The objective of this project is to evaluate a new high-throughput and ultra-sensitive platform that will enable more effective and higher throughput proteomics measurements to support and advance cancer research. The new platform will provide substantially higher resolution ion mobility spectrometry (IMS) separations than current platforms. This work also leverages previous developments at our laboratory by combining these new capabilities with more sensitive and efficient ion source and high accuracy MS technologies. The resolution of the IMS achieved will be greatly increased by using electric traveling waves applied to an extremely long path design based upon Structures for Lossless Ion Manipulations (SLIM), while also enabling very high sensitivity to be achieved. The platform will provide approximately two orders of magnitude improvement in measurement throughput for similar or better measurement coverage, quantification, etc. over conventional condensed-phase liquid chromatography-mass spectrometry (LC-MS) platforms, enabling thousands of samples to be analyzed in hours, rather than weeks as at present. We will also adapt and refine bioinformatics tools developed in our laboratory to provide automated and efficient data processing. Finally, the platform will be evaluated utilizing complex clinical samples in terms of proteomic peptide/protein coverage, measurement throughput, CVs of replicate analyses and platform robustness and in comparison to leading-edge conventional LC-MS platforms available in our laboratory.

Public Health Relevance

This project aims at evaluating and validating a new high resolution and high throughput ion mobility spectrometry-mass spectrometry (IMS-MS)-based platform for cancer research and future clinical applications. The new platform will provide much higher throughput and improved data qualities based upon a new approach providing greatly improved higher speed and higher resolution IMS separations integrated with a sensitive and robust ion source and high performance MS. This project will also adapt bioinformatics tools to provide automated and streamlined data acquisition, processing, and analysis to enable early application of the new platform.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
5R33CA217699-03
Application #
9751068
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Knowlton, John R
Project Start
2017-08-01
Project End
2020-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Battelle Pacific Northwest Laboratories
Department
Type
DUNS #
032987476
City
Richland
State
WA
Country
United States
Zip Code
99352