Until recently, the field of disease proteomics was focused on separation techniques coupled with mass-spectrometric identification of proteins. However, technological limitations due to patient-to-patient variability and loss of signal from low-abundance proteins have lead researchers to a different technique: affinity proteomics.
Based on the use of capture reagents such as antibodies, affinity proteomics has emerged as a tool capable of gathering information on the global level in a high-throughput format. In the last 10 years, antibody microarray technology rapidly evolved from proof-of-concept to state-of-the-art technology capable of targeting complex, nonfractionated protein samples.
Multiple versions of affinity reagents are deployed in this space, including full-length antibodies, aptamers, affibody molecules, and single-chain variable fragments of antibodies. Various capture formats are also being explored, ranging from planar arrays (similar to commonly used printed DNA arrays) to beads, to direct synthesis of antibodies in the array format.
Affinity arrays are rapidly emerging as powerful biomarker discovery tools and have become key topics for discussion at biotech conferences worldwide. Antibody-based proteomics has already delivered multiple specific biomarker candidates, and many of those are being translated into clinical practice.
“The field of disease proteomics is in agreement that a clinical state is more likely to be described by a complex protein signature rather than a single biomarker,” says Christer Wingren, Ph.D., associate professor, CREATE Health and department of immunology, Lund University.
“Under the assumption that the immune system is highly sensitive to changes in health, like a sensor, we decided to focus on inflammatory and immunoregulatory proteins,” continues Dr. Wingren, who spoke at the Select Biosciences Advances in Microarray Technology meeting in March in Edinburgh.
“Our arrays combine molecules commonly associated with immune system regulations, but their combinations, or signatures, are unique to each disease. Moreover, these signatures seem to be robust enough to cope with population biological variability.”
Dr. Wingren’s team worked closely with clinicians to determine unmet clinical needs that could be addressed by serum proteomics. Systemic lupus erythromatosis (SLE) is a severe autoimmune disease, diagnosed on the basis of multiple clinical criteria. A more precise diagnosis of SLE, including classifying it in categories and predicting the onset of flare, would enable rheumatologists to optimize therapy accordingly.
“We also had to adapt our technology to a common clinical format, which means using crude unfractionated blood samples,” continues Dr. Wingren. “Our cross-disciplinary approach led to simultaneous optimization of all major array parameters, including antibody design, array surface, sample handling, array detection, and bioinformatic analysis, which has turned out to be essential in our efforts to design a state-of-the-art antibody array platform.”
The team used well-characterized single-chain antibody fragments directed against a few hundred key analytes involved in immunoregulation. Serum proteome profiles revealed SLE-specific inflammatory portraits. Moreover, the signatures were able to differentiate between phenotypic subsets of SLE, as well as between states of flare and remission.
Immunovia, a Lund University spin-off, will continue to validate and commercialize diagnostic tests based on the immune signatures. Notably, Dr. Wingren says he and his team have also made significant progress in defining cancer-associated biomarker signatures using the same technology platform.