Evidence map›Paper›PMID 33536534›Full record

ArticleScientific reports2021

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

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 and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Gina L Eagle *Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
John M J Herbert *Computational Biology Facility, University of Liverpool, Liverpool, UK.
Jianguo ZhuangDepartment of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
Melanie OatesDepartment of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
Umair T KhanDepartment of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
Neil R KitteringhamDepartment Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, UK.
Kim ClarkeComputational Biology Facility, University of Liverpool, Liverpool, UK.
B Kevin ParkDepartment Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, UK.
Andrew R PettittDepartment of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
Rosalind E JenkinsDepartment Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, MRC Centre for Drug Safety Science, University of Liverpool, Liverpool, UK. R.Jenkins@liverpool.ac.uk.
Francesco FalcianiComputational Biology Facility, University of Liverpool, Liverpool, UK. F.Falciani@liverpool.ac.uk.
University of Liverpool · GBClatterbridge Cancer Centre NHS Foundation Trust · GB

Funding

Medical Research Council MR/N025989/1
6 · The paper itself

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.

Indexed as

Genetic HeterogeneityAgedBiological Variation, PopulationDatasets as TopicFemaleGene Expression ProfilingHumansLeukemia, Lymphocytic, Chronic, B-CellMaleMiddle AgedMutationProteomeProteomicsReceptors, Antigen, B-CellTandem Mass SpectrometryProteomeReceptors, Antigen, B-Cell

Identifiers

PMID33536534
PMCPMC7858606
OpenAlexW3127917460

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.