Ultrathroughput Multiple Reaction Monitoring Mass Spectrometry for Large-Scale Ca

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Protein biomarkers have enormous potential in the diagnosis, prognosis and treatment of cancer. Realization of the high therapeutic and financial potential of cancer biomarkers demands new technologies for speedy and cost-effective production of high-quality biomarkers and facile adjustments for measuring newly-produced biomarkers. Liquid chromatography- stable isotope dilution-multiple reaction monitoring mass spectrometry (LC-SID-MRM MS) of signature peptides of candidate biomarkers is an emerging technology well suited to this field. This application will establish the feasibility of transforming this mass spectrometry method to break through the sample-throughput bottleneck. The new technology is termed Ultrathroughput Multiple Reaction Monitoring (UMRM) MS and is an integration of LC-SID-MRM MS and peptide derivatization. Two specific aims will be pursued: (1) identification of suitable peptide derivatizations for UMRM measurements, and (2) validation of derivatizations for UMRM analysis of prostate-specific antigen in 108 serum samples in a single experiment. The fundamental novelty of the new technology rests on the novel transformation of LC-SID-MRM MS to produce unprecedented sample throughput. It has three unique advantages: the throughput advantage, the flexibility and immediate-impact advantage, and the economic advantage. The new technology can be implemented with inexpensive reagents and commercial mass spectrometers for focused quantitation of cancer biomarker candidates in many phases of a biomarker pipeline. The drastically increased sample throughput of the new technology will in particular impact the verification and validation of biomarker candidates, which require targeted quantitation of hundreds to thousands of patient-control samples. Thus, the UMRM technology will significantly accelerate new cancer biomarker generation. The new technology also has potential in advancing quantitative biology of cancer.