MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry

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 q...

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Main Authors: Yun-Sheng Liu, 劉昀昇
Other Authors: Sung-Fang Chen
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/16931637281732461334
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spelling ndltd-TW-102NTNU50650222016-05-22T04:40:27Z http://ndltd.ncl.edu.tw/handle/16931637281732461334 MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry 利用化學標定與質譜技術分析經由人類乳突病毒 E7 轉染癌細胞之第一型 MHC 胜肽 Yun-Sheng Liu 劉昀昇 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. Sung-Fang Chen 陳頌方 2014 學位論文 ; thesis 93 zh-TW
collection NDLTD
language zh-TW
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sources NDLTD
description 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.
author2 Sung-Fang Chen
author_facet Sung-Fang Chen
Yun-Sheng Liu
劉昀昇
author Yun-Sheng Liu
劉昀昇
spellingShingle Yun-Sheng Liu
劉昀昇
MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
author_sort Yun-Sheng Liu
title MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
title_short MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
title_full MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
title_fullStr MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
title_full_unstemmed MHC Class I-Associated Peptide Analysis of HPV E7-Transformed Cancer Cell by Chemical Labeling and Mass Spectrometry
title_sort mhc class i-associated peptide analysis of hpv e7-transformed cancer cell by chemical labeling and mass spectrometry
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/16931637281732461334
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