Neoantigen vaccines Flashcards
Define neoantigen
tumour specific antigen generated by mutations in tumour cells, which are not expressed within normal tissue
- The presence of neoantigens is one of the key differences between normal and tumour cells
Difference between classsical antigens and neoantigens
Self-antigens expressed primarily on tumour cells (e.g. oncofetal or cancer-testes antigen)
o Usually gene products from early development or from specific tissue
Self-tolerance (our T cells have been made tolerant) and easily evaded
Not many results have been disappointing – a small number of vaccines with limited effectiveness
o Neoantigens
Mutant proteins unique to the tumour
New promising approach
• Examples are mutated normal protein (will focus on these), but also viral antigens being expressed (e.g. in cervical cancer) and also ‘dark antigens’ – come from genomic dark matter e.g. the portion of the genome that is not normally expressed as protein, genes usually silenced in healthy but activated in cancer cells
What has recently allowed us to study neoantigens between?
- Together with bioinformatics, NGS has enabled mapping of all mutations in cancer and the prediction of MHC molecule-binding neoepitopes (epitope = part of antigen that binds to receptor)
What are 3 possible ways of targeting neoantigens?
- Synthetic neoantigen vaccines
- ICIs
- T cells specific to the neoantigen
o Castle et al 2012
First direct evidence of cancer exome-based approach used to identify neoantigens that could be targetted by T cells cells (this was only one of the groups, another also independently contributed)
Used NGS of exome to identify ~1000 mutations present in cells from a murine model of melanoma
Immunised melanoma mice with 50 synthetic long peptides encoded by some of these mutated epitopes.
1/3 of these peptides were found to be immunogenic
Results showed that neoantigen peptide vaccines targeting MU30 and MUT44, two mutated antigens, had significant preventative and therapeutic effects in the mouse tumour models
• They don’t seem to have any stats on their in vivo data for example, they don’t show a stat sig difference between untreated mice and the two vaccinated groups in terms of decrease in tumour growth and survival
Carreno et al 2015
In-human support of Castle 2012
• Trialled 3 patients with metastatic melanoma
• Given autologous DCs loaded ex vivo with synthetic peptides representing individual mutations of each patient predicted to bind to frequent class I haplotype HLA-A2
• Vaccine-induced CD8+ T cell responses with specificity for the immunogen were detected in several peptides (9 of 21 peptides)
• Cav – recognition of autologous melanoma cells was not assessed, so the relevance of the vaccine response was not clear
What 3 features does a vaccine in clinical practice need?
- Target tumour specific antigens that induce potent T cell responses. Multiple needed to avoid immune evasion
- Platform need a suitable approach – either provide and concentrated antigen source or material that can be used by the body to generate antigens (e.g. mRNA)
- Delivery combine with adjuvant & ICI
When were neoantigen vaccines first properly shown to be successful? By whatt groups? Which cancer type?
2017 - two small trials of pts with melanoma
o Sahin et al 2017
o Ott et al 2017
o Limitations of both – neither had a control arm, small cohorts
o Sahin et al 2017
Same group that made Pfizer vaccine
1-3 months of neoepitope discovery and vaccine manufacturing
8 neoepitope RNA vaccinations over 43 days - previously shown that RNA molecules can be taken up by APCs
13 patients given it
8 of these had no tumour development on follow-up (12-23 months)
Looked at number of metastatic events before and after the vaccine was given – metastatic event plateaued
Immunosurveillance analysis of PBMCs in pts showed the RNA vaccine could enhance the neoantigen-specific T cell response and induce new T cell response
They’re now conducting phase 2 trials and we hope they will be published soon
o Ott et al 2017
6 people who had undergone surgery to remove a tumour
Sequenced DNA and healthy cells and then used algorithm to predict which neoantigen would bind well to MHC
Each participant vaccinated with long peptides, representing up to 20 neoantigens
4/6 no tumour recurrence, 2/6 had tumours but these regressed after PD1 inhibition
None of these patients had measurable disease at the time of vaccine initiation this prevents direct evaluation of in situ vaccine induced tumour efficacy
Discuss technical limitations of methods used to if neoantigens in studies such as Sahin and Ott 2017?
Technical limitations!
- The technological pipeline used to identify neoantigens in these studies varies substantially and further optimisation is likely possible
- Also, erroneous mutation detection
o Standard techniques work well for SNPs – but other mutation types might be relevant such as gene fusions, indels and epigenetic, transcriptional, translational and post-translation aberrations may generate neoepitopes
o These are difficult to assess with current technologies
- Process of preparing a vaccine from a sample usually takes 3-5 months limits the clinical applications – Sahin et al (2017) took 1-3 months
What do we currently use to find mutations with likelihood of immunogenicity? What is an example of a model used to predict this and what is it?
(1) expression of the gene in the tumour and (2) an estimation of MHC binding
NetMHC is an example
• Artificial neural networks trained on binding data from different MHCs much better for MHC I than MHC II
o Liu et al (2019)
found that only 14% of predicted neoantigens (via computational analysis) induced IFN gamma response, 12% of antigens not robustly expressed induced a response
o Has been suggested that the stability of peptide-MHC complex is a better predictor for immunogenicity rather than MHC binding alone – current prediction algorithms for stability cover only a few MHC alleles and rely on small data sets
Aside from technical limitations of methods used to identify neoantigens what else is there?
Also limitations to do with the tumour itself
e.g. tumour heterogeneity, the dynamic nature of the genome, targetting of driver mutations
How may tumour heterogeneity be a limiting factor?
o Typically, analyses rely on small biopsy from a single tumour may not represent the full clonal spectrum
o Targeting one clone may cause outgrowth of antigen-negative clones