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Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, December 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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
50 news outlets
twitter
3 tweeters

Citations

dimensions_citation
85 Dimensions

Readers on

mendeley
182 Mendeley
Title
Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance
Published in
Proceedings of the National Academy of Sciences of the United States of America, December 2017
DOI 10.1073/pnas.1712064115
Pubmed ID
Authors

Yapeng Su, Wei, Lidia Robert, Min Xue, Jennifer Tsoi, Angel Garcia-Diaz, Blanca Homet Moreno, Jungwoo Kim, Rachel H. Ng, Jihoon W. Lee, Richard C. Koya, Begonya Comin-Anduix, Thomas G. Graeber, Antoni Ribas, James R. Heath

Abstract

Continuous BRAF inhibition of BRAF mutant melanomas triggers a series of cell state changes that lead to therapy resistance and escape from immune control before establishing acquired resistance genetically. We used genome-wide transcriptomics and single-cell phenotyping to explore the response kinetics to BRAF inhibition for a panel of patient-derived BRAFV600 -mutant melanoma cell lines. A subset of plastic cell lines, which followed a trajectory covering multiple known cell state transitions, provided models for more detailed biophysical investigations. Markov modeling revealed that the cell state transitions were reversible and mediated by both Lamarckian induction and nongenetic Darwinian selection of drug-tolerant states. Single-cell functional proteomics revealed activation of certain signaling networks shortly after BRAF inhibition, and before the appearance of drug-resistant phenotypes. Drug targeting those networks, in combination with BRAF inhibition, halted the adaptive transition and led to prolonged growth inhibition in multiple patient-derived cell lines.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 182 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 58 32%
Researcher 39 21%
Student > Bachelor 13 7%
Student > Master 11 6%
Student > Postgraduate 10 5%
Other 22 12%
Unknown 29 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 67 37%
Agricultural and Biological Sciences 36 20%
Engineering 10 5%
Chemistry 9 5%
Medicine and Dentistry 7 4%
Other 18 10%
Unknown 35 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 393. 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 28 December 2017.
All research outputs
#22,563
of 12,357,782 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#613
of 77,292 outputs
Outputs of similar age
#1,421
of 350,383 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#35
of 914 outputs
Altmetric has tracked 12,357,782 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 77,292 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.0. This one has done particularly well, scoring higher than 99% 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 350,383 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 99% of its contemporaries.
We're also able to compare this research output to 914 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.