DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery.

Abstract

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

• Authors: Tiansheng Zhu, Yi Zhu, Yue Xuan, Huanhuan Gao, Xue Cai, Sander R Piersma, Thang V Pham, Tim Schelfhorst, Richard R G D Haas, Irene V Bijnsdorp, Rui Sun, Liang Yue, Guan Ruan, Qiushi Zhang, Mo Hu, Yue Zhou, Winan J Van Houdt, Tessa Y S Le Large, Jacqueline Cloos, Anna Wojtuszkiewicz, Danijela Koppers-Lalic, Franziska Böttger, Chantal Scheepbouwer, Ruud H Brakenhoff, Geert J L H van Leenders, Jan N M Ijzermans, John W M Martens, Renske D M Steenbergen, Nicole C Grieken, Sathiyamoorthy Selvarajan, Sangeeta Mantoo, Sze S Lee, Serene J Y Yeow, Syed M F Alkaff, Nan Xiang, Yaoting Sun, Xiao Yi, Shaozheng Dai, Wei Liu, Tian Lu, Zhicheng Wu, Xiao Liang, Man Wang, Yingkuan Shao, Xi Zheng, Kailun Xu, Qin Yang, Yifan Meng, Cong Lu, Jiang Zhu, Jin'e Zheng, Bo Wang, Sai Lou, Yibei Dai, Chao Xu, Chenhuan Yu, Huazhong Ying, Tony K Lim, Jianmin Wu, Xiaofei Gao, Zhongzhi Luan, Xiaodong Teng, Peng Wu, Shi'ang Huang, Zhihua Tao, Narayanan G Iyer, Shuigeng Zhou, Wenguang Shao, Henry Lam, Ding Ma, Jiafu Ji, Oi L Kon, Shu Zheng, Ruedi Aebersold, Connie R Jimenez, Tiannan Guo
• Journal: Genomics, proteomics & bioinformatics (Genomics Proteomics Bioinformatics) Vol. 18 Issue 2 Pg. 104-119 (04 2020) ISSN: 2210-3244 [Electronic] China
• PMID: 32795611 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Chemical References

• Biomarkers, Tumor
• Neoplasm Proteins
• Peptides

Topics

• Biomarkers, Tumor (analysis, blood)
• Cell Line, Tumor
• Humans
• Lymphoma, Large B-Cell, Diffuse (blood)
• Male
• Mass Spectrometry
• Neoplasm Proteins (analysis)
• Peptides (metabolism)
• Prostatic Neoplasms (metabolism)
• Proteomics
• Reproducibility of Results