Assessing Technical and Biological Variation in SWATH-MS-based Proteomic Analysis of Chronic Lymphocytic Leukaemia Cells

Overview

Journal Sci Rep

Specialty Science

Date 2021 Feb 4

PMID 33536534

Citations 3

Authors

Gina L Eagle

John M J Herbert

Jianguo Zhuang

Melanie Oates

Umair T Khan

Neil R Kitteringham

Kim Clarke

B Kevin Park

Andrew R Pettitt

Rosalind E Jenkins

Francesco Falciani

Affiliations

Soon will be listed here.

Abstract

Chronic lymphocytic leukaemia (CLL) exhibits variable clinical course and response to therapy, but the molecular basis of this variability remains incompletely understood. Data independent acquisition (DIA)-MS technologies, such as SWATH (Sequential Windowed Acquisition of all THeoretical fragments), provide an opportunity to study the pathophysiology of CLL at the proteome level. Here, a CLL-specific spectral library (7736 proteins) is described alongside an analysis of sample replication and data handling requirements for quantitative SWATH-MS analysis of clinical samples. The analysis was performed on 6 CLL samples, incorporating biological (IGHV mutational status), sample preparation and MS technical replicates. Quantitative information was obtained for 5169 proteins across 54 SWATH-MS acquisitions: the sources of variation and different computational approaches for batch correction were assessed. Functional enrichment analysis of proteins associated with IGHV mutational status showed significant overlap with previous studies based on gene expression profiling. Finally, an approach to perform statistical power analysis in proteomics studies was implemented. This study provides a valuable resource for researchers working on the proteomics of CLL. It also establishes a sound framework for the design of sufficiently powered clinical proteomics studies. Indeed, this study shows that it is possible to derive biologically plausible hypotheses from a relatively small dataset.

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