High Resolution High Throughput Proteomics Platform for Cancer Research

用于癌症研究的高分辨率高通量蛋白质组学平台

• 批准号: 9534591
• 负责人: Yehia Ibrahim
• 金额: $ 41.65万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9534591
• 关键词: Address; Advanced Malignant Neoplasm; Bioinformatics; Biological; Clinical; Complex; DNA Sequence Alteration; Data; Data Quality; Detection; Development; Devices; Fractionation; Future; Hour; Informatics; Ions; Laboratories; Length; Liquid Chromatography; Mass Spectrum Analysis; Measurement; Peptides; Performance; Phase; Population; Population Study; Proteins; Proteome; Proteomics; Reproducibility; Resolution; Route; Sampling; Spectrometry; Speed; Structure; Technology; Time; Travel; Work; anticancer research; base; clinical application; computerized data processing; data acquisition; design; genetic regulatory protein; improved; ion mobility; ion source; liquid chromatography mass spectrometry; novel; novel strategies; operation; tool; tumor

PROJECT SUMMARY/ABSTRACT 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.

项目总结/文摘