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Biomarkers help understand complex biological networks

1st April 2013


Ronald Koop looks at a robotic whole-cell imaging technology that integrates cell biology and biomathematical tools.

Drug development is a complicated process. Drugs must work well in patients yet because organisms are much more complex than current molecular models have led us to believe, a more comprehensive understanding of biological networks is needed for a rational drug design. For this reason, in the long run, a systems biology-based understanding of complex organisms is indispensable. Combinatorial biomarkers represent a first step toward this goal. They are based on systematic approaches and provide a more holistic view of the organism, while not requiring systematic modelling.

As the main components of metabolic pathways, proteins are the preferred drug targets and therefore a logical opportunity for biomarker identification.

Unlike the genome, the proteome is in a constant state of change. Cellular function or dysfunction depends upon the protein network environment as a whole. The topology of protein networks that comprise the proteome depends on timing, gene expression patterns, and cellular environment.

Advances in studies of protein-protein interactions, protein expression profiling, annotated proteomics databases, and sophisticated protein function methodologies all offer the promise of accelerating diagnostic and therapeutic product development.

While proteins are not randomly distributed within cells or throughout tissue, their precise location and specific inter-relationships are of paramount importance for the elucidation of cellular functional protein networks.

A toponomics approach therefore provides the highest possible information content and quality thus enabling pharmaceutical companies to obtain maximum return on their investment in genomics technology because analyses are not based solely on physical protein-protein interactions, but on functional protein network units.

MelTec has developed MELK as a solution to this significant industry problem by combining high content analysis with the combinatorial potential of proteomics. MELK is a robotic whole-cell imaging technology that integrates cell biology and biomathematical tools to simultaneously visualise dozens of proteins in a structurally intact cell or tissue. MelTec then processes the visualised information generated by MELK through their proprietary, advanced data analysis software, enabling the identification of protein networks that play a crucial role in biological processes.

These powerful tools simultaneously elucidate disease mechanisms and screen for the effects of compounds on these and toxicology-related pathways in a given tissue. By screening for changes in the distribution of all possible combinations of proteins (50 proteins give rise to 1015 different possible combinatorial protein patterns) upon drug treatment or the presence of disease, MelTec can identify very specific combinatorial biomarkers for tox analysis, lead compound selection, and clinical monitoring.

The advantage of combinatorial biomarkers is in their broad application, since they can be used even if the action mechanism of a drug is less clear. It can also show details about the mechanism and monitor toxic side effects at the same time. MelTec has identified novel powerful biomarkers for toxic effects that can be further improved by including customer specific marker needs. Furthermore, it is possible to monitor multiple markers and pathways from very small blood or tissue samples in their natural biological context which is useful for patient monitoring and stratification.

Ronald Koop is with MelTec GmbH & Co KG, Magdeburg, Germany. www.meltec.de





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