Technology & Data Science for Enhanced Patient Care

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UNITED STATES 2016

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Scaling Discovery Proteomics to Large Lung Cancer Cohorts Using Data Independent Acquisition
John Koomen
Moffitt Cancer Center
[email protected]

Discovery proteomics using data independent acquisition (DIA) provides the maximum content from a single LC-MS/MS analysis. After a pilot project to compare DIA to discovery proteomics using traditional data dependent acquisition techniques, DIA strategies have been optimized and applied to 2 cohorts of lung cancer patients. The biology of the proteome detected and quantified in DIA experiments has been explored, and the resulting data have been used to classify lung cancer patients by their proteomic phenotypes. Feasibility has also been demonstrated for analysis of tissue microarrays using this technique, producing quantitative data for >3,000 proteins from a single section of a lung tumor core (0.6 mm in diameter and 5 microns thick). These data indicate the potential utility of DIA for assessment of tumor biology in situ using archived tumor specimens.

Presented at MSACL 2016 US