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Circulating tumor DNA analysis depicts subclonal architecture and genomic evolution of small cell lung cancer

Overview of attention for article published in Nature Communications, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

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43 X users
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1 patent
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1 Facebook page

Citations

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126 Dimensions

Readers on

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135 Mendeley
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Title
Circulating tumor DNA analysis depicts subclonal architecture and genomic evolution of small cell lung cancer
Published in
Nature Communications, August 2018
DOI 10.1038/s41467-018-05327-w
Pubmed ID
Authors

Jingying Nong, Yuhua Gong, Yanfang Guan, Xin Yi, Yuting Yi, Lianpeng Chang, Ling Yang, Jialin Lv, Zhirong Guo, Hongyan Jia, Yuxing Chu, Tao Liu, Ming Chen, Lauren Byers, Emily Roarty, Vincent K. Lam, Vassiliki A. Papadimitrakopoulou, Ignacio Wistuba, John V. Heymach, Bonnie Glisson, Zhongxing Liao, J. Jack Lee, P. Andrew Futreal, Shucai Zhang, Xuefeng Xia, Jianjun Zhang, Jinghui Wang

Abstract

Subclonal architecture and genomic evolution of small-cell lung cancer (SCLC) under treatment has not been well studied primarily due to lack of tumor specimens, particularly longitudinal samples acquired during treatment. SCLC is characterized by early hematogenous spread, which makes circulating cell-free tumor DNA (ctDNA) sequencing a promising modality for genomic profiling. Here, we perform targeted deep sequencing of 430 cancer genes on pre-treatment tumor biopsies, as well as on plasma samples collected prior to and during treatment from 22 SCLC patients. Similar subclonal architecture is observed between pre-treatment ctDNA and paired tumor DNA. Mean variant allele frequency of clonal mutations from pre-treatment ctDNA is associated with progression-free survival and overall survival. Pre- and post-treatment ctDNA mutational analysis demonstrate that mutations of DNA repair and NOTCH signaling pathways are enriched in post-treatment samples. These data suggest that ctDNA sequencing is promising to delineate genomic landscape, subclonal architecture, and genomic evolution of SCLC.

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 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 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 135 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 20%
Student > Ph. D. Student 20 15%
Student > Bachelor 14 10%
Other 12 9%
Student > Doctoral Student 7 5%
Other 16 12%
Unknown 39 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 34 25%
Medicine and Dentistry 30 22%
Agricultural and Biological Sciences 12 9%
Immunology and Microbiology 3 2%
Engineering 3 2%
Other 6 4%
Unknown 47 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 25 February 2021.
All research outputs
#1,548,033
of 25,559,053 outputs
Outputs from Nature Communications
#22,314
of 57,618 outputs
Outputs of similar age
#31,550
of 341,145 outputs
Outputs of similar age from Nature Communications
#552
of 1,333 outputs
Altmetric has tracked 25,559,053 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 57,618 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.5. This one has gotten more attention than average, scoring higher than 61% 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 341,145 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 90% of its contemporaries.
We're also able to compare this research output to 1,333 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 58% of its contemporaries.