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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
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NeoFuse: predicting fusion neoantigens from RNA sequencing data
Georgios Fotakis1, Dietmar Rieder1, Marlene Haider1
1Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, Innsbruck 6020, Austria.
Bioinformatics (Oxford, England)
|November 23, 2019
Summary
NeoFuse predicts fusion neoantigens from tumor RNA sequencing data, identifying potential targets for cancer immunotherapy. This computational pipeline simplifies the complex process for broader application in oncology.
Area of Science:
- Bioinformatics
- Immunology
- Oncology
Background:
- Gene fusions can create neoantigens that stimulate anti-cancer immune responses.
- Predicting these neoantigens computationally requires complex bioinformatics workflows.
Purpose of the Study:
- To present NeoFuse, a computational pipeline for predicting fusion neoantigens from tumor RNA sequencing data.
- To simplify the identification of neoantigens for potential immunotherapy targets.
Main Methods:
- Development of a computational pipeline integrating prediction of fusion transcripts, translated proteins/peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity.
- Application to tumor RNA sequencing data.
Main Results:
- NeoFuse enables the identification of fusion neoantigens.
- The pipeline streamlines the prediction process.
Conclusions:
- NeoFuse can be applied to cancer patient RNA-seq data to identify fusion neoantigens.
- This may expand the range of targets for cancer immunotherapy.
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