| Summary: | 碩士 === 國立臺灣師範大學 === 化學系 === 102 === Major histocompatibility complex class I (MHC class I), which is present on the cell surface, play an important role in assisting immune system to recognize intracellular pathogens and tumor-derived peptide fragments. The goal of this study is to identify and to quantify tumor-associated peptides from HPV transformed cancer cell by citric acid treatment, isobaric tags for relative and absolute quantitation (iTRAQ) and mass spectrometric analysis. To reduce sample complexity for the quantitative dynamic range improvement, extracted MHC class I-bound peptides were fractionated by offline strong cationic exchange chromatography (SCX), hydrophilic interaction chromatography (HILIC) and solution isoelectric focusing (sIEF) before nanoLC mass spectrometric analysis. The tandem MS spectra were first searched against Swiss-Prot database for the possible MHC class I-associated peptide screening. Two algorithms, SYFPEITHI and immune epitope database (IEDB), were applied to calculate the binding affinity of MS-identified peptide sequence with MHC class I molecule. The results indicated that there were 115 MHC class I-associated peptides identified from the citric acid treated sample mixtures, and 78 of them were specific HLA*02:01-bound candidates. Among them, FAG-, YVA- and YIP- peptides were found to be stably bound with MHC class I by flow cytometry binding assay. Protein abundance across organisms (PaxDb) and multi-omics profiling expression database (MOPED) were also applied to validate the associate protein expression profiles of the predicted peptides in various organs and diseases. The proposed method provides an attractive alternative to discover native MHC class I-associated peptides by the MS-based platform. If these MHC class I-associated peptides can be recognized by T cells and be able to stimulate immune response, they will be of great assist in tumor vaccine development.
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