Dataset Information

LFQbench enables a multi-centered benchmark study demonstrating robust proteomic label-free quantification

ABSTRACT: The consistent and accurate quantification of proteins is a challenging task for mass spectrometry (MS)-based proteomics. SWATH-MS uses data-independent acquisition (DIA) for label-free quantification. Here we evaluated five software tools for processing SWATH-MS data: OpenSWATH, SWATH2.0, Skyline, Spectronaut, DIA-Umpire, in collaboration with the respective developers to ensure an optimal use of each tool. We analyzed data from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments applying different SWATH isolation windows setups. Using the resulting high-complexity datasets we benchmarked precision and accuracy of quantification and evaluated identification performance, robustness and specificity of each software tool. To consistently evaluate the high complexity datasets, we developed the LFQbench R-package. LFQbench results enabled developers to improve their software tools, thereby underlining the value of the reference datasets for software development and benchmarking. All tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Homo Sapiens (human) Escherichia Coli Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Yasset Perez-Riverol

LAB HEAD: Stefan Tenzer

PROVIDER: PXD002952 | Pride | 2016-09-27

REPOSITORIES: Pride

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Publications

A multicenter study benchmarks software tools for label-free proteome quantification.

Navarro Pedro P Kuharev Jörg J Gillet Ludovic C LC Bernhardt Oliver M OM MacLean Brendan B Röst Hannes L HL Tate Stephen A SA Tsou Chih-Chiang CC Reiter Lukas L Distler Ute U Rosenberger George G Perez-Riverol Yasset Y Nesvizhskii Alexey I AI Aebersold Ruedi R Tenzer Stefan S

Nature biotechnology 20161003 11

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DI ...[more]

PMID: 27701404

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Project description:The global rise of HPV(+) oropharyngeal squamous cell carcinoma (OPSCC) has generated considerable interest underlying its etiology and management. Despite an overall decline in head and neck malignancies, the incidence in OPSCC has by contrast sharply risen, with HPV(+) subtypes now comprising 80% of all OPSCC.1,2 Relative to HPV(-) OPSCC, HPV(+) patients are more responsive to chemoradiation and harbor a 52% risk-of-death reduction.3 Despite this distinct outcome, treatment regimens remain the same for all OPSCC subtypes (smoking-driven and virus-driven), rather than an adaptive approach to what most consider distinct diseases. The short-term effects (e.g., mucositis, odynophagia) and long-term toxicities (e.g., xerostomia, dysphagia, ototoxicity) from treatment substantially affect quality of life, and rival the impact of the cancer itself. Recently published as well as ongoing trials are actively examining deintensification approaches2,4-9, with the goal of diminishing treatment sequelae for HPV(+) subtypes. While deintensification may decrease chemoradiation-related toxicities, it nonetheless may also undertreat a meaningful percentage of HPV(+) patients who may then recur. In examining national trials, 19% of HPV(+) patients had disease progression after therapy, with a two-year survival rate of 60%.10 Current methods to ascertain HPV status involve p16 staining. However, on comparison with gold standard E6/E7 expression by qPCR, p16 harbored a 15% false positivity rate11, suggesting limited utility as a sole biomarker for deintensification. Improved molecular stratification would greatly enhance the clinician’s ability to precisely tailor treatment while minimizing the risk of jeopardizing outcomes. One approach encompasses in-depth proteomic profiling of HPV(+) OPSCC to reveal distinct protein expression profiles and delineate clinically relevant upstream pathways. In turn, these proteomic differences may distinguish higher-risk disease (cases predisposed to recurrence that may benefit from treatment intensification) from lower-risk phenotypes (cases whose treatment response is sufficiently robust to warrant deintensification). Here, two HPV(+) OPSCC cohorts stratified by treatment response are compared via a hybrid data dependent acquisition/data independent acquisition (DDA/DIA) approach via mass spectrometry. We focused on detection of low-abundance proteins to highlight proteomic signatures that can be potentially exploited for treatment stratification.

Dataset Information

LFQbench enables a multi-centered benchmark study demonstrating robust proteomic label-free quantification

Publications

A multicenter study benchmarks software tools for label-free proteome quantification.

Similar Datasets

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