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.

Keywords: Data-independent acquisition; Diffuse large B cell lymphoma; Parallel reaction monitoring; Prostate cancer; Spectral library.

Figure 1

Workflow for building DPHL A. Schematic representation of DDA shotgun proteomics data acquisition. Numbers in parentheses indicate the number of DDA files per tissue type. B. Protein identification and iRT detection from DDA raw files using pFind. C. SiRT detection and calibration. D. CiRT detection and calibration. E. Generation of DPHL. Details of the commands are presented in File S18. DDA, data-dependent acquisition; DIA, data-independent acquisition; iRT, indexed retention time; PCT, pressure cycling technology; SCX, strong cation-exchange; SiRT, synthetic iRT; CiRT, common internal iRT; DPHL, DIA pan-human library.

Figure 2

Comparison of DPHL and PHL A. Venn diagram showing the comparison of transition groups (i.e., peptide precursors), peptides, protein groups, and proteins in DPHL and PHL. B. Visualization of tissue intersections using R package UpSet. C. Bar plots displaying the number of transition groups, peptides, protein groups, proteins in DPHL library for each sample type. PHL, pan-human spectral library.

Figure 3

PCa proteome using 60-min gradient DIA A. Number of protein groups and peptide precursors identified using SiRT and CiRT. B. Technical reproducibility of proteome matrix using CiRT and SiRT. C. Comparison of protein quantification based on MS intensity using the SiRT and CiRT methods. D. 2D plane t-SNE plot of disease classes, color coded by sample type using CiRT and SiRT. E. Boxplots showing the expression (MS intensity) of the significantly dysregulated proteins; P values adjusted with Benjamini & Hochberg are shown under each protein name. ROC curves of the proteins were also shown. R1, technical replicate 1; R2, technical replicate 2; PCa, prostate cancer; BPH, benign prostate hyperplasia; t-SNE, t-distributed stochastic neighbor embedding; FASN, fatty acid synthetase, UniProtKB: P49327; TPP1, tripeptidyl-peptidase 1, UniProtKB: O14773; SPON2, spondin-2, UniProtKB: Q9BUD6.

Figure 4

DIA analysis of plasma samples from DLBCL patients and HC subjects A. Technical reproducibility for protein quantification of four plasma samples from two DLBCL patients and two healthy control subjects. B. 2D plane t-SNE plot showing that proteomes are separated. C. Volcano plot showing significantly down-regulated (blue) and up-regulated (red) proteins in 37 plasma samples (19 samples from DLBCL patients and 18 samples from HC subjects). D. The relative protein expression as calculated by MS intensity for CRP and SAA1. P values adjusted with Benjamini & Hochberg are shown under each protein name Left: Boxplot and ROC curve of CRP. Right: Boxplot and ROC curve of SAA1. DLBCL, diffuse large B cell lymphoma; HC, healthy control; CRP, C-reactive protein, UniProtKB: P02741; SAA1, serum amyloid A1, UniProtKB: P0DJI8.

Figure 5

PRM validation of TPP1, FASN, and SPON2 across 73 peptide samples from 53 PCa patients Two best flying peptides were selected for each protein. For each peptide, boxplot shows the relative abundance of the peptide across 73 PRM runs as calculated from MS intensity (on the left), and XIC demonstrates a representative peak group of the peptide (on the right). P values are computed using Student’s t test. PRM, parallel reaction monitoring; XIC, extracted ion chromatogram.