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A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy.

ABSTRACT: Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, which are tumour-specific, mutated peptides presented on the surface of cancer cells. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the major histocompatibility complex (MHC) and subsequent recognition by T cells. We estimate these components using the relative MHC binding affinity of each neoantigen to its wild type and a nonlinear dependence on sequence similarity of neoantigens to known antigens. To describe the evolution of a heterogeneous tumour, we evaluate its fitness as a weighted effect of dominant neoantigens in the subclones of the tumour. Our model predicts survival in anti-CTLA-4-treated patients with melanoma and anti-PD-1-treated patients with lung cancer. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumours and rapidly evolving pathogens.

SUBMITTER: Luksza M

PROVIDER: S-EPMC6137806 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy.

Łuksza Marta M Riaz Nadeem N Makarov Vladimir V Balachandran Vinod P VP Hellmann Matthew D MD Solovyov Alexander A Rizvi Naiyer A NA Merghoub Taha T Levine Arnold J AJ Chan Timothy A TA Wolchok Jedd D JD Greenbaum Benjamin D BD

Nature 20171108 7681

Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, which are tumour-specific, mutated peptides presented on the surface of cancer cells. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentati ...[more]

PMID: 29132144

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Project description:The immune system influences the fate of developing cancers by not only functioning as a tumour promoter that facilitates cellular transformation, promotes tumour growth and sculpts tumour cell immunogenicity, but also as an extrinsic tumour suppressor that either destroys developing tumours or restrains their expansion. Yet, clinically apparent cancers still arise in immunocompetent individuals in part as a consequence of cancer-induced immunosuppression. In many individuals, immunosuppression is mediated by cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) and programmed death-1 (PD-1), two immunomodulatory receptors expressed on T cells. Monoclonal-antibody-based therapies targeting CTLA-4 and/or PD-1 (checkpoint blockade) have yielded significant clinical benefits-including durable responses--to patients with different malignancies. However, little is known about the identity of the tumour antigens that function as the targets of T cells activated by checkpoint blockade immunotherapy and whether these antigens can be used to generate vaccines that are highly tumour-specific. Here we use genomics and bioinformatics approaches to identify tumour-specific mutant proteins as a major class of T-cell rejection antigens following anti-PD-1 and/or anti-CTLA-4 therapy of mice bearing progressively growing sarcomas, and we show that therapeutic synthetic long-peptide vaccines incorporating these mutant epitopes induce tumour rejection comparably to checkpoint blockade immunotherapy. Although mutant tumour-antigen-specific T cells are present in progressively growing tumours, they are reactivated following treatment with anti-PD-1 and/or anti-CTLA-4 and display some overlapping but mostly treatment-specific transcriptional profiles, rendering them capable of mediating tumour rejection. These results reveal that tumour-specific mutant antigens are not only important targets of checkpoint blockade therapy, but they can also be used to develop personalized cancer-specific vaccines and to probe the mechanistic underpinnings of different checkpoint blockade treatments.

Dataset Information

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy.

Publications

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy.

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