Scientists have created a pipeline for identifying, prioritising and evaluating potential tumour antigens for the fast generation of cancer vaccines, according to a report published today in eLife.
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The new approach could help researchers quickly identify tumour-specific antigens recognised by cytotoxic T cells, generating a powerful, durable and highly specific response against an individual’s tumour. This could lead in turn to a quicker and easier way to generate effective, personalised cancer vaccines based on the identified antigens.
“For a cancer vaccine to be effective, we need to select target antigens that elicit a strong immune response, are exclusively present on cancer cells and are tailored to an individual’s unique tumour type,” explains first author Sara Feola, Postdoctoral Researcher at the ImmunoViroTherapy Lab (IVTLab), University of Helsinki, Finland. “However, only a few, if any, of the antigens on a tumour meet those characteristics, making it very difficult to identify and prioritise potentially effective candidates. Our pipeline comprises all the essential steps for the optimal development of a therapeutic cancer vaccine, but which could be carried out much more quickly on an individual patient basis, enabling true personalised therapy.”
“Developing personalised cancer vaccines needs several different technologies working together and working fast,” adds senior author Vincenzo Cerullo, Professor of Biological Drug Development at the University of Helsinki and group leader at IVTLab. “We need fast and reliable methods to identify and prioritise antigens, as well as rapid, inexpensive and feasible approaches to deliver these antigens to patients. During the past six years, we’ve been working on a project supported by the European Research Council (ERC) to make all the pieces of this complex puzzle work together, creating the pipeline that has been partially described in this work.
“Our research, which builds on previous work, involves developing a novel approach to identify tumour-specific antigens from very small samples, creating a novel algorithm to prioritise peptides based on their similarity to pathogen-derived peptides, and building several different plug-and-play technologies to deliver these peptides together with viruses or bacteria that kill cancer cells.”
In the current study, the team began by investigating the antigen landscape of a tumour cell – that is, all the different peptides on the cell surface. They studied a mouse model of colon cancer and used state-of-the-art technologies, such as an immunopeptidomic approach based on mass spectrometry analysis, to explore surface antigens on the cell. This generated a list of thousands of peptide candidates and presented a challenge of how to prioritise them.
The team used two parallel lines of investigation: first, they looked at the relative amounts of the peptides on cancer cells compared with 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, exploiting their potential ability to cause a similar immune response to the pathogen antigens.
Using these methods, the team narrowed their candidate list down from thousands to 26 antigen candidates. They then studied the potential of these antigens further by testing how well they stimulated T cells, and how effectively they bind to an adenoviral vector that would form the basis of the vaccine. All the candidate antigen peptides interacted with the viral vector, but six peptides performed best and were taken forward for further tests.
The next stage was to see whether a vaccine carrying these target antigens could stimulate enough of an immune response to control or halt tumour growth. To test this, the team used mice with colon tumours on their left and right flanks. They then treated one side of the mice with the vaccine coated with each of the candidate peptide antigens. As hoped, they found that vaccines carrying the peptides improved anti-tumour growth in the treated tumour, but one of the vaccines improved anti-tumor growth in the untreated tumours – suggesting that the peptide antigen in this vaccine had mounted a powerful systemic immune response against the tumours.
“We have developed and validated a pipeline that covers for the first time all the stages of personalised cancer vaccine development, starting with isolating peptides from a primary tumour to analysing them to identify the best candidates,” Cerullo concludes. “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 generate a tailored cancer vaccine by focusing on the prioritisation and selection criteria and adopting quick plug-and-play technology, called PeptiCRAd, through decorating a clinically approved adenovirus vector with the selected peptides. This opens up the possibility of rapidly generating vaccines for clinical use, where effective personalised therapies represent a major goal of successful treatment.”
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To learn more about the IVTLab, visit www.ivtlab.org or https://www.instagram.com/ivt.lab.
And for more information about iCAN, see https://ican.fi.
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