Why Picking the Right Peptide Targets Is the Biggest Challenge in Personalized Cancer Vaccines | Research

The takeaway

Despite strong preclinical promise, most neoantigen cancer vaccines have failed to generate robust anti-tumor T cell responses in vivo, largely due to challenges in selecting and prioritizing the right tumor-specific peptides.

Few vaccines succeed in vivo
Despite hundreds of predicted neoantigen peptides per tumor, most cancer vaccines fail to generate the robust T cell responses needed for tumor rejection

What the researchers found

The review identifies several critical challenges in neoantigen cancer vaccine development:

- Bioinformatic algorithms predict hundreds of potential neoepitopes per tumor, but most are not immunogenic

- Few neoantigen cancer vaccines have generated strong epitope-specific T cell responses in vivo, despite promising preclinical data

- HLA diversity means each patient's immune system recognizes different peptides, requiring fully personalized vaccines

- Intratumoral heterogeneity of mutations means targeting one neoantigen may allow resistant clones to escape

- Suboptimal delivery and immune activation strategies may explain the gap between preclinical and clinical results

Why it matters

Personalized cancer vaccines are one of the most exciting frontiers in oncology, but they have largely underdelivered in clinical trials. Understanding why — and how to fix the neoantigen selection and delivery pipeline — is essential for realizing the potential of this approach. Better peptide selection could transform cancer vaccines from a promising concept into a clinical reality.

How the study worked

Methods chapter reviewing published preclinical and clinical data on neoantigen prediction, prioritization, vaccine design, and delivery. Discusses bioinformatic approaches, HLA-peptide binding prediction, immunogenicity assessment, and combination with standard chemotherapies.

What this study cannot tell us

This is a review chapter, not an original study. It reflects the state of knowledge at the time of writing (2022) and may not include the most recent clinical trial results. The discussion is primarily theoretical and does not present novel computational tools or clinical data. The chapter focuses on T cell-mediated immunity and gives less attention to antibody-based neoantigen recognition.

How to read the evidence

This is a methods review chapter synthesizing existing preclinical and clinical evidence. It provides expert perspective on the current state and challenges of the field but does not include original data.

When this study was published

Published in 2022, this review captures the state of neoantigen vaccine development before several large Phase II/III trials reported results. Some of the challenges discussed may have been partially addressed by more recent work.

The bigger picture

The advent of rapid tumor sequencing made personalized neoantigen vaccines technically feasible, but clinical success has been limited. Companies like Moderna and BioNTech are pursuing mRNA-based neoantigen vaccines (building on COVID-19 mRNA vaccine technology), while others use long peptide or dendritic cell approaches. This review provides a clear-eyed assessment of why the field has struggled and what needs to change — making it valuable for researchers and companies investing in this space.

Questions still open

Can machine learning approaches that incorporate immunogenicity data (not just HLA binding) improve neoantigen prediction accuracy?
Would multi-epitope vaccines targeting 20+ neoantigens overcome the immune escape problem of single-target approaches?
How do mRNA, peptide, and dendritic cell delivery platforms compare for generating strong neoantigen-specific T cell responses?

Common questions

What are neoantigens and why are they good cancer vaccine targets?

Neoantigens are abnormal peptide fragments produced by mutated proteins in cancer cells. Because these mutations exist only in the tumor — not in normal cells — the immune system can potentially recognize them as foreign and mount an attack. This makes them ideal vaccine targets: you can train the immune system to kill cancer cells while sparing healthy tissue.

Why is it so hard to choose the right neoantigens for a vaccine?

Each tumor has hundreds of mutations, and each mutation might produce peptides that the immune system could recognize. But not all of these are equally visible to the immune system, and what works depends on each patient's unique HLA molecules (the proteins that present peptides to T cells). Additionally, tumors are genetically diverse — not all cancer cells share the same mutations — so targeting a single neoantigen may leave resistant cells behind.

Read the original research

Beyond Sequencing: Prioritizing and Delivering Neoantigens for Cancer Vaccines.

Methods in molecular biology (Clifton, N.J.), 2410, 649-670

View on PubMed ↗Publisher’s paper ↗

Citation

Roesler, Alexander S; Anderson, Karen S. (2022). Beyond Sequencing: Prioritizing and Delivering Neoantigens for Cancer Vaccines.. Methods in molecular biology (Clifton, N.J.), 2410, 649-670. https://doi.org/10.1007/978-1-0716-1884-4_35