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Evaluation of two high-throughput proteomic technologies for plasma biomarker discovery in immunotherapy-treated melanoma patients

Overview of attention for article published in Biomarker Research, November 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#21 of 320)
  • High Attention Score compared to outputs of the same age (84th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
facebook
1 Facebook page

Citations

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35 Dimensions

Readers on

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52 Mendeley
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Title
Evaluation of two high-throughput proteomic technologies for plasma biomarker discovery in immunotherapy-treated melanoma patients
Published in
Biomarker Research, November 2017
DOI 10.1186/s40364-017-0112-9
Pubmed ID
Authors

Su Yin Lim, Jenny H. Lee, Sarah J. Welsh, Seong Beom Ahn, Edmond Breen, Alamgir Khan, Matteo S. Carlino, Alexander M. Menzies, Richard F. Kefford, Richard A. Scolyer, Georgina V. Long, Helen Rizos

Abstract

Selective kinase and immune checkpoint inhibitors, and their combinations, have significantly improved the survival of patients with advanced metastatic melanoma. Not all patients will respond to treatment however, and some patients will present with significant toxicities. Hence, the identification of biomarkers is critical for the selection and management of patients receiving treatment. Biomarker discovery often involves proteomic techniques that simultaneously profile multiple proteins but few studies have compared these platforms. In this study, we used the multiplex bead-based Eve Technologies Discovery assay and the aptamer-based SomaLogic SOMAscan assay to identify circulating proteins predictive of response to immunotherapy in melanoma patients treated with combination immune checkpoint inhibitors. Expression of four plasma proteins were further validated using the bead-based Millipore Milliplex assay. Both the Discovery and the SOMAscan assays detected circulating plasma proteins in immunotherapy-treated melanoma patients. However, these widely used assays showed limited correlation in relative protein quantification, due to differences in specificity and the dynamic range of protein detection. Protein data derived from the Discovery and Milliplex bead-based assays were highly correlated. Our study highlights significant limitations imposed by inconsistent sensitivity and specificity due to differences in the detection antibodies or aptamers of these widespread biomarker discovery approaches. Our findings emphasize the need to improve these technologies for the accurate identification of biomarkers.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 31%
Researcher 11 21%
Professor 4 8%
Other 4 8%
Student > Bachelor 2 4%
Other 6 12%
Unknown 9 17%
Readers by discipline Count As %
Medicine and Dentistry 10 19%
Biochemistry, Genetics and Molecular Biology 8 15%
Immunology and Microbiology 6 12%
Agricultural and Biological Sciences 5 10%
Chemistry 2 4%
Other 8 15%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 May 2019.
All research outputs
#2,436,748
of 23,007,887 outputs
Outputs from Biomarker Research
#21
of 320 outputs
Outputs of similar age
#49,685
of 328,166 outputs
Outputs of similar age from Biomarker Research
#1
of 3 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 320 research outputs from this source. They receive a mean Attention Score of 4.4. 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 328,166 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them