NeoFuse

NeoFuse predicts fusion neoantigens from tumor RNA sequencing (RNA-seq) data to identify candidate peptide–HLA binders for cancer immunotherapy.

Key Features:

• Fusion Transcript Prediction: Identifies fusion transcripts from RNA-seq data to detect gene fusions that may produce novel antigenic proteins.
• Protein and Peptide Translation: Translates fusion transcripts into protein sequences and derives peptide fragments for downstream immunogenicity assessment.
• HLA Typing Integration: Incorporates Human Leukocyte Antigen (HLA) typing data to determine patient-specific HLA alleles for peptide presentation analysis.
• Peptide–HLA Binding Affinity Prediction: Evaluates binding affinities between predicted peptides and HLA molecules to prioritize candidate neoantigens.

Scientific Applications:

• Cancer immunotherapy target discovery: Identifies fusion-derived peptide candidates presented by patient HLA alleles to expand potential immunotherapeutic targets.
• Personalized neoantigen selection: Supports selection of patient-specific fusion neoantigens from RNA-seq data for personalized therapeutic strategies.

Methodology:

Identification of fusion transcripts from RNA-seq data, translation of fusion transcripts into protein sequences and derivation of peptide fragments, integration of Human Leukocyte Antigen (HLA) typing, and prediction/evaluation of peptide–HLA binding affinities.