Bioinformatic pipeline to identify potential therapeutic targets with subsequent isolation and characterization of novel human anti- DDR1 antibodies.

Breast cancer remains a major global health challenge, driving the need for safer and more effective targeted therapies. This study aimed to systematically identify therapeutic targets for breast cancer using an integrated bioinformatics approach and to generate novel human monoclonal antibodies against an identified potential target followed by characterization. A multi-step bioinformatic pipeline was developed to analyse paired tumour and matched non-cancerous breast tissue samples from The Cancer Genome Atlas. Differential expression analysis, target selection criteria, and surface-protein enrichment identified several dysregulated and therapeutically relevant candidates, including established markers such as HER2, supporting the robustness of the approach. From the shortlisted targets, epithelial discoidin domain-containing receptor 1 was selected for antibody discovery. A naïve human phage display library was screened to isolate DDR1-specific single-chain variable fragments that were reformatted into full-length human IgG1. These antibodies were expressed, purified, and characterized through biophysical evaluation and in vitro assays. Several candidates demonstrated high-affinity binding to native DDR1 on breast cancer cells and showed the ability to mediate tumour cell lysis through antibody-dependent cell cytotoxicity. Overall, this study highlights the effectiveness of combining publicly available omics datasets with phage display technology to identify and develop new therapeutic antibody candidates for breast cancer.