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Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood

Version 2 2024-09-18, 23:37
Version 1 2023-07-28, 04:21
journal contribution
posted on 2024-09-18, 23:37 authored by Camila Espejo, Alan Lyons, Gregory WoodsGregory Woods, Richard WilsonRichard Wilson
<p>One of the cornerstones of effective cancer treatment is early diagnosis. In this context, the identification of proteins that can serve as cancer biomarkers in bodily fluids ("liquid biopsies") has gained attention over the last decade. Plasma and serum fractions of blood are the most commonly investigated sources of potential cancer liquid biopsy biomarkers. However, the high complexity and dynamic range typical of these fluids hinders the sensitivity of protein detection by the most commonly used mass spectrometry technology (data-dependent acquisition mass spectrometry (DDA-MS)). Recently, data-independent acquisition mass spectrometry (DIA-MS) techniques have overcome the limitations of DDA-MS, increasing sensitivity and proteome coverage. In addition to DIA-MS, isolating extracellular vesicles (EVs) can help to increase the depth of serum/plasma proteome coverage by improving the identification of low-abundance proteins which are a potential treasure trove of diagnostic molecules. EVs, the nano-sized membrane-enclosed vesicles present in most bodily fluids, contain proteins which may serve as potential biomarkers for various cancers. Here, we describe a detailed protocol that combines DIA-MS and EV methodologies for discovering and validating early cancer biomarkers using blood serum. The pipeline includes size exclusion chromatography methods to isolate serum-derived extracellular vesicles and subsequent EV sample preparation for liquid chromatography and mass spectrometry analysis. Procedures for spectral library generation by DDA-MS incorporate methods for off-line peptide separation by microflow HPLC with automated fraction concatenation. Analysis of the samples by DIA-MS includes recommended protocols for data processing and statistical methods. This pipeline will provide a guide to discovering and validating EV-associated proteins that can serve as sensitive and specific biomarkers for early cancer detection and other diseases.</p>

History

Sub-type

  • Article

Publication title

Methods Mol Biol

Medium

Print

Volume

2628

Pagination

127-152

eISSN

1940-6029

ISSN

1064-3745

Department/School

Central Science Laboratory, Medicine, Menzies Institute for Medical Research

Publisher

Springer Nature

Publication status

  • Published

Place of publication

United States

Event Venue

Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia.

Rights statement

Copyright 2023 TheAuthor(s), under exclusive license to Springer Science+Business Media, LLC, part of SpringerNature