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dc.contributor.authorKrasny, L
dc.contributor.authorHuang, PH
dc.date.accessioned2020-10-12T08:42:44Z
dc.date.issued2020-10-09
dc.identifier.citationMolecular omics, 2020
dc.identifier.issn2515-4184
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/4135
dc.identifier.eissn2515-4184
dc.identifier.doi10.1039/d0mo00072h
dc.description.abstractData-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic methodology that generates permanent digital proteome maps offering highly reproducible retrospective analysis of cellular and tissue specimens. The adoption of this technology has ushered a new wave of oncology studies across a wide range of applications including its use in molecular classification, oncogenic pathway analysis, drug and biomarker discovery and unravelling mechanisms of therapy response and resistance. In this review, we provide an overview of the experimental workflows commonly used in DIA-MS, including its current strengths and limitations versus conventional data-dependent acquisition mass spectrometry (DDA-MS). We further summarise a number of key studies to illustrate the power of this technology when applied to different facets of oncology. Finally we offer a perspective of the latest innovations in DIA-MS technology and machine learning-based algorithms necessary for driving the development of high-throughput, in-depth and reproducible proteomic assays that are compatible with clinical diagnostic workflows, which will ultimately enable the delivery of precision cancer medicine to achieve optimal patient outcomes.
dc.formatPrint-Electronic
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleData-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology.
dc.typeJournal Article
rioxxterms.versionofrecord10.1039/d0mo00072h
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2020-10-09
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfMolecular omics
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology
pubs.publication-statusPublished
pubs.embargo.termsNo embargo
icr.researchteamMolecular and Systems Oncologyen_US
dc.contributor.icrauthorKrasny, Lukasen
dc.contributor.icrauthorHuang, Paulen


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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0