Day 1 :
Cleveland Diagnostics, USA
Time : 09:05-09:35
Boris Zaslavsky graduated in Analytical Chemistry from the Moscow State University. He holds a PhD and a DSc (USSR Academy of Sciences), was a scientist at USSR Academy of Sciences (1971-1991), Visiting Fellow at Cornell University Medical School (NYC, 1991-1992), and KV Pharmaceuticals (1993-1994), Argonne National Laboratory (1994-1995). He is the founder of Analiza, Inc. (1996-present) and Cleveland Diagnostics (2014-present), where serves as a Chief Scientific Officer. He published 1 monograph, over 120 scientific papers, and 7 patents. His research interests are development of analytical applications of aqueous two-phase partitioning, new clinical tests for early cancer detection and other applications, role of water in biology, and protein-water interactions.
It is well known that a disease process is commonly associated with changes in protein structure or protein-protein interaction. These changes are under-utilized in clinical practice. In complex diseases such as cancer, structural changes in proteins within the tumor cells are vast, ranging from alternative splicing to posttranslational modifications and can be used as highly efficacious markers for clinical diagnostics. The lack of robust low-cost technologies to evaluate structural changes in proteins, however, precludes the use of these changes in clinical diagnostics. Hence protein biomarkers are defined solely based on changes in their relative expression. We present a new hypothesis-free technology based on the firm physicochemical principles enabling one to discover, develop and apply new structural protein biomarkers directly in circulating biofluids. These biomarkers are defined via changes in protein structure instead of variations in protein amounts. Solvent Interaction Analysis (SIA) is a novel technology that could be combined with many downstream conventional proteomics and clinical-level instruments. The method is based on analytical application of protein partitioning in aqueous two-phase systems which is highly sensitive to changes in protein structure and protein-partner interactions. The technique is simple, low-cost and can be conducted manually or with conventional lab automation. The technology can be used for discovery of single protein markers using ELISA or for finding multiplexed biomarkers by interfacing with downstream multiplexed bead-based assays or for label-free discovery of structure-based biomarkers using mass spectrometry. We demonstrate the utility of the SIA technology as basic tool for clinical diagnostics and discuss a recently introduced assay that monitors changes in the structure of Prostate-Specific Antigen (PSA) for prostate cancer diagnosis instead of evaluating the PSA amounts in serum. We illustrate the assay development, clinical performance results vs. gold-standard assays and commercial implementation. Finally, we discuss the future of structure-based approaches to protein biomarkers as a basis for high performance clinical-grade protein biomarkers.
Center for Biologics Evaluation and Research-USFDA, USA
Time : 09:35-10:05
John F Cipollo completed his PhD work at the State University of New York at Albany. He performed Post-doctoral studies at Boston University School of Medicine where he was the first to report the glycome of the model organism Caenorhabditis elegans, discovered phosphorylcholinyl oligosaccharides and demonstrated their synthesis in this organism. These compounds are host immune response modulators in parasitic nematodes. He was a Professor of Biochemistry at Boston University until recruited in 2007 to Center for Biologics Evaluation and Research at the US Food and Drug Administration where he has made meaningful contributions to the understanding of vaccine antigen glycosylation. He has published over 30 papers in reputed journals. He has also written guidance documents for the World Health Organization and United States Pharmacopeial Convention.
Currently the majority of seasonal influenza vaccine is produced in embryonated hen eggs. However, due to an inconsistent egg supply, many manufacturers are moving towards alternative cell substrates for vaccine antigen production such as MDCK (canine), VERO (primate), Sf9 (insect) and tobacco mosaic based (plant) systems. Because these cell systems derive, from different species, the proteins or viruses expressed in them, that will harbor species specific glycosylation characteristics. As glycosylation can have significant impact on antigenicity and processing by the innate and humoral immune systems, these cell specific differences in major influenza vaccine antigen glycosylation can impact vaccine efficacy and safety. To investigate the impact of glycosylation on influenza and other vaccines containing glycoprotein antigens, we have developed a glycomics workflow to investigate potential impact of these post translational modifications on antigen structure and function. This workflow includes: 1) Analysis of released and permethylated glycans; 2) glycopeptide analysis by nano-LC/MSE; 3) Molecular modeling of antigenic sites with regard to glycosylation sites and their resident glycans. We have also developed in-house glycoinformatics tools to aid in our analyses.
Berlin Institute for Medical Systems Biology - MDC Berlin, Germany
Time : 10:05-10:35
Metabolic reprogramming is a required step during oncogenesis. It is triggered by activation of oncogenes and loss of tumor suppressors and leads to an activation of central metabolic pathways to support cell growth and proliferation. In order to quantify the usage and activity of metabolic pathways in vitro and in vivo, we have developed pulsed stable isotope resolved metabolomics (pSIRM). The applied GC-MS based technology enables the absolute quantification of metabolites and at the same time the determination of stable isotope incorporation. Using pSIRM, we have characterized the action of inhibitors of glycolysis in cell cultures. We observed that the commonly used compound 2-deoxyglucose is not a specific glycolytic inhibitor, the action of 3-bromopyruvate as glycolytic inhibitor could be confirmed. We next analyzed the metabolic program of hepatocellular carcinoma using quantitative proteomics and in vivo isotope labelling. We further characterized the action of glycolytic inhibitors in a HCC-mouse model. Finally, we compared the metabolic phenotype of HCC between mice and humans.