Evidence map›Paper›PMID 29501709›Full record

ArticleJournal of proteomics2018

SWATH mass spectrometry as a tool for quantitative profiling of the matrisome.

Lukas Krasny, Philip Bland, Naoko Kogata, Patty Wai, Beatrice A Howard, Rachael C Natrajan, Paul H Huang

Abstract read
In one paragraph

Article in Journal of proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
–field-weighted citation impact
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

43 citing papers in PubMed.

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  7. Clinical Implications and Molecular Features of Extracellular Matrix Networks in Soft Tissue Sarcomas.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
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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

7 authors.

Lukas KrasnyDivision of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK.
Philip BlandThe Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK.
Naoko KogataThe Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK.
Patty WaiDivision of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK; The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK.
Beatrice A HowardThe Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK.
Rachael C NatrajanDivision of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK; The Breast Cancer Now Toby Robins Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, SW3 6JB, UK.
Paul H HuangDivision of Molecular Pathology, The Institute of Cancer Research, London, SW3 6JB, UK. Electronic address: paul.huang@icr.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteomic analysis of extracellular matrix (ECM) and ECM-associated proteins, collectively known as the matrisome, is a challenging task due to the inherent complexity and insolubility of these proteins. Here we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins in both non-enriched and ECM enriched tissue without the need for prior fractionation. Utilising a spectral library containing 201 matrisomal proteins, we compared the performance and reproducibility of SWATH MS over conventional data-dependent analysis mass spectrometry (DDA MS) in unfractionated murine lung and liver. SWATH MS conferred a 15-20% increase in reproducible peptide identification across replicate experiments in both tissue types and identified 54% more matrisomal proteins in the liver versus DDA MS. We further use SWATH MS to evaluate the quantitative changes in matrisome content that accompanies ECM enrichment. Our data shows that ECM enrichment led to a systematic increase in core matrisomal proteins but resulted in significant losses in matrisome-associated proteins including the cathepsins and proteins of the S100 family. Our proof-of-principle study demonstrates the utility of SWATH MS as a versatile tool for in-depth characterisation of the matrisome in unfractionated and non-enriched tissues. SIGNIFICANCE: The matrisome is a complex network of extracellular matrix (ECM) and ECM-associated proteins that provides scaffolding function to tissues and plays important roles in the regulation of fundamental cellular processes. However, due to its inherent complexity and insolubility, proteomic studies of the matrisome typically require the application of enrichment workflows prior to MS analysis. Such enrichment strategies often lead to losses in soluble matrisome-associated components. In this study, we present sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH MS) as a tool for the quantitative analysis of matrisomal proteins. We show that SWATH MS provides a more reproducible coverage of the matrisome compared to data-dependent analysis (DDA) MS. We also demonstrate that SWATH MS is capable of accurate quantification of matrisomal proteins without prior ECM enrichment and fractionation, which may simplify sample handling workflows and avoid losses in matrisome-associated proteins commonly linked to ECM enrichment.

Indexed as

AnimalsChemical FractionationData Interpretation, StatisticalExtracellular MatrixExtracellular Matrix ProteinsFemaleMass SpectrometryMiceMice, SCIDProteomeProteomicsExtracellular Matrix ProteinsProteomeDIA MSExtracellular matrixMass spectrometryMatrisomeProteomicsSWATH MS

Identifiers

PMID29501709
PMCPMC6215756

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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.