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Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma[S]

Overview of attention for article published in Molecular and Cellular Proteomics, September 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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2 X users
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2 patents

Citations

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34 Dimensions

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Title
Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma[S]
Published in
Molecular and Cellular Proteomics, September 2015
DOI 10.1074/mcp.m115.050922
Pubmed ID
Authors

Alok K Shah, Kim-Anh Lê Cao, Eunju Choi, David Chen, Benoît Gautier, Derek Nancarrow, David C Whiteman, Nicholas A Saunders, Andrew P Barbour, Virendra Joshi, Michelle M Hill

Abstract

We report an integrated pipeline for efficient serum glycoprotein biomarker candidate discovery and qualification that may be used to facilitate cancer diagnosis and management. The discovery phase used semi-automated lectin magnetic bead array (LeMBA)-coupled tandem mass spectrometry with a dedicated data-housing and analysis pipeline; GlycoSelector (http://glycoselector.di.uq.edu.au). The qualification phase used LeMBA-multiple reaction monitoring-mass spectrometry incorporating an interactive web-interface, Shiny mixOmics (http://mixomics-projects.di.uq.edu.au/Shiny), for univariate and multivariate statistical analysis. Relative quantitation was performed by referencing to a spiked-in glycoprotein, chicken ovalbumin. We applied this workflow to identify diagnostic biomarkers for esophageal adenocarcinoma (EAC), a life threatening malignancy with poor prognosis in the advanced setting. EAC develops from metaplastic condition Barrett's esophagus (BE). Currently diagnosis and monitoring of at-risk patients is through endoscopy and biopsy which is expensive and requires hospital admission. Hence there is a clinical need for a noninvasive diagnostic biomarker of EAC. In total 89 patient samples from healthy controls, and patients with BE or EAC were screened in discovery and qualification stages. Of the 246 glycoforms measured in the qualification stage, 40 glycoforms (as measured by lectin affinity) qualified as candidate serum markers. The top candidate for distinguishing healthy from BE patients' group was Narcissus pseudonarcissus lectin (NPL)-reactive Apolipoprotein B-100 (P value=0.0231; AUROC=0.71); BE vs EAC, Aleuria aurantia lectin (AAL)-reactive complement component C9 (P value=0.0001; AUROC=0.85); healthy vs EAC, Erythroagglutinin Phaseolus vulgaris (EPHA)-reactive gelsolin (P value=0.0014; AUROC=0.80). A panel of 8 glycoforms showed an improved AUROC of 0.94 to discriminate EAC from BE. Two biomarker candidates were independently verified by LeMBA-immunoblotting, confirming the validity of the relative quantitation approach. Thus, we have identified candidate biomarkers which, following large-scale clinical evaluation, can be developed into diagnostic blood tests. A key feature of the pipeline is the potential for rapid translation of the candidate biomarkers to lectin-immunoassays.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
Unknown 44 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 22%
Student > Ph. D. Student 7 16%
Student > Master 4 9%
Other 3 7%
Student > Bachelor 3 7%
Other 10 22%
Unknown 8 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 18%
Agricultural and Biological Sciences 8 18%
Medicine and Dentistry 5 11%
Chemistry 3 7%
Immunology and Microbiology 2 4%
Other 11 24%
Unknown 8 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 April 2018.
All research outputs
#4,836,328
of 25,377,790 outputs
Outputs from Molecular and Cellular Proteomics
#938
of 3,220 outputs
Outputs of similar age
#58,476
of 285,947 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#20
of 63 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,220 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 69% 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 285,947 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 78% 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 68% of its contemporaries.