L1
Cancer Neoantigen Discovery – Transcriptome-Wide Splice Analysis
Bioinformatics Research Intern (Seoul National University) · Sep 2018 – Mar 2019
Bioinformatics pipeline for identifying novel immunotherapy targets derived from aberrant alternative splicing in RNA-Seq data.
Technologies
PythonRMapSpliceRNA-SeqTCGA DatasetsMHC-I Prediction Tools
Contributions
- Developed a discovery pipeline to identify tumor-specific splice junctions across large-scale cancer datasets.
- Mapped the epitope landscape by predicting high-affinity MHC-I binding peptides from non-canonical transcripts.
- Validated the predictive model by cross-referencing findings with high-impact transcriptomic studies.
- Evaluated synergistic strategies for co-targeting mutation-derived and splice-derived neoantigens.
Outcome
Demonstrated that alternative splicing is a viable source for high-affinity epitopes, expanding target discovery beyond traditional somatic mutations.