Unlocking the future of cancer care: Overcoming challenges in personalized neoantigen vaccine development

By Dr. Priyom Bose, Ph.D.Reviewed by Benedette Cuffari, M.Sc.Oct 5 2023

A recent Nature Reviews Immunology study discusses challenges associated with the development and design of neoantigen cancer vaccines.

Study: Challenges in developing personalized neoantigen cancer vaccines. Image Credit: Lightspring / Shutterstock.com

Development of cancer therapy using neoantigens

Several genetic factors are associated with cancer manifestations, including DNA mutations, deletion, fusions, and translocation. It is imperative to understand the process of tumorigenesis to identify potential targets essential for developing effective cancer therapies.

After genomic mutations of cancer cells, altered or new protein products are generated. These proteins are antigenically novel for the host and referred to as neoantigens, which are recognized as foreign by the host immune system. Based on neoantigens, several immunotherapies, such as adoptive T-cell therapies and immune checkpoint blockade (ICB) therapy, have been developed.

Cancer-associated neoantigens have been used to develop therapeutic vaccines that specifically target the tumor without affecting healthy tissues. Most clinical cases exhibit endogenous T-cell responses induced by these vaccines, which are unable to control the proliferation of cancer cells. Thus, there remains an urgent need for new therapeutic vaccines that can enhance or induce T-cell responses against neoantigens and improve anticancer immunity.

Smaller clinical trials of many neoantigen vaccines, including NCT03897881 for melanoma and NCT04161755 for pancreatic cancer, have shown promise for future use. However, before commercialization, several challenges associated with these vaccines must be addressed to optimize their safety and efficacy.

Challenges of developing effective neoantigen cancer vaccines

The efficacy of any vaccine depends on the immunogenicity of its antigen. Next-generation sequencing (NGS) provides invaluable information about the individual patient and individual tumors.

In addition to these data, bioinformatics analysis and major histocompatibility complex (MHC)-peptide binding prediction algorithms have facilitated the prediction of potential targets, such as neoantigen peptides or neopeptides. Whole exome sequencing (WES) of tumors and blood cells can also be used to detect mutations that can generate novel neopeptide sequences.

Computational algorithms, such as predictor of immunogenic epitopes (PRIME), are used to identify immunogenic peptides; however, the efficacy of these bioinformatics tools is debatable.

For example, neopeptides identified through bioinformatics prediction tools did not generate significant endogenous antitumor immunity. This unfavorable outcome could be linked to tumor mutations based on deletion or insertion, which can lead to frameshift translation of polypeptide sequences that may not resemble its wild-type counterpart. These neoantigenes are known as defective ribosomal products (DRiPs), which lack function and structural stability.

It is not prudent to rely on pre-existing T-cell immunity to validate neopeptides in patients, as they might not elicit effector cytotoxic T-cell (CTL) responses due to inefficient cross-presentation. Recent bioinformatics neopeptide prediction tools have encountered challenges due to the use of mass spectrometry (MS) to identify neopeptides loaded onto MHC class I molecules on the surface of tumors. Nevertheless, MS-based immunopeptidomics have the potential to identify immunogenic peptides with further refinement in its methodology.

A common limitation linked with mutation-dependent neoantigens is clonal diversity and intra-tumor heterogeneity present within primary and metastatic tumors, which indicates that all neoantigens are not potential targets for vaccines. As compared to branched mutations, trunk mutations found in tumor cells serve as better vaccine targets. Taken together, the identification of suitable immunologically relevant neopeptides is a major challenge for the development of personalized neoantigen cancer vaccines.

Many cancer types have low mutational burden, which limits the global utility of mutation-dependent neoantigens and indicates the importance of mutation-independent neoantigens.

Recently, scientists have used dark proteome to identify cryptic neoantigen targets for cancer immunotherapy. At present, the neoantigen pool of the dark proteome is poorly characterized, which is used to generate neopeptides with high T-cell receptors (TCR) affinity.

For vaccine development, it is important to consider the number and length of neopeptides, which are properties that are often not considered during the development of personalized neoantigen cancer vaccines. The number of neopeptides required for an effective vaccine depends on the nature of the epitopes.

Two factors that influence vaccine efficiency include the inability of T-cells to detect immune-evading tumors and suppression of T-cells by the immunosuppressive tumor microenvironment (TME). Many cells within TME can inhibit or impair the function of neoantigen vaccine-induced T-cells.

Tumor accessibility is a critical step after the generation of a robust neoantigen-specific T-cell response. Tumor accessibility is dependent on multiple mechanisms, poor vascularization, physical barriers, and presence of vessels that restrict endothelium crossing by T-cells.

Personalized neoantigen cancer vaccine is also challenged with T-cell exhaustion and dysfunction, which is characterized by loss of effector function, enhanced inhibitory receptor expression, and propensity to undergo cell death. Thus, T-cell exhaustion could significantly restrict the benefit of these vaccines.