Combinatorial Chemistry & High Throughput Screening

Author(s): Shufang Liang, Zhizhong Xu, Xuejiao Xu, Xia Zhao, Canhua Huang and Yuquan Wei

DOI: 10.2174/138620712799218635

Quantitative Proteomics for Cancer Biomarker Discovery

Page: [221 - 231] Pages: 11

  • * (Excluding Mailing and Handling)

Abstract

The mass spectrometry (MS)-based quantitative proteomics is powerful to discover disease biomarkers that can provide diagnostic, prognostic and therapeutic targets, and it also can address important problems in clinical and translational medical research. The current status of MS-based quantification strategy and technical advances of several main quantitative assays (two-dimensional (2-D) gel-based methods, stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tag (ICAT), the isobaric tags for relative and absolute quantification (iTRAQ),18O labeling, absolute quantitation and label-free quantitation) have been summarized and reviewed. At present, except 2-D gel-based methods, several stable isotope labeling quantitative techniques, including SILAC, ICAT and iTRAQ, etc, have been widely applied in identification of differential expression of proteins, post-translational modifications and protein-protein interactions in order to look for novel candidate cancer biomarkers from different physiological states of cells, body fluids or tissue samples. Also, the advantages and challenges of different quantitative proteomic approaches are discussed in identification and validation of candidate targets.

Keywords: Absolute quantitation, cancer biomarker, ICAT, iTRAQ, label-free quantitation, quantitative proteomics, SILAC, mass spectrometry, biological molecule, hepatocellular carcinoma (HCC),, mortality, morbidity, isotope, post-translational modifications (PTMs), protein-protein interactions (PPIs), body fluids, metabolic labeling, chemical labeling), chemical manipulations, protein expression