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제124회 대한화학회 학술발표회, 총회 및 기기전시회 안내 Proteogenomics Study for Identifying Cancer Biomarker Peptide Candidate with PTMs based on Novel Data Analysis Strategy utilizing Multi-Stage approach

2019년 8월 29일 19시 42분 11초
LIFE.P-229 이곳을 클릭하시면 발표코드에 대한 설명을 보실 수 있습니다.
10월 18일 (금요일) 11:00~12:30
Life Chemistry
저자 및
Madar Inamul Hasan, Hokeun Kim1, Sang-Won Lee1,*
Center for Proteogenome Research (CPGR), Korea University, Korea
1Department of Chemistry, Korea University, Korea
Large-scale cancer genome sequencing studies have generated an extensive catalogue of mutations as disease biomarker and potential therapeutic targets. Difficulty in differentiating the driver and passenger mutations hurdles in the future development of drug targets hypothesis. Proteins are central to cellular functions, and mutated proteins can drive the initiation of tumor, progression and thereby act as targets to treatment. Proteomics enable an opportunity for functional interpretation of these mutations for better understanding of etiology of cancer development and thence target for therapeutic developments. Proteogenomics provide opportunities for protein level validation of genomic alterations guided by genomics data (RNA-Seq/Exome Seq). More than 300 different types of protein modifications have been described, many of which are known to have pivotal roles in cellular physiology. Protein and their PTM sites is key to dissection of PTM-mediated cellular processes and disease. Here we developed a sensitive method utilizing multi-stage database search for comprehensive proteomics data analysis to complement genomics sequencing data. We employed two complementary search engines, MS-GF+ and MODa/MODi here. The tandem MS data were first subjected to MS-GF+ database search (1st stage search) for mutation search using RNA-Seq guided sample specific mutated proteomics database (generated using CustomProDB) and the unidentified MS/MS data from the 1st stage search were analyzed with the combined use of MODa and MODi (2nd stage search), tools for blind and unrestrictive modification search using the same sample specific mutated proteomics database, respectively. When combined with mPE-MMR, a tool for accurate and extensive precursor masses assignments to co-fragmented MS/MS data, our method was shown to significantly increase the identification of peptides, post-translationally modified(PTMs) peptides, mutated peptides/genes. The developed method will be used for integrated cancer proteogenomic analyses. Keywords: mPE-MMR, Proteogenomics, PTMs, Mutations,Multi-stage database search.