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Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps

Authors: Hannes L. Röst; Silke Gillessen; Ben C. Collins; Ludovic C Gillet; George Rosenberger; George Rosenberger; Ruedi Aebersold; +7 Authors

Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps

Abstract

Clinical specimens are each inherently unique, limited and nonrenewable. Small samples such as tissue biopsies are often completely consumed after a limited number of analyses. Here we present a method that enables fast and reproducible conversion of a small amount of tissue (approximating the quantity obtained by a biopsy) into a single, permanent digital file representing the mass spectrometry (MS)-measurable proteome of the sample. The method combines pressure cycling technology (PCT) and sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. The resulting proteome maps can be analyzed, re-analyzed, compared and mined in silico to detect and quantify specific proteins across multiple samples. We used this method to process and convert 18 biopsy samples from nine patients with renal cell carcinoma into SWATH-MS fragment ion maps. From these proteome maps we detected and quantified more than 2,000 proteins with a high degree of reproducibility across all samples. The measured proteins clearly distinguished tumorous kidney tissues from healthy tissues and differentiated distinct histomorphological kidney cancer subtypes.

Country
United Kingdom
Keywords

Proteomics, Proteome, Kidney Neoplasms/metabolism, Biopsy, 610, Peptides/chemistry, ta3111, Kidney, Article, Mass Spectrometry, Pressure, Humans, Carcinoma, Renal Cell/metabolism, /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; name=SDG 3 - Good Health and Well-being, Carcinoma, Renal Cell, Mass Spectrometry/methods, Ions, Reproducibility of Results, ResearchInstitutes_Networks_Beacons/mcrc; name=Manchester Cancer Research Centre, Kidney Neoplasms, name=SDG 3 - Good Health and Well-being, Kidney/metabolism, /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being, Proteomics/methods, Peptides

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    349
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
349
Top 1%
Top 1%
Top 0.1%
Green
bronze