title: Identification of functional metabolic biomarkers from lung cancer patient serum using PEP technology.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: The Third Hospital Affiliated to Nantong University School of Medicine, Wuxi, China.
authors.forename: Zhenyu
authors.initials: Z
authors.lastname: Sun
authors.affiliation: Shanghai Huashan Hospital, Fudan University School of Medicine, Shanghai, China.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Chen
authors.affiliation: Institute of Environmental Health Sciences, Wayne State University, 259 Mack Avenue, Detroit, MI 48201 USA.
authors.forename: Gan
authors.initials: G
authors.lastname: Wang
authors.affiliation: Zibo Central Hospital, Zibo, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Li
authors.affiliation: Array Bridge Inc, St. Louis, USA.
authors.forename: Guofeng
authors.initials: G
authors.lastname: Fu
authors.affiliation: Biotech Support Group, LLC, Monmouth Junction, NJ USA.
authors.forename: Matthew
authors.initials: M
authors.lastname: Kuruc
authors.affiliation: Array Bridge Inc, St. Louis, USA.
authors.forename: Xing
authors.initials: X
authors.lastname: Wang
keywords: Biomarkers; Cancer metabolism; Enzyme profile; Functional proteomics; Lung cancer; Protein Elution Plates (PEP); Two-dimensional Gel Electrophoresis (2-D Gel)