Immunoaffinity Mass Spectrometry Diagnostic Tests for Multi-Biomarker Assays.

Assay development Biomarkers Diabetic kidney disease Immunoaffinity Targeted mass spectrometry

Journal

Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969

Informations de publication

Date de publication:
2023
Historique:
entrez: 13 2 2023
pubmed: 14 2 2023
medline: 16 2 2023
Statut: ppublish

Résumé

Immunoaffinity mass spectrometry as an approach for diagnostic biomarker assays combines the advantages of antibody selectivity with the multiplexing and analytical performance of mass spectrometry. A method has been developed to detect and quantify three protein biomarkers for a diabetic kidney disease prognostic assay, PromarkerD. The methodology reflects an immunoaffinity approach compatible with higher throughput and robust clinical application. After preparation and purification of antibody-bead conjugates for the three target proteins, an immunoaffinity capture step provides a solution for reduction, alkylation, and digestion on-bead. Targeted mass spectrometry provides a quantitative measure of each biomarker in a rapid 8 min run using a microflow LCMS workflow.

Identifiants

pubmed: 36781787
doi: 10.1007/978-1-0716-2978-9_13
doi:

Substances chimiques

Proteins 0
Biomarkers 0
Antibodies 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

195-206

Informations de copyright

© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Références

Nedelkov D (2017) Mass spectrometry protein tests: ready for prime time (or not). Expert Rev Proteomics 14:1–7. https://doi.org/10.1080/14789450.2017.1256777
doi: 10.1080/14789450.2017.1256777
Crutchfield CA, Thomas SN, Sokoll LJ, Chan DW (2016) Advances in mass spectrometry-based clinical biomarker discovery. Clin Proteomics 13:1. https://doi.org/10.1186/s12014-015-9102-9
doi: 10.1186/s12014-015-9102-9
Nakayasu ES, Gritsenko M, Piehowski PD et al (2021) Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation. Nat Protoc 16:3737–3760. https://doi.org/10.1038/s41596-021-00566-6
doi: 10.1038/s41596-021-00566-6
He T (2019) Implementation of proteomics in clinical trials. Proteomics Clin Appl 13:1800198. https://doi.org/10.1002/prca.201800198
doi: 10.1002/prca.201800198
Chen J, Zheng N (2020) Accelerating protein biomarker discovery and translation from proteomics research for clinical utility. Bioanalysis 12:1469–1481. https://doi.org/10.4155/bio-2020-0198
doi: 10.4155/bio-2020-0198
Frantzi M, Bhat A, Latosinska A (2014) Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development. Clin Transl Med 3:7. https://doi.org/10.1186/2001-1326-3-7
doi: 10.1186/2001-1326-3-7
Ioannidis JPA, Bossuyt PMM (2017) Waste, leaks, and failures in the biomarker pipeline. Clin Chem 63:963–972. https://doi.org/10.1373/clinchem.2016.254649
doi: 10.1373/clinchem.2016.254649
Bringans S, Ito J, Casey T et al (2020) A robust multiplex immunoaffinity mass spectrometry assay (PromarkerD) for clinical prediction of diabetic kidney disease. Clin Proteomics 17:37. https://doi.org/10.1186/s12014-020-09302-w
doi: 10.1186/s12014-020-09302-w

Auteurs

Scott Bringans (S)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia. scott@proteomics.com.au.

Tammy Casey (T)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia.

Jun Ito (J)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia.

Tasha Lumbantobing (T)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia.

Ronan O'Neill (R)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia.

Richard Lipscombe (R)

Proteomics International, QEII Medical Centre, Nedlands, Perth, WA, Australia.

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Classifications MeSH