Effective anti-tumour immunity in humans has been associated with the presence of T cells directed at cancer neoantigens1, a class of HLA-bound peptides that arise from tumour-specific mutations. They are highly immunogenic because they are not present in normal tissues and hence bypass central thymic tolerance. Although neoantigens were long-envisioned as optimal targets for an anti-tumour immune response2, their systematic discovery and evaluation only became feasible with the recent availability of massively parallel sequencing for detection of all coding mutations within tumours, and of machine learning approaches to reliably predict those mutated peptides with high-affinity binding of autologous human leukocyte antigen (HLA) molecules. We hypothesized that vaccination with neoantigens can both expand pre-existing neoantigen-specific T-cell populations and induce a broader repertoire of new T-cell specificities in cancer patients, tipping the intra-tumoural balance in favour of enhanced tumour control. Here we demonstrate the feasibility, safety, and immunogenicity of a vaccine that targets up to 20 predicted personal tumour neoantigens. Vaccine-induced polyfunctional CD4+ and CD8+ T cells targeted 58 (60%) and 15 (16%) of the 97 unique neoantigens used across patients, respectively. These T cells discriminated mutated from wild-type antigens, and in some cases directly recognized autologous tumour. Of six vaccinated patients, four had no recurrence at 25 months after vaccination, while two with recurrent disease were subsequently treated with anti-PD-1 (anti-programmed cell death-1) therapy and experienced complete tumour regression, with expansion of the repertoire of neoantigen-specific T cells. These data provide a strong rationale for further development of this approach, alone and in combination with checkpoint blockade or other immunotherapies.
We thank J. Russell and the Dana-Farber Cancer Institute (DFCI) Center for Immuno-Oncology (CIO) staff; M. Copersino (Regulatory Affairs), B. Meyers, C. Harvey, and S. Bartel (Clinical Pharmacy); A. Lako (CIO), M. Bowden (Center for Molecular Oncologic Pathology); O. Sturtevant, H. Negre, S. Y. Kim, M. A. Kelley (Cell Manipulation Core Facility) and the Pasquarello Tissue Bank (all at DFCI); T. Bowman (DFHCC Specialized Histopathology Core Laboratory); the Broad Institute’s Biological Samples, Genetic Analysis, and Genome Sequencing Platforms; S. Hodi, G. Dranoff, M. Rajasagi, U. Burkhardt, S. Sarkizova, J. Fan, and P. Bachireddy for discussions; J. Petricciani and M. Krane for regulatory advice; B. McDonough (CSBio) and S. Thorne (CuriRx) for peptide development. This research was made possible by a gift from the Blavatnik Family Foundation, and was supported by grants from the Broad Institute SPARC program and the National Institutes of Health (NCI-1RO1CA155010-02 (to C.J.W.), NHLBI-5R01HL103532-03 (to C.J.W.), NCI-SPORE-2P50CA101942-11A1 (to D.B.K.); NCI-R50 RCA211482A (to S.S.)), from the Francis and Adele Kittredge Family Immuno-Oncology and Melanoma Research Fund (to P.A.O.), the Faircloth Family Research Fund (to P.A.O.), and the DFCI Center for Cancer Immunotherapy Research fellowship (to Z.H.). C.J.W. is a scholar of the Leukemia and Lymphoma Society.
This table contains QC metrics of whole-exome sequencing and RNA-sequencing for Patients 1-10. Sheet a contains whole exome sequencing. Sheet b contains RNA sequencing.
This table contains somatic mutations identified from Patients 1-10.
This table contains a summary of the number of identified somatic mutations, predicted HLA binders and synthesized immunizing peptides for Patients 1-10.
This table contains patient information. Sheet a contains HLA allotypes of all subjects. Sheet b contains treatment-related adverse events.
This table contains a summary of expression and class I prediction related to the immunizing peptides for Patients 1-6.
This table a summary of class II prediction related to the immunizing peptides for Patients 1-6.
This table contains differential analysis of single cell gene expression of CD4+ T cells pre-vaccination and tetramer-positive CD4+ T cells post-vaccination for Patients 1 and 4. Sheet a contains Patient 1, sheet b contains Patient 4, sheet c contains Patient 1 and 4 and sheet d Patient 1 and 4 intersection.