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Updated: Mar 15, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Current tools for predicting cancer-specific T cell immunity
David Gfeller1, Michal Bassani-Sternberg2, Julien Schmidt3
1Ludwig Center for Cancer Research, University of Lausanne, Epalinges, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Abstract:
Tumor exome and RNA sequencing data provide a systematic and unbiased view on cancer-specific expression, over-expression, and mutations of genes, which can be mined for personalized cancer vaccines and other immunotherapies. Of key interest are tumor-specific mutations, because T cells recognizing neoepitopes have the potential to be highly tumoricidal. Here, we review recent developments and technical advances in identifying MHC class I and class II-restricted tumor antigens, especially neoantigen derived MHC ligands, including in silico predictions, immune-peptidome analysis by mass spectrometry, and MHC ligand validation by biochemical methods on T cells.
Insights
Cancer sequencing reveals tumor-specific mutations for personalized vaccines. Identifying neoantigens through advanced methods enhances immunotherapy potential for highly targeted cancer treatments.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Tumor exome and RNA sequencing offer comprehensive insights into cancer genetics and gene expression.
- Understanding tumor-specific mutations is crucial for developing effective immunotherapies, particularly personalized cancer vaccines.
- Neoantigens, derived from tumor mutations, are key targets for T cell-mediated tumor destruction.
Purpose of the Study:
- To review recent advancements in identifying tumor antigens, focusing on neoantigen-derived MHC ligands.
- To discuss technical progress in detecting MHC class I and class II-restricted tumor antigens.
- To highlight methods for mining sequencing data for cancer immunotherapy targets.
Main Methods:
- In silico prediction of potential neoantigens.
- Immune-peptidome analysis utilizing mass spectrometry.
- Biochemical validation of MHC ligands using T cell assays.
Main Results:
- Review of current methodologies for neoantigen identification and validation.
- Emphasis on the potential of neoantigen-specific T cells in cancer therapy.
- Integration of sequencing data with analytical and validation techniques.
Conclusions:
- Advanced sequencing and analytical techniques are crucial for identifying neoantigens.
- Neoantigen-derived MHC ligands are promising targets for personalized cancer vaccines and immunotherapies.
- Further research and technical refinement will enhance the efficacy of neoantigen-based cancer treatments.
