Epitope Binning-Seq: Revolutionizing Antibody Drug Discovery

Monoclonal antibodies are powerful medical tools because they can precisely target specific sites on antigens called epitopes. These interactions stimulate the immune response, making monoclonal antibodies essential for developing effective therapies.

However, understanding how antibodies work requires a detailed analysis of the epitopes they target. Unfortunately, traditional methods for studying epitopes are time-consuming and complex. This poses a significant hurdle in the development of new antibody-based treatments.

Consequently, there is an urgent need for more effective methods that can assist in mapping epitopes quickly and precisely, thereby speeding up the creation of next-generation treatments.

Tokyo Institute of Technology researchers conducted ground-breaking research to close this gap, which led to the creation of the unique platform known as Epitope Binning-seq. The study was published in the journal Communications Biology.

Using next-generation sequencing (NGS) and genetically encoded query antibodies (qAbs) on antigen-expressing cells, Epitope Binning-seq assesses epitope similarity. This process enables the evaluation of multiple qAbs simultaneously without requiring their individual purification.

This investigation used query antibodies (qAbs) that were present on the surface of HER2-expressing cells. Using flow cytometry analysis and fluorescently labeled reference antibodies (rAbs), researchers were able to discriminate between cells where the qAbs masked the epitopes and cells where they did not.

Certain qAbs successfully prevented rAb from binding to the antigen, creating a population of cells known as the rAb-negative population. On the other hand, other qAbs enabled rAb to bind to the antigen, producing a population of cells with rAb binding—known as the rAb-positive population.

 The differential binding behavior served as a basis for evaluating epitope similarity between different antibodies. We performed NGS analysis on the sorted rAb-negative populations to identify and group similar qAbs into epitope bins. This comprehensive approach enabled efficient analysis of a large number of antibodies and classification based on their epitope specificity.”

Tetsuya Kadonosono, Study Corresponding Author and Associate Professor, Tokyo Institute of Technology

The outcomes showed great promise. The epitope Binning-seq method effectively categorized antibodies into discrete epitope bins, offering a significant understanding of their binding behaviors. The technique effectively identified and enriched particular qAbs, even detecting clones at very low initial abundances in experiments using model antibodies pertuzumab and trastuzumab.

The platform accurately and precisely classified 14 qAbs into the appropriate epitope bins. These results highlight the potential of Epitope Binning-seq to expedite antibody drug development in the early stages by assessing millions of qAbs concurrently and speeding up the identification of viable therapeutic candidates.

This platform offers many advantages. By expediting epitope comparison and facilitating the quick identification of antibodies with comparable binding patterns, epitope Binning-seq has the potential to advance targeted and successful antibody-based therapies. The method’s large-scale evaluation can evaluate millions of qAbs at once, which has the potential to revolutionize antibody characterization.

The development of Epitope Binning-seq represents a major advancement in antibody drug discovery. By providing a rapid, comprehensive, and cost-effective method for evaluating antibody epitope similarity, this novel platform overcomes the limitations of traditional epitope analysis techniques.”

Tetsuya Kadonosono, Study Corresponding Author and Associate Professor, Tokyo Institute of Technology

The study's encouraging findings demonstrate how this approach may revolutionize early antibody drug development and antibody affinity maturation, opening the door to more potent treatment approaches down the road.