Genomics, Proteomics & Bioinformatics (Apr 2020)

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

  • 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 volume & issue
Vol. 18, no. 2
pp. 104 – 119

Abstract

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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.

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