Neoantigenic Epitopes Associated with SF3B1 Mutations
20230212243 · 2023-07-06
Assignee
Inventors
- Olivier Lantz (Paris, FR)
- Marc-Henri Stern (Paris, FR)
- Jérémy Bigot (Eaunes, FR)
- Alexandre Houy (Vitry sur Seine, FR)
- Ana Ines Lalanne (Paris, FR)
Cpc classification
C07K14/4748
CHEMISTRY; METALLURGY
C07K14/00
CHEMISTRY; METALLURGY
International classification
Abstract
The present application relates to a tumor specific neoantigenic peptide, wherein said peptide is encoded by a part of an ORF sequence from a transcript associated with a SF3B1 or a SF3B1-like mutation, comprises at least 8 amino acids and binds at least one MHC molecule with an affinity of less than 500 nM; and is not expressed in normal healthy cells. The present application further relates to vaccine or immunogenic composition, antibodies, T cell receptors, polynucleotides, vectors and immune cells derived thereof as well as their use in therapy of cancer.
Claims
1-17. (canceled)
18. A tumor specific neoantigenic peptide, wherein said peptide (a) is encoded by a part of an ORF sequence from a transcript associated with a SF3B1 or a SF3B1-like mutation, present in a SF3B1 mutant tumor sample; (b) comprises at least 8 amino acids and binds at least one MHC molecule with an affinity of less than 500 nM; and (c) is not expressed in normal healthy cells; or is any of SEQ ID NO: 1-1058.
19. The tumor specific neoantigenic peptide according to claim 18, wherein said peptide is 8 or 9 amino acids long, and binds at least one MHC class I molecule.
20. The tumor specific neoantigenic peptide according to claim 18, wherein the SF3B1 mutant tumor is selected from uveal melanoma, hematological malignancies, breast cancers, skin melanoma, renal cell carcinoma, pulmonary adenocarcinoma, hepatocarcinoma, pancreatic carcinoma, endometrial cancers and uveal melanoma.
21. The tumor specific neoantigenic peptide according to claim 18, which is encoded by a part of an ORF sequence from a transcript associated with a SF3B1 or SUGP1 mutation.
22. A population of autologous dendritic cells or antigen presenting cells that have been pulsed with one or more or two or more neoantigenic peptides according to claim 18 or transfected with a polynucleotide encoding one or more or two or more neoantigenic peptides according to claim 18.
23. A vaccine or immunogenic composition capable of rising a specific T-cell response comprising: (a) one or more neoantigenic peptides according to claim 18; (b) one or more polynucleotides encoding one or more neoantigenic peptides according to claim 18; (c) one or more of said polynucleotides in b., further linked to a heterologous regulatory control nucleotide sequence; (d) a population of autologous dendritic cells or antigen presenting cells that have been pulsed with one or more or two or more neoantigenic peptides according to claim 18, or transfected with a polynucleotide encoding one or more or two or more neoantigenic peptides according to claim 18; (e) one or more recombinant MHC molecules loaded with neoantigenic peptides according to claim 18; and/or (f) one or more of said neoantigenic peptides in (a), said polynucleotides in (b) or (c), said recombinant MHC molecules in e., or said population of autologous dendritic cells or antigen presenting cells in (d), wherein the neoantigenic peptides comprise at least one peptide which is encoded by a canonical ORF and/or at least one which is encoded by a non-canonical ORF.
24. An antibody, or an antigen-binding fragment thereof, a T cell receptor (TCR), or a chimeric antigen receptor (CAR) that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule, with a Kd affinity of about 10.sup.−6 M or less.
25. A T cell receptor that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule, with a Kd affinity of about 10.sup.−6 M or less, wherein said T cell receptor is made soluble and fused to an antibody fragment directed to a T cell antigen.
26. The T cell receptor according to claim 25, wherein the targeted antigen is CD3 or CD16.
27. An antibody that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule, with a Kd affinity of about 10.sup.−6 M or less, wherein said antibody is a multi-specific antibody that further targets at least an immune cell antigen.
28. The antibody according to claim 27, wherein the immune cell is a T cell, a NK cell or a dendritic cell, and/or wherein the targeted antigen is CD3, CD16, CD30 or a TCR.
29. A polynucleotide encoding a neoantigenic peptide according to claim 18, or an antibody, a CAR or a TCR that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule with a Kd affinity of about 10.sup.−6 M or less, or a vector comprising the polynucleotide.
30. An immune cell that specifically binds to one or more neoantigenic peptides according to claim 18.
31. The immune cell according to claim 30, which is an allogenic or autologous cell selected from T cell, NK cell, CD4+/CD8+, TILs/tumor derived CD8 T cells, central memory CD8+ T cells, Treg, MAIT, and γδ T cell.
32. An immune cell which is a T cell comprising: (a) a T cell receptor that specifically binds one or more neoantigenic peptides according to claim 18, or (b) a TCR or a CAR that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule, with a Kd affinity of about 10.sup.−6 M or less.
33. A method of cancer vaccination therapy, comprising administering to a subject in need thereof, a therapeutically effective amount of: (i) a neoantigenic peptide according to claim 18; (ii) a population of dendritic cells or antigen presenting cells that have been pulsed with one or more or two or more neoantigenic peptides according to claim 18 or transfected with a polynucleotide encoding one or more or two or more neoantigenic peptides according to claim 18; (iii) one or more recombinant MHC molecules loaded with neoantigenic peptides according to claim 18; or (iv) a polynucleotide encoding one or more neoantigenic peptides according to claim 18 or a vector comprising the polynucleotide.
34. The method according to claim 33, wherein the subject is suffering from an SF3B1 mutant associated uveal melanoma or is at risk of suffering from an SF3B1 mutant associated uveal melanoma.
35. The method according to claim 33, wherein the therapy is administered in combination with a chemotherapeutic agent or an immunotherapeutic agent.
36. A method for inhibiting cancer cell proliferation, or for the treatment of cancer in a subject in need thereof, comprising administering to the subject, a therapeutically effective amount of: (i) a neoantigenic peptide according to claim 18; (ii) a population of dendritic cells or antigen presenting cells that have been pulsed with one or more or two or more neoantigenic peptides according to claim 18 or transfected with a polynucleotide encoding one or more or two or more neoantigenic peptides according to claim 18; (iii) a polynucleotide encoding one or more neoantigenic peptides according to claim 18 or a vector comprising the polynucleotide; (iv) an antibody, or an antigen-binding fragment thereof, a T cell receptor (TCR), or a chimeric antigen receptor (CAR) that specifically binds a neoantigenic peptide according to claim 18, in association with an MHC molecule, with a Kd affinity of about 10.sup.−6 M or less; or (v) an immune cell that specifically binds to one or more neoantigenic peptides according to claim 18.
37. The method according to claim 36, wherein the subject is suffering from an SF3B1 mutant associated uveal melanoma or is at risk of suffering from an SF3B1 mutant associated uveal melanoma.
38. The method according to claim 36, wherein the treatment is administered in combination with a chemotherapeutic agent or an immunotherapeutic agent.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0334]
[0335] b. Principal component analysis of the selected 449 cases (including cases with high SBT scores, cases with mutations in splicing factors SF3B1, SRSF2 and U2AF1, and tissue-matched control tumor cases) characterized by the ratio of aberrant to canonical 3′ss expression in top 400 cryptic 3′ss junctions selected in an unsupervised way (see Methods). Cases with SUGP1 alterations are highlighted (magenta spots). The two first principal components, PC1 and PC2 are plotted on x and y-axes, respectively. The fraction of variance explained by each principal component is indicated.
[0336] c. Hierarchical clustering and the heatmap of differentially spliced junctions in the LUAD cohort. Cases are denoted according to their alterations in SF3B1 or SUGP1. For comparison, gene expression level of the junction clustering is shown (differential expression of junctions is not the consequence of differential gene expression).
[0337] d. Distances between the cryptic and canonical 3′ss in the LUAD cohort for the top differentially expressed junctions in SF3B1 mutated and SUGP1 altered cases. The position of the canonical 3′ss is set to 0.
[0338]
[0339] a. Effect of siRNA-mediated knockdown of SUGP1, on the aberrant splice forms of DPH5, DLST and ARMC9 in HEK293T cell line. Relative expression of cryptic 3′ss junction normalized to the canonical 3′ss junction was determined by quantitative RT-PCR, and effect of the different siRNA #1,3,6 and 21 was compared with the control (CTL) (Paired t-test; *, p<0.05; **, p<0.005; ***, p<0.0005). The protein knockdown was confirmed by immunoblotting with anti-SUGP1, using β-actin as a loading control.
[0340] b. Effect of siRNA-mediated knockdown of SUGP1, overexpression of wild-type SUGP1 or SF3B1, overexpression of SUGP1.sup.L515P, R625T or P636L or SF3B1.sup.K700E on the aberrant splice form of DPH5 in HEK293T cell line. Relative expression of cryptic 3′ss junction normalized to the canonical 3′ss junction of DPH5 was determined by quantitative RT-PCR. The results are average of three replicates and are represented as mean±sd, and each condition is compared to the control (Paired t-test;*, p<0.05; **, p<0.005). The protein knockdown or overexpression was confirmed by immunoblotting with anti-Flag and anti-SUGP1 using β-actin as a loading control.
[0341] c. 2-D plot of the differential aberrant splice junction expression in transiently SUGP1-depleted HEK293T cells (y-axis) and cells overexpressing SF3B1K700E (x-axis), as measured by RNA-seq.
[0342] d. Minigene splice assay of two SF3B1.sup.MUT-sensitive 3′ (ENOSF1, TMEM14C) and their cryptic (BP′) and canonical (BP) branchpoint mutants. Gel electrophoresis shows the different splicing processes for minigene ExonTrap constructions in SF3B1.sup.WT cell line HEK293T with or without siRNA-mediated knockdown of SUGP1. The lower band corresponds to the usage of the canonical 3′ss. The intermediate band corresponds to the usage of the cryptic 3′ss. The upper band corresponds to the heteroduplex formation from the two products.
[0343]
[0344] a. Hierarchical clustering and heatmap analysis of differential splice junctions in HAP1 and HAP1SUGP1-P636L isogenic cell lines. Three biological replicates for each cell lines (R1-R3) were analyzed by RNA-seq. Below the array tree and the subtype identification row, the heatmap of the differential splice junctions is shown. The corresponding gene level expression heatmap is shown (right panel).
[0345] b. Barplot representing the expressed aberrant splicing events in HAP1 and HAP1SUGP1-P636L. A3SS: junctions with alternative 3′ splice site; A5SS: junctions with alternative 5′ splice site; MXE: junctions with alternative 3′SS and 5′SS; RI: intron retention; SE: exon skipping.
[0346] c. Distances between the cryptic and canonical 3′ss in HAP1 and HAP1.sup.SUGP1-P636L isogenic cell lines. For cryptic 3′ss within the 50 nts preceding the canonical 3′ss, the distance between the cryptic and corresponding canonical 3′ss was plotted as a histogram. The position of the canonical 3′ss is set to 0.
[0347] d. siRNA-mediated knockdown of SUGP1.sup.WT and SUGP1.sup.P636L impact on DPH5 aberrant junction expression in HAP1 isogenic cell lines. Relative expression of cryptic 3′ss junction normalized to the canonical 3′ss junction of DPH5 was determined by quantitative RT-PCR. The results are average of three replicates and are represented as mean±s.d, and each condition is compared to the control (Paired t test; **, p<0.005; ***, p<0.0005).
[0348]
[0349]
[0350] (A) Identification of CD8.sup.+ T cells recognizing the indicated specificities using HLA-A2:peptide tetramers labelled with two different fluorochomes. Representative staining enabling to divide the Tet.sup.+CD8.sup.+ cells into naive (CCR7.sup.+ECD45RA.sup.+), central memory (CCR7.sup.+CD45RA.sup.−), effector-memory (CCR7.sup.−CD45RA.sup.−) and effector-memory (CCR7.sup.−CD45RA.sup.+). Non-naïve CD8.sup.+ T cells specific for Melan-A are only found in UM patients whereas A2:37-specific non-naïve CD8.sup.+ T cells are only found in SF3B1.sup.mut patients. (B) Frequency of the indicated specificities in CD8.sup.+ cells from the blood of patients with SF3B1.sup.mut tumors. (C) Each dot corresponds to the proportion of the CD8.sup.+ T cells that are not naive in healthy donors (n=4), SF3B1.sup.mut (n=8) or SF3B1.sup.wt (n=5) patients. Dots on the X axis correspond to a number of Ter.sup.+ cells below 10.
[0351]
EXAMPLES
[0352] 1—Genetic Alterations of SUGP1 Mimic Mutant-SF3B1 Splice Pattern in Lung Adenocarcinoma and Other Cancers
[0353] Genes involved in 3 ‘-splice site recognition during mRNA splicing and maturation constitute an emerging class of oncogenes’. SF3B1 is the most frequently mutated splicing factor in cancer and its mutants corrupt branchpoint recognition leading to usage of cryptic 3′-splice sites and subsequent aberrant junctions.sup.2-5. For a comprehensive determination of alterations leading to this splicing pattern, The inventors performed a pan-TCGA splice junction analysis. While cryptic 3′-splice usage was strongly associated with SF3B1 mutations, they also detected 10 SF3B1 wild-type tumors (including 5 lung adenocarcinomas). Genomic profile analysis of these tumors identified somatic mutations combined with loss-of-heterozygosity in the splicing factor SUGP1 in 5 of these cases. Modeling of SUGP1 loss and mutations in cell lines showed that both alterations induced mutant-SF3B1-like aberrant splicing. This study provides the first evidence of the involvement of genetic alterations of SUGP1 as an SF3B1 genocopy in lung adenocarcinoma and other cancers.
[0354] During splicing, SF3B1 mediates U2 snRNP recruitment to the branchpoint (BP) by interacting with the intronic pre-mRNA.sup.6. Cancer-associated SF3B1 Major Hot Spots (SF3B1MHS) are change-of-function mutations targeting codons R625, K666 and K700. SF3B1MHS lead to recognition of an alternative branchpoint (BP′) upstream of the canonical BP, consequent cryptic 3′ splice site (3′ss) usage and an aberrant junction in a subset of mRNA defined by sequence requirements.
[0355] For a comprehensive view of pathogenic mutations inducing usage of cryptic 3′ss as observed in a SF3B1-mutant context, the inventors first used a Sequence Bloom Tree (SBT).sup.8,9 constructed from RNA-seq data for a total of 11,350 different samples and 33 tumor types from TCGA. They tested occurrence of 1443 aberrant junctions reported in two complementary analyses.sup.4,5 as consequences of SF3B1MHS. The SBT score, representing the number of these junctions found at least once in raw RNA-seq data (fastq) is a fast and highly sensitive approach for such pre-defined patterns. After adjustment for RNA-seq coverage, the 112 top SBT-score cases were selected following the cutoff determined by the lowest SBT score of a validated SF3B1p.A633V case (table 2,
TABLE-US-00002 TABLE 2 Tumor cases harbouring the SF3B1-like splice pattern with no SF3B1 mutation Tumor Sample Alteration LUAD TCGA-55-7576 SUGP1_LOH MESO TCGA-3H-AB3K SUGP1_p.R625T_LOH LUAD TCGA-05-4432 SUGP1_p.L515P_LOH LIHC TCGA-ZP-A9CV SUGP1_LOH LUAD TCGA-78-7542 SUGP1_p.G519V_LOH LUAD TCGA-NJ-A4YQ SUGP1_p.P636L_LOH LUAD TCGA-91-6829 SUGP1_p.G26*_LOH LAML TCGA_AB_2882 ND (U2AF1_S34Y) UVM TCGA_WC_A87W ND SKCM TCGA_EE_A2A1 ND LUAD: Lung Adenocarcinoma LIHC: Liver Hepatocellular Carcinoma MESO: Mesothelioma LAML: Acute Myeloid Leukemia *Stop mutation ND: causal alteration not determined
[0356] These high SBT-score cases were thoroughly verified for SF3B1 mutations and further characterized for aberrant splice junctions, together with additional cases including those with mutations in other splice factors as well as control tumor cases without splice factor alteration (449 total cases). Based on the direct analysis of cryptic 3′ splice site usage obtained from RNA-seq data (STAR 2.0.5) in this series, the exhaustive list of the TCGA cases exhibiting SF3B1-like splice aberration was obtained. Principal component analysis of 3′ss usage showed the main source of variation to be SF3B1 mutations. The aberrant splice pattern was validated in 87 cases, including 77 SF3B1-mutated cases (51 SF3B1MHS) (
[0357] The inventors then further mined the 5 SF3B1-like cases associated with neither SF3B1 nor SUGP1 mutation. Normalized SUGP1 expression levels in 2 cases (1 LUAD and 1 LIHC) were the lowest by orders of magnitude in the corresponding cohorts. Interestingly, they also observed LOH in the SUGP1 locus for these two cases. The remaining three cases (1 each LAML, SKCM and UVM) associated with the SF3B1-like splice pattern were not found altered for SUGP1. Of note, while the LAML case harbored a U2AF/S34Y hotspot mutation, this is not likely to be causal of the SF3B1-like splice pattern as 20 other U2AF1S34Y/F cases showed no evidence of such pattern and U2AF1 mutations are known to drive a different splicing pattern.sup.1,11. Taking into account that 5 out of the 10 cases were LUAD, including 4 SUGP1LOH/Mut and 1 case with the lowest SUGP1 expression (SUGP1 Low), they performed a splice junction analysis in the LUAD cohort, comparing 4 SUGP/LOH/Mut, 1 SUGP1 Low, 6 SF3B1MHS and 98 LUAD cases with no splice gene mutation (See Methods). This showed coherent changes in SUGP/LOH/Mut and
[0358] SF3B1MHS splice profiles, with the similar profile of aberrant junctions showing increased usage cryptic 3′ ss located 10-25 nts upstream of the canonical 3′ ss (
[0374] 2—Splicing Patterns in SF3B1 Mutated Uveal Melanoma Generate Shared Immunogenic Tumor-Specific Neo-Epitopes
SUMMARY
[0375] Disruption of splicing patterns due to mutations of splicing factors in tumors have been proposed for several years as a source of tumor neo-epitopes, which would be both public (shared between patients) and tumor-specific (not expressed in normal tissues). In this work, we show that mutations of the splicing factor SF3B1 in uveal melanoma (UM) generate immunogenic neo-epitopes. Memory CD8 T cells specific for these neo-epitopes are only found in the 20% of UM patients whose tumor is mutated for SF3B1. Single cell analyses of neo-epitope specific T cells from the blood identified large clonal T-cell expansions with various and distinct effector transcription patterns. Some of these clones were found in the corresponding tumor. Clones of CD8 T cells specific for the neo-antigens specifically recognized and killed SF3B1-mutated tumor cells supporting the use of these germline-encoded neoantigens related to SF3B1 mutations as therapeutic targets.
[0376] Methods
[0377] Human Samples
[0378] Blood and leukaphereses from healthy donors (HD) were provided by the Establishment Français du Sang. Leukaphereses from patients with metastatic uveal melanoma (UM) were obtained from peptide vaccine trials CP-99-03 and IC-2004-01 before treatment. We selected the patients that had more than 30 frozen vials of PBL and for whom liver metastasis RNA was available. Cells were stored in liquid nitrogen until the time of analysis. RNA from the confirmatory diagnostic biopsy of the UM liver metastasis performed at inclusion was used for SF3B1 mutation confirmation and TCR sequencing. SF3B1 was sequenced as previously described (10). In the inventor's institution, all patients were informed that pathological specimens might be used for research purposes.
[0379] RNA-Sequencing, Analysis and Neoepitope Prediction
[0380] RNA was isolated from fresh tumor samples using a CsCl cushion as described (22) then quantified with Qubit RNA HS assay kit (Thermo Fisher Scientific). RNA-seq libraries were constructed using the TruSeq Stranded mRNA Sample Preparation Kit (Illumina) and sequenced on an Illumina HiSeq 2500 platform using 100-bp paired-end sequencing. An average depth of global sequence coverage of 111 million and a median coverage of 75 million was attained. Differential junctions using alternative acceptors were identified as previously described (10) comparing the 8 SF3B1′ tumors with 5 SF3B1.sup.wt tumors. Sequences of aberrant and corresponding normal transcripts were extracted using ANNOVAR and ENSEMBL database (23) NetMHCpan v4, an artificial neural network-based algorithm was used to predict MHC class I affinity for splicing anomalies derived peptides (12). Only nonamer peptides with strong affinity for HLA-A2:01 (rank<0.5% compared to a set of 400,000 random peptides) were retained for this study.
[0381] MHC/Peptide Complex Generation:
[0382] Recombinant HLA-A*02:01 molecules (13) were purchased from immunAware (Copenhagen, Denmark) as easYmers® (catalog #1002-1). All peptides were synthesized at <95% purity (Synpeptide) and tested for HLA-A2 monomer avidity following immunAware bead-based recommended assay and ELISA (24). Briefly, for each tetramer, MHC/peptide complex at 100 μM were combined 1H at room temperature with fluorescent streptavidin (Biolegend) or oligo-tagged streptavidin (Biolegend) for single cell experiment. Tetramers were stored at 4° C. for maximum 3 months.
[0383] Facs Analysis and Abs:
[0384] PBMC were thawed in CO.sub.2-independent medium (GIBCO) and incubated during 30 minutes in culture medium containing 50 nM dasatinib (25) to improve tetramer staining. CD8.sup.+ T cells were enriched using human CD8 T cell enrichment kit (Stemcell) according to manufacturer instructions. Dead cells were stained with live/dead aqua (Invitrogen). For tetramer staining, tetramers for each specificity were labelled separately with 2 different fluorochromes in order to combine 10 different tetramer/peptide complexes in the same experiment and to decrease the noise related to non-specific binding (26). Briefly, cells were incubated for 20 min with each tetramer complex in brilliant stain buffer (BD) then cells were stained for 20 min with indicated antibodies, (CD3-BUV737, CD8-BUV395 (BD), CCR7-BV421 (Biolegend), CD45-RA FITC (Miltenyi Biotec), CD25 (BD), CD8 FITC, CD3 Alexa fluor 700). Cells were then washed and analyzed in a LSR Fortessa cytometer (BD)
[0385] T Cell Clone Generation and Cells Culture:
[0386] After tetramer staining, double tetramer positive CD8.sup.+ single cells were FAC sorted into 96 wellcntaining 1:1 AIM-V/RPMI medium supplemented with 5% human serum, 100 U/mL penicillin, 100 μg/mL streptomycin in the presence of 2×10.sup.5 irradiated (50 Gy) allogenic feeder cells. Cells were stimulated with human IL-2 (Novartis) (3000 UI/ml) and anti-CD3 (OKT3) (30 ng/ml). Starting on day 5, half of media was replaced with a 1:1 mixture of AIM-V/RPMI containing IL-2 (3000 IU/ml) every three days. When lymphocyte growth was evident, clones were transferred into T25 flasks. The clones were re-stimulated every 3 weeks using the same media containing IL-2, OKT3 and irradiated feeders. After each cycle of clone amplification, each clone was tested for tetramer binding by cytometry and their capacity to respond to peptide stimulation using IFN-γ and GrzB secretion (BD) and/or intracellular IFN-γ staining (eBioscience). cDNA from each clone was amplified by PCR using primers for TRAY, TRBV and constant regions (27), the PCR products sequenced and the resulting sequences analyzed using IMGT/V-QUEST (28).
[0387] Clone activation, cytokine release and killing assay: T cells clones were cocultured at 1:1 ratio with indicated cell line pulsed or not with 15 μM to 0.3 pM of peptide in AIM-V/RPMI medium for 18 hours at 37° C. Activation was measured by CD69, CD25, CD107a staining while cytokine secretion was analyzed in supernatant using cytometric beads array kits (BD) according to manufacturer's instruction. Killing assay was performed by culturing SF3B1′ or SF3B1′ Mel202 cell line.
[0388] Cell Lines
[0389] A Degron-KI system was used to generate isogenic cell lines from Mel202, a uveal melanoma cell line mutated for SF3B1 (c.R625G) as described in (15). Shortly, a Degron sequence was inserted by CRISPR/cas9 5′ to the start codon of the mutated SF3B1 allele. An expression vector for HLA-A2 kindly provided by 0. Schwartz (29) was stably integrated in both wild-type and edited Mel202 cell lines and validated by FACS analysis for HLA-A2 membrane expression using BB7.2-FITC antibody (BD).
[0390] Single Cell Experiments:
[0391] Thawed PBMC from patient UM1 were stained with PE and APC tetramers loaded with peptide 37, then tetramer positive cells were positively enriched using anti-APC and anti-PE microbeads (Miltenyi Biotech), stained with CD3 A700 and CD8 FITC and finally with DAPI. The positive fraction was sorted in a FACS ARIA (BD). To combine 5 tetramer positive populations from 2 donors (14, 17, 26 and 37 for UM2 and 18 for UM3) the tetramers were prepared using 5 different TotalSeq-PE streptavidins (BioLegend) and 1 classical fluorochrome-streptavidin (APC, PE-CF594, PE-Cy5, PE-Cy7), PE-CF594 was used for UM3 who had only one population sorted. The PBMC were stained with the 4 pairs of tetramers for patient UM2 and 1 pair of tetramers for patient UM3, enriched with anti PE-microbeads (Milteny Biotech), stained with CD3 A700 and CD8 FITC and DAPI and sorted separately. The cells were then counted, mixed and loaded onto a Chromium controller using Chromium next GEM Single Cell V(D)J reagent kit with feature barcoding technology according manufacturer's instructions.
[0392] Single-Cell RNA-Seq Processing
[0393] Single-cell expression was analyzed using the Cell Ranger single-cell Software Suite (v3.0.2, 10× Genomics) (30) to perform quality control, sample de-multiplexing, barcode processing, and single-cell 5′ gene counting. Sequencing reads were aligned to the GRCh38 human reference genome. Further analysis was performed in R (v3.5.1) using the Seurat package (v3.1.1) (31). Cells were then filtered out when expressing less than 500 genes for UM1 and 1000 genes for UM2/UM3 since this sample was of lower quality. Cells were also filtered out when expressing more than 10% mitochondrial genes, indicative of potential cell death or stress. Samples were then filtered for contaminating cells using classical markers. Notably, CD19 was used to remove B cells, MAFB was used to remove myeloid cells and CD3D/E/G and CD8A/B were used as positive controls. Altogether, 3441 cells were kept for UM1 and 3231 were kept for UM2 and UM3. For each sample, the gene-cell-barcode matrix of the samples was then normalized to a total of 1×10.sup.4 molecules. TotalSeq values were normalized according to the CLR method implemented in Seurat. The top 2000 variable features were identified using the “vst” method from Seurat. For UM2/UM3 samples, the fraction of doublets could be removed leveraging the TotalSeq information. Since the TotalSeq features were bimodal, we first binarized the TotalSeq features. The expression threshold was defined as 1 for UM2-A2:26 and 1.2 for the rest of the specificities. Cells were then labelled cells as doublets if they were expressing more than 1 TotalSeq above the expression threshold. 490 cells out of the 3213 (15%) were removed after removing TotalSeq doublets.
[0394] Dimension Reduction and Unsupervised Clustering
[0395] Top 30 Principal Components were computed and UMAP was performed using the top 30 PCs of the normalized matrix. Clusters were identified using the FindNeighbors and FindClusters function in Seurat with a resolution parameter of 0.4 for UM1 and 0.35 for UM2/UM3 and using the first 30 principal components. To choose the optimal number of clusters and prevent overclustering, clustree analysis was performed using the clustree package (32). Unique cluster-specific genes were identified by running the Seurat FindAllMarkers function using Wilcoxon test.
[0396] Analysis of Aberrant Peptides by Mass Spectrometry
[0397] Endogenous NET1 was immunoprecipitated from protein extracts using of antibody targeting the N-terminus part of NET1 (sc-271941; 2 μg per 200 μg of cell extract), as described (Kweh F, Zheng M, Kurenova E, Wallace M, Golubovskaya V, Cance W G. Neurofibromin physically interacts with the N-terminal domain of focal adhesion kinase. Mol Carcinog. 2009; 48:1005-17.). Peptidic samples were analyzed using an Orbitrap Exploris 480 mass spectrometer (Thermo Scientific) coupled to a RSLCnano system (Ultimate 3000, Thermo Scientific). To identify the endogenous aberrantly spliced NET1, cell lines and PDXs were lysed in Lysis buffer (50 mM Tris, 150 mM NaCl, 1% Triton, 0.5% NaDOC, 0.1% SDS, 5 mM EDTA, 10% glycerol supplemented with protease inhibitors (Roche) and phosphatase inhibitors) for 30 min on ice. Insoluble material was pelleted by centrifugation (16,000 g, 15 min at 4° C.). Lysates were then pre-cleared by incubation with 10 μL of nonspecific mouse IgG (Santa Cruz, sc-2025) plus 20 μL of packed and pre-washed Dynabeads coupled with protein G (10003D, Life Technologies) for 30 minutes at 4° C. The non-specific antibodies were then removed using magnetic rack and 250 μL of pre-cleared supernatant was incubated with 20 μL of anti-NET1 antibodies (sc-271941, Santa Cruz) overnight under gentle rotation. The immunocomplexes were then incubated with 20 μL of packed protein G coupled Dynabeads (10003D, Life Technologie) for 20 minutes at RT under gentle rotation.
[0398] Immunocomplexes bound to the beads were pelleted using magnetic rack and wash once with washing buffer (300 mM NaCl, 150 mM KOAc, 50 mM Tris, 2 mM MgCl.sub.2, phosphatase and protease inhibitors) containing 1% NP-40-substitute and 3 times with washing buffer containing 0.1% NP40-substitute. The immunocomplexes were finally washed 3 times with 500 μL of 25 mM Ammonium bicarbonate.
[0399] Finally, beads were resuspended in 100 μl of 25 mM NH.sub.4HCO.sub.3 and digested by adding 0.4 μg of trypsine/LysC (Promega) for 1 hour at 37° C. The resulting peptide mixtures were then loaded onto homemade C18 StageTips packed with AttractSPE™ Disks Bio C18 (Affinisep™ SPE-Disks-Bio-C18-100.47.20) for desalting. Peptides were eluted using 40/60 MeCN/H2O+0.1% formic acid, vacuum concentrated to dryness and reconstituted in injection buffer (2% MeCN/0.3% TFA).
[0400] Liquid chromatography-mass spectrometry (LC-MS/MS) analysis. LC was performed with an RSLCnano system (Ultimate 3000, Thermo Scientific) coupled online to a Orbitrap Exploris 480 mass spectrometer (MS).
[0401] Peptides were trapped on a C18 column (75 μm inner diameter×2 cm; nanoViper Acclaim PepMap™ 100, Thermo Scientific) with buffer A (2/98 MeCN/H.sub.2O in 0.1% formic acid) at a flow rate of 3.0 μL/min over 4 min. Separation was performed on a 50 cm×75 μm C18 column (nanoViper Acclaim PepMap™ RSLC, 2 μm, 100 Å, Thermo Scientific) regulated to a temperature of 40° C. with a linear gradient of 3% to 29% buffer B (100% MeCN in 0.1% formic acid) at a flow rate of 300 nL/min over 91 min. MS full scans were performed in the ultrahigh-field Orbitrap mass analyzer in ranges m/z 375-1500 with a resolution of 120 000 at m/z 200. In the data-dependent acquisition (DDA) mode, top 15 intense ions were subjected to Orbitrap for further fragmentation via high energy collision dissociation (HCD) activation and a resolution of 15 000 with the auto gain control (AGC) target set to 100%. We selected ions with charge state from 2+ to 6+ for screening. Precursor ions were isolated with an isolation width of 1.6 m/z unite, normalized collision energy (NCE) was set to 30% and the dynamic exclusion to 40 s. In parallel reaction monitoring (PRM) mode acquisition list (Table 1.) was generated from the peptides obtained from the synthetic aberrant NET1 peptides (TALLPGLPAANPSPR and LFPISPETLHFPVSR, ordered from Genscript at purity >75%) based on the DDA results (data not shown).
TABLE-US-00003 TABLE 1 Peptide Modified Mass Sequence Full Names [m/z] Charge Extracted fragments LFPISPETLHFPVSR 580.6542 3 y4, y5, y6, y10, y10++, y11++ TALLPGLPAANPSPR 737.9225 2 b3, y8, y8++, y10, y11, y11++
[0402] PRM data analysis: all raw files were processed using Skyline (version 13.1.1.193) MacCoss Lab Software, Seattle, Wash.; (https://skyline.ms/project/home/software/Skyline/begin.view) for the generation of the extracted-ion chromatograms and peak integration. To robustly identify peptides in the skyline platform, a mass accuracy of withing 5 ppm was imposed for fragment ions. The targeted peptides were manually checked to ensure that the transitions for multiple fragment ions exhibit the same elution time in the pre-selected retention time window of the synthetic peptide. The data were then processed so that the distribution of relative intensities of multiple transitions associated with the same precursor ion must be correlated with the theoretical distribution in the MS/MS spectral library entry. The assessment of MS/MS matching was performed by Skyline and Proteome Discoverer (version 2.4). It is worth noting that the same retention time and dot product (dotp) values (1) of at least 0.9 were found for all PRM transitions, thereby providing accurate peptide identification.
[0403] For protein identification, the data were searched against the Homo sapiens (UP000005640) UniProt database with the two aberrant sequences of NET1 using SequestHT Proteome Discoverer (version 2.4). Enzyme specificity was set to trypsin and a maximum of two-missed cleavage sites was allowed. Oxidized methionine, Met-loss, Met-loss-Acetyl and N-terminal acetylation were set as variable modifications. Maximum allowed mass deviation was set to 10 ppm for monoisotopic precursor ions and 0.02 Da for MS/MS peaks. The resulting files were further processed using myProMS v3.9.2. FDR calculation used Percolator and was set to 1% at the peptide level for the whole study.
[0404] The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (3) with the dataset identifier PXD023968 corresponding to the X2185VM, X2186VM, X2188VM, X2189VM datasets.
[0405] Single-Cell TCR-Seq Data Processing and Analysis
[0406] TCR-seq data for each sample was processed using Cell Ranger software with the command ‘cellranger vdj’ using the human reference genome GRCh38. Because of dropouts, both TCRα and TCRβ are not always sequenced in a given T cell. Thus, as a T cell can express up to two TCRα chains and one TCRβ chain, it is easy to artificially split true T cell clones into two different clonotypes. To the contrary, incompletely sequenced doublets can mistakenly lead to the creation of artefactual clonotypes. Because, the obtained data sets encompassed very large clonal expansions and the drop-out and the number of cells loaded on the chip was high for patient UM2/3, data sets, the inventors manually curated all the recurrent clonotypes to exclude doublets and merge clonotypes. They merged clonotypes using the same TCRα or TCRβ chains. The inventors excluded from downstream analysis all “cells” made of a non-attributed TCRα or TCRβ chains that would be associated with a TCRα or TCRβ chains belonging to a clonal expansion. TotalSeq features were also used to exclude doublets.
[0407] TCR-Seq
[0408] Reverse transcription of tumor RNA was performed using random hexamers and SuperScript IV according to manufacturer instruction (ThermoFisher). cDNAs were cleaned using Agencourt RNAclean XP kit (Beckman Coulter). A combination of Va and VP specific primers slightly modified from (27) was used in 2 semi-nested PCR steps followed by a barrecoding step. The first PCR reaction was performed separately for alpha and beta TCRs using multiplex Va and VP primer associated with constant TCRα (TRAC) and TCRβ (TRBC) region primers. Each primer was used at 0.2 μM each (95° C. 3 min) and 22 cycles (90° C. 30s, 58° C. 30s, 72° C. 30s). cDNAs were cleaned using Agencourt AMPure XP kit. In the second step, two distinct semi nested PCR multiplex for Va and VP reactions were performed 95° C. 3 min followed by 35 cycles (90° C. 30s, 63° C. 30s, 72° C. 30s). Barcoding and incorporation of the sequencing primers for Paired-end Illumina sequencing was performed with PE1_CS1 forward primer and PE2_barcode_CS2 reverse primer (Fluidigm) at 400 nM using Platinium Taq DNA Polymerase High Fidelity (ThermoFisher). PCR product were sequenced using Miseq V3 PE-300 kit (I lumina)
[0409] Results
[0410] Activation of the immune system by various immunomodulators can eradicate large tumors as well as the disseminated disease. Tumor destruction is most often related to the recognition by T cells of peptides derived from somatically mutated proteins expressed by cancerous cells and presented by major histocompatibility complex (MHC) molecules. Indeed, the clinical response to anti-checkpoint treatments is loosely correlated with the number of somatic mutations present in the tumor suggesting that the neo-epitope load expressed by the tumor is important to generate an efficient immune response (1). However, most of these neo-epitopes correspond to passenger mutations that are different in each tumor and thus are unique to each patient. In the absence of a spontaneous response that could be therapeutically amplified, inducing an immune response to such epitopes requires personalized vaccines which are costly and logistically complicated to set up (2). For these reasons, public (shared between individuals) epitopes deriving from germline encoded antigens that are aberrantly expressed in tumors with limited expression in normal tissues, such as onco-testis antigens, are often used in vaccine strategies (3). However, many of these antigens are also expressed in the thymus, potentially leading to deletion of the high avidity antigen reactive T cells (4).
[0411] An alternative vaccine strategy would be to target neo-epitopes resulting from cancer specific mutations in splicing factors (5) that are mutated in a notable proportion of tumors (6). Indeed, mutations in these factors lead to the presence of aberrant open reading frames specifically in tumor cells. The inclusion of intronic sequences in the mature transcript results in new peptides often with an additional frameshift in the following exon. Since the peptides are germline-encoded, they are present in all tumors bearing the mutated splicing factor. When presented by the patient MHC alleles, the resulting peptides generate neo-epitopes common to all patients bearing a given MHC allele opening the way for generic therapeutic products adapted to common MHC haplotypes. Although proposed for several years (7), the clinical relevance of neo-epitopes resulting from mutated splicing factors in tumors has not been demonstrated in humans so far.
[0412] Uveal melanoma (UM) is a rare disease (˜600 cases/year in France) with a dismal prognosis once metastatic, which occurs in more than 30% of cases and for which no therapy is currently available (8). Contrary to skin melanoma, UMs display very few somatic mutations (16±4.0 per exome, (9)) and are accordingly resistant to anti-checkpoint immunomodulation. Twenty percent of the tumors harbor a mutation in the splicing factor 3b subunit 1 (SF3B1) gene generating over 1000 new splice junctions (10, 11). SF3B1 mutations induce an upstream shift of the splice acceptor sites leading to inclusion of intronic sequences in the mRNA. The resulting additional amino-acids and the frameshift that is often associated potentially generate a large number of public neo-epitopes.
[0413] In this work, the inventors show that among metastatic UM patients, only those whose tumors harbored a mutated SF3B1 displayed memory CD8.sup.+ T cells with specificities for SF3B1.sup.mut-derived neo-epitopes. The corresponding TCRs could also be found in the tumor. SF3B1.sup.mut UM cell lines were recognized and killed by neo-epitope specific T cell clones demonstrating that these neo-epitopes are expressed by tumor cells in a way that can be recognized by CD8.sup.+ T cells.
[0414] Selection of the Patients and Identification of SF3B1.sup.mut Induced Epitopes
[0415] Thirteen HLA-A2 metastatic UM patients (8 SF3B1.sup.mut and 5 SF3B1.sup.wt) and 4 healthy donors were studied. It was first verified that the tumors were correctly classified by resequencing SF3B1 in tumors. Based on the previous work of the inventors (10), RNA-seq of the tumors allowed us to measure the proportion of SF3B1.sup.mut-modified splice junctions as compared to the SF3B1.sup.wt tumors. The pattern of junctions according to SF3B1 status reproduced our previous results (10). They also verified the expression pattern of selected alternative junctions in 3 HLA-A2.sup.+ patient-derived xenografts (PDX): 1 SF3B1.sup.mut and 2 SF3B1.sup.wt PDXs (
[0416] The alternative splice junctions may give rise to proteins, which may however be unstable and difficult to detect using biochemical methods. As a proof of concept, the inventors focused on the NET1 protein, in which an alternative junction is predicted to lead to an alternative transcript encoding a polypeptide generating epitope. An immunoprecipitating antibody for a domain upstream of the alternative coding-frame aberrant-splicing event was available (detailed in Material and Methods) and used to immune-precipitate endogenous NET1 from two UM cell lines (MP41 and Mel202; SF3B1wt and SF3B1mut respectively) as well as two PDXs (PDX-MP41 and PDX-MM267; SF3B1 wt and SF3B1mut respectively). After trypsin digestion, the immunoprecipitated samples were analyzed by targeted mass-spectrometry. As shown by their retention time and MS fingerprints comparatively similar to the synthetic peptides, the two predicted peptides corresponding to the aberrant reading frame were readily detected in SF3B1mut cells (Mel202 and PDX-MM267), but absent in the SF3B1wt cells (MP41 and PDX-MP41), whereas the wildtype NET1 peptides were present in all samples. These findings obtained for NET1 demonstrate that aberrantly spliced transcripts in SF3B1mut cells can be translated into detectable aberrant protein products.
[0417] Frequency and Phenotype of SF3B1.sup.mut-Related HLA-Epitopes Reacting CD8 T Cells.
[0418] In order to detect and characterize a potential immune response against the SF3B1.sup.mut related neo-epitopes, The inventors stained blood CD8.sup.+ T cells from UM patients and healthy controls with tetramers labeled with two different fluorochromes to increase specificity, thereby sensitivity. As controls, they used HLA-A2 tetramers loaded with pp65 from cytomegalovirus (CMV) and with Melan-A, a melanocyte differentiation antigen (
[0419] The frequency of CD8.sup.+ T cells specific for the 39 HLA-A2 restricted SF3B1.sup.mut neo-epitopes varied between <0.0001% to 0.3% in the patients with SF3B1.sup.mut tumor (
[0420] Characterization of T Cells Specific for the SF3B1-Induced A2 Restricted Neo-Epitopes in Three Patients.
[0421] To characterize the SF3B1.sup.mut-induced specific T cells, the inventors isolated A2:37 specific CD8.sup.+ T cells from the blood of patient UM1 to analyze their transcriptome and TCR repertoire by single cell RNA sequencing (scRNA-seq) coupled to VDJ analysis. After quality control and filtering, 3213 A2:37-specific CD8.sup.+ T cells could be divided into 7 expression clusters Cluster #1 (n=355 cells) expressed SELL and LEF1, characteristic of naive CD8.sup.+ T cells and probably corresponds to the 8% naive A2-37 specific T cells found in this patient by flow cytometry (
[0422] Using FAC sorting of oligo-barcoded tetramers followed by 5′ transcriptome and VDJ single cell 10× technology, the inventors analyzed the transcriptome and TCR repertoire of the blood CD8.sup.+ T cells specific for A2:18 in patient UM3 and 4 SF3B1.sup.mut-related specificities (A2:14, :17, :26 and :37) in patient UM2, three of which were strikingly increased in the blood of this patient (
[0423] T Cells Specific for SF3B1.sup.mut Induced Neo-Epitopes are Also Found in the Tumor.
[0424] To determine in patient UM1 whether A2:37 specific T cells were present in the tumor, the inventors amplified all the TCRα and TCRβ chains in UM1 liver metastasis RNA and deep sequenced them (Table 3 below). Eighteen A2:37 specific TCRs found in the blood were also detected in the tumor. Notably, 5 out of 18 (28%) recurrent TCRs in the blood, including the most abundant one #1, were found in the tumor. The 13 TCR singletons found in the tumor belonged to the effector memory clusters. These results indicate that the some of the most expanded T cell clones and singletons from blood are found in the UM liver metastasis. Interestingly, the clonally expanded blood T cells whose TCR was found in the tumor belonged to 6 out of 7 of the transcriptional clusters indicating various differentiation patterns. These results suggest that the effector/memory A2:37 specific T cells found in blood, some of which are highly amplified, may represent an ongoing anti-tumor immune response at the tumor site. In patient UM2, although their clonal size was much smaller than in patient UM1, only TCRs corresponding to A2:26 and A2:37 specificities were found in the tumor. All these TCRs belonged to effector or memory clusters with various transcriptome patterns. Interestingly, in this patient UM2 harboring increased frequency of memory CD8.sup.+ T cells specific for several SF3B1.sup.mut-related neo-epitopes, an unusually large lymphoid infiltrate was observed in the liver metastasis. Thus, some of the expanded clonotypes found in the blood were also observed in the tumor of the two patients harboring increased frequency of SF3B1.sup.mut neo-epitope specific CD8.sup.+ T cells suggesting an active immune response towards SF3B1.sup.mut-related neo-epitopes at the tumor site.
TABLE-US-00004 TABLE 3 HLA re- stricted Peptide TRAV TRAJ CDR3 TCR alpha AA TRBV TRBJ CDR3 TCR beta AA A2:14 TRAV12-2 TRAJ26 CAFDNYGQNFVF TRBV7-8 TRBJ2- CASSPMDRDEQYF 7 A2:14 TRAV1-1 TRAJ34 CAVRSSYNTDKLIF TRBV4-3 TRBJ1- CASSQESVGSNQPQHF 5 A2:14 TRAV27 TRAJ24 CAGGMTTDSWGKL TRBV7-9 TRBJ1- CASSPGTGVTKDGYTF QF 2 A2:14 TRAV24 TRAJ37 CAFDRGSSNAGKLIF TRBV2 TRBJ2- CASEGVHEQFF 1 A2:17 TRAV35 TRAJ26 CAGLPYGQNFVF TRBV18 TRBJ1- CASSPVGWGNTIYF 3 A2:17 TRAV12-1 TRAJ28 CVVNIPLYSGAGSYQ TRBV19 TRBJ2- CASSYKAEPIYNEQFF LTF 1 A2:17 TRAV29 TRAJ47 CAAREYGNKLVF TRBV7-6 TRBJ2- CASSQLGETGELFF 2 A2:17 TRAV26-1 TRAJ42 CIVGGTALENYGGS TRBV29-1 TRBJ1- CGGQGYHTEAFF QGNLIF 1 A2:17 TRAV14 TRAJ42 CAMREGTLRGSQG CASSLEAPGVISGANVLT NLIF F A2:17 TRAV14 TRAJ3 CAMSLYSSASKIIF TRBV7-9 TRBJ2- CASSLDLRQNEQFF 1 A2:17 TRAV12-3 TRAJ12 CAMSGVDSSYKLIF A2:17 TRAV13-1 TRAJ21 CAASRYGNNFNKFY TRBV29-1 TRBJ1- CSVDWYGGLTNTEAFF F 1 A2:17 TRAV29 TRAJ49 CAASAPGNQFYF TRBV9 TRBJ2- CASSAEGSWGQETQYF 5 A2:17 TRAV29 TRAJ29 CAASTSYSGNTPLVF TRBV14 TRBJ1- CASSQGGGGNQPQHF 5 A2:17 TRAV21 TRAJ20 CAVRGSNDYKLSF TRBV4-3 TRBJ2- CASSFLAGGPNEQYF 7 A2:18 TRAV17 TRAJ53 CATDKGSGGSNYKL TRBV14 TRBJ2- CASSTMGDYYEQYF TF 7 A2:18 TRAV24 TRAJ20 CAFWSAYKLSF A2:18 TRAV25 TRAJ26 CAGRDNYGQNFVF TRBV7-8 TRBJ1- CASSPWGAGNQPQHF 5 A2:26 TRAV8-2 TRAJ49 CAVRNTGNQFYF TRBV15 TRBJ1- CAINSGFGSPLHF 6 A2:26 TRAV17 TRAJ43 CATDDDMRF A2:26 TRAV13 TRAJ26 CAAPGNYGQNFVF TRBV20-1 TRBJ2- CSASQIYEQYF 7 A2:26 TRAV35 TRAJ30 CAGIVRDDKIIF TRBV7-7 TRBJ2- CASSFSLQYEQYF 7 A2:26 TRAV22 TRAJ30 CAALGGDKIIF TRBV7-6 TRBJ1- CASSLWAGNTIYF 3 A2:37 TRAV14 TRAJ5 CAMIEWDTGRRALI TRBV29-1 TRBJ2- CSVEDLGAGVSNEQFF F 1 A2:37 TRAV38-1 TRAJ31 CAFFEYDNNARLMF TRBV3-1 TRBJ2- CASSYEDHEQYF 7 A2:37 TRAV38 TRAJ57 CAFLQGGSEKLVF TRBV28 TRBJ2- CASSLFGLAGVEETQYF 5 A2:37 TRAV38 TRAJ28 CAFMKHEDSGAGSY TRBV3-1 TRBJ2- CASSQAISDREVWDQET QLTF 5 QYF A2:37 TRAV19 TRAJ12 CALTEVDSSYKLIF TRBV27 TRBJ2- CASSLAGGSYEQYF 7 A2:37 TRAV17 TRAJ5 CAPSLMDTGRRALT TRBV12-3 TRBJ2- CASSFGGDGYNEQFF F 1 A2:37 TRAV9-2 TRAJ29 CASGLPDTPLVF TRBV13 TRBJ1- CASSLRDRGNQPQHF 5 A2:37 TRAV12- TRAJ9 CAMSAPDTGGFKTIF 3 A2:37 TRAV5 TRAJ45 CAESEGADGLTF TRBV20-1 TRBJ1- CSASEGYTF 2 A2:37 TRAV8-4 TRAJ20 CAVRNDYKLSF TRBV6-3 TRBJ2- CASSYPTSGYNEQFF 1 A2:37 TRAV21 TRAJ24 CAVITTDSWGKLQF TRBV13 TRBJ2- CASSSGLAGASNEQFF 1 A2:37 TRAV21 TRAJ49 CAVLGNQFYF TRBV7-3 TRBJ1- CASSLVAGTDGYTF 2 A2:37 TRAV13-2 TRAJ24 CADPTDSWGKLQF TRBV14 TRBJ2- CASSLIGLAEQFF 1 A2:37 TRAV12-1 TRAJ20 CVVIGPFNDYKLSF TRBV29-1 TRBJ1- CSVEKGNNYGYTF 2 A2:37 TRAV38-1 TRAJ29 CAFMKHEDTGGNT TRBV7-6 TRBJ2- CASSLSQGIYYEQYF PLVF 7 A2:37 TRAV12-2 TRAJ56 CAVKGAGANSKLTF TRBV13 TRBJ2- CASRSDRVTEHTQYF 3 A2:37 TRAV38- TRAJ49 CAYYPWNTGNQFYF TRBV10-1 TRBJ2- CASSDGSYEQYF 2DV8 7 A2:37 TRAV21 TRAJ26 CAVSDYGQNFVF TRBV10-2 TRBJ1- CASSDSGTEAFF 1 A2:37 TRAV12-1 TRAJ53 CVGGGGSNYKLTF TRBV27 TRBJ2- CASSLTPPGSYNEQFF 1 A2:37 TRAV38-1 TRAJ34 CAFMKPDSGTYKYIF TRBV7-6 TRBJ2- CASSRDPQPDTQYF 3 A2:37 TRAV21 TRAJ49 CAVLGNQFYF TRBV7-3 TRBJ1- CASSLVAGTDGYTF 2 A2:37 TRAV38- TRAJ48 CAYRSPTALNEKLTF TRBV28 TRBJ2- CASSLWTSGYETQYF 2DV8 5 A2:37 TRAV3 TRAJ21 CAVRAFGYNFNKFYF TRBV28 TRBJ2- CASSLASGNYEQYF 7 A2:37 TRAV12-2 TRAJ30 CAVSVRDDKIIF TRBV5-6 TRBJ2- CASSFDRAEYEQYF 7 A2:37 TRAV41 TRAJ54 CAPQGAQKLVF TRBV27 TRBJ2- CASSLSAGAFSDTQYF 3 A2:37 TRAV38- TRAJ43 CAYMNNNNDMRF TRBV28 TRBJ2- CASSLPTQGGLIEQFF 2DV8 1 A2:37 TRAV19 TRAJ31 CALSEVDRLMF TRBV28 TRBJ2- CASSLTGTDTQYF 3 A2:37 TRAV13-2 TRAJ15 CAEMEGTALIF TRBV4-1 TRBJ1- CASSQGAAEAFF 1 A2:37 TRAV9-2 TRAJ48 CALSDPDMEKLTF TRBV5-6 TRBJ2- CASSFGTPYEQYF 7 A2:37 TRAV8-2 TRAJ34 CVVSFQGTDKLIF TRBV20-1 TRBJ2- CSATGEAWTGWNEQFF 1 A2:37 TRAV13-1 TRAJ30 CAAERDDKIIF TRBV12-4 TRBJ2- CASSMTSGSPYNEQFF 1 A2:37 TRAV3 TRAJ28 CAVRDSGAGSYQLT TRBV12-4 TRBJ1- CATQDSLFMNTEAFF F 1 A2:37 TRAV38- TRAJ33 CAYSNYQLIW TRBV28 TRBJ2- CASSFVTSYEQYF 2DV8 7 A2:37 TRAV21 TRAJ37 CAVESGNTGKLIF TRBV19 TRBJ2- CASSISSTGELFF 2 A2:37 TRAV12-2 TRAJ11 CAGYPGYSTLTF TRBV7-9 TRBJ1- CASSLGQYNSPLHF 6 A2:37 TRAV8-4 TRAJ20 CAVRINYKLSF TRBV6-2 TRBJ2- CASSRVTSGHNEQFF 1 A2:37 TRAV3 TRAJ30 CAVRDGHRDDKIIF TRBV7-9 TRBJ2- CASSLGVRAQKTQYF 5 A2:37 TRAV38- TRAJ9 CAYNTGGFKTIF TRBV28 TRBJ2- CATGPRGSSYNEQFF 2/DV8 1 A2:37 TRAV5 TRAJ42 CAESQGNLIF TRBV14 TRBJ2- CASSQSPGGEQFF 1 A2:37 TRAV38- TRAJ49 CAYRSPVSGNQFYF TRBV28 TRBJ1- CASTPPRGPQHF 2/DV8 5 A2:37 TRAV27 TRAJ44 CAGGSGTASKLTF TRBV27 TRBJ2- CASSVAGSYGDTQYF 3 A2:37 TRAV27 TRAJ54 CAGAGEAGAQKLVF TRBV27 TRBJ2- CASSPTGLVYEQFF 1 A2:37 TRAV17 TRAJ54 CATDRDQGAQKLVF TRBV4-2 TRBJ2- CASSQEVGIWQTQYF 5 A2:37 TRAV8-6 TRAJ33 CTSNYQLIW TRBV11-2 TRBJ1- CASSLFRETEAFF 1 A2:37 TRAV12-2 TRAJ49 CAVSGGNQFYF TRBV5-4 TRBJ1- CASSLTGETEKLFF 4 A2:37 TRAV2 TRAJ33 CAVENYQLIW TRBV18 TRBJ2- CASSQGQEKETQYF 5 A2:37 TRAV14/ TRAJ42 CAMREGGSQGNLIF TRBV19 TRBJ1- CASRFDGSNQPQHF DV4 5 A2:37 TRAV12-3 TRAJ13 CAMRGYQKVTF TRBV3-1 TRBJ2- CASSHELTRADTQYF 3 A2:37 TRAV1-2 TRAJ28 CAVRDSGAGSYQLT TRBV5-6 TRBJ2- CASSAPVWEGTGELFF F 2 A2:37 TRAV5 TRAJ28 CAEENSGAGSYQLTF TRBV5-5 TRBJ1- CASSLGDSTEAFF 1 A2:37 TRAV5 TRAJ13 CAESMSYQKVTF TRBV5-1 TRBJ2- CASSLEASTDTQYF 3 A2:37 TRAV26-2 TRAJ43 CILDNNNDMRF TRBV7-6 TRBJ1- CASSLAPGTTNEKLFF 4 A2:37 TRAV8-1 TRAJ33 CAVNAVDSNYQLIW TRBV28 TRBJ1- CASSGFGKLFF 4 A2:37 TRAV19 TRAJ40 CALSEANEGTYKYIF TRBV27 TRBJ2- CASSNSIGSADTDTQYF 3 A2:37 TRAV29 TRAJ47 CAASDGGNKLVF TRBV12-4 TRBJ2- CASMGGLAGGYADTQY 3 F A2:37 TRAV8-6 TRAJ43 CAVSPYNNNDMRF TRBV12-3 TRBJ2- CASRPLAAQETQYF 5 A2:37 TRAV5 TRAJ12 CAEYAMDSSYKLIF TRBV2 TRBJ1- CASSEGEGFYGYTF 4 A2:37 TRAV38- TRAJ30 CAYRTPLRDDKIIF TRBV28 TRBJ2- CASSDTAGSSYNEQFF 2/DV8 1 A2:37 TRAV41 TRAJ56 CAADTNYYTGANSK TRBV27 TRBJ2- CASSFGRDLNTGELFF LTF 2 A2:37 TRAV21 TRAJ48 CAVKGFFGNEKLTF A2:37 TRAV1-2 TRAJ31 CAVRDNNARLMF TRBV10-3 TRBJ1- CAIDPTGSLNQPQHF 5 A2:37 TRAV8-6 TRAJ8 CAVSDPDTGFQKLV TRBV14 TRBJ2- CASSRQQGVEQYV F 7 A2:37 TRAV22 TRAJ43 CAVDITWNDMRF TRBV28 TRBJ2- CATQNNEQFF 1 A2:37 TRAV22 TRAJ57 CAVPLRADLTKLVF TRBV27 TRBJ2- CASSLEVGLAPNEQFF 1 A2:37 TRAV9-2 TRAJ52 CALSDRDGGTSYGKL TRBV6-5 TRBJ2- CASSYSPGYEQYF TF 7 A2:37 TRAV19 TRAJ40 CALSEATSGTYKYIF TRBV27 TRBJ1- CASSLITGDTEAFF 1 A2:47 TRAV14 TRAJ48 CAMRAFGNEKLTF TRBV7-9 TRBJ2- CASSPRDEQFF 1
[0425] SF3B1.sup.mut-Induced Neo-Epitopes on Tumor Cells are Recognized by Specific CD8 T Cells.
[0426] To determine whether the SF3B1-induced neo-epitopes were presented on the surface of the tumor cells themselves, the inventors generated tools to analyze the direct interaction between the neo-epitope specific CD8 T cells and tumor cells. The available SF2B1.sup.mut UM cell line (Mel-202) being HLA-A2.sup.neg, it was transduced with an HLA-A2 expression vector. They also generated an isogenic negative control by inserting a DEGRON sequence in the SF3B1-mutated allele using Crispr-Cas9 technology, fully normalizing the splicing pattern (15). The resulting SF3B1.sup.wt cell line was also transfected with HLA-A2. In parallel, we generated T cell clones for 4 SF3B1.sup.mut neo-epitopes (A2:14, :18, :26 and:37) by direct FACS assisted single cell cloning of tetramer.sup.+ CD8.sup.+ T cells from both healthy donors (HD) and UM patients, followed by expansion and verification of the specificity using the relevant tetramers. 20 clones were obtained. The T cell clone functionality was verified by stimulating them with HLA-A2 transfected K562 loaded with the relevant peptide followed by assessment of interferon gamma (IFN-γ, granzyme B (GzmB) and IL-6 release. For each specificity, the clones with the highest sensitivity (activated by the lowest peptide concentration) were selected for the following functional assays.
[0427] SF3B1.sup.mut and SF3B1.sup.wt HLA-A2.sup.+ or HLA-A2.sup.− Mel-202 UM cell lines were used to stimulate the T cell clones. An A2:18 specific T cell clone from an HD was specifically activated by SF3B1.sup.mut and not by SF3B1.sup.wt Mel-202 UM cells as seen by CD25 upregulation (
[0428] Importantly, a T cell clone specific for neo-epitope A2:18 killed SF3B1.sup.mut HLA-A2.sup.+ Mel-202 UM cells and not the SF3B1.sup.wt isogenic cells, while an irrelevant A2-CMV clone did not (
[0429] Concluding Remarks
[0430] In this work, the inventors show that mutations in the splicing factor SF3B1 in UM tumors generate MHC class I restricted tumor neo-epitopes that are detected by patients' CD8 T cells. Expanded T cells specific for these antigens are enriched at the tumor site. These neo-epitopes are expressed by tumor cells and can be directly recognized by the specific CD8 T cells able to kill the SF3B1.sup.mut UM cells.
[0431] To their knowledge, this work is the first experimental demonstration of an immune response against public neo-epitopes generated by an abnormal splicing process, an hypothesis that was suggested some time ago (5, 16). Here, they identified and demonstrated a relevant immune response towards MHC class I restricted epitopes. It is probable that MHC-II restricted epitopes are also generated and presented by antigen presenting cells to induce neo-epitope specific CD4.sup.+ T cells that may correspond to the chronically activated CD4.sup.+ T cells they previously described in cancer patients (17).
[0432] Since the splicing factor SF3B1 is only mutated in the tumor cells and modifies the splicing pattern in over 1000 junctions, the neo epitopes are tumor-specific and numerous. Being germline encoded, these neo-epitopes are shared across most patients according to their particular HLA haplotype. HLA-A2 is expressed by ˜45% of the individuals in Europe. By characterizing SF3B1.sup.mut-related epitopes presented by other prevalent HLA alleles, it can be envisioned that a limited (15-20) number of public neo-epitopes would enable treatment of almost all patients. Efficient vaccination using long peptides, DNA- or RNA-based vaccines would be relatively easy to manufacture (2). Neo-epitopes are also attractive targets for adoptive transfer therapies relying either on T cells transduced with specific TCRs or on soluble bi-specific reagents redirecting the activity of effector T cells towards neo-epitopes expressing tumor cells with antibodies or affinity matured TCR, similarly to what is proposed for the Melan-A HLA-A2 epitope (18). Notably, SF3B1 mutations are not restricted to uveal melanoma, but also found in a wide range of malignancies (7), including hemopathies (19, 20), carcinomas and other melanomas(21), in which a significant proportion of abnormal junctions are shared with UM (11), further extending the potential therapeutic importance of our finding. [0433] 1. N. A. Rizvi et al., Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 348, 124-128 (2015). [0434] 2. U. Sahin, O. Tureci, Personalized vaccines for cancer immunotherapy. Science 359, 1355-1360 (2018). [0435] 3. P. G. 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Gigascience 7, (2018).
SEQUENCE LISTING
[0465]
TABLE-US-00005 SEQ ID NO: 1-1058 Neoantigenic peptides that bind with high stringency (rank < 0; 5% see methods) on at least one HLA allele and wherein frequency in a human population (n > 5000) is at least of 1% SEQ ID NO: 1059-1148 CDR3 TCR alpha AA SEQ ID NO: 1149-1233 CDR3 TCR beta AA