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Identification of functional metabolic biomarkers from lung cancer patient serum using PEP technology

Overview of attention for article published in Biomarker Research, January 2016
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Title
Identification of functional metabolic biomarkers from lung cancer patient serum using PEP technology
Published in
Biomarker Research, January 2016
DOI 10.1186/s40364-016-0065-4
Pubmed ID
Authors

Sun, Zhenyu, Chen, Xiaofeng, Wang, Gan, Li, Liang, Fu, Guofeng, Kuruc, Matthew, Wang, Xing

Abstract

Reprogrammed metabolism is a new hallmark of cancer. In many types of cancer, most of the genes in the glycolytic pathway are overexpressed, reflecting an essential shift of metabolism during cancer development. The reprogrammed metabolism contributes to cancer development in multiple ways, from supplying the elevated energy requirement to creating a microenvironment suitable for tumor growth and suppressing the human immune surveillance system. In this study, a functional proteomics top-down approach was used to systematically monitor metabolic enzyme activities in resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. We found that the enrichment of low abundance proteins with a bead based product called AlbuVoid™(,) is important to increase the number of observable features and to increase the level of signal achievable from the assay used. From our methods, significant metabolic enzyme activities were detected in both normal and lung cancer patient sera in many fractions after the elution of the 2-D gel separated proteins to the Protein Elution Plate (PEP). Eighteen fractions with the most dramatic metabolic enzyme activity difference between the normal and lung cancer patient sera were submitted for mass spectrometry protein identification. Proteins from the glycolytic metabolic pathway, such as GAPDH along with other proteins not previously annotated to the glycolytic pathway were identified. Further verification with commercially purified GAPDH showed that the addition of purified GAPDH to the metabolic enzyme assay system employed enhanced the enzyme activity, demonstrating that proteins identified from the PEP technology and mass spectrometry could be further verified with biological assay. This study identified several potential functional enzyme biomarkers from lung cancer patient serum, it provides an alternative and complementary approach to sequence annotation for the discovery of biomarkers in human diseases.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Ph. D. Student 2 18%
Lecturer 1 9%
Student > Bachelor 1 9%
Student > Master 1 9%
Other 2 18%
Unknown 1 9%
Readers by discipline Count As %
Medicine and Dentistry 4 36%
Biochemistry, Genetics and Molecular Biology 2 18%
Materials Science 2 18%
Mathematics 1 9%
Agricultural and Biological Sciences 1 9%
Other 0 0%
Unknown 1 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 03 June 2016.
All research outputs
#6,799,087
of 7,849,747 outputs
Outputs from Biomarker Research
#48
of 61 outputs
Outputs of similar age
#224,334
of 269,243 outputs
Outputs of similar age from Biomarker Research
#2
of 3 outputs
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So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 1.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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