According to a report published today in eLife, scientists have created a pipeline for identifying, prioritizing, and evaluating potential tumor antigens for the rapid development of cancer vaccines.
Using a new approach, researchers may quickly identify tumour-specific antigens recognized by cytotoxic T cells, generating a powerful, durable and highly specific response against an individual tumour. This may lead to a quicker and easier process to produce effective, personalized cancer vaccinations based on the identified antigens.
Defining a cancer vaccine, we must select antigens that express a strong immune response, are exclusive to cancer cells, and are tailored to an individual tumour type, according to Sara Feola, the first author of the ImmunoViroTherapy Lab (IVTLab) in Helsinki, Finland. However, only a few of the antigens on the tumour meet these criteria, making it extremely difficult to identify and prioritize potentially beneficial candidates. Our approach includes all the essential steps to achieve the best
Multimedia technology and collaboration are required for identifying and prioritizing antigens, as well as rapid, inexpensive and effective approaches to administer these antigens to patients. During the past six years, we have been working on a project funded by the European Research Council (ERC) to establish an alignment of all of this complex puzzle.
"Our research, which builds on previous research, involves developing a novel approach to identify tumour-specific antigens from very small samples, developing a novel algorithm to prioritize peptides based on their similarity to pathogen-derived peptides, and developing several hybrid plug-and-play technologies to deliver these peptides together with viruses or bacteria that kill cancer cells.
The team developed a new approach to investigate the antigen landscape of a tumor cell that is, among others, all of the different peptides on the cell surface. They used advanced technologies, such as an immunopeptidomic approach with mass spectrometry to investigate surface antigens on the cell. This produced a list of tens of thousands of peptide candidates and posed a challenge of prioritizing them.
The results were investigated by two parallel methods: first, they examined the relative amounts of the peptides on cancer cells compared to normal cells. This gave them clues as to whether the antigen was truly tumour specific. Second, they used a software tool previously developed in their lab to identify tumour antigens that are similar to known pathogen antigens, maximizing their potential potential ability to produce a similar immune response to the pathogen antigens.
The team then divided their candidate list to 26 antigen candidates. They then investigated how well they stimulated T cells and how effectively they bind to an adenoviral vector that would form the basis of the vaccine. All candidate antigen peptides performed the best, but six were taken forward for further experiments.
The next stage was to see if a vaccination that contains these target antigens might stimulate sufficient immune response to stop tumour growth. To demonstrate this, the team analyzed mice with colon tumours on their left and right flanks. One side of the mice was then treated with a vaccine coated with each candidate peptide antigens. This suggests that the immune system had a strong immune response against tumours.
Cerullo finds that a pipeline has been developed and validated for the first time on all the stages of personalized cancer vaccination development, from iolating peptides to analysing them to identify the best candidates. This pipeline is currently being validated in human cancer patients under our flagship project on precision cancer medicine, iCAN.
"Together, our findings demonstrate the feasibility of applying the pipeline to create a customized cancer vaccine by focusing on the prioritization and selection criteria and adopting a quick plug-and-play technique, called PeptiCRAd. This opens up the possibility of rapidly developing vaccines for clinical use, where effective personalized therapies are a key goal.