An innovative AI-driven computational pipeline, NeoDisc, has been developed by researchers at the Ludwig Institute for Cancer Research to enhance the development of personalized cancer vaccines. This comprehensive tool integrates genomic, transcriptomic, and immunopeptidomic data to identify and prioritize tumor-specific antigens, offering a more accurate selection of effective targets for immunotherapies.
Addressing Gaps in Neoantigen Prediction
Existing pipelines for predicting clinically relevant neoantigen targets often fall short. NeoDisc addresses these gaps by combining multiple molecular and genetic analyses of tumors with mass spectrometry data. This integrated approach allows for a more nuanced understanding of the tumor's immunobiology and mechanisms of immune evasion.
"NeoDisc provides unique insights into the immunobiology of tumors and the mechanisms by which they evade targeting by cytotoxic T cells of the immune system," said senior author Michal Bassani-Sternberg, PhD, assistant professor of immunopeptidomics at the Lausanne Branch of the Ludwig Institute for Cancer Research. "These insights are invaluable to the design of personalized immunotherapies."
How NeoDisc Works
NeoDisc leverages AI to detect various types of tumor-specific antigens, including neoantigens. It applies machine learning and rule-based algorithms to prioritize antigens most likely to elicit a T-cell response. The pipeline integrates genomic, transcriptomic, and immunopeptidomic data into a single framework, enabling a holistic analysis of potential neoantigens.
To design personalized immunotherapies, researchers must conduct large-scale, in depth analyses of cancer mutations that generate potential neoantigens, the HLA molecules that present them to the T cells and the molecular characteristics that will allow their recognition by T cell receptors. Potential personalized immunotherapies are informed by the analysis of tumor and blood cells that represent the healthy genome of the patient, transcriptomics, and the analysis of what is called the immunopeptidome conducted by mass spectrometry.
Clinical Applications and Future Directions
NeoDisc is currently being used in Phase I clinical trials for personalized cancer vaccines and adoptive T cell therapies in Switzerland. The tool also identifies potential defects in antigen presentation, alerting clinicians to mechanisms of immune evasion that could compromise immunotherapy efficacy.
"Notably, NeoDisc can also detect potential defects in the machinery of antigen presentation, alerting vaccine designers and clinicians to a key mechanism of immune evasion in tumors that can compromise the efficacy of immunotherapy," Bassani-Sternberg noted.
While acknowledging that the accuracy of antigen identification and prioritization depends on the quality and depth of input data, the researchers plan to continue feeding data from various tumor types into NeoDisc and integrating additional machine-learning algorithms to improve its predictive capabilities.
