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July 31, 2025PROTEOMICS - CLINICAL APPLICATIONSOpen Access

Artificial Intelligence and the Evolving Landscape of Immunopeptidomics

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Authors

TVThanh Hoa VoEMEdel A. McNeelaÓOÓrla O’Donovan

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Overview

Review demonstrates how artificial intelligence advances neoantigen discovery in immunopeptidomics, indicating improved peptide identification and immunogenicity prediction.

Key Points

  • Artificial intelligence is critical in enhancing the efficiency of neoantigen discovery within immunopeptidomics.
  • Challenges in mass spectrometry data and immune response variability complicate peptide identification.
  • A case study in breast cancer illustrates AI's potential in revealing immunogenic features of less immunogenic tumors.
  • Advancements in AI models are paving the way for more personalized and effective cancer immunotherapy strategies.

Cite This Study

Vo et al. (2025) studied this question.

synapsesocial.com/papers/689a0c5fe6551bb0af8cf686https://doi.org/10.1002/prca.70018
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Computational immunogenomics: Leveraging AI to uncover novel biomarkers for disease diagnosis and therapy2025
  2. 2Advances in Bioinformatics Techniques to Predict Neoantigen: Exploring Tumor Immune Microenvironment and Transforming Data into Therapeutic Insights2024
  3. 3Artificial intelligence-based digital pathology using H&E-stained whole slide images in immuno-oncology: from immune biomarker detection to immunotherapy response prediction2025
  4. 4Accelerating Neoantigen Discovery: A High-Throughput Approach to Immunogenic Target Identification2025
  5. 5Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics2025