Literature DB >> 33536534

Assessing technical and biological variation in SWATH-MS-based proteomic analysis of chronic lymphocytic leukaemia cells.

Gina L Eagle1, John M J Herbert2, Jianguo Zhuang1, Melanie Oates1, Umair T Khan1,3, Neil R Kitteringham4, Kim Clarke2, B Kevin Park4, Andrew R Pettitt1,3, Rosalind E Jenkins5, Francesco Falciani6,7.   

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.

Entities:  

Year:  2021        PMID: 33536534     DOI: 10.1038/s41598-021-82609-2

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  31 in total

Review 1.  The molecular pathogenesis of chronic lymphocytic leukaemia.

Authors:  Giulia Fabbri; Riccardo Dalla-Favera
Journal:  Nat Rev Cancer       Date:  2016-03       Impact factor: 60.716

Review 2.  Genomic and epigenomic heterogeneity in chronic lymphocytic leukemia.

Authors:  Romain Guièze; Catherine J Wu
Journal:  Blood       Date:  2015-06-11       Impact factor: 22.113

3.  Building high-quality assay libraries for targeted analysis of SWATH MS data.

Authors:  Olga T Schubert; Ludovic C Gillet; Ben C Collins; Pedro Navarro; George Rosenberger; Witold E Wolski; Henry Lam; Dario Amodei; Parag Mallick; Brendan MacLean; Ruedi Aebersold
Journal:  Nat Protoc       Date:  2015-02-12       Impact factor: 13.491

4.  Proteomics-based strategies to identify proteins relevant to chronic lymphocytic leukemia.

Authors:  Suliman A Alsagaby; Sanjay Khanna; Keith W Hart; Guy Pratt; Christopher Fegan; Christopher Pepper; Ian A Brewis; Paul Brennan
Journal:  J Proteome Res       Date:  2014-07-14       Impact factor: 4.466

Review 5.  Mass-spectrometric exploration of proteome structure and function.

Authors:  Ruedi Aebersold; Matthias Mann
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

6.  Protein profiles distinguish stable and progressive chronic lymphocytic leukemia.

Authors:  Pauline Y Huang; Swetlana Mactier; Natalie Armacki; O Giles Best; Larissa Belov; Kimberley L Kaufman; Dana Pascovici; Stephen P Mulligan; Richard I Christopherson
Journal:  Leuk Lymphoma       Date:  2015-11-16

Review 7.  Chronic lymphocytic leukaemia.

Authors:  Thomas J Kipps; Freda K Stevenson; Catherine J Wu; Carlo M Croce; Graham Packham; William G Wierda; Susan O'Brien; John Gribben; Kanti Rai
Journal:  Nat Rev Dis Primers       Date:  2017-01-19       Impact factor: 52.329

8.  Altered expression of metabolic pathways in CLL detected by unlabelled quantitative mass spectrometry analysis.

Authors:  Lauren A Thurgood; Eveline S Dwyer; Karen M Lower; Tim K Chataway; Bryone J Kuss
Journal:  Br J Haematol       Date:  2019-01-17       Impact factor: 6.998

Review 9.  Prognostic factors in chronic lymphocytic leukemia-what do we need to know?

Authors:  Paula Cramer; Michael Hallek
Journal:  Nat Rev Clin Oncol       Date:  2010-10-19       Impact factor: 66.675

Review 10.  Cancer proteomics by quantitative shotgun proteomics.

Authors:  Emily I Chen; John R Yates
Journal:  Mol Oncol       Date:  2007-09       Impact factor: 6.603

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