Protein phosphorylation is a key mechanism of cellular signaling pathways and aberrant phosphorylation has been implicated in a number of human diseases. Thus, approaches in phosphoproteomics can contribute to the identification of key biomarkers to assess disease pathogenesis and drug targets. Moreover, careful validation of large-scale phosphoproteome analysis, which is lacking in the current protein-based biomarker discovery, significantly increases the value of identified biomarkers. Here, we performed large-scale differential phosphoproteome analysis using IMAC coupled with the isobaric tag for relative quantification (iTRAQ) technique and subsequent validation by selected/multiple reaction monitoring (SRM/MRM) of human breast cancer tissues in high- and low-risk recurrence groups. We identified 8309 phosphorylation sites on 3401 proteins, of which 3766 phosphopeptides (1927 phosphoproteins) were able to be quantified and 133 phosphopeptides (117 phosphoproteins) were differentially expressed between the two groups. Among them, 19 phosphopeptides were selected for further verification and 15 were successfully quantified by SRM using stable isotope peptides as a reference. The ratio of phosphopeptides between high- and low-risk groups quantified by SRM was well correlated with iTRAQ-based quantification with a few exceptions. These results suggest that large-scale phosphoproteome quantification coupled with SRM-based validation is a powerful tool for biomarker discovery using clinical samples.
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