Professor Jonathan Blackburn, Chief Scientific Officer (CSO) of Sengenics, featured in a sponsored DDW Sitting Down With podcast to discuss the advantages of functional protein microarrays, challenges to overcome for biomarker discovery, Sengenics’ new i-Ome Discovery chip, and more.
Professor Blackburn began by sharing an overview of his current research, including the work he does with Sengenics. He’s the CSO of Sengenics, but also has an academic appointment at the University of Cape Town where he holds a research chair in proteomics and chemical biology. His academic lab is technology-driven and focuses on developing and applying proteomic technologies to the study of underlying disease mechanisms, as well as the identification of diagnostic and prognostic markers across several different disease areas.
Following an outline of the particular ways in which his lab uses both protein microarray and mass spectrometry tools to study different cancers, autoimmune conditions, and infectious diseases, Blackburn elaborated on the release of Sengenics’ new protein microarray, i-Ome Discovery, and why this new chip is an exciting addition to proteomics research.
i-Ome Discovery is Sengenics’ latest protein microarray product, designed to enable the discovery of novel, reproducible, biologically relevant quantitative autoantibody biomarkers with high diagnostic and prognostic value, and ability to stratify of patients into disease subgroups for better study and treatment. The platform comprises over 1800 human antigens that meet the criteria for candidate auto antigens, and which Sengenics have selected for their biological relevance across numerous different disease areas including oncology, rheumatology, neurology, endocrinology, infectious diseases, and even immune deficiency.
Blackburn elaborates in detail on the reason why only 1800 antigens, what the literature suggests, and why it is unnecessary to build a platform to assay the full human proteome.
He speaks about the importance of proper protein folding for high specificity binding on the arrays, because unfolded and denatured proteins can bind non-specifically to exposed hydrophobic surfaces resulting in data that this has no biological meaning. He also highlights the importance of keeping these factors, amongst others, in mind.
Blackburn proceeds to outline some recent developments and breakthroughs in biomarker discovery that he finds particularly promising. Referencing the unmet potential for both genomic medicine, as well as the interest in cell-free DNA markers, particularly for early detection of cancers, he goes on to share the hopefulness that proteomics will do better. He says in reality, the number of FDA approved protein biomarkers discovered de novo through proteomics is vanishingly small today. He elaborates in the podcast. Blackburn also shares what he is most excited about for the biomarker field today, notably his lab’s recent data that has gone beyond measuring just IgG and blood to quantifying the different antigen specific antibody classes, or isotypes. “That’s where I think there’s massive potential and real hope for a new wave of biomarkers coming soon,” he says.
When it comes to the biggest challenges to overcome in the realm of biomarker discovery and whether Sengenics’ technology, i-Ome Discovery specifically, can help overcome these challenges, Blackburn encourages using the expertise of a seasoned biostatistician early in study design to ensure proper statistical power, noting that with i-Ome Discovery’s high reproducibility, biologically relevant proteins and manageable chip size, fewer subjects are necessary than other platforms.
Sengenics can also help comb through all the data. Blackburn says: “We realised early on that autoantibody datasets have an intrinsically different underlying structure to other omics datasets.” He continues on how the company uses machine learning to drive biologically meaningful insight and value on complex dynamic disease states.
The episode concludes with a summary of the potential applications of this work, recapping the episode’s coverage of how Sengenics’ technology is used. Blackburn concludes: “I really think that everybody should now be including autoantibody- based profiling in their biomedical studies to complement other omic measurements.”
DDW Volume 25 – Issue 1, Winter 2023/2024