Multi-Layered Proteomic Approaches for Cancer Proteomes and Phosphoproteomes

Abstract

Quantitative proteomics based on mass spectrometry is widely applied to various research fields according to the development of proteome sample preparation and data analysis along with the rapid development of mass spectrometry. The current bottom-up proteomics is a strategy that can produce the most comprehensive depth of proteomic data by digesting protein at peptide level and then introducing into liquid chromatography-mass spectrometry (LC-MS). As the rate of generation of various omics data, as well as the proteomic data on mass spectrometry, increases, attempts to elucidate novel biological phenomena by generating complementary data through integrated analysis of various omics data, no longer a single type of omics analysis. In this dissertation, I focused on the optimization of data analysis methods and sample analysis that could be used for multi-layered analysis of proteomics. In part 1, I focused to integrate multi-layered proteomic data generated from colorectal cancer (CRC) models. Secretome controlled by MMP-2 (Matrix metaloproteinase-2) in CRC cell line, plasma proteome profiled from CRC patients, and CRC tissue-derived proteomes, a total of three types of proteomic data were integrated and analyzed to identify the novel secretory protein targets regulated by MMP-2 as well as to evaluate the clinical meaning of each target protein. The results showed that secretory proteins regulated by MMP-2 expression showed similar expression patterns in clinical samples along with the progression of the cancer stage. A key strength of this study is the integration of genetic perturbation data from cell lines and profiling data from clinical samples. In part 2, the study focused on optimization of the isobaric labeling method for quantitative analysis of phosphoproteomics. Phosphorylation is the most studied post-translational modification in cell metabolism, and the whole phosphorylated proteins participating in cellular signaling pathway could be observed by mass spectrometric analysis. Therefore, in multi-layered proteomic analysis, complementary data can be generated to understand in vivo cell signaling through the integrated analysis of phosphoproteomic data with various omics data generated from the identical samples. The most commonly used isobaric labeling method for quantitative mass analysis has also been widely used in phosphoproteomics, however, the optimized labeling method for phosphoproteins has not been studied yet. In part 2, the isobaric labeling method was optimized for phosphoproteome, increasing the number of identification and quantitative accuracy. In particular, for the NHS-amine reaction used in the labeling, the quenching reaction is essential to prevent cross-contamination between samples. It was confirmed that hydroxylamine, a quenching reagent used for this reaction, has deleterious effect on phosphopeptide and it is suggested that immediate removal of hydroxylamine after quenching process recover phosphoproteome yield in isobaric labeling experiment.