Therapeutic antibodies have transformed the treatment of cancer and autoimmune diseases, but even though new antibodies keep entering the clinic, they keep targeting the same antigens. Antibodies would be more helpful then, if, as a whole, they made it possible to target a wider variety of targets. The problem, however, is that developing a new antibody typically requires that a molecular target be identified beforehand.

To get around this problem, developers would like to use phenotypic screening. That is, they would like to test candidate antibodies against cells, such as cancer cells or immune cell subsets, without specifying a molecular target ahead of time. They would like to start by discovering an interaction between an antibody and a cell, and only then would they undertake the work of identifying the actual molecular target on the cell.

This work, however, is difficult. It is called deconvolution. Typically, it relies on techniques such as immunoprecipitation and protein library overexpression that are notoriously time- and resource-consuming and unreliable. They also scale poorly with the number of antibodies.

A better deconvolution technique, one that would enable phenotypic antibody discovery, may have been developed by researchers at Lund University. They report that a CRISPR-Cas9 screen, coupled to cell sorting and massively parallel single-molecule sequencing, can provide a fast and robust way to deconvolute the targets of cell surface antibodies.

Details recently appeared in Nature Communications, in an article titled, “Accelerating target deconvolution for therapeutic antibody candidates using highly parallelized genome editing.”

“Applying this approach within three real-world phenotypic discovery programs, we rapidly deconvolute the targets of 38 of 39 test antibodies (97%), a success rate far higher than with existing approaches,” the article’s authors wrote. “Moreover, the approach scales well, requires much less work, and robustly identifies antibodies against the major histocompatibility complex.”

Antibody drugs are the fastest growing class of drug, and several therapeutic antibodies are used to treat cancer. They are effective, often have few side effects, and benefit from the body’s own immune system by identifying foreign substances in the body. By binding to a specific target molecule on a cell, the antibody can either activate the immune system, or cause the cell to self-destruct.

However, most antibody drugs used today have been developed against an antibody target chosen beforehand. This approach is limited by the knowledge of cancer we have today and restricts the discovery of new medicines to currently known targets. Phenotypic discovery, however, could allow new, unexpected targets to be identified.

“Many antibody drugs currently target the same molecule, which is a bit limiting,” said Jenny Mattsson, the article’s first author and a doctoral student at Lund University. “Antibodies targeting new molecules could give more patients access to effective treatment.

“Using the CRISPR-Cas9 gene scissors, we were able to quickly identify the target molecules for 38 of 39 test antibodies. Although we were certain that the method would be effective, we were surprised that the results would be this precise. With previous methods, it has been difficult to find the target molecule even for a single antibody.”

The research project is a collaboration between Lund University, BioInvent International, and the Foundation for Strategic Research. The researchers’ method has already been put into practical use in BioInvent’s ongoing research projects.

“We believe the method can help antibody developers and hopefully contribute to the development of new antibody-based drugs in the future,” concluded Björn Nilsson, professor and leader of the research project as well as the article’s senior author.