Personalized cancer vaccines are moving from an experimental promise toward a more structured form of immunotherapy, but the field still faces a problem that cannot be solved by sequencing tumors alone: the lack of harmonized methods. In a perspective published in Experimental & Molecular Medicine, Cho, Lee, Lee and colleagues argue that the next stage of progress will depend on bringing consistency to every step of vaccine development, from identifying tumor-specific mutations to measuring whether a patient’s immune system has mounted a meaningful response. Their article, titled “Take Five: harmonization in personalized cancer vaccines for cancer immunotherapy,” presents standardization as a scientific necessity rather than an administrative detail. Without comparable methods, results from different laboratories and clinical trials can be difficult to interpret, even when the underlying therapies are biologically similar.
Personalized cancer vaccines are designed for an individual patient rather than a broad population. Most target neoantigens, abnormal protein fragments created by mutations in tumor cells but absent from healthy tissues. Because these altered fragments can be recognized as foreign by T cells, they offer a way to direct the immune system toward malignant cells with greater precision than conventional cancer treatments. A typical development process begins with tumor and normal-tissue sequencing, followed by computational analysis to identify mutations that could generate recognizable peptides. The selected targets are then encoded in a vaccine platform, such as messenger RNA, synthetic peptides, DNA, or viral vectors. Although the concept is straightforward in principle, each stage contains variables that can influence the final treatment.
The first challenge is the quality and interpretation of tumor genomic data. Tumors are genetically diverse and often contain a mixture of malignant and nonmalignant cells, meaning that a mutation detected in a biopsy may not be present in every cancer cell. Samples can also differ in their purity, sequencing depth and storage conditions. Computational pipelines must distinguish genuine tumor mutations from technical errors and inherited variants, then determine which mutations are likely to produce peptides presented by the patient’s human leukocyte antigen molecules. These HLA proteins display intracellular protein fragments on the cell surface for inspection by T cells. Because HLA genes vary substantially between individuals, an antigen predicted to be visible in one patient may be poorly presented in another. Harmonized sequencing standards and prediction benchmarks are therefore essential for determining whether candidate neoantigens are truly comparable across studies.
A second concern is how researchers define a high-value neoantigen. Prediction algorithms commonly evaluate factors such as mutation type, gene expression, peptide binding to HLA molecules and the likelihood that T-cell receptors can recognize the displayed fragment. Yet a strong computational score does not guarantee an immune response. Some predicted peptides are produced inefficiently, degraded before reaching the cell surface or hidden by the tumor’s mechanisms of immune evasion. Others may be recognized only by a small population of T cells. The authors’ emphasis on harmonization highlights the need to combine computational predictions with experimental validation, including mass-spectrometry analysis of naturally presented peptides and functional tests using patient immune cells. Establishing shared criteria for evidence could reduce the number of weak targets entering clinical development.
The vaccine platform itself introduces another layer of variation. Messenger RNA vaccines can be manufactured rapidly and translated directly into antigenic proteins inside cells, while peptide vaccines require delivery systems and adjuvants to stimulate sufficient immune activation. Viral-vector vaccines use engineered viruses to carry tumor-antigen genes into cells, taking advantage of the strong innate and adaptive immune responses that viral infections naturally provoke. However, pre-existing immunity against a vector can limit its effectiveness, and repeated dosing may be affected by antibodies or T cells directed against the delivery virus rather than the tumor antigen. Each platform also differs in stability, manufacturing requirements, dose, timing and safety profile. Comparing these technologies requires common reporting standards that separate the effect of the antigen from the effect of the delivery system.
The third major issue is manufacturing speed and reliability. A personalized vaccine is produced for a specific patient, often after surgery or biopsy has provided sufficient tumor material. The treatment team must complete sequencing, antigen selection, design, production and quality control within a clinically useful window. Delays can be particularly consequential for patients with rapidly progressing disease. Manufacturing must also confirm the identity, purity, concentration and structural integrity of the vaccine product. For RNA-based approaches, for example, important variables include RNA sequence accuracy, chemical modification, encapsulation efficiency and resistance to degradation. For viral vectors, investigators must monitor infectivity, genetic stability, replication competence and the absence of unwanted contaminants. Harmonized release criteria could help ensure that a product made at one facility is equivalent in quality to a product made elsewhere.
The fourth challenge involves measuring immune responses in a consistent way. A vaccine may expand neoantigen-specific CD8-positive cytotoxic T cells, CD4-positive helper T cells, or both, but the presence of these cells in blood does not necessarily demonstrate that they can enter a tumor and destroy malignant cells. Researchers use tools including peptide–HLA multimer staining, interferon-gamma release assays, intracellular cytokine analysis, T-cell receptor sequencing and single-cell profiling. These methods provide different types of information and can produce different estimates of response magnitude. A patient may show a detectable immune response under one assay but not another, depending on the peptide concentration, cell culture conditions and definition of positivity. Shared reference materials, controls and reporting rules would make it easier to determine whether an immune response is robust, durable and clinically relevant.
Immune monitoring must also be connected to the biology of the tumor. Cancer cells can lose the targeted mutation, reduce antigen production or disrupt antigen presentation through defects in HLA molecules and associated processing machinery. The tumor microenvironment may further suppress immunity through regulatory T cells, myeloid-derived suppressor cells, inhibitory cytokines and checkpoint molecules such as PD-L1. For this reason, personalized vaccines are increasingly considered as components of combination treatment rather than stand-alone products. Checkpoint inhibitors may release brakes on activated T cells, while radiation or chemotherapy can alter antigen release and tumor visibility. Viral-vector vaccines may provide additional inflammatory signals that help recruit immune cells, but their effects must be distinguished from those of the accompanying therapies. Harmonized clinical designs are needed to identify which combinations truly improve outcomes.
The fifth area concerns clinical trials and regulation. Personalized vaccine studies often enroll relatively small numbers of patients because every treatment is individually designed, making conventional trial structures difficult to apply. Differences in cancer type, disease stage, prior therapy, tumor mutation burden and vaccine composition can complicate comparisons between studies. Investigators therefore need agreed definitions for endpoints, including feasibility, manufacturing success, immune response, recurrence-free survival and overall survival. Regulatory agencies must evaluate not only the final vaccine but also the computational pipeline used to select its targets and the manufacturing process used to produce it. A transparent framework could allow a platform to be validated once while individual vaccine sequences are assessed under controlled procedures, reducing duplication without compromising safety.
The authors’ message arrives as personalized oncology expands into a field where speed, precision and reproducibility must advance together. A vaccine that is biologically sophisticated but produced too slowly may not benefit a patient; a vaccine that generates immune cells but targets an irrelevant or poorly presented antigen may fail for biological reasons; and a promising clinical result that cannot be compared with other studies may delay progress across the field. Harmonization does not mean forcing every research group to use one technology. Instead, it means defining common standards for data quality, antigen selection, manufacturing, immune monitoring and clinical evaluation while preserving room for innovation. By organizing the challenges around five interconnected priorities, the review frames personalized cancer vaccines as an emerging medical system that requires coordination across genomics, immunology, bioinformatics, engineering and regulation. The prospect is not simply a faster way to make individualized vaccines, but a more reliable path toward determining which patients are most likely to benefit and why.
Subject of Research: Harmonization and standardization of personalized cancer vaccines for cancer immunotherapy, including neoantigen identification, vaccine platforms, manufacturing, immune monitoring and clinical evaluation.
Article Title: Take Five: harmonization in personalized cancer vaccines for cancer immunotherapy
Article References:
Cho, S., Lee, J., Lee, YM. et al. Take Five: harmonization in personalized cancer vaccines for cancer immunotherapy. Exp Mol Med (2026). https://doi.org/10.1038/s12276-026-01807-y
Image Credits: AI Generated
DOI: https://doi.org/10.1038/s12276-026-01807-y
Keywords: personalized cancer vaccines, cancer immunotherapy, neoantigens, tumor sequencing, HLA presentation, viral vectors, messenger RNA vaccines, immune monitoring, vaccine manufacturing, clinical trial harmonization
Tags: cancer immunotherapycancer vaccine harmonizationimmune response measurementimmunogenic tumor mutationsimmunotherapy clinical trialslaboratory method consistencyneoantigen identificationpersonalized cancer vaccinespersonalized immunotherapy strategiestumor mutation sequencingtumor-specific neoantigensvaccine development standardization
