↓ Skip to main content

Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition

Overview of attention for article published in Nature Medicine, February 2016
Altmetric Badge

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)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
120 X users
patent
10 patents
facebook
4 Facebook pages

Citations

dimensions_citation
763 Dimensions

Readers on

mendeley
829 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition
Published in
Nature Medicine, February 2016
DOI 10.1038/nm.4040
Pubmed ID
Authors

Aaron N Hata, Matthew J Niederst, Hannah L Archibald, Maria Gomez-Caraballo, Faria M Siddiqui, Hillary E Mulvey, Yosef E Maruvka, Fei Ji, Hyo-eun C Bhang, Viveksagar Krishnamurthy Radhakrishna, Giulia Siravegna, Haichuan Hu, Sana Raoof, Elizabeth Lockerman, Anuj Kalsy, Dana Lee, Celina L Keating, David A Ruddy, Leah J Damon, Adam S Crystal, Carlotta Costa, Zofia Piotrowska, Alberto Bardelli, Anthony J Iafrate, Ruslan I Sadreyev, Frank Stegmeier, Gad Getz, Lecia V Sequist, Anthony C Faber, Jeffrey A Engelman

Abstract

Although mechanisms of acquired resistance of epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancers to EGFR inhibitors have been identified, little is known about how resistant clones evolve during drug therapy. Here we observe that acquired resistance caused by the EGFR(T790M) gatekeeper mutation can occur either by selection of pre-existing EGFR(T790M)-positive clones or via genetic evolution of initially EGFR(T790M)-negative drug-tolerant cells. The path to resistance impacts the biology of the resistant clone, as those that evolved from drug-tolerant cells had a diminished apoptotic response to third-generation EGFR inhibitors that target EGFR(T790M); treatment with navitoclax, an inhibitor of the anti-apoptotic factors BCL-xL and BCL-2 restored sensitivity. We corroborated these findings using cultures derived directly from EGFR inhibitor-resistant patient tumors. These findings provide evidence that clinically relevant drug-resistant cancer cells can both pre-exist and evolve from drug-tolerant cells, and they point to therapeutic opportunities to prevent or overcome resistance in the clinic.

X Demographics

X Demographics

The data shown below were collected from the profiles of 120 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 829 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 1%
United Kingdom 6 <1%
Germany 3 <1%
Japan 2 <1%
Canada 2 <1%
Spain 2 <1%
Netherlands 1 <1%
Belgium 1 <1%
Switzerland 1 <1%
Other 3 <1%
Unknown 797 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 189 23%
Student > Ph. D. Student 188 23%
Student > Master 90 11%
Student > Bachelor 57 7%
Student > Doctoral Student 42 5%
Other 120 14%
Unknown 143 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 262 32%
Agricultural and Biological Sciences 172 21%
Medicine and Dentistry 119 14%
Pharmacology, Toxicology and Pharmaceutical Science 28 3%
Chemistry 17 2%
Other 73 9%
Unknown 158 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 74. 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 06 July 2023.
All research outputs
#573,873
of 25,381,783 outputs
Outputs from Nature Medicine
#1,796
of 9,291 outputs
Outputs of similar age
#10,449
of 409,384 outputs
Outputs of similar age from Nature Medicine
#24
of 63 outputs
Altmetric has tracked 25,381,783 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 9,291 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 105.0. This one has done well, scoring higher than 80% 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 409,384 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 63 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 63% of its contemporaries.