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.
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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.
E.F.F. is a founder and employee of Neon Therapeutics. N.H. and C.J.W. are founders of Neon Therapeutics and members of its scientific advisory board. P.A.O. has advised Neon Therapeutics. E.S.L. is a founder of Neon Therapeutics and a member of its board of directors. K.N. and I.J. are employees of CuriRx. Patent applications have been filed on aspects of the described work entitled as follows: Compositions and Methods for Personalized Neoplasia Vaccines (N.H., E.F.F., and C.J.W.), Methods for Identifying Tumour Specific Neo-Antigens (N.H. and C.J.W.), Formulations for Neoplasia Vaccines (E.F.F., K.N., and I.J.), and Combination Therapy for Neoantigen Vaccine (N.H., C.J.W., and E.F.F.). S.J.R. receives research funding from Bristol-Myers Squibb, MedImmune, and is on the scientific advisory board for Perkin Elmer. The remaining authors declare no competing financial interests. A.M.S. is a founder and employee of Oncovir, Inc. C.J.W. is subject to a conflict of interest management plan for the reported studies because of her competing financial interests in Neon Therapeutics. Under this plan, C.J.W. may not access identifiable human subjects’ data nor otherwise participate directly in the IRB-approved protocol reported herein. C.J.W.’s contributions to the overall program strategy and data analyses occurred on a de-identified basis.
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Extended data figures and tables
Extended Data Figure 1 Mutational landscape of patient melanoma and radiographic evidence of complete response after anti-PD-1 therapy for patients 2 and 6.
a, Numbers of mutations and predicted epitopes per patient tumour. Red solid lines, patients with vaccines generated and vaccinations completed (n = 6); red dashed lines, vaccines generated but vaccinations not initiated (n = 2); grey, insufficient mutation number for vaccine generation (n = 2). b, Expression (measured and normalized as transcripts per million base pairs (TPM) from the RNA-seq data) of known melanoma-associated genes in the tumour specimens for all ten patients entered into the trial (circles) compared with skin tissue (blue box, (GTEx data)) and melanoma from TCGA (red box; see Methods for analysis). The upper, middle, and lower hinge of the box are 75%, 50%, and 25% quantiles. All points above or below whiskers are the outliers. c, The overall mutational landscape of the eight patient melanoma samples for which immunizing peptides were generated (top, number of mutations per megabase; bottom, distribution of nucleotide changes) and the presence of mutations in genes previously identified as recurrent in melanoma TCGA samples (n = 290) by the MutSig2CV algorithm (middle, doi:10.7908/C1J67GCG; genes ordered on the basis of significance of recurrence reported per TCGA, Supplementary Information 2). d, Patient (Pt.) 2. Left: positron emission tomography/computed tomography (PET/CT) scans obtained 8 weeks after the last booster vaccine demonstrate new intensely fludeoxyglucose F 18 (FDG)-avid right hilar lymphadenopathy measuring ~2.1 cm (maximal standardized uptake value 20.3 (yellow arrow)). Right: PET/CT obtained 12 weeks later, after four doses of pembrolizumab at 2 mg per kg (body weight) given every 3 weeks, revealing complete interval resolution of the right hilar lymphadenopathy consistent with a complete response. Patient 6. Left panels: CT scans of the chest obtained 1 week after the last booster vaccine demonstrate multiple soft-tissue nodules along the left lateral and posterolateral chest wall (left upper panel, yellow arrow indicates a 2.1 cm × 1.8 cm soft-tissue nodule as an example) and a left lower lobe pulmonary nodule (left lower panel, yellow arrow). Right panels: CT scans obtained 16.5 weeks later, after four doses of pembrolizumab at 2 mg per kg (body weight) given every 3 weeks, revealing complete interval resolution of all lesions consistent with a complete response. On the upper panels, note that the liver is partly visualized on the pre-treatment scan (left upper panel) as a result of expirational state and not visualized on the post-treatment scan (right upper panel) as a result of inspirational state. The cross sections visualizing the soft-tissue metastases in the left chest wall versus their resolution after treatment correspond.
Extended Data Figure 2 Polyfunctional neoantigen-specific CD4+ T-cell responses are induced by vaccination in all six patients.
Frequencies of CD4+ T cells secreting cytokines in response to pools of 15- to 16-mer ASP, as measured by ICS after stimulation of PBMCs ex vivo with ASP pools. a, IFN-γ-producing CD4+ T cells detected by flow cytometry before vaccination and at week 16 after vaccination for all six vaccinated patients. Fluorescence-activated cell sorting (FACS) plots were pre-gated on CD4+ T cells. Red values, frequencies of ASP-pool-reactive IFN-γ+ cells as a proportion of all CD4+ T cells. b, Frequencies of IFN-γ-, TNF-α-, and IL-2-producing cells within CD4+ T cells in response to ASP pools tested in samples collected before vaccination (blue) and at week 16 after vaccination (red). c, Pie charts of the total CD4+ T-cell responses positive for one, two, or three cytokines. Bar graphs are shown of absolute frequencies of ASP-pool-reactive CD4+ T cells producing one, two, or three cytokines. d, Median percentage cytokine production across six patients by CD4+ T cells ex vivo against ASP peptide pools.
Extended Data Figure 3 Polyfunctional neoantigen-specific CD8+ T-cell responses are induced by vaccination in all six patients.
Frequencies of CD8+ T cells secreting cytokines in response to pools of 9- to 10-mer predicted class I EPT after a single round of pre-stimulation. PBMCs were cultured with EPT pools for 10–21 days followed by ICS. a, IFN-γ-producing CD8+ T cells detected by flow cytometry pre-vaccination and at week 16 after vaccination for all six vaccinated patients. FACS plots were pre-gated on CD8+ T cells. Percentages shown in red are frequencies of EPT-pool-reactive IFN-γ+ cells as a proportion of all CD8+ T cells. b, IFN-γ responses of CD8+ T cells against EPT pools after one round of pre-stimulation measured by ICS pre-vaccination and at 16 weeks after vaccination. c, Bar graphs show absolute frequencies of EPT-pool-reactive CD8+ T cells producing one, two, or three cytokines. Pie charts summarize the fractions of the total CD8+ T-cell responses positive for one, two, or three cytokines. d, Median percentage cytokine production across six patients by CD8+ T cells after one round of pre-stimulation against EPT peptide pools.
Extended Data Figure 4 Deconvolution of peptide pools to identify neoantigen-specific T-cell responses ex vivo against individual 15- to 16-mer ASP.
Deconvolution of T-cell reactivity against individual ASP by ex vivo IFN-γ ELISPOT using the week 16 post-vaccination PBMCs, tested in duplicate or triplicate wells per peptide (error bars, s.e.m.). *Responses were scored positive if >55 spot-forming cells (SFC) were detected and were at least 1.5 s.d. over the DMSO control (>3 s.d. over background for patients 5 and 6). a, Patient 3 deconvolution. Inset: examples of positive IMP/ASP sequences; red, ASP stimulating reactivity; boxed, the mutated amino acids. b, Deconvolution for all other patients. c, IFN-γ ELISPOT response of patient 3 CIT-specific CD8+ T-cell line from week 16 (7 × 104 CD8+ T cells per well) against mutated (Mut) versus corresponding wild-type peptide across a range of concentrations (10 pg ml−1 to 10 μg ml−1) pulsed on 1 × 104 T-cell-depleted PBMCs (hereafter referred to as APCs) per well.
Extended Data Figure 5 Mapping of CD4+ and CD8+ T-cell responses to individual ASP and EPT to the IMP for all six patients.
ASP and EPT covering the IMP are shown for the IMP that induced T-cell responses. T cells from week 16 PBMCs were tested. Red bold and shading: mutated amino acids, absent in those IMP arising from neoORFs. Blue underline: for class I epitopes, predicted epitopes (IC50 < 300 nM) based on NetMHCpan36,45; for class II epitopes, predicted epitopes <10th percentile based on the Immune Epitope Database and Analysis Resource (IEDB)-recommended consensus approach combining NN-align, SMM-align, and CombLib if allele predictions are available, otherwise NetMHCIIpan (Supplementary Information 6)45. Red font, peptides that generated an ex vivo CD4+ T-cell response; blue font, peptides that generated a T-cell response after one round of pre-stimulation with peptides, Triangle, ASP- or EPT-specific T cells that also recognized a corresponding mutated minigene; *T-cell responses against minigenes that were blocked by pan anti-HLA-DR or anti-HLA class I blocking antibodies for CD4+ or CD8+ T cells, respectively.
Extended Data Figure 6 IFN-γ response of pre- and post-vaccination PBMCs against individual ASP, and IFN-γ response and CD107αβ degranulation by neoantigen-specific T-cell response against expressed minigenes.
PBMCs from week 16 after vaccination were pre-stimulated with ASP and EPT for measuring CD4+ and CD8+ T-cell responses, respectively. a, Detection of IFN-γ responses by ELISPOT of CD4+ T cells against individual ASP after one round of pre-stimulation with ASP pools in matched pre- and 16-week post-vaccination samples for patients 1–6 (1 × 104 APCs and 1 × 104 T cells per well), tested in duplicate or triplicate wells per peptide (error bars, s.e.m.). b, Autologous B cells were nucleofected with in vitro translated RNA generated from mutated (Mut) or wild-type minigenes (MG). T-cell lines were cultured with mutated or wild-type minigene nucleofected B cells, mutated minigene nucleofected B cells with anti-HLA class I or anti-HLA-DR antibodies, and non-nucleofected B cells with DMSO in IFN-γ ELISPOT (8 × 104 B cells per well were plated with 5 × 103 T cells per well and 1 × 104 CD8+ T cells per well for CD4+ and CD8+ T-cell response detection, respectively), tested in duplicate or triplicate wells per each condition (error bars, s.e.m.). c, T-cell lines were cultured with mutated minigene nucleofected B cells or non-nucleofected B cells followed by CD107αβ degranulation assay. Representative FACS plot of patient 3 CD107αβ degranulation assay for VPS16-specific CD8+ T-cell lines (top) and other neoantigen-specific CD4+ and CD8+ T-cell lines (bottom) from week 16 against autologous B cells nucleofected or not with mutated minigenes. FACS plots were pre-gated on CD8+ T cells.
Extended Data Figure 7 Surface expression of HLA class I and class II on patient melanoma cell lines and originally resected tumour.
a, Flow cytometric staining of autologous melanoma cell lines generated from primary tumour samples with anti-class I and anti-class II or isotype antibodies. b, Dual chromogenic immunohistochemical staining of excised FFPE tumours (see Methods for details). Representative images of positive staining for HLA class I (patients 4 and 2) and HLA class II (patient 6) and negative staining for class II (patient 2). Red, melanoma transcription factor SOX10; brown, HLA class I or class II. c, Summary of immunohistochemical results of five patients with available FFPE tissue. Semi-quantitative scoring was performed for the intensity of positive staining of melanoma cell membranes for class I or II (0, negative; 1, weak; 2, moderate; 3, strong) and for the percentage of positive staining malignant cells (0–100%). A cumulative H score was obtained by multiplying intensity score by the percentage of malignant cells with positive staining.
Extended Data Figure 8 Repertoire of neoantigen-specific T-cell responses persists and broadens following PD-1 blockade, and summary of all CD4+ and CD8+ T-cell responses against neoantigens across the six patients.
a, Persistent or new responses to mutated peptides after PD-1 blockade (pembrolizumab) are shown. PBMCs from patients 2 and 6 (before vaccination, week 16 after vaccination, or 11.5 months (patient 2) or 8.5 months (patient 6) after initiation of pembrolizumab therapy) were pre-stimulated for 21 days with ASP or EPT pools, and reactivity against individual ASP and EPT was then tested by IFN-γ ELISPOT. Ten thousand APCs per well were plated with 1 × 104 T-cell lines per well and 1 × 104 CD8+ T-cell lines per well for CD4+ and CD8+ T-cell response detection, respectively, tested in duplicate or triplicate wells per peptide (error bars, s.e.m.). Each line represents the IFN-γ response against a single ASP or EPT tested per immunizing peptide. Number for each gene: total number of ASP or EPT tested per immunizing peptide. b, The rings, from outer to inner, show the following: (1) predicted affinity of peptide for HLA; heat map scaled from darkest (lowest half-maximal inhibitory concentration (IC50) (nM), or highest affinity) to lightest (highest IC50 (nM), or lowest affinity); (2) level of transcript expression of the tumour, scaled from darkest (highest number of transcripts per million reads) mapped to lightest (lowest number of transcripts per million reads); (3) reactivity to peptide-pulsed autologous APCs; (4) reactivity to B cells nucleofected with minigenes; (5) reactivity to cultured autologous melanoma cells. c, d, Ex vivo class II tetramer staining of patient 1 CD4+ T cells. Visualization of transcriptomes of single CD4+ T cells before vaccination and tetramer-positive CD4+ T cells after vaccination by t-distributed stochastic neighbour embedding (t-SNE).
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. (XLSX 14 kb)
This table contains somatic mutations identified from Patients 1-10. (XLSX 1128 kb)
This table contains a summary of the number of identified somatic mutations, predicted HLA binders and synthesized immunizing peptides for Patients 1-10. (XLSX 10 kb)
This table contains patient information. Sheet a contains HLA allotypes of all subjects. Sheet b contains treatment-related adverse events. (XLSX 29 kb)
This table contains a summary of expression and class I prediction related to the immunizing peptides for Patients 1-6. (XLSX 44 kb)
This table a summary of class II prediction related to the immunizing peptides for Patients 1-6. (XLSX 36 kb)
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. (XLSX 163 kb)
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Ott, P., Hu, Z., Keskin, D. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017). https://doi.org/10.1038/nature22991
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