Rapid and direct discovery of functional tumor specific neoantigens by high resolution mass spectrometry and novel algorithm prediction

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On 2025-05-202025-10-21By In Featured User Publications

Tian, H., Li, G., Chiu, C. K., Li, E., Chen, Y., Zhu, T., ... & Kang, X. (2025). Rapid and direct discovery of functional tumor specific neoantigens by high resolution mass spectrometry and novel algorithm prediction. Cell Insight, 100251. doi:10.1016/j.cellin.2025.100251

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.