Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology

摘要

Data-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic methodologythat generates permanent digital proteome maps offering highly reproducible retrospective analysis ofcellular and tissue specimens. The adoption of this technology has ushered a new wave of oncologystudies across a wide range of applications including its use in molecular classification, oncogenicpathway analysis, drug and biomarker discovery and unravelling mechanisms of therapy response andresistance. In this review, we provide an overview of the experimental workflows commonly used inDIA-MS, including its current strengths and limitations versus conventional data-dependent acquisitionmass spectrometry (DDA-MS). We further summarise a number of key studies to illustrate the power ofthis technology when applied to different facets of oncology. Finally we offer a perspective of the latestinnovations in DIA-MS technology and machine learning–based algorithms necessary for driving thedevelopment of high-throughput, in-depth and reproducible proteomic assays that are compatible withclinical diagnostic workflows, which will ultimately enable the delivery of precision cancer medicine toachieve optimal patient outcomes.