| Literature DB >> 25778709 |
Tsung-Heng Tsai1, Ehwang Song2, Rui Zhu2, Cristina Di Poto1, Minkun Wang1, Yue Luo1, Rency S Varghese1, Mahlet G Tadesse3, Dina Hazem Ziada4, Chirag S Desai5, Kirti Shetty6, Yehia Mechref2, Habtom W Ressom1.
Abstract
Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label-free proteomic analysis by LC-MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC-associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 (http://proteomecentral.proteomexchange.org/dataset/PXD001171).Entities:
Keywords: Biomedicine; Cancer biomarker discovery; Hepatocellular carcinoma; LC-MS/MS; Liver cirrhosis; MRM
Mesh:
Year: 2015 PMID: 25778709 PMCID: PMC4490019 DOI: 10.1002/pmic.201400364
Source DB: PubMed Journal: Proteomics ISSN: 1615-9853 Impact factor: 3.984