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Genomic Landscape of Non-Small Cell Lung Cancer in Smokers and Never-Smokers

Overview of attention for article published in Cell, September 2012
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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
1 news outlet
blogs
2 blogs
twitter
534 tweeters
patent
8 patents
facebook
4 Facebook pages

Citations

dimensions_citation
581 Dimensions

Readers on

mendeley
583 Mendeley
citeulike
3 CiteULike
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Title
Genomic Landscape of Non-Small Cell Lung Cancer in Smokers and Never-Smokers
Published in
Cell, September 2012
DOI 10.1016/j.cell.2012.08.024
Pubmed ID
Authors

Ramaswamy Govindan, Li Ding, Malachi Griffith, Janakiraman Subramanian, Nathan D. Dees, Krishna L. Kanchi, Christopher A. Maher, Robert Fulton, Lucinda Fulton, John Wallis, Ken Chen, Jason Walker, Sandra McDonald, Ron Bose, David Ornitz, Donghai Xiong, Ming You, David J. Dooling, Mark Watson, Elaine R. Mardis, Richard K. Wilson

Abstract

We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.

Twitter Demographics

The data shown below were collected from the profiles of 534 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 583 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 2%
Japan 6 1%
United Kingdom 6 1%
Italy 5 <1%
Canada 3 <1%
China 3 <1%
Netherlands 3 <1%
Korea, Republic of 2 <1%
Germany 2 <1%
Other 8 1%
Unknown 531 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 166 28%
Researcher 159 27%
Student > Master 53 9%
Student > Bachelor 44 8%
Professor > Associate Professor 33 6%
Other 128 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 285 49%
Medicine and Dentistry 129 22%
Biochemistry, Genetics and Molecular Biology 84 14%
Unspecified 33 6%
Computer Science 11 2%
Other 41 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 261. 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 21 June 2018.
All research outputs
#38,180
of 12,010,149 outputs
Outputs from Cell
#233
of 14,336 outputs
Outputs of similar age
#254
of 117,333 outputs
Outputs of similar age from Cell
#2
of 53 outputs
Altmetric has tracked 12,010,149 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 14,336 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.3. 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 117,333 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 53 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.