All research
2026-06-11 PubMed

Immunopeptidomics-guided approach boosts neoantigen identification success to 83% in NSCLC patients

Immunopeptidomics-guided identification of functional neoantigens in non-small cell lung cancer.

Background

Despite advances with checkpoint inhibitor therapies, Non-Small Cell Lung Cancer (NSCLC) continues to have poor survival rates. Personalised cancer vaccines, leveraging short peptide neoantigens derived from tumor mutations, represent a promising precision medicine strategy. However, a significant challenge lies in accurately identifying therapeutically relevant neoantigens, as current prediction methods often yield low positive response rates, typically around 6%. This gap highlights the critical need for improved strategies to select functional neoantigens that can effectively stimulate a targeted anti-tumor immune response.

Study Design

Researchers developed an immunopeptidomics approach to enhance neoantigen identification in 24 NSCLC patients (15 adenocarcinoma, 9 squamous cell carcinoma). They directly identified one neoantigen and, using whole exome sequencing, transcriptomics, and mass spectrometry-based immunopeptidomics, filtered predicted neoantigens. This filtering was based on observed cohort HLA peptide presentation patterns. The primary endpoint was the rate of positive functional immune responses elicited by the identified neoantigens, comparing their novel method against existing prediction strategies.

Results

The novel immunopeptidomics-guided approach significantly improved the success rate of identifying functional neoantigens. The method achieved positive functional responses in 5 of 6 patients tested, demonstrating an impressive 83% success rate. This is a substantial improvement over the 6% success rate typically observed with existing methods. Furthermore, 13% of the putative neoantigens identified (9 out of 70) elicited strong immune responses. Bayesian modeling of their initial rules-based neoantigen selection further revealed patient-specific HLA peptide presentation patterns and propensities, underscoring the personalized nature of immune recognition. This data highlights the critical role of incorporating donor-specific HLA peptide presentation information.

The immunopeptidomics approach achieved positive functional responses in 5 of 6 patients tested (83% success rate), with 13% of putative neoantigens (9 out of 70) eliciting strong responses.

Key Findings

  • Immunopeptidomics-guided neoantigen identification achieved an 83% success rate in eliciting functional immune responses.
  • The method produced positive functional responses in 5 of 6 NSCLC patients tested.
  • 13% of putative neoantigens (9 out of 70) identified by the method elicited strong immune responses.
  • Incorporating donor-specific HLA peptide presentation data substantially improved neoantigen identification success rates.

Why It Matters

This study offers a significant leap forward for personalized cancer vaccine development, particularly in challenging cancers like NSCLC. By incorporating donor-specific HLA peptide presentation data, the method dramatically improves the reliability of neoantigen identification, moving closer to clinically viable personalized immunotherapies. This refined protocol for neoantigen selection could lead to more effective cancer vaccines, potentially synergizing with existing checkpoint inhibitors and expanding treatment options for patients who currently have limited choices. The high success rate suggests a more efficient and targeted approach to harnessing the immune system against cancer, reducing the number of ineffective vaccine candidates.


nsclc immunotherapy neoantigen cancer-vaccine immunopeptidomics hla-peptide-presentation
Source: pubmed:42270771 · Ingested 2026-06-11 · Digest: gemini-2.5-flash