1. DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery
- Author
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Tian Lu, Shu Zheng, Xue Cai, Qin Yang, Geert J.L.H. van Leenders, Sangeeta Mantoo, Henry H N Lam, Chantal Scheepbouwer, Jin’e Zheng, Danijela Koppers-Lalic, Xiao Liang, Yi Zhu, Shaozheng Dai, Renske D.M. Steenbergen, Sai Lou, Connie R. Jimenez, Anna Wojtuszkiewicz, Serene Jie Yi Yeow, Tony Kiat Hon Lim, Wenguang Shao, Franziska Böttger, Kailun Xu, Zhihua Tao, Xiao Yi, Nicole Cornelia Theodora van Grieken, Wei Liu, Chenhuan Yu, Yue Zhou, Cong Lu, Mo Hu, Huazhong Ying, Tiansheng Zhu, Liang Yue, Tiannan Guo, Richard R Goeij De Haas, Shiang Huang, Rui Sun, Yue Xuan, Narayanan G. Iyer, Shuigeng Zhou, Huanhuan Gao, Jianmin Wu, John W.M. Martens, Jiang Zhu, Chao Xu, Tim Schelfhorst, Yibei Dai, Sander R. Piersma, Tessa Y S Le Large, Sathiyamoorthy Selvarajan, Sze S. Lee, Xiaofei Gao, Yingkuan Shao, Jiafu Ji, Nan Xiang, Zhongzhi Luan, Winan J. van Houdt, Syed Muhammad Fahmy Alkaff, Oi Lian Kon, Ruud H. Brakenhoff, X D Teng, Yifan Meng, Zhicheng Wu, Ding Ma, Jan N. M. IJzermans, Man Wang, Peng Wu, Yaoting Sun, Jacqueline Cloos, Guan Ruan, Qiushi Zhang, Thang V. Pham, Xi Zheng, Irene V. Bijnsdorp, Bo Wang, Ruedi Aebersold, Medical oncology laboratory, CCA - Imaging and biomarkers, VU University medical center, Urology, Surgery, Hematology laboratory, Neurosurgery, Otolaryngology / Head & Neck Surgery, Pathology, AGEM - Re-generation and cancer of the digestive system, Amsterdam Neuroscience - Neurodegeneration, Medical Oncology, Graduate School, and AGEM - Amsterdam Gastroenterology Endocrinology Metabolism
- Subjects
Male ,Proteomics ,Protein mass spectrometry ,Protein biomarkers ,Computer science ,Data-independent acquisition ,Parallel reaction monitoring ,Spectral library ,Prostate cancer ,Diffuse large B cell lymphoma ,Computational biology ,Biochemistry ,Mass Spectrometry ,03 medical and health sciences ,0302 clinical medicine ,Cell Line, Tumor ,Healthy control ,Biomarkers, Tumor ,Genetics ,Humans ,Biomarker discovery ,lcsh:QH301-705.5 ,Molecular Biology ,Original Research ,030304 developmental biology ,0303 health sciences ,Plasma samples ,Selected reaction monitoring ,Prostatic Neoplasms ,Reproducibility of Results ,Neoplasm Proteins ,Computational Mathematics ,Targeted proteomics ,lcsh:Biology (General) ,Lymphoma, Large B-Cell, Diffuse ,Peptides ,030217 neurology & neurosurgery - 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., Genomics, Proteomics and Bioinformatics, 18 (2)
- Published
- 2020
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