Systematic Optimization of the iMALDI Workflow for the Robust and Straightforward Quantification of Signaling Proteins in Cancer Cells.
clinical mass spectrometry
formalin-fixed paraffin-embedded (FFPE)
immunohistochemistry
protein assays
translation
Journal
Proteomics. Clinical applications
ISSN: 1862-8354
Titre abrégé: Proteomics Clin Appl
Pays: Germany
ID NLM: 101298608
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
24
04
2020
revised:
13
06
2020
pubmed:
10
7
2020
medline:
6
7
2021
entrez:
10
7
2020
Statut:
ppublish
Résumé
Immuno-MALDI (iMALDI) combines immuno-enrichment of biomarkers with MALDI-MS for fast, precise, and specific quantitation, making it a valuable tool for developing clinical assays. iMALDI assays are optimized for the PI3-kinase signaling pathway members phosphatase and tensin homolog (PTEN) and PI3-kinase catalytic subunit alpha (p110α), with regard to sensitivity, robustness, and throughput. A standardized template for developing future iMALDI assays, including automation protocols to streamline assay development and translation, is provided. Conditions for tryptic digestion and immuno-enrichment (beads, bead:antibody ratios, incubation times, direct vs. indirect immuno-enrichment) are rigorously tested. Different strategies for calibration and data readout are compared. Digestion using 1:2 protein:trypsin (wt:wt) for 1 h yielded high and consistent peptide recoveries. Direct immuno-enrichment (antibody-bead coupling prior to antigen-enrichment) yielded 30% higher peptide recovery with a 1 h shorter incubation time than indirect enrichment. Immuno-enrichment incubation overnight yielded 1.5-fold higher sensitivities than 1 h incubation. Quantitation of the endogenous target proteins is not affected by the complexity of the calibration matrix, further simplifying the workflow. This optimized and automated workflow will facilitate the clinical translation of high-throughput sensitive iMALDI assays for quantifying cell-signaling proteins in individual tumor samples, thereby improving patient stratification for targeted treatment.
Identifiants
pubmed: 32643306
doi: 10.1002/prca.202000034
pmc: PMC7539945
doi:
Substances chimiques
Neoplasm Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2000034Informations de copyright
© 2020 The Authors. Proteomics - Clinical Applications published by Wiley-VCH GmbH.
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