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Publications

Journal Article Preprint Epublish 1 citation

PubMed: 38895237 DOI: 10.1101/2024.06.04.597422

IMMUNOTAR - Integrative prioritization of cell surface targets for cancer immunotherapy.

bioRxiv

Authors: Rawan Shraim, Brian Mooney, Karina L Conkrite, Amber K Weiner, Gregg B Morin, Poul H Sorensen, John M Maris, Sharon J Diskin, Ahmet Sacan

Affiliations

  • Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
  • School of Biomedical Engineering, Science and Health System, Drexel University, Philadelphia, PA 19104, USA.
  • Department of Molecular Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
  • Canada's Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Vancouver, BC, Canada.
  • Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada.
  • Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
  • Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Abstract

Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of less toxic immunotherapies; however, identifying targets for immunotherapies remains a challenge in the field. To address this challenge, we developed IMMUNOTAR, a computational tool that systematically prioritizes and identifies candidate immunotherapeutic targets. IMMUNOTAR integrates user-provided RNA-sequencing or proteomics data with quantitative features extracted from publicly available databases based on predefined optimal immunotherapeutic target criteria and quantitatively prioritizes potential surface protein targets. We demonstrate the utility and flexibility of IMMUNOTAR using three distinct datasets, validating its effectiveness in identifying both known and new potential immunotherapeutic targets within the analyzed cancer phenotypes. Overall, IMMUNOTAR enables the compilation of data from multiple sources into a unified platform, allowing users to simultaneously evaluate surface proteins across diverse criteria. By streamlining target identification, IMMUNOTAR empowers researchers to efficiently allocate resources and accelerate immunotherapy development.

MeSH

Immunotherapy, Cells, Neoplasms, Membrane Proteins