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QSurface: fast identification of surface expression markers in cancers

Overview of attention for article published in BMC Systems Biology, March 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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3 X users
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1 patent

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7 Dimensions

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Title
QSurface: fast identification of surface expression markers in cancers
Published in
BMC Systems Biology, March 2018
DOI 10.1186/s12918-018-0541-6
Pubmed ID
Authors

Yourae Hong, Choa Park, Nayoung Kim, Juyeon Cho, Sung Ung Moon, Jongmin Kim, Euna Jeong, Sukjoon Yoon

Abstract

Cell surface proteins have provided useful targets and biomarkers for advanced cancer therapies. The recent clinical success of antibody-drug conjugates (ADCs) highlights the importance of finding selective surface antigens for given cancer subtypes. We thus attempted to develop stand-alone software for the analysis of the cell surface transcriptome of patient cancer samples and to prioritize lineage- and/or mutation-specific over-expression markers in cancer cells. A total of 519 genes were selected as surface proteins, and their expression was profiled in 14 cancer subtypes using patient sample transcriptome data. Lineage/mutation-oriented analysis was used to identify subtype-specific surface markers with statistical confidence. Experimental validation confirmed the unique over-expression of predicted surface markers (MUC4, MSLN, and SLC7A11) in lung cancer cells at the protein level. The differential cell surface gene expression of cell lines may differ from that of tissue samples due to the absence of the tumor microenvironment. In the present study, advanced 3D models of lung cell lines successfully reproduced the predicted patterns, demonstrating the physiological relevance of cell line-based 3D models in validating surface markers from patient tumor data. Also QSurface software is freely available at http://compbio.sookmyung.ac.kr/~qsurface .

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 32%
Student > Bachelor 4 21%
Researcher 3 16%
Other 2 11%
Student > Master 1 5%
Other 1 5%
Unknown 2 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 26%
Agricultural and Biological Sciences 4 21%
Computer Science 2 11%
Business, Management and Accounting 1 5%
Nursing and Health Professions 1 5%
Other 4 21%
Unknown 2 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 October 2022.
All research outputs
#6,093,815
of 23,482,849 outputs
Outputs from BMC Systems Biology
#199
of 1,144 outputs
Outputs of similar age
#106,242
of 333,509 outputs
Outputs of similar age from BMC Systems Biology
#10
of 43 outputs
Altmetric has tracked 23,482,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,144 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 81% 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 333,509 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.