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T-SCAPE: T cell immunogenicity scoring via cross-domain aided predictive engine.

Jeonghyeon Kim1, Nuri Jung1, Jayyoon Lee2

  • 1Department of Chemistry, Seoul National University, Gwanak-gu, Seoul 08826, Republic of Korea.

Science Advances
|December 5, 2025
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Summary
This summary is machine-generated.

Predicting T cell immunogenicity is crucial for safer vaccines and therapeutics. A new deep learning framework, T-SCAPE, integrates diverse data to accurately forecast T cell activation and therapeutic antibody immunogenicity.

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Area of Science:

  • Immunology
  • Computational Biology
  • Biotechnology

Background:

  • T cell immunogenicity is vital for vaccine and therapeutic protein development.
  • Predicting immunogenicity is challenging due to limited data and complex biological interactions.
  • Current methods struggle with comprehensive in silico prediction of T cell responses.

Purpose of the Study:

  • To develop a novel deep learning framework, T-SCAPE, for predicting T cell immunogenicity.
  • To integrate diverse immunological data sources for improved predictive accuracy.
  • To assess T-SCAPE's ability to predict T cell activation and therapeutic antibody immunogenicity.

Main Methods:

  • Developed T cell immunogenicity scoring via cross-domain aided predictive engine (T-SCAPE), a multidomain deep learning framework.
  • Employed adversarial domain adaptation to integrate data on MHC presentation, pMHC binding, TCR-pMHC interaction, and T cell activation.
  • Validated T-SCAPE using leakage-controlled benchmarks for predicting T cell activation and antidrug antibody induction.

Main Results:

  • T-SCAPE demonstrated exceptional performance in predicting T cell activation for specific peptide-MHC pairs.
  • The framework accurately predicted the antidrug antibody-inducing potential of therapeutic antibodies without MHC inputs.
  • Multidomain pretraining based on biological relevance and data significantly contributed to T-SCAPE's success.

Conclusions:

  • T-SCAPE offers a robust and accurate method for predicting T cell immunogenicity.
  • The framework's ability to integrate diverse data enhances its predictive power.
  • T-SCAPE has the potential to significantly advance the development of safer and more effective vaccines and protein therapeutics.