↓ Skip to main content

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets

Overview of attention for article published in Cancer Cell, August 2017
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)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
8 news outlets
blogs
1 blog
twitter
91 X users
patent
3 patents
facebook
5 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
230 Dimensions

Readers on

mendeley
397 Mendeley
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
Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets
Published in
Cancer Cell, August 2017
DOI 10.1016/j.ccell.2017.07.004
Pubmed ID
Authors

Myron G. Best, Nik Sol, Sjors G.J.G. In ‘t Veld, Adrienne Vancura, Mirte Muller, Anna-Larissa N. Niemeijer, Aniko V. Fejes, Lee-Ann Tjon Kon Fat, Anna E. Huis In ‘t Veld, Cyra Leurs, Tessa Y. Le Large, Laura L. Meijer, Irsan E. Kooi, François Rustenburg, Pepijn Schellen, Heleen Verschueren, Edward Post, Laurine E. Wedekind, Jillian Bracht, Michelle Esenkbrink, Leon Wils, Francesca Favaro, Jilian D. Schoonhoven, Jihane Tannous, Hanne Meijers-Heijboer, Geert Kazemier, Elisa Giovannetti, Jaap C. Reijneveld, Sander Idema, Joep Killestein, Michal Heger, Saskia C. de Jager, Rolf T. Urbanus, Imo E. Hoefer, Gerard Pasterkamp, Christine Mannhalter, Jose Gomez-Arroyo, Harm-Jan Bogaard, David P. Noske, W. Peter Vandertop, Daan van den Broek, Bauke Ylstra, R. Jonas A. Nilsson, Pieter Wesseling, Niki Karachaliou, Rafael Rosell, Elizabeth Lee-Lewandrowski, Kent B. Lewandrowski, Bakhos A. Tannous, Adrianus J. de Langen, Egbert F. Smit, Michel M. van den Heuvel, Thomas Wurdinger

Abstract

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

X Demographics

X Demographics

The data shown below were collected from the profiles of 91 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 397 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 397 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 73 18%
Student > Ph. D. Student 70 18%
Student > Master 41 10%
Student > Bachelor 32 8%
Other 28 7%
Other 58 15%
Unknown 95 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 88 22%
Medicine and Dentistry 76 19%
Agricultural and Biological Sciences 52 13%
Computer Science 24 6%
Engineering 12 3%
Other 28 7%
Unknown 117 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 118. 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 04 June 2023.
All research outputs
#356,951
of 25,559,053 outputs
Outputs from Cancer Cell
#200
of 3,167 outputs
Outputs of similar age
#7,563
of 327,933 outputs
Outputs of similar age from Cancer Cell
#5
of 36 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 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,167 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.4. This one has done particularly well, scoring higher than 93% 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 327,933 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 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.