One of the biggest challenges in the translation of mass spectrometry (MS)-based biomarkers into the development of clinical research methods is the lack of fully developed tools and workflows to deliver the throughput specificity, sensitivity, and robustness needed for clinical applications. In addition, many existing protein biomarker candidates may prove too non-specific to be clinically useful such that significant discovery work focused on protein isoforms still remains to be done.
Immunoenrichment coupled to selected-reaction monitoring (MSIA-SRM) allows high-throughput, quantitative and highly selective detection of clinically important proteins in plasma, serum and cerebrospinal fluid. The method is robust and scalable, can be multiplexed and automated, and extends the limits of detection for low-abundance molecules. In this webinar, Dr. Mary Lopez (Director of Biomarker Research Initiatives in Mass Spectrometry (BRIMS) at ThermoFisher Scientific) will discuss the crucial parameters that must be considered when developing MSIA-SRM assays. She will also describe how this method has been applied to the study of Alzheimer’s Disease plasma samples. In one series of studies, variants of beta amyloid (Aβ) and apolipoprotein E (Apo E), both important protein biomarkers associated with Alzheimer’s Disease, were detected and quantified from plasma for the first time using MSIA-SRM. This powerful technology workflow has also recently been applied to quantify biomarkers for other diseases including endocrine disorders, cancer and cardiovascular disease.
What you will learn:
- The key challenges in the translation of mass spectrometry (MS)-based biomarkers into the development of routine clinical assays
- Sample preparation and analysis using MSIA-SRM quantification methods, their advantages and disadvantages compared to other methods
- How MSIA-SRM has been used in a study of Alzheimer’s Disease
Speaker:
Dr. Mary Lopez
Director, Thermo Fisher Scientific's Biomarker Research Initiative in Mass Spectrometry Center
Original Broadcast: December 10, 2013
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