Clinical Proteomics: The Path Towards Implementation
Harald Mischak (Presenter)
mosaiques therapeutics GmbH & University of Glasgow
Presenter Bio(s): Harald Mischak, born 1961 in St. Pölten, Austria, received his PhD in technical science from the Technical University of Vienna, Austria, in 1986.
Between 1988 and 1993, after postdoctoral work on the Rhinovirus receptor at the University of Vienna (Institute for Biochemistry), he was on leave as an invited scientist on signalling by protein kinase C and Raf at the Laboratory of Viral Carcinogenesis (funded by the Fulbright Foundation) and as a Schroedinger and Fogarty Fellow at the Laboratory of Genetics at the NIH National Cancer Institute in Bethesda, Maryland, USA.
He continued his research on kinases as Group Leader at the GSF, Munich, Germany from 1993-1998. He wrote his habilitation in clinical microbiology at the Technische Universität München on Protein Kinase C in Signal Transduction. After one year as a scientific group leader at Franz-Volhard Klinikum (MDC) at Berlin-Buch, he worked on the structure of kinases and related molecules at the NIDDK, Bethesda, Maryland, USA. In 1999 he took up a position at the Department of Nephrology at Medical School of Hannover. Here he founded Mosaiques diagnostics and therapeutics AG in 2002, which was started with the aim to identify disease-specific polypeptides. Currently, he holds a position as Professor for Proteomics and Systems Medicine at the University of Glasgow, and he is the chief scientific officer of Mosaiques AG as well as executive director of Mosaiques diagnostics GmbH and Mosaiques DiaPat GmbH. With more than 300 scientific publications on signaling and proteomics that have been cited over 20000 times, he is one of the leading experts worldwide in the field of proteome research and applied systems biology. Prof. Mischak is named as inventor on more than 100 patent applications, the majority on proteomic biomarkers.
Among his major achievements is the identification of distinct biological roles of Protein Kinase C. He demonstrated that Protein Kinase C isoforms display highly divergent biological properties in differentiation and oncogenic transformation (Mischak et al. 1993, J Biol Chem 268, 1749-1756 and 20110-20115) and associated these with distinct intracellular localization (Goodnight, Mischak, et al. 1995, J Biol Chem 270:9991-10001). Together with Walter Kolch (for Raf signaling, e.g. Kolch et al. 1993, Nature 364:249-252) and Hans Hacker (for CpG signaling, e.g. Hacker, Mischak et al. 1998, EMBO J 17:6230-6240) he pinpointed the role of kinases in several major signaling mechanisms. Based on his experience on proteomics in basic research, he initiated the use of urinary proteomics and capillary electrophoresis coupled mass spectrometry for clinical application, and is the leading authority in clinical proteomics and biomarker identification. Among his achievements in this field are the development of guidelines for clinical proteome analysis, where he led a large international and multidisciplinary group to develop clinically relevant proteomic biomarkers (Mischak et al. 2007, Proteomics Clin Appl 1:148-156; 2010, Sci Transl Med 2:46ps42; 2012, Eur. J Clin Invest 42, 1027-1036), and the demonstration of successful application in the diagnosis and prognosis of several diseases (e.g. Decramer et al. 2006, Nat. Med. 12:398-400; Theodorescu et al. 2006, Lancet Oncol. 7:230-240; Rossing et al. 2008, JASN 19:1283-1290; Good et al. 2010, Molecular & Cellular Proteomics 9:2424-2437; Kuznetsova et al. 2012, Eur. Heart J. 33, 2342-2350).
The two main focuses of Prof Mischak’s work are:
1) identification, validation, and especially implementation of proteomic biomarkers, aiming especially at biomarkers associated with chronic kidney disease, coronary artery disease, heart failure, and certain types of cancer
2) uncovering the molecular changes on a proteomic level that are relevant in, or even cause of, the major diseases mentioned above. This approach is based on the biomarkers identified, but also on addition proteomic, metabolomic and genomic data. Using appropriate bioinformatic approaches, the high-dimensional data are combined to identify the underlying molecular structures and ultimately develop a molecular model of the respective disease, which in turn will allow identifying the most appropriate therapeutic targets for intervention.