Production of high-complexity frameshift neoantigen peptide microarrays

Predicting response and toxicity to immune checkpoint inhibitors in lung cancer using antibodies to frameshift neoantigens

PURPOSE

To evaluate a new class of blood-based biomarkers, anti-frameshift peptide antibodies, for predicting both tumor responses and adverse immune events to immune checkpoint inhibitor (ICI) therapies in advanced lung cancer patients.

EXPERIMENTAL DESIGN

Serum samples were obtained from 74 lung cancer patients prior to palliative PD-(L)1 therapies with subsequently recorded tumor responses and immune adverse events (irAEs). Pretreatment samples were assayed on microarrays of frameshift peptides (FSPs), representing ~ 375,000 variant peptides that tumor cells can be informatically predicted to produce from translated mRNA processing errors. Serum-antibodies specifically recognizing these ligands were measured. Binding activities preferentially associated with best-response and adverse-event outcomes were determined. These antibody bound FSPs were used in iterative resampling analyses to develop predictive models of tumor response and immune toxicity.

RESULTS

Lung cancer serum samples were classified based on predictive models of ICI treatment outcomes. Disease progression was predicted pretreatment with ~ 98% accuracy in the full cohort of all response categories, though ~ 30% of the samples were indeterminate. This model was built with a heterogeneous sample cohort from patients that (i) would show either clear response or stable outcomes, (ii) would be administered either single or combination therapies and (iii) were diagnosed with different lung cancer subtypes. Removing the stable disease, combination therapy or SCLC groups from model building increased the proportion of samples classified while performance remained high. Informatic analyses showed that several of the FSPs in the all-response model mapped to translations of variant mRNAs from the same genes. In the predictive model for treatment toxicities, binding to irAE-associated FSPs provided 90% accuracy pretreatment, with no indeterminates. Several of the classifying FSPs displayed sequence similarity to self-proteins.

CONCLUSIONS

Anti-FSP antibodies may serve as biomarkers for predicting ICI outcomes when tested against ligands corresponding to mRNA-error derived FSPs. Model performances suggest this approach might provide a single test to predict treatment response to ICI and identify patients at high risk for immunotherapy toxicities.

Vaccines for immunoprevention of DNA mismatch repair deficient cancers

The development of cancer vaccines to induce tumor-antigen specific immune responses was sparked by the identification of antigens specific to or overexpressed in cancer cells. However, weak immunogenicity and the mutational heterogeneity in many cancers have dampened cancer vaccine successes. With increasing information about mutational landscapes of cancers, mutational neoantigens can be predicted computationally to elicit strong immune responses by CD8 +cytotoxic T cells as major mediators of anticancer immune response. Neoantigens are potentially more robust immunogens and have revived interest in cancer vaccines. Cancers with deficiency in DNA mismatch repair have an exceptionally high mutational burden, including predictable neoantigens. Lynch syndrome is the most common inherited cancer syndrome and is caused by DNA mismatch repair gene mutations. Insertion and deletion mutations in coding microsatellites that occur during DNA replication include tumorigenesis drivers. The induced shift of protein reading frame generates neoantigens that are foreign to the immune system. Mismatch repair-deficient cancers and Lynch syndrome represent a paradigm population for the development of a preventive cancer vaccine, as the mutations induced by mismatch repair deficiency are predictable, resulting in a defined set of frameshift peptide neoantigens. Furthermore, Lynch syndrome mutation carriers constitute an identifiable high-risk population. We discuss the pathogenesis of DNA mismatch repair deficient cancers, in both Lynch syndrome and sporadic microsatellite-unstable cancers. We review evidence for pre-existing immune surveillance, the three mechanisms of immune evasion that occur in cancers and assess the implications of a preventive frameshift peptide neoantigen-based vaccine. We consider both preclinical and clinical experience to date. We discuss the feasibility of a cancer preventive vaccine for Lynch syndrome carriers and review current antigen selection and delivery strategies. Finally, we propose RNA vaccines as having robust potential for immunoprevention of Lynch syndrome cancers.