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Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

ABSTRACT: Despite improved methods for MHC affinity prediction, the vast majority of computationally predicted tumor neoantigens are not immunogenic experimentally, indicating that high-quality neoantigens are beyond current algorithms to discern. To enrich for neoantigens with the greatest likelihood of immunogenicity, we developed an analytic method to parse neoantigen quality through rational biological criteria across five clinical datasets for 318 cancer patients. We explored four quality metrics, including analysis of dissimilarity to the non-mutated proteome that was predictive of peptide immunogenicity. In patient tumors, neoantigens with high dissimilarity were unique, enriched for hydrophobic sequences, and correlated with survival after PD-1 checkpoint therapy in patients with non-small cell lung cancer independent of predicted MHC affinity. We incorporated our neoantigen quality analysis methodology into an open-source tool, antigen.garnish, to predict immunogenic peptides from bulk computationally predicted neoantigens for which the immunogenic "hit rate" is currently low.

SUBMITTER: Richman LP

PROVIDER: S-EPMC6813910 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

Richman Lee P LP Vonderheide Robert H RH Rech Andrew J AJ

Cell systems 20191009 4

Despite improved methods for MHC affinity prediction, the vast majority of computationally predicted tumor neoantigens are not immunogenic experimentally, indicating that high-quality neoantigens are beyond current algorithms to discern. To enrich for neoantigens with the greatest likelihood of immunogenicity, we developed an analytic method to parse neoantigen quality through rational biological criteria across five clinical datasets for 318 cancer patients. We explored four quality metrics, in ...[more]

PMID: 31606370

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Project description:BackgroundTransforming growth factor beta (TGFβ) is well-recognized as an immunosuppressive player in the tumor microenvironment but also has a significant impact on cancer cell phenotypes. Loss of TGFβ signaling impairs DNA repair competency, which is described by a transcriptomic score, βAlt. Cancers with high βAlt have more genomic damage and are more responsive to genotoxic therapy. The growing appreciation that cancer DNA repair deficits are important determinants of immune response prompted us to investigate βAlt's association with response to immune checkpoint blockade (ICB). We predicted that high βAlt tumors would be infiltrated with lymphocytes because of DNA damage burden and hence responsive to ICB.MethodsWe analyzed public transcriptomic data from clinical trials and preclinical models using transcriptomic signatures of TGFβ targets, DNA repair genes, tumor educated immune cells and interferon. A high βAlt, immune poor mammary tumor derived transplant model resistant to programmed death ligand 1 (PD-L1) antibodies was studied using multispectral flow cytometry to interrogate the immune system.ResultsMetastatic bladder patients in IMvigor 210 who responded to ICB had significantly increased βAlt scores and experienced significantly longer overall survival compared to those with low βAlt scores (hazard ratio 0.62, P=0.011). Unexpectedly, 75% of high βAlt cancers were immune poor as defined by low expression of tumor educated immune cell and interferon signatures. The association of high βAlt with immune poor cancer was also evident in TCGA and preclinical cancer models. We used a high βAlt, immune poor cancer to test therapeutic strategies to overcome its inherent anti-PD-L1 resistance. Combination treatment with radiation and TGFβ inhibition were necessary for lymphocytic infiltration and activated NK cells were required for ICB response. Bioinformatic analysis identified high βAlt, immune poor B16 and CT26 preclinical models and paired biopsies of cancer patients that also demonstrated NK cell activation upon response to ICB.ConclusionsOur studies confirm βAlt as a biomarker that predicts response to ICB in immune poor cancers., which has implications for the development of therapeutic strategies to increase the number of cancer patients who will benefit from immunotherapy.

Dataset Information

Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

Publications

Neoantigen Dissimilarity to the Self-Proteome Predicts Immunogenicity and Response to Immune Checkpoint Blockade.

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