title: Computational selection of antibody-drug conjugate targets for breast cancer.
abstract: The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics.
authors.affiliation: Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: François
authors.initials: F
authors.lastname: Fauteux
authors.affiliation: Human Health Therapeutics, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Jennifer J
authors.initials: JJ
authors.lastname: Hill
authors.affiliation: Human Health Therapeutics, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Maria L
authors.initials: ML
authors.lastname: Jaramillo
authors.affiliation: Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Youlian
authors.initials: Y
authors.lastname: Pan
authors.affiliation: Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Sieu
authors.initials: S
authors.lastname: Phan
authors.affiliation: Information and Communication Technologies, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Fazel
authors.initials: F
authors.lastname: Famili
authors.affiliation: Human Health Therapeutics, National Research Council Canada, Ottawa, Ontario, Canada.
authors.forename: Maureen
authors.initials: M
authors.lastname: O'Connor-McCourt
mesh_terms: D000911:Antibodies, Monoclonal / Q000378:metabolism*; D000970:Antineoplastic Agents / Q000378:metabolism*; D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000145:classification* / Q000188:drug therapy / Q000235:genetics / Q000473:pathology; D019295:Computational Biology / Q000379:methods*; D016503:Drug Delivery Systems; D004847:Epithelial Cells; D058750:Epithelial-Mesenchymal Transition; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D018796:Immunoconjugates / Q000235:genetics*; D014407:Tumor Cells, Cultured
chemical_list: D000911:Antibodies, Monoclonal; D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D018796:Immunoconjugates
keywords: ADC; drug target; ensemble classification; feature selection; microarray