancer vulnerabilities. Finally, we illustrate how this knowledge can be utilized for the rational design of synergistic drug combinations with high potential for clinical translation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 15%
Student > Doctoral Student 3 12%
Student > Master 3 12%
Student > Bachelor 2 8%
Researcher 2 8%
Other 2 8%
Unknown 10 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 19%
Agricultural and Biological Sciences 2 8%
Chemistry 2 8%
Medicine and Dentistry 2 8%
Computer Science 1 4%
Other 3 12%
Unknown 11 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 63. 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 December 2018.
All research outputs
#673,050
of 25,385,509 outputs
Outputs from Molecular and Cellular Proteomics
#37
of 3,221 outputs
Outputs of similar age
#14,423
of 348,075 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#4
of 48 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,221 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 98% 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 348,075 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 95% of its contemporaries.
We're also able to compare this research output to 48 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 91% of its contemporaries.