Construction of Synthetic Human Antibody Library Based on Repertoire Sequencing

Human monoclonal antibody is a good modality of molecular targeting therapy for various diseases including inflammatory dysregulations and malignant tumors. Recent advances in immune-repertoire sequencing have enabled us to identify disease-related human antibodies as well as candidate therapeutic antibodies for malignancies from disease specimens (#1-3). By analyzing immunoglobulin repertoires of tumor infiltrating B-lymphocytes in human cancers and synthesizing antibodies based on the sequencing information, we discovered that approximately one-third of dominant B-lymphocyte clones in tumors expressed antibodies that reacted to sulfated glycosaminoglycans (#1), and another one-third expressed those corresponding to ribonucleoproteins in the focal adhesion complex (#2). Moreover, the anti-sulfated glycosaminoglycan antibodies found in human disease specimens have been revealed to be candidate therapeutic antibodies. Thus, the sequencing information of the repertoire sequencing by itself can be precious database to develop therapeutic human antibodies.

However, although next generation repertoire sequencing acquires hundreds of thousands of immunoglobulin repertoires from a single specimen, methods for the construction of disease-specific antibody library, its amino acid modification strategy, and functional screening has not been established to date. Here, based on repertoire information, we show a high-throughput method for the selection and synthesis of cDNA library of disease-related human antibodies and a rational designing strategy of amino acid modifications to obtain higher functional human monoclonal antibodies.

#1. Katoh H, et. al., Immunogenetic profiling for gastric cancers identifies sulfated glycosaminoglycans as major and functional B cell antigens in human malignancies. Cell Rep 2017.

#2. Konishi H, et. al., Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning. BMC Bioinformatics 2019.

#3. Atsumi S, et. al., Focal adhesion ribonucleoprotein complex proteins are major humoral cancer antigens and targets in autoimmune diseases. Commun Biol 2020.