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Data-Driven Discovery of Molecular Targets for Antibody-Drug Conjugates in Cancer Treatment Publisher Pubmed



Razzaghdoust A1 ; Rahmatizadeh S2 ; Mofid B3 ; Muhammadnejad S4 ; Parvin M5 ; Torbati PM5 ; Basiri A1
Authors
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Authors Affiliations
  1. 1. Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  2. 2. Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  3. 3. Department of Oncology, Shohada-e-Tajrish Medical Center, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  4. 4. Gene Therapy Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Pathology, Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: BioMed Research International Published:2021


Abstract

Antibody-drug conjugate therapy has attracted considerable attention in recent years. Since the selection of appropriate targets is a critical aspect of antibody-drug conjugate research and development, a big data research for discovery of candidate targets per tumor type is outstanding and of high interest. Thus, the purpose of this study was to identify and prioritize candidate antibody-drug conjugate targets with translational potential across common types of cancer by mining the Human Protein Atlas, as a unique big data resource. To perform a multifaceted screening process, XML and TSV files including immunohistochemistry expression data for 45 normal tissues and 20 tumor types were downloaded from the Human Protein Atlas website. For genes without high protein expression across critical normal tissues, a quasi H-score (range, 0-300) was computed per tumor type. All genes with a quasi H-score≥150 were extracted. Of these, genes with cell surface localization were selected and included in a multilevel validation process. Among 19670 genes that encode proteins, 5520 membrane protein-coding genes were included in this study. During a multistep data mining procedure, 332 potential targets were identified based on the level of the protein expression across critical normal tissues and 20 tumor types. After validation, 23 cell surface proteins were identified and prioritized as candidate antibody-drug conjugate targets of which two have interestingly been approved by the FDA for use in solid tumors, one has been approved for lymphoma, and four have currently been entered in clinical trials. In conclusion, we identified and prioritized several candidate targets with translational potential, which may yield new clinically effective and safe antibody-drug conjugates. This large-scale antibody-based proteomic study allows us to go beyond the RNA-seq studies, facilitates bench-to-clinic research of targeted anticancer therapeutics, and offers valuable insights into the development of new antibody-drug conjugates. © 2021 Abolfazl Razzaghdoust et al.