Accelerating Personalized Cancer Vaccines with LC-MS Immunopeptidomics and PEAKS
Personalized cancer vaccines are transforming oncology by targeting tumor-specific neoantigens – peptides uniquely presented on the surface of cancer cells. Identifying these neoantigens rapidly and accurately is a critical step in designing effective, patient-specific immunotherapies.
While next-generation sequencing (NGS) plays a foundational role in cancer vaccine development, it predicts neoantigen candidates based on DNA or RNA sequences, not the actual peptides displayed on the cell surface. In contrast, LC-MS–based immunopeptidomics directly detects peptides presented by MHC complexes, making it a more reliable approach for identifying functional neoantigens.
A Six-Week Workflow from Discovery to Validation
In a recent study, researchers implemented a streamlined six-week workflow, from tumor tissue to validated neoantigen candidates, to accelerate personalized cancer vaccine development. The key to this rapid turnaround was integrating RNA-seq and LC-MS data from the same tumor sample, providing both transcriptomic and immunopeptidomic insights.
PEAKS Online played a central role in this integration, enabling scientists to search LC-MS immunopeptidome data against both:
- Public protein databases (UniProt), and
- Personalized, patient-specific protein sequences derived from RNA-seq.
The Power of De Novo Sequencing
In addition to traditional database searching, the team leveraged PEAKS’ de novo sequencing capabilities to uncover peptides not found in standard databases. Using database-identified peptides as ground truth, they estimated that approximately 60% of de novo peptides were correctly sequenced, highlighting their potential to reveal novel, patient-specific antigens missed by conventional search methods.
To prioritize candidates for further testing, the team used two different algorithms to predict peptide-MHC binding affinities and selected top-ranked peptides for in vitro validation.
Why In Vitro Validation Still Matters
Interestingly, in vitro T-cell response assays revealed that the top five predicted candidates did not trigger a strong immune response, while lower-ranked peptides, candidates 6 through 15, did. This result underscores a crucial lesson in neoantigen discovery: computational predictions must be validated experimentally. Immunogenicity cannot always be inferred from binding scores alone.
Conclusion
This study reinforces the value of LC-MS–based immunopeptidomics, particularly when paired with advanced software like PEAKS for database and de novo sequencing. The ability to discover and validate tumor-specific immunopeptides in just six weeks is a promising step forward in making personalized cancer vaccines faster, more accurate, and more accessible.
Read the full article: ScienceDirect
Leave a Reply
You must be logged in to post a comment.