Extensive tumour inflammation, which is reflected by high levels of infiltrating T cells and interferon-γ (IFNγ) signalling, improves the response of patients with melanoma to checkpoint immunotherapy1,2. Many tumours, however, escape by activating cellular pathways that lead to immunosuppression. One such mechanism is the production of tryptophan metabolites along the kynurenine pathway by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1), which is induced by IFNγ3,4,5. However, clinical trials using inhibition of IDO1 in combination with blockade of the PD1 pathway in patients with melanoma did not improve the efficacy of treatment compared to PD1 pathway blockade alone6,7, pointing to an incomplete understanding of the role of IDO1 and the consequent degradation of tryptophan in mRNA translation and cancer progression. Here we used ribosome profiling in melanoma cells to investigate the effects of prolonged IFNγ treatment on mRNA translation. Notably, we observed accumulations of ribosomes downstream of tryptophan codons, along with their expected stalling at the tryptophan codon. This suggested that ribosomes bypass tryptophan codons in the absence of tryptophan. A detailed examination of these tryptophan-associated accumulations of ribosomes—which we term ‘W-bumps’—showed that they were characterized by ribosomal frameshifting events. Consistently, reporter assays combined with proteomic and immunopeptidomic analyses demonstrated the induction of ribosomal frameshifting, and the generation and presentation of aberrant trans-frame peptides at the cell surface after treatment with IFNγ. Priming of naive T cells from healthy donors with aberrant peptides induced peptide-specific T cells. Together, our results suggest that IDO1-mediated depletion of tryptophan, which is induced by IFNγ, has a role in the immune recognition of melanoma cells by contributing to diversification of the peptidome landscape.
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Data have been deposited in the Gene Expression Omnibus (GEO) with accession code GSE142822. The genomic data relevant to the MD55A3 cells are found in BioProject with accession code PRJNA316754 (sample ID 1M1). Proteomics and peptidomics data have been deposited in the PRIDE repository78 with accession code PXD020224. The codes used in the study are available on GitHub (https://github.com/apataskar/bump_finder_example2 and https://github.com/apataskar/accessory_scripts_manuscript).
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R.A. is supported by the Dutch Cancer Society (KWF projects 10315, 11037 and 11574), the European Research Council (ERC–PoC 665317 and ERC-AdG 832844) and the Dutch science organization (NWO-TOP 91216002).Y.S. is supported by the Israel Science Foundation grant no. 696/17, the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 770854), MRA (622106), Israel Science Foundation (696/17), Rising Tide Foundation, Henry Chanoch Krenter Institute for Biomedical Imaging and Genomics, Estate of Alice Schwarz-Gardos, Estate of John Hunter, Knell Family and the Hamburger Family. A.P. is supported by a long-term EMBO fellowship grant (EMBO ALTF 796-2018). O.B.B. and M. Alterlaar are supported by the Dutch NWO X-omics Initiative. J.O. and M.L. are supported by the South-Eastern Regional Health Authority Norway, the Research Council of Norway, the Norwegian Cancer Society, Stiftelsen Kristian Gerhard Jebsen, the University of Oslo and Oslo University Hospital. We thank M. Delic-Sarac, S. Meyer and T. J. Gjerdingen for HLA typing and processing of blood from in-house healthy donors; P. Kvistborg for providing selected tetramers; and S. Reich-Zeliger, A. Nachshon, L. Eisenbach, A. Navon, S. Pinto, A. Peri, S. Cohen, A. Admon, A. Kacen and all members of the Agami laboratory for discussions.
The authors declare no competing interests.
Peer review information Nature thanks Nahum Sonenberg, Petra Van Damme, Jonathan Yewdell and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Diricore analysis characterizes ribosome occupancy changes after IFNγ and tryptophan-depletion treatments of melanoma cells.
a, Western blot analysis for IDO1 expression in control and IFNγ-treated conditions in three different melanoma cell lines as indicated (n = 3). b, Tryptophan (left) and kynurenine (right) levels as determined by mass spectrometry of the indicated melanoma cell lines in control conditions or 48h after the start of IFNγ treatment. Data represent averages of three independent experiments ± s.d. c, Schematic depicting the principle behind diricore analysis: E, P and A-site occupancy of the ribosome can be mapped on a typical RPF at 9th, 12th and 15th positions, respectively. This allows a position-specific sub-sequence analysis to be performed (bottom left) to probe for the codon enriched differentially between two conditions at E, P or A sites (presented as bar-plots). In addition, diricore analysis depicts 5′-RPF densities across a codon of interest (bottom right, presented as line-plots). d, Metagene density profiles depicting global shifts of RPFs to the start of the coding sequence upon IFNγ treatment (red, yellow) as compared to control (grey). The y axis is intra-gene normalized RPF density. Ribosome profiling data of two independent biological replicates for MD55A3 (top) and 108T (bottom) are represented. e, Diricore analysis line plots depicting differential ribosome occupancy (5′-RPF) at −30 to +60 codons in MD55A3 (left) and 108T (right) cells. Plots depict 5′-RPF densities after the start ATG codon (top, in green), tryptophan codon (middle, in red) and cysteine codon (lower, in grey). The y axis is the ratio between number of reads in IFNγ versus control conditions. f, Diricore analysis bar-plots depicting differential codon usage (at position 15 of the RPFs) in IFNγ versus the control condition for MD55A3 (top) and 108T cells (bottom). Data represent the average of two independent biological replicates. g, Diricore line plots depicting cumulative signal of RPFs across the coding region normalized into percentiles for ATF4, CDC6 and ATP5G1 in 12T control (grey tones) and IFNγ-treated cells (yellow, red). W-bumps (greyed areas) indicate an increased number of reads downstream of the tryptophan codons (dashed lines). h, Tryptophan levels as measured by mass spectrometry from 12T cells subjected to the indicated treatments. Bars represent the average of three independent experiments ± s.d. i, UCSC tracks representing IDO1 mRNA reads in MD55A3 cells in the indicated conditions as a measure for the induction of transcription of this gene. j, Metagene RPF density profiles for control (black), IFNγ (red), IDOi (grey) and IFNγ + IDOi (green)-treated 12T cells. k, Diricore analysis bar plots depicting differential codon usage (at position 15 of the RPFs) in IFNγ- versus control-treated 12T cells. The graph represents the average of two independent biological replicates. This experiment is the control of Fig. 1f. l, Tryptophan levels as measured by mass spectrometry in MD55A3 cells following 48-h growth in control or tryptophan-depleted medium. Values represent the average of three independent replicates ± s.d. m, Metagene density profiles for 12T control (dark grey) and tryptophan depletion cells (red). The lines represent the average of two independent biological replicates. n, Diricore analysis line plots depicting differential (IFNγ/control) ribosome occupancy (5′-RPF) at −30 to +30 codons of the indicated amino acid in control versus tryptophan-depleted 12T cells. o, Diricore analysis bar plots depicting differential codon usage (at position 15 of the RPFs) in control and tryptophan-depleted 12T cells. All diricore plots represent the average of at least two biological replicates.
a, Computational approach for unbiased detection of bumps in comparative ribosome profiling experiments. The algorithm scans transcripts in 100 windows of equal length for peaks in ribosome occupancy and filters for differential peaks in treated versus untreated samples. b, c, Density of codons per amino acid in the region of 60 codons upstream and downstream of the peak of bumps identified with bump-finder in ribosome profiling data of 12T cells. Data shown iare derived from two independent biological replicates treated with either IFNγ (b) or control (c). d, Ratio between upstream and downstream reads 30 codons from the peak of bumps identified in control conditions when treated with IFNγ in MD55A3 (top) and 108T cells (bottom). e, RPF density in control- (grey line) and IFNγ- (red line) treated conditions in MD55A3 and 108T cells. The area marked in grey indicates the W-bump region. f, Densities (top lines) and heat maps (bottom) of ribosomal P-sites 100 nucleotides surrounding every tryptophan codon in control and IFNγ conditions in 12T, MD55A3 and 108T cells. g, Classification of all transcripts containing tryptophan codons, one group associated with W-bumps (‘Bumps’), and another group that is not associated with bumps (‘No bumps’). Graphs represent RPF density in the region of 300 nucleotides surrounding the tryptophan codon. Bumps indicated in grey shading. h, Bar plot depicting the enrichment of presence of two tryptophan codons within a region of eight codons in the bumps group over the no bumps group. W indicates a codon for tryptophan, whereas X indicates all remaining amino acids. i, Heat map depicting frequencies of codons for each amino-acid at every position 25 codons upstream and downstream, with respect to tryptophan. j, Line plots depicting RPF density at tryptophan stratified by distance between two tryptophan residues (black). In each graph the control (the occurrence of a single tryptophan) is presented in red.
a, Volcano plot depicting overall changes in the proteome upon IFNγ treatment as observed by analysis of quantitative mass-spectrometry data. x axis: log-transformed fold change between IFNγ versus control conditions in MD55A3 cells; y axis: corresponding log-transformed adjusted P value calculated from three independent biological replicates. Highlighted in blue are proteins that are significantly differentially expressed. Both IFNγ-mediated induction of IDO1 and WARS and the immunoproteasome components are indicated. b, Left, box plots depicting log-transformed fold change in the levels of protein (red; average of three replicates) and mRNA (brown; average of two replicates) in IFNγ-versus control-treated cells. Proteins were grouped according to the number of asparagine (N), tyrosine (Y) or phenylalanine (F) residues in the protein sequence. Boxes depict first, second and third quartiles; whiskers depict the range excluding the outliers. Test: Wilcoxon test (two-tailed); NS, not significant, *P < 0.05. For asparagine box plots the actual P values are 0.7, 0.8, 0.055 for protein quantification (left) and 0.8,0.2, 0.013 for RNA quantifications (right) in the order shown. Middle, same as left but for number of tyrosine (Y) residues. Actual P values are 0.7, 0.86 and 0.02 for protein quantification (left) and 0.98, 0.13 and 0.14 for RNA quantifications (right) in the order shown. Right, same as middle but for number of phenylalanine (F) residues. Actual P values are 0.7, 0.97 and 0.23 for protein quantification (left) and 0.3, 0.015 and 0.0038 for RNA quantifications (right) in the order shown. c, Western blot analysis of ubiquitinylated proteins in total cell lysates of MD55A3 cells mock- or IFNγ-treated, which were additionally incubated minus or plus MG132 (n = 1). d, A panel showing proteins with increased abundance in total cell lysates of MD55A3 cells treated with MG132 versus controls. Log2-transformed fold changes were calculated on data of three independent replicates. e, Box plots depicting log fold change in protein levels (average of three replicates) in IFNγ-treated versus control conditions in MD55A3 cells treated with proteasome inhibitor, for proteins stratified for different numbers of aspargine (N), tyrosine (Y) and phenylalanine (F) residues in their sequence. Boxes depict first, second and third quartiles; whiskers depict the range excluding the outliers. Test: Wilcoxon test (two-tailed); NS, not significant and *P < 0.05. Actual P values are 0.34, 0.44, 0.77 and 0.96, 0.84, 0.024 and 0.29, 0.84, 0.34 in the order shown. f, Box plots depicting protein length (number of amino acids) for stratified group of genes with increasing number of tryptophan (left) and asparagine (middle), with their ratios (right). g, Density of RPFs (average of two replicates) 300 codons across individual tryptophan codons (black line), two tryptophans that are present within a distance of 8 codons (green line) and two tryptophans that are present at a distance greater than 8 codons (red line). h, Box plot depicting bump scores (average of two replicates) for instances of two tryptophans separated by fewer than 8 codons (green) and more than 8 codons (red). Bump scores are calculated in MD55A3 cells. Boxes depict first, second and third quartiles; whiskers depict the range excluding the outliers. Test: Wilcoxon Ttest (two-tailed); ***P < 0.0005. Actual P value is < 2.2 ×10−16. i, Box plot depicting protein level changes (log-transformed fold change, average of three replicates) between IFNγ and control conditions. The graph represents genes that have two tryptophan codons within a distance of 8 codons (green) or genes having a distance of more than 8 codons between two tryptophans (red). Test: Wilcoxon test (two-tailed); ***P < 0.0005. Actual P value is < 2 ×10−16 j, Same as i, but for asparagine (N), in MD55A3 cells. Test: Wilcoxon test (two-tailed); NS, not significant. Actual P value is 0.83.
Extended Data Fig. 4 Reporter assays for the detection of tryptophan-associated out-of-frame events.
a, A hypothetical model suggesting a possible mechanism causative for W-bumps. In the normal scenario, ribosomes do not encounter problems when translating a tryptophan and progress translation at regular speed (top). Tryptophan shortage, on the other hand, can lead to stalling on the tryptophan codon (bottom left), or could in theory induce frameshifting events, leading to aberrant peptide production (bottom right). As the secondary structure of growing polypeptide chains is attained in the lower tunnel of the ribosome, the loss of an α-helical secondary structure in this tunnel could hamper ribosomal progression. b, Box plot depicting bump-score (from two replicates) in MD55A3 cells from the group of selected peptides with ordered out-of-frame peptides (‘Selected’ from Fig. 3b) and every tryptophan in the proteome (‘All’ from Fig. 3b). Boxes depict first, second and third quartiles; whiskers depict the range excluding the outliers. Test: two-sample t-test; *P = 0.056. c, Schematic representation of the final protein sequences that would form due to frameshifting events. The in-frame construct (top) contains a His tag and would end up in the pull-down (PD) fraction. Whenever a frameshift occurs at the position of the tryptophan in ATF4, this protein would lose its His tag, and consequently would end up in the supernatant fraction (S). The +1 and +2 out-of-frame constructs (bottom) do not contain a His tag, whereby the resulting proteins always end up in the supernatant fraction (S) in a His-tag pull-down assay. When frameshifting events take place, however, the His tag is incorporated into the peptide, whereby the resulting protein ends up in the pull-down fraction (PD). d, Western blot analysis of a sequential V5-tag immunoprecipitation on the supernatant samples of the Frame reporter expressing cells from Fig. 3e (n = 1). The image indicates the presence of V5-tag-containing peptides that do not contain a His tag generated from the in-frame reporter. e, Tryptophan levels in MD55A3 cells expressing the V5-ATF4-His reporter constructs that were used in Fig. 3e and in d. Tryptophan levels were analysed by mass spectrometry after 48 h of treatment. Bars represent the average of three independent replicates ± s.d. f, Tryptophan levels in MD55A3 cells expressing the V5-ATF4-His reporter constructs that were used in h. Tryptophan levels were analysed by mass spectrometry after 24 and 48 h of treatment in triplicate. g, Western blot analysis showing V5-tagged peptides in pull-down samples of MD55A3 reporter cells that were mock-, IFNγ- or IFNγ + IDOi-treated (n = 2). h, Western blot analysis of V5-tagged proteins in pull-down samples of MD55A3 reporter cells that were either mock-treated or cultured in tryptophan-depleted medium (n = 1). i, Western blot analyses showing pull-down assays followed by V5 staining on western blot of MD55A3 cells expressing the original reporter constructs as depicted in Fig. 3d (Wt), or MD55A3 cells expressing the same reporters where the tryptophan codon was mutated to a codon for tyrosine (Y mut, n = 1). j, Amino acid levels as determined by mass spectrometry from lysates of Tyr-depleted cells (48 h) versus control cells. Bars represent the average of three independent replicates ± s.d. k, Western blot analysis showing V5-tagged peptides in pull-down samples of MD55A3 reporter cells that were mock-treated or depleted of tyrosine for 48 h (n = 1). l, Flow cytometry analyses showing the histograms obtained of MD55A3 cells expressing the V5-ATF4-tGFP reporters in all 3 frames in mock- and IFNγ-treated conditions. Plots are a representative graph out of a triplicate biological experiment. m, Flow cytometry analyses showing the quantification of histograms obtained in l. Bars represent the average of three independent replicates ± s.d., *P values in order from left to right: 4.0 × 10−6 and 9.5 × 10−4 as determined by a two-sided t-test. n, Anti-V5-tag and anti-tGFP western blot analysis of whole cell lysates from MD55A3 cells expressing the indicated reporters, which were subjected to mock or IFNγ treatments. In each blot the position of the full-length in-frame protein and the shorter out-of-frame protein are marked by the arrowheads (n = 2).o, Western blot analyses with anti-V5 antibody of His-tag pull-down samples of 888-Mel and D10 cells expressing the in-frame and +1 reporters (n = 2). The cells were either grown in isolation (−), or co-cultured with MART-1 specific T cells for 16 h (+) before the pull-down was performed. p, Western blot analysis showing IDO1 upregulation in 888-Mel and D10 cells in control and T cell co-culture conditions (n = 2). The same cells were used for pull-down experiments in Fig. 3m. q, His-tag pull-down was executed on the lysates of mock and IFNγ-treated 888-Mel and D10 cells expressing the in-frame and +1 reporters (n = 2). Both supernatant (S) and His-tag pull-down samples (PD) of these cells were stained with V5 antibodies. r, The lysates of cells used in q were used for a western blot analysis to show the level of IDO1 induction (n = 1). s, Tryptophan levels as determined by mass spectrometry analysis of 888-Mel and D10 lysates in mock, IFNγ-treated and tryptophan-depleted conditions. Bars represent the average of three independent replicates ± s.d., except for the first bar, which is an average of two independent replicates. t, Western blot analyses with anti-V5 antibody of His-tag pull-down samples of 888-Mel and D10 that were mock-treated (+), or grown in tryptophan-less medium for 48 h (−) before the pull-down was performed (n = 2).
Extended Data Fig. 5 Proteomics analysis of 2D-LC–MS/MS data reveals the induction of endogenous aberrant peptides after IFNγ treatment of MD55A3 melanoma cells.
a, PCA plot illustrating the clustering of 2D-LC-MS/MS data from MD55A3 cells that were treated with IFNγ for 48 h as compared to mock. Both conditions were treated with MG-132 for the last 4 h. b, Gene set enrichment analysis (GSEA)-based depiction of the proteomics data showing the induction of the IFN response genes following IFNγ treatment of MD55A3 cells. c, Schematic representation of the in silico generation of +1 and −1 frameshifted protein database (Methods). d, Bar plot depicting number of hits for the detected aberrant (frameshifted) polypeptides in the Ensemble translations database of coding and non-coding genes. Only the aberrant peptides without any matches (n = 0) were retained as true hits (red bar). e, Heat map showing frameshifted peptides identified in the full proteome of IFN-treated MD55A3 cells along with sequence information. f, Line plot depicting log-scaled fold change in proteomic intensity values of IFNγ- versus mock-treated MD55A3 cells. g, Same as f, but for LFQ normalized intensity values of frameshifted peptides hits along with reverse peptide hits. h, Same as f, but only for reverse peptide hits. i, Same as f, but only for frameshifted peptide hits. j, Gene set enrichment analysis (GSEA)-based depiction of the proteomics data showing the induction of the HLA genes following IFNγ treatment of MD55A3 cells. k, GO term analysis on the differentially expressed proteins detected in j. l, Anti-V5-tag and anti-tGFP western blot analysis of whole cell lysates from A375 cells expressing the indicated reporters, which were subjected to mock treatment or tryptophan depletion (n = 2). In each blot the position of the full-length in-frame protein and the shorter out-of-frame protein are marked by the arrowheads. m, FACS plots representing the signal for H-2Kb-bound SIINFEKL peptides in A375 cells expressing H-2Kb in combination with in-frame (Frame) or +1 out-of-frame (+1) V5-ATF41–63-tGFP-SIINFEKL reporters. Graphs shown are a representative curve from one of three independent experiments.
a, Length distribution of the identified peptides. b, HLA binding prediction using netMHCpan shows a high percentage of eluted peptides predicted to bind MD55A3 haplotypes. c, HLA‐I peptides were clustered by Gibbs clustering to assign the peptides to the different HLA alleles of the patient. Logos were created to identify the HLA alleles’ motif using all peptides matching to this allele in the IEDB database (top). Peptides that were identified in the cells treated with IFNγ, tryptophan-derived (mTRP) and non–treated (NT) were clustered to 1–6 clusters, and only the best fit (highest Kullbach Leiber distance) was used for comparison with the IEDB. The clusters show the motifs expected of the cells’ HLA alleles. The last column indicates the outlier peptides that were not clustered.
a, Scheme summarizing the filtration steps that led to the detection of HLA-bound aberrant peptides, containing W-associated frameshift sequences (derived from 16 samples: 4 NT, 4 +IFNγ, 4 mTpr, 4 metastases from patient 55); immunopeptidomics spectra were searched against W-specific frameshifted human proteome. MS-identified peptides were filtered according to described steps, including HLA binding prediction, spectral quality and source gene expression validation in transcriptome or translatome datasets. Following the above steps, 28 aberrant peptides were detected either in MD55 metastasis or treated MD55A3 samples, and not in the untreated cells. b, Predicted hydrophobicity index (HI) and observed retention time (RT) of canonical peptides (black) and aberrant peptides at two filtration steps described in a, step 3 (blue) and step 7 (red). The observed correlation between the RT versus HI, (using the SSRCalc tool31,70) supports the identification of the aberrant peptides presented in a. c, Schematic representation of aberrant peptides KCNK6 and PCNX2 detected via immunopeptidomics, derived from a −1 and +1 frameshift at a Trp codon (marked in red), respectively. The in-frame and out of frame amino acid sequences are indicated above (black) and below (red/green) the mRNA sequence, respectively. d, Venn diagram including the 28 aberrant peptides detected following the filtration steps presented in a (were not identified in the untreated MD55A3 cells), grouped according to the samples they were detected in. e, Mean LFQ normalized intensities. Canonical and aberrant peptides that exhibit above threefold change in their intensities, are marked in black and blue/red, respectively. f, g, Similarities between the aberrant (n = 28) and canonical (n = 6,304) bound peptides. f, Andromeda score. g, Binding affinity prediction with NetMHCpan showing a similar binding distribution of the canonical and aberrant peptides. The aberrant peptides are highlighted in red. Dashed line mark strong binders rank cutoff (<0.5). h, A list of eight out of the thirteen −1 and +1 out-of-frame and trans-frame peptides found in the metastasis samples of patient 55. The colours of the peptide sequences represent in-frame (black), +1 frame (green) and −1 frame (red).
Extended Data Fig. 8 Tandem mass spectra of endogenous aberrant peptides identified in patient 55 match the spectra identified in metastasis samples from patient 42.
Left, experimental spectra of peptides identified in metastasis samples from patient 42, who shares three of six HLA-I alleles with patient 55 (A03:01; B07:02; C07:02). Right, head-to-tail plots show similarities between overlapping ions of the two spectra, Top (blue), patient 42; bottom (red), patient 55 (MD55).
a, Flow cytometry analysis of CD8+ T cells reactive to BV421 and PE-labelled pMHC multimers complexed with the ZNF513-derived aberrant peptide in co-cultures of naïve CD8+ T cells and autologous monocyte-derived dendritic cells pulsed with peptide (right) or DMSO vehicle (left). Cells were from an HLA-C*07:02pos healthy donor. b, Boolean gating strategy for analysis of combinatorial pMHC multimer staining limits false positive signals arising due to background fluorescence when combining in one staining multiple different pMHC multimers labelled with different fluorochromes. In total, four different fluorochromes were used in pMHC multimer preparation and combined into four dual-colour pMHC multimer pairs, each pair complexed with a different peptide. For simplicity, gating for only one dual-colour pMHC multimer population is shown. Gating strategy: (1) Live CD8+ T cell singlets were identified with the use of FSC and SSC gates, live/dead fixable near-IR dead cell and CD8 staining. (2) Separate gates were used to define positive events in each pMHC channel. (3) NOT gates were used to select CD8+/pMHC multimer− events for each pMHC channel. (4) AND gates for two pMHC multimer+ populations and NOT gates for each of the remaining pMHC channels were used to select for cells that are positive only in two channels. Events staining positively for one or more than two pMHC channels were gated out. (5) AND gate was used to combine all pMHC NOT gates. (6) OR gate was made with gates from step 4 and 5. The final plot shows only CD8+ T cells that are positive for two pMHC channels and excludes cells positive for only one or positive for more than two channels. c, For analysis of T cells upregulating the activation marker CD137, viable CD8+ T cell singlets were identified by FSC and SSC gates, live/dead fixable near-IR dead cell staining and CD8 staining. Subsequently, activated CD8+ T cells were identified as CD137+ events, in which cut-off was set based on staining of T cells incubated without target cells. Plots depicting CD137+ events show the KCNK6 T cell clone 1 incubated with target cells pulsed with the KCNK6 aberrant peptide (1 μg ml−1, top), or not (bottom).
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Bartok, O., Pataskar, A., Nagel, R. et al. Anti-tumour immunity induces aberrant peptide presentation in melanoma. Nature 590, 332–337 (2021). https://doi.org/10.1038/s41586-020-03054-1
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