Hengchao Li1, Yishen Mao1, Yueting Xiong2, Huan Huan Zhao2, Fenglin Shen2, Xing Gao2,3, Pengyuan Yang4,3, Xiaohui Liu4,3, Deliang Fu5. 1. Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, P.R. China. 2. Institute of Biomedical Sciences, Fudan University, Shanghai, P.R. China. 3. The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, P.R. China. 4. Institute of Biomedical Sciences, Fudan University, Shanghai, P.R. China pyyang@fudan.edu.cn liuxiaohui@fudan.edu.cn surgeonfu@163.com. 5. Department of Pancreatic Surgery, Huashan Hospital, Fudan University, Shanghai, P.R. China pyyang@fudan.edu.cn liuxiaohui@fudan.edu.cn surgeonfu@163.com.
Abstract
BACKGROUND/AIM: Pancreatic cancer (PC) is currently the fourth leading cause of cancer-related mortality worldwide. Peripheral blood mononuclear cells (PBMCs) is a subpopulation of accessible and functional immune cells. Comparative analysis of the proteome of PBMCs can help us elucidate the mechanism of disease and find potential biomarkers for diagnosis. MATERIALS AND METHODS: PBMCs were collected from healthy individuals, patients with benign diseases, and pancreatic cancer. iTRAQ-2DLC-MS/MS and SWATH methodologies were applied to make a comparative proteomics analysis of PBMCs. RESULTS: A total of 3,357 proteins with a false discovery rate (FDR) <1% were identified, of which 114 proteins were found dysregulated in the PC group. An extensive SWATH library was constructed which showed a potential application for large scale clinical sample analysis. CONCLUSION: A PBMCs proteome with extensive protein representation was achieved, which will potentially allow the identification of novel biomarkers for PC. Copyright
BACKGROUND/AIM: Pancreatic cancer (PC) is currently the fourth leading cause of cancer-related mortality worldwide. Peripheral blood mononuclear cells (PBMCs) is a subpopulation of accessible and functional immune cells. Comparative analysis of the proteome of PBMCs can help us elucidate the mechanism of disease and find potential biomarkers for diagnosis. MATERIALS AND METHODS: PBMCs were collected from healthy individuals, patients with benign diseases, and pancreatic cancer. iTRAQ-2DLC-MS/MS and SWATH methodologies were applied to make a comparative proteomics analysis of PBMCs. RESULTS: A total of 3,357 proteins with a false discovery rate (FDR) <1% were identified, of which 114 proteins were found dysregulated in the PC group. An extensive SWATH library was constructed which showed a potential application for large scale clinical sample analysis. CONCLUSION: A PBMCs proteome with extensive protein representation was achieved, which will potentially allow the identification of novel biomarkers for PC. Copyright
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