ImmunoTar-integrative prioritization of cell surface targets for cancer immunotherapy.
Rawan Shraim, Brian Mooney, Karina L Conkrite, Amber K Hamilton, Gregg B Morin, Poul H Sorensen, John M Maris, Sharon J Diskin, Ahmet Sacan
Author Information
Rawan Shraim: Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States. ORCID
Brian Mooney: Department of Molecular Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 0B4, Canada.
Karina L Conkrite: Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Amber K Hamilton: Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Gregg B Morin: Canada's Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Vancouver, BC V5Z 4S6, Canada. ORCID
Poul H Sorensen: Department of Molecular Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 0B4, Canada.
John M Maris: Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
Sharon J Diskin: Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States. ORCID
Ahmet Sacan: School of Biomedical Engineering, Science and Health System, Drexel University, Philadelphia, PA 19104, United States.
MOTIVATION: Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of targeted and less toxic immunotherapies, such as chimeric antigen receptor (CAR)-T cells and antibody-drug conjugates (ADCs). These therapies, effective in treating both pediatric and adult patients with solid and hematological malignancies, rely on the identification of cancer-specific surface protein targets. While technologies like RNA sequencing and proteomics exist to survey these targets, identifying optimal targets for immunotherapies remains a challenge in the field. RESULTS: To address this challenge, we developed ImmunoTar, a novel computational tool designed to systematically prioritize candidate immunotherapeutic targets. ImmunoTar integrates user-provided RNA-sequencing or proteomics data with quantitative features from multiple public databases, selected based on predefined criteria, to generate a score representing the gene's suitability as an immunotherapeutic target. We validated ImmunoTar using three distinct cancer datasets, demonstrating its effectiveness in identifying both known and novel targets across various cancer phenotypes. By compiling diverse data into a unified platform, ImmunoTar enables comprehensive evaluation of surface proteins, streamlining target identification and empowering researchers to efficiently allocate resources, thereby accelerating the development of effective cancer immunotherapies. AVAILABILITY AND IMPLEMENTATION: Code and data to run and test ImmunoTar are available at https://github.com/sacanlab/immunotar.
