A newly published study in Nature Biotechnology introduces NeoDisc, an innovative computational pipeline that combines genomics, transcriptomics, and mass spectrometry-based immunopeptidomics. NeoDisc provides an advanced solution for identifying and prioritizing tumor-specific antigens, enabling the design of personalized cancer vaccines and improving immunotherapy outcomes.
A team of researchers lead by Florian Huber and directed by Dr Michal Bassani-Sternberg, at Department of Oncology UNIL-CHUV and part of the Lausanne Branch of the Ludwig Institute for Cancer Research, have developed a computational discovery pipeline called NeoDisc. Published in Nature Biotechnology, this new tool integrates multi-omics data, including genomics, transcriptomics, and mass spectrometry, to accurately identify tumor-specific antigens. These antigens can be used to create personalized cancer vaccines and inform T cell-based immunotherapies.
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NeoDisc stands out by addressing a critical challenge in cancer immunotherapy—the identification of immunogenic peptides that are specific to a patient’s tumor. Through advanced machine learning and rule-based algorithms, NeoDisc prioritizes antigens from a wide range of sources, including neoantigens, viral antigens, and non-canonical proteins. This pipeline also highlights defects in antigen presentation, providing insights into why some tumors evade immune detection.
"Our comprehensive proteogenomic approach helps refine immunotherapy by targeting the unique antigenic landscape of each patient’s tumor," explains lead researcher Dr Michal Bassani-Sternberg. "NeoDisc offers a significant leap in developing personalized cancer treatments."
Research for this study was supported by the Lausanne University Hospital (CHUV), the University of Lausanne (UNIL), Ludwig Institute for Cancer Research.
* A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy