Quantitative proteomics for identification of cancer biomarkers

Authors

  • Raghothama Chaerkady,

    1. Institute of Bioinformatics, International Technology Park, Bangalore, India
    2. Departments of Biological Chemistry, Pathology and Oncology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
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  • Akhilesh Pandey Dr.

    Corresponding author
    1. Departments of Biological Chemistry, Pathology and Oncology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
    • McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, 733 North Broadway, Baltimore, MD 21205, USA Fax: +1-410-502-7544
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Abstract

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and 18O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.

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