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Michael Jones is currently a technology leader in the Oncology and Biomarker Discovery unit at Novartis Institute of Biomedical Research. He is also an independent consultant advising and contributing to computational algorithm development for machine learning and data-mining solutions as well as sophisticated software engineering projects. After achieving his degree in Biochemistry from UCLA he worked at Amgen as a biotechnology wet lab scientist in the fields of proteomics, protein characterization and biophysics. His later transition to computational biology and bioinformatics allowed him to explore new solutions to scientific problems. Michael advanced his computational and scientific skills at Netgenics and Millennium Pharmaceuticals and has contributed to and provided leadership in multidisciplinary teams to create solutions to complex scientific problems. He has also contributed to Open Source and private software development projects.
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Application of Proteomics to Biomarker Discovery
Michael Jones, Novartis
The search for biomarkers has been intensified in recent years as the need for more accurate and less invasive methods for detecting disease progression, assessing drug efficacy and performing pharmacogenomic analysis has increased. In an attempt to discover surrogate molecular biomarkers in the background of complex disease states and population heterogeneity high throughput methods have been utilized. One popular high throughput biomarker discovery method is microarray analysis which requires obtaining patient tissue biopsies to extract the mRNA needed for profiling. Validation of discovered biomarkers is later done through more sensitive and quantitative methods in more easily obtained sources such as serum. Using tissue biopsies is problematic, since acquiring biopsies requires invasive techniques, and since the tissues may not be representative of the clinical method used for measuring molecular biomarkers. Biomarker discovery through proteomics has arisen as an alternative. Proteomics technologies have the potential to determine protein identity and quantity directly from body fluids. Potentially, with proteomics, the same tissue source could be used for biomarker discovery, validation and clinical use.
Several methods in proteomics have been developed for high throughput molecular biomarker discovery. We will discuss Mass Spectrometry (MS) related profiling technologies. Two commonly used techniques are the use of LC-MS/MS or LC-MS analysis of complex peptide mixtures. A third approach involves the direct measurement of complex mixture of undigested proteins. Each of these methods has advantages and deficiencies in the ability to produce quantitative profiles.
These methods will be assessed in terms of their advantages and disadvantages in the areas of quantitation, identification and sample preparation. We will finally discuss the technical hurdles that need to be overcome to make proteomic profiling competitive with microarray analysis for biomarker discovery.
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