A self-validating quantitative mass spectrometry method for assessing the accuracy of high-content phosphoproteomic experiments.

Protein kinase pathways play pivotal roles in cell signaling and biology. The phosphoproteome is a reflection of protein kinase pathway activation and therefore there is considerable interest in its quantification as a means to assess the wiring of signaling networks. Although different approaches for quantitative phosphoproteomics have been described, there is no data on how accurate these are for each quantified phosphorylated site. We report a liquid chromatography-MS approach to objectively assess data quality in high-content comparison of phosphoproteomes in which samples to be compared are mixed at different proportions. The experimental data is then used to derive a linear regression function that allows calculating correlation values, linearity, and accuracy. We applied the technique to investigate phosphorylation in P31/Fuj and Kasumi-1, two leukemia cells lines showing strikingly different sensitivities to scr and PI3K inhibitors. We found that phosphopeptides quantified with accuracy were not always quantified with precision because of low ion statistics contributing to variability. Thus our approach was complementary to standard methods for calculating the precision of replicate measurements based on the coefficient of variation and provided additional information on data quality for each quantified phosphopeptide. We quantified > 2250 phosphorylation sites across cell lines with different levels of sensitivity to kinase inhibitors, of which 1847 showed an accuracy variation of < 30% (with an overall mean of 22%). Hundreds of phosphorylation sites on proteins with diverse function (including kinases, transcription, and translation factors) showed significantly distinct intensities across sensitive and resistant cells lines, indicating that kinase pathways are differentially regulated in cancer cells of distinct sensitivity to signaling inhibitors.