Finding therapies for neurodegenerative disorders is probably one of today’s most urgent scientific needs. According to WHO statistics, deaths due to dementia have more than doubled between 2000 and 2015, making it the 7th leading cause of death in 2015. But scientists studying neurodegenerative disorders are stuck in a classic catch-22 situation.
Despite long-term research efforts worldwide, the molecular background of conditions such as Alzheimer’s disease is still unknown. In the absence of diagnostic biomarkers, patients go undiagnosed for decades before the actual disease onset. But even if patients were diagnosed earlier, they could still not be treated, as drug development is nearly impossible without an addressable molecular target. And to obtain meaningful results in clinical studies, suitable patient cohorts must be identifiable based on a clear diagnosis.
Introducing high protein expression profiling
Now, there might be a way out of the stagnant situation: A new approach to biomarker discovery and validation that uses high protein expression profiling—in other words, high-throughput, microchip-based immunoassays. In a joint project of academic and business partners, a set of more than a thousand antibodies has been collected. It allows for sensitive protein detection from a broad range of animal and human samples, including plasma, serum, CSF, tissue, cells, and interstitial fluids.
Dr. Ronny Schmidt, Head of Business Development at Sciomics, a German Cancer Research Center (DKFZ) spin-off biotech, presents the concept: “Genetic information alone has not provided sufficient insight on neurodegenerative diseases. We need to look at information on protein expression levels and post-translational modifications—and monitor changes over time.”
Armed with this high protein expression profiling technology, it is now possible to identify a diagnostic biomarker and its corresponding therapeutic target in parallel, integrating biomarker discovery and validation into the drug development process and facilitating companion diagnostics.
Challenging mass spectrometry for biomarker discovery
The Sciomics immunoassay-based approach enables applying sufficient throughput in the early phase of biomarker detection, a process dominated by mass spectrometry (MS) methods. Although MS provides a higher level of information detail, the need for expensive instrumentation and technological and bioinformatics knowledge prevents its use in the later biomarker validation and clinical application phases, where immunoassays are the standard method.
Streamlining the entire process to immunoassays has significant advantages, as Ronny explains: “Immunoassays are well established in every protein lab, and most clinical investigations and drug development efforts rely on this technology. The switch from MS to immunoassays between the early discovery phase to the validation or preclinical stage often leads to high attrition rates, as MS calls for extensive sample preparation – including depletion, fractionation, digestion, and separation – while immunoassays use a different analytical approach and analyze the entire sample”.
The Sciomics business model
Sciomics offers the full service from sample to data interpretation and also provides recommendations about the next experimental steps to take.
“We pursue a holistic approach to all our projects, and our business relationships are more like research collaborations”, Ronny emphasizes. “For example, if a subset of proteins that might be involved in a disease mechanism has been identified, we can produce custom arrays for a follow-up study or recommend the best antibody source from our vast network of suppliers so our customers can develop their own immunoassays for their next experiments.”
Analyzing ubiquitination—a key process in Alzheimer’s disease
Although the molecular mechanism of Alzheimer’s disease has not yet been identified, defects in the recognition and degradation of misfolded proteins such as amyloid beta plaques and tau tangles are hot candidates. In addition, mitochondrial dysfunction and the resulting accumulation of active oxygen species have been shown to be one of the earliest and most prominent features in AD patient neurons.
Oxidized and misfolded proteins accumulate as a result of defects in ubiquitination, a post-translational modification (PTM) that marks proteins for degradation in the proteasome clearance system.
“For example, analyzing the ubiquitination status of the tau protein could allow monitoring tau tangle formation at a very early stage, providing both a diagnostic biomarker and a therapy approach,” Ronny explains.
Ubiquitination: A central metabolic process
Ubiquitination studies are especially insightful not only for studying neurodegenerative diseases, such as Alzheimer’s disease, but also immune disorders, immuno-oncology, aging, and regenerative medicine. So it is no surprise that after addressing phosphorylation as the most common PTM, the Sciomics development team now sets their focus on ubiquitination.
ScioUbi, a novel immunoarray developed for analyzing the ubiquitination status of over a thousand proteins, will officially be presented at the Analytica laboratory trade fair in Munich in April 2018.
“While there are some competitors in the market that address parallel immunoassays of up to several hundred proteins, the ScioUbi assay dedicated to protein ubiquitination is clearly unique,” Ronny says. “Our next goal is to expand our portfolio to other post-translational modifications such as acetylation, glycosylation, or sumoylation. We currently seek collaboration partners interested in particular scientific questions related to post-translational modifications.”
Sciomics is a spin-off from the German Cancer Research Center based in Heidelberg, Germany. It was founded in 2013 by a team of researchers led by Dr. Christoph Schröder and Dr. Jörg Hoheisel. Sciomics has developed antibody microarrays as a tool for analyzing complex protein samples. Using their expertise, they are able to address the complete workflow of sample analysis with both standardized and customized arrays. Learn more about their work here!
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