Journal of Proteome Research · 2007 · 46 citations · 18 references
PharmacyBiochemistryChromatographic AnalysisMass Spectrometric AnalysisProteomicsLiquid ChromatographyMass SpectrometryMass Spectrometry-based ProteomicsPeptide AnalysisPeptide IdentificationBiomarkersLiquid Chromatography-mass SpectrometryMaldi-tof IdentificationMaldi-tof Mass SpectrometryPeptide Mass SpectrometryPeptide SeparationSize-exclusion ColumnsSize-exclusion Liquid Chromatography
Peptidome analysis has received increasing attention in recent years. Cancer diagnosis by serum peptidome has also been reported by peptides' profiling for discovery of peptide biomarkers. Tissue, which may have a higher biomarker concentration than blood, has not been investigated extensively by means of peptidome analysis. Here, a method for the peptidome analysis of mouse liver was developed by the combination of size exclusion chromatography (SEC) prefractionation with nano-liquid chromatography-tamdem mass spectrometry (nanoLC-MS/MS) analysis. The extracted peptides from mouse liver were separated according to their molecular weight using a size exclusion column. MALDI-TOF MS was used to characterize the molecular weight distribution of the peptides in fractions eluted from the SEC column. The low molecular weight (LMW) (MW < 3000 Da) peptides in the collected fractions were directly analyzed by LC-MS/MS which resulted in the identification of 1181 unique peptides (from 371 proteins). The high molecular weight (HMW) (MW > 3000 Da) peptides in the early two fractions from the SEC column were first digested with trypsin, and the resulted digests were then analyzed by LC-MS/MS, which led to the identification of 123 and 127 progenitor proteins of the HMW peptides in fractions 1 and 2, respectively. Analysis of the peptides' cleavage sites showed that the peptides are cleaved in regulation, which may reflect the protease activity and distribution in body, and also represent the biological state of the tissue and provide a fresh source for biomarker discovery.
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Use of proteomic patterns in serum to identify ovarian cancer
Emanuel F. Petricoin, Ali M. Ardekani, Ben A. Hitt et al. · The Lancet · 2002 · 3.3K citations
Medicine, Gynecology, Oncology +17
Adrienne Boire, Lidija Covic, Anika Agarwal et al. · Cell · 2005 · 840 citations · Full text
Medicine, Cancer Biology, Oncology +13