Patient accrual started after approval of the study protocol (CCMO NL33428.058.10) by each local Institutional Review Board. Only patients of whom formalin-fixed-paraffin-embedded (FFPE) first disease onset (FDO) LCH tissue biopsies were available were asked to participate in the study. Informed consent was provided by n = 135 patients and/or their parents/legal guardians. LCH diagnosis was confirmed by a combination of clinical findings and the presence of phenotypically aberrant CD1a⁺ histiocytes in the tissue biopsy. The tissue samples were handled according to the code of conduct for proper secondary use of human tissue of the Federation of Dutch Medical Scientific Societies (FEDERA). Clinical information was collected by each participating center separately using a standardized Case Report Form (CRF) and anonymized data were provided to the researchers of the LUMC. Events were defined as LCH disease progression or reactivation. Progression was defined as (i) progression of existing lesions requiring start or intensification of systemic chemotherapy and/or radiotherapy, or (ii) the development of new lesions when Non-Active Disease (NAD) state had not yet been attained. LCH reactivation was defined as the development of new lesions after NAD had been attained for LCH FDO.

Fresh LCH tissue was dissociated using a gentle MACS tissue dissociator (Miltenyi Biotec) and single cells were cryopreserved in DMSO and albumin containing Roswell Park Memorial Institute (RPMI) culture medium. Before flow cytometric analysis, cells were thawed in RPMI + 20% fetal calf serum (FCS) + Penicillin-Streptomycin (P/S) containing 1,600 IU/ml DNAase (Sigma-Aldrich). After washing, the cells were stained with a mixture of different antibodies: CD45 (2D1, 1:50, BD Biosciences), CD1a (HI149, 1:50, BD Biosciences), CD207 (DCGM4, 1:25, Beckman Coulter), CD14 (MØP9, 1:20, BD Biosciences), CD3 (UCHT1, 1:200, BD Biosciences), CD8 (SK1, 1:100, BD Biosciences), HLA-DR (G46-6, 1:200, BD Biosciences), and panHLA class I (G46-2.6, 1:40, BD Biosciences). The cells were then re-washed and immediately analyzed on a FACS ARIA3 or FACS Fusion cell sorter (BD Biosciences).

High-resolution HLA genotyping was performed by DKMS Life Sciences Lab on DNA extracted from buccal swabs obtained from n = 104 LCH-patients using an ampliqon sequencing-based approach, as previously described (48, 49). For n = 14 additional patients, low-resolution HLA genotype data were acquired using a sequence specific oligoprimer-based approach (50). Hardy-Weinberg Equilibrium testing and HLA association analyses were performed using the HLA genotype data of Dutch LCH-patients. To evaluate statistical significance, two-sided Fisher's exact tests were carried out. The p-values were corrected for multiple comparisons conform the Šidák method (51). Odds ratios and corresponding 95% confidence intervals were calculated according to the method of Woolf with the Haldane correction (52, 53). Since a large control group could lead to significant differences that are clinically irrelevant, p-values were standardized to a smaller control sample size following the method of Good (54). The smaller control sample size was obtained using the following calculation: the total number of LCH-patients plus 3 times the number of patients as maximum allowed size for the control group.

FFPE tissue sections (4–10 μm) were deposited on Superfrost™ (Thermo Fisher Scientific) glass slides, dried overnight at 37°C and stored at 4°C. Prior to immunohistochemical (IHC) staining, selected 4 μm slides were preheated at 66°C for 1 h and deparaffinized in xylol. For enzymatic CD1a IHC staining, endogenous peroxidase was blocked using Methanol/0.3% H₂O₂ for 20 min, before slides were rehydrated in ethanol and demineralized in water baths. Antigen retrieval was performed in boiling citrate buffer (pH 6.0) for 10 min and sections were incubated overnight with mouse IgG1-anti-human CD1a antibody (Clone 010, 1:800, DAKO) diluted in phosphate buffered saline (PBS)/0.5% bovine serum albumin (BSA). The next day, Envision+ System-HRP labeled polymer anti-mouse (DAKO) was applied for 30 min and color development was attained using commercial DAB+ (DAKO) for 10 min in the dark. This reaction was stopped using demineralized water and slides were counterstained with Mayer's hematoxylin (Klinipath) for 5 s prior to mounting with Pertex (Leica Microsystems).

An earlier published protocol was used for triple CD1a/CD3/CD8 fluorescent IHC staining (14). In brief, antigen retrieval was performed in boiling EDTA buffer (pH 8.0) for 10 min followed by a blocking step using 10% Normal Goat Serum in PBS/0.5% BSA for 15 min at room temperature. Slides were incubated overnight with the following primary antibody mix: rabbit IgG-anti-human CD3 (polyclonal, 1:300, DAKO), mouse IgG2b-anti-human CD8 (clone 4B11, 1:100, Novocastra, via Leica Microsystems), and mouse IgG1-anti-human CD1a (Clone 010, 1:400, DAKO). The next day, tissue slides were incubated for 30 min in the dark with 1:300 diluted goat-anti-mouse IgG1 Alexa Fluor 488, goat-anti-mouse IgG2b Alexa Fluor 546 and goat-anti-mouse IgG2a Alexa Fluor 647 antibodies (all from Invitrogen, via Thermofisher Life Technologies Europe). After washing in PBS, the sections were mounted with Mowiol (homemade) or Prolong Gold (Thermo Fisher Scientific) and stored in the dark at 4°C.

CD1a⁺ enriched tissue parts were marked by a blinded pathologist on enzymatically CD1a stained LCH tissue slides. Based on these reference slides, CD1a⁺ enriched tissue parts were manually microdissected from multiple consecutively cut 10 μm tissue sections prepared from the remainder of the LCH tissue blocks. Total nucleic acid was automatically isolated from microdissected tissue using the Siemens Tissue Preparation System (Siemens Healthcare) robot (55). Presence of the BRAF^V600E mutation was assessed by allele-specific real-time qPCR, as previously described (56). Of the n = 54 BRAF^V600E negative samples, absence of the BRAF^V600E mutation was confirmed in 46 samples (85%) by next-generation sequencing (n = 39), whole exome sequencing (n = 1) (57) or BRAF^V600E droplet digital PCR (n = 6).

For the manual cell counting method, multiple representative images were taken of each tissue slide at 400× magnification using a conventional Leica DM5500 fluorescent microscope equipped with LAS AF software (Leica Microsystems). Images were solely taken of representative areas containing phenotypically aberrant CD1a⁺ LCH-cells. Using Image J software (version 1.47v) with the public Cell Counter plugin, fluorescently stained CD1a⁺, CD3⁺CD8⁻ and CD3⁺CD8⁺ cells were manually counted in all images by two independent researchers (PGK and ECS) who were unaware of patient identity and outcome data. The cell counts of the individual images were added to form total CD1a⁺, CD3⁺CD8⁻ and CD3⁺CD8⁺ cell counts. When total cell counts differed more than 10% between the two researchers, a third researcher (AGSH) reviewed the cell counting results and selected the most appropriate scoring (19/101 cases). Total CD3⁺ cell counts were obtained by adding total CD3⁺CD8⁻ and CD3⁺CD8⁺ cell counts. To adjust for substantial differences in biopsy size between different patients, which may lead to profound disparities in absolute numbers of counted cells, ratios between the final numbers of total CD3⁺ and CD3⁺CD8⁺ T cells and CD1a⁺ LCH-cells were calculated for each patient.

For the manual semi-quantitative eyeball estimation method, whole slide images were taken of the same immunostained tissue slides at 400× magnification using a Pannoramic 250 Flash II slidescanner (3DHISTECH). These images were scored semi-quantitatively for LCH-lesional CD3⁺ and CD3⁺CD8⁺ T cell density as has been previously described (58, 59): 1+, no, or sporadic T cells; 2+, moderate number of T cells; 3+, abundant occurrence of T cells; and 4+, highly abundant occurrence of T cells. Scoring examples are shown in Figure S1. Unfortunately, n = 21/101 (21%) of the tissue slides could not be reanalyzed due to considerable photobleaching of the fluorophores, induced by the earlier collection of high-power images for the manual cell counting analysis. Slides were scored independently by three researchers (PGK, ECS and AGSH). When scorings between two or more researchers differed more than 1 value (15/80 cases), the scoring was reviewed by all three researchers collectively and a consensus score was attained. Otherwise, the average score of the three scorings determined the final result, rounded to the nearest whole value (1–4+).

Whole slide images of sufficient quality (without significant color casts and/or folded tissue parts that are highly autofluorescent and/or out of focus) from n = 48 LCH-patients were analyzed using a quantitative automated digital image analysis method (Figure S2). First, the LCH-lesion and its directly adjacent T cells were encircled in the whole slide image in CaseViewer software and exported. In this way, cells that clearly did not belong to the microenvironment of the CD1a⁺ LCH-cells were excluded. Using a custom in-house developed macro in ImageJ software, a white balance was then set for each individual exported image by designating background, foreground and autofluorescence. Next, uniform color thresholds for green (CD1a⁺), red (CD3⁺CD8⁻), and purple (CD3⁺CD8⁺) were applied to all images, so that only green, red, and purple areas with color intensities higher than the threshold remained. Since automated quantification of individual cells was not feasible, the cumulative area of the remaining green, red, and purple areas was measured for each image, representing the total quantity of CD1a⁺, CD3⁺CD8⁻, and CD3⁺CD8⁺ cells. Purple and Red (CD3⁺) area/Green (CD1a⁺) area and Purple (CD3⁺CD8⁺) area/Green (CD1a⁺) area ratios could then be calculated for each patient. Comparison of the results obtained using our three separate analysis methods showed substantial concordance (Figure S3), supporting the validity of the findings in this study.

Competition-based peptide-HLA class I binding assays were performed as previously described (60). The HLA binding affinities of the target peptides and strong binding reference peptides are expressed as the concentration that inhibits 50% binding of a fluorescently-labeled standard peptide (IC₅₀). The standard peptides were FLPSDCFPSV for HLA-A^*02:01 and KVFPCALINK for HLA-A^*03:01 and HLA-A^*11:01. Notably, the ratio between the IC₅₀ of a target peptide and the IC₅₀ of an established strong binding reference peptide (for example 260:250 vs. 100:5) provides superior information on the true HLA class I binding capacity of the target peptide than the absolute IC₅₀ of the target peptide.

The full length BRAF^V600E sequence incorporated in a pBABE-Puro-BRAF-V600E plasmid was re-cloned into a LZRS-ires-Green Fluorescent Protein (GFP) retroviral vector by introducing the SwaI restriction site and a kozak sequence in front of the ATG start codon at the 5′end of the BRAF^V600E sequence using Phusio DNA polymerase. In addition, a stop codon and NotI restriction site was introduced at the 3′end of the BRAF^V600E sequence. The original pBABE-Puro-BRAF-V600E plasmid was kindly provided by William Hahn (Addgene plasmid #15269; http://n2t.net/addgene:15269; RRID:Addgene_15269) (61). Ligation of the BRAF PCR product in the LZRS vector digested with SwaI and NotI was performed overnight at 16°C. Prior to spin inoculation of Phoenix packaging cells, the correct sequence of the re-cloned BRAF^V600E gene was confirmed by Sanger sequencing (data not shown). Retrovirus containing supernatant was subsequently used to transduce Epstein-Barr virus-immortalized B cell lines (EBV-LCLs) with either a control empty LZRS vector (mock transduced EBV-LCL) or with the new BRAF^V600E containing LZRS vector (BRAF^V600E transduced EBV-LCL). Stably transduced GFP^high cells were purified using an ARIA3 flow cytometer prior to bulk expansion in RPMI medium containing 10% bovine serum.

Cells were lysed at a concentration of 100e6 cells/ml lysis buffer [50 mM Tris-Cl pH 8.0, 150 mM NaCl, 5 mM EDTA, 0.5% Zwittergent 3–12 (N-dodecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate) and protease inhibitor (Complete, Roche Applied Science)] for 2 h at 0°C (62). Lysates were successively centrifuged for 10 min at 2,500 × g and for 45 min at 31,000 × g to remove nuclei and other insoluble material, respectively. Next, lysates were cleared through a CL-4B Sepharose column (1 ml/1e9 cells) and passed through an anti-panHLA class I column containing 2.5 mg W6/32 IgG per ml protein A Sepharose (62). The W6/32 column was washed three times each with 1 ml of lysis buffer, 3 ml of low salt buffer (20 mM Tris-Cl pH 8.0, 120 mM NaCl), 1 ml of high salt buffer (20 mM Tris-Cl pH 8.0, 1 M NaCl), and finally with 3 ml of low salt buffer. Peptides were eluted with 5 ml of 10% acetic acid per ml column, diluted with 10 ml of 0.1% formic acid and purified by SPE (Oasis HLB, Waters) using 20 and 30% acetonitrile in 0.1% formic acid to elute the peptides.

For parallel reaction monitoring (PRM) analyses, the samples were lyophilized and resuspended in buffer A. HLA-eluates were injected together with a mix of 40 fmol of each heavy labeled peptide. The Orbitrap Fusion LUMOS mass spectrometer was operated in PRM-mode. Peptides KIGDFGLATE, KIGDFGLATV, KIGDFGLATEK, and KIGDFGLATVK were monitored. Selected peptides, the transitions and collision energies can be found in Table S1. The isolation width of Q1 was 1.2 Da. MS2 resolution was 35,000 at an AGC target value of 1 million at a maximum fill time of 100 ms. The gradient was run from 2 to 36% solvent B (20/80/0.1 water/acetonitrile/formic acid (FA) v/v) in 120 min. The nano-HPLC column was drawn to a tip of ~5 μm and acted as the electrospray needle of the MS source. PRM data analysis and data integration were performed in Skyline 3.6.0.10493. Peptide abundances were calculated by comparing the peak area of the eluted (light) and the peak area of the spiked-in heavy peptides.

Statistical analysis was performed using GraphPad Prism version 8.0.1 and IBM SPSS Statistics version 25. Comparisons of (sub)groups were performed with the Mann-Whitney U test for continuous data and the Fisher exact test for categorical data. The Cox proportional hazards model was used for univariate analysis. Notably, log transformation of the widely differing CD8⁺ T cell:CD1a⁺ LCH-cell ratios was performed to increase the validity of the univariate analysis. Survival curves were estimated with the Kaplan-Meier method and compared with the Log-rank test. A p-value of <0.05 was considered statistically significant.

Since loss or downregulation of HLA expression has been shown to be a major tumor escape mechanism from T lymphocytes in a wide variety of cancers (63), we first evaluated by flow cytometric analysis the levels of HLA class I and HLA-DR expression on the surface of CD1a⁺ (LCH-)cells present in n = 6 LCH-biopsies. The gating strategy applied is shown in Figure S4. The mean fluorescent intensity (MFI) of HLA class I and HLA-DR expression by CD1a⁺ (LCH-)cells was comparable to MFI levels of HLA class I and HLA-DR expression by CD1a⁻ CD14⁺ (monocytic) cells present in the same LCH-biopsies (Figure 1; HLA class I, p = 0.69; HLA-DR, p = 0.94).

Besides HLA expression, HLA subtype is a crucial factor influencing whether a (neo)antigen is actually presented at the surface of nucleated cells. Several earlier published studies have suggested associations between particular HLA subtypes and LCH disease (extension) (64–67). To investigate this, we compared HLA genotype data from n = 94 Dutch LCH-patients to the HLA genotypes of 5,604 healthy Dutch blood donors reflecting the HLA genotype of the Dutch population (50). To maintain sufficient statistical power, HLA genotype was compared at low resolution level. No significant differences between Dutch LCH-patients and the Dutch reference population were observed (Table S2). Thus, our data do not support previous reports describing excess frequency of HLA-Bw61 and HLA-Cw7 (64), HLA-B7 and HLA-DR2 (65), and HLA-DR4 and/or HLA-Cw7 (66) genotypes in LCH-patients (Tables S2, S3). Moreover, our results neither confirm that LCH-patients with unifocal bone disease have significantly more often HLA-DR4 and/or HLA-Cw7 (66) subtypes nor that patients with single-system LCH have an increased prevalence of HLA-DRB1^*03 (67) when compared to patients with multisystem LCH (Table S4 and Figure S5, respectively).

Assured that LCH-cells express HLA class I (and II) molecules and that there is a normal HLA subtype distribution among LCH-patients, we next investigated the presence of CD8⁺ T cells in LCH-lesions. Various methods for the quantification of cell numbers in (specific areas of) tissue sections exist, including eyeball estimation, manual cell counting and automated digital image analysis. Although automated digital image analysis is increasingly being applied, manual cell counting is still considered the golden standard (68). Accordingly, we first determined the relative number of total CD3⁺ and CD3⁺CD8⁺ T cells in LCH-lesions using this method. Fluorescently stained CD1a⁺, CD3⁺CD8⁻ and CD3⁺CD8⁺ cells (Figure 2A) were manually counted in LCH-biopsies from n = 101 patients collected at first disease onset using the public ImageJ Cell Counter plugin. A median of 1,810 cells (range: 188–9,301) were counted in a median of 16 representative images (range: 2–56) taken at 400× magnification of tissue areas containing phenotypically aberrant CD1a⁺ LCH-cells. Large inter- and intrapatient heterogeneity was seen in the relative number of LCH-lesional CD3⁺ and CD8⁺ T lymphocytes (Figure S6 and Figure 2B, respectively). Calculated CD8⁺ T cell:CD1a⁺ LCH-cell ratios (CD8 ratios) ranged from 0.00 to 4.96. The median CD8 ratio was 0.06, corresponding to 1 CD8⁺ T cell per 16 CD1a⁺ LCH-cells. No significant difference in LCH-lesional CD8 ratios was observed between bone and skin biopsies (p = 0.37) nor between patients with single- or multisystem LCH disease (p = 0.55). Yet, BRAF^V600E mutated patients displayed significantly lower LCH-lesional CD8 ratios when compared to BRAF wildtype (BRAF^WT) patients (p = 0.01; Figure 2C). BRAF^V600E mutated LCH-lesions had a median CD8 ratio of 0.0316, corresponding to 1 CD8⁺ T cell per 32 CD1a⁺ LCH-cells. In contrast, BRAF^WT lesions had a median CD8 ratio of 0.0775, corresponding to 1 CD8⁺ T cell per 13 CD1a⁺ LCH-cells. BRAF^V600E mutated lesions also had significantly lower total CD3⁺ T cell:CD1a⁺ LCH-cell ratios than BRAF^WT lesions (p = 0.001; Figure S7). As manual selection of representative tissue areas may introduce bias, we also analyzed whole slide images taken from a subset of immunostained tissue sections using a previously described semi-quantitative eyeball estimation method (58, 59) (Figure S1) and a quantitative automated digital image analysis method (Figure S2). The correlation between the BRAF^V600E mutation and decreased LCH-lesional CD3⁺ and CD8⁺ T cell density was confirmed by these two additional analysis methods (Figure S8).

We subsequently assessed whether lesional CD8⁺ T cell density is of prognostic value in LCH. Using univariate cox regression analysis, no significant association was observed between LCH-lesional CD8 ratio and event-free survival (p = 0.46; Hazard Ratio = 0.89; 95% Confidence Interval = 0.66–1.21). In addition, no significant difference was present when patients were divided by a median split, grouped in patients with HIGH or LOW CD8 ratios (Figure 2B and Table 1) and compared with regard to event-free survival (p = 0.96, Figure 2D). Thus, LCH-lesional CD8⁺ T cell density did not correlate with disease outcome in this retrospective patient cohort.

To investigate the immunogenicity of the BRAF^V600E mutation, we used the online NetMHC 4.0 server (69) to explore putative HLA class I binding 8–12 amino acid long (8–12mer) neopeptides derived from the BRAF^V600E protein. In addition, NetCHOP 3.1 software (70) was used to predict proteasomal cleavage motifs and thereby identify peptides that are presumably generated by the human proteasome. From all 8–12mer BRAF^V600E derived neopeptides that are generated by the human proteasome according to NetCHOP, only a single neopeptide, the 11mer KIGDFGLATEK, is predicted to bind to one or more of the analyzed HLA class I molecules (Table S5). According to NetMHC, KIGDFGLATEK binds weakly to HLA-A^*11:01 and HLA-A^*03:01, expressed by respectively n = 11/104 (11%) and n = 25/104 (24%) LCH-patients from our cohort. The remainder of the 8–12mer BRAF^V600E derived neopeptides are all considered not be generated by the human proteasome and/or to be non-binders. Additional in vitro peptide-HLA binding studies however demonstrated that KIGDFGLATEK binds with comparable affinity to HLA-A^*11:01 as the strong binding reference peptide (QVPLRPMTYK) that was used in our competition-based peptide-HLA binding assay (60). In line with the predicted binding affinity, this neopeptide was shown to also bind, albeit less efficiently, to HLA-A^*03:01 (Table 2), as evidenced by the small difference in nanomolar concentration that inhibited 50% binding (IC₅₀) of the fluorescently-labeled standard peptide (KVFPCALINK) between KIGDFGLATEK and QVPLRPMTYK (672 vs. 297 nM, respectively). Notably, NetMHCstab 1.0 software (71) predicts that the KIGDFGLATEK-HLA-A^*11:01 complex is highly stable (predicted half-life: 8.87 h) and that the KIGDFGLATEK-HLA-A^*03:01 complex is weakly stable (predicted half-life: 3.29 h). We also assessed the in vitro HLA binding affinity of the 11mer KIGDFGLATVK and 10mer KIGDFGLATV BRAF wildtype peptides and of the 10mer KIGDFGLATE neopeptide (Table 2). In accordance with the predictions made by NetMHC, KIGDFGLATVK was shown to bind with comparable affinity to HLA-A^*11:01 as the strong binding reference peptide QVPLRPMTYK, and to confer weaker binding to HLA-A^*03:01, just like KIGDFGLATEK. Moreover, the 10mer BRAF wildtype peptide KIGDFGLATV was shown to bind with comparable affinity to HLA-A^*02:01 as the strong binding reference peptide (FLPSDFFPSV) used in our assay. In contrast, its mutant counterpart KIGDFGLATE does not bind at all to this particular HLA class I molecule.

Having established that the BRAF^V600E derived neopeptide KIGDFGLATEK can bind to two HLA class I molecules that are relatively frequent in the Caucasian population, we evaluated whether BRAF^V600E mutated LCH-patients expressing HLA-A^*03:01 and/or HLA-A^*11:01 had increased event-free survival as compared to LCH-patients without these HLA genotypes. High-resolution HLA genotype data was available for n = 48 BRAF^V600E mutated LCH-patients. Patient characteristics are shown in Table S6. No significant difference in event-free survival was observed between BRAF^V600E mutated LCH-patients with and without HLA-A^*03:01 and/or HLA-A^*11:01 (p = 0.32, Figure S9).

To assess whether KIGDFGLATEK is actually presented on the surface of cells that express BRAF^V600E and HLA-A^*03:01 and/or HLA-A^*11:01, we performed mass spectrometry-based targeted peptidomics of HLA class I presented peptides isolated from various EBV-LCL transduced with a LZRS-retroviral vector containing full length BRAF^V600E protein and reporter Green Fluorescent Protein (GFP) encoding DNA sequences. Based on the results of the in silico analysis and in vitro peptide-HLA binding assays, three different EBV-LCL were selected for the transduction experiments with HLA-A^*03:01/HLA-A^*02:01 (SB), HLA-A^*11:01/HLA-A^*02:01 (MLA), and HLA-A^*02:01/HLA-A^*02:01 (JY) genotypes. Extended HLA genotypes are shown in Table S7. After retroviral transduction, GFP^high cells were sorted and expanded in bulk. JY and MLA cell lines that were mock transduced with a control (empty-)GFP retroviral vector were analyzed in parallel. Flow cytometric analysis demonstrated that neither retroviral transduction with the BRAF^V600E containing vector (Figure S10) nor transduction with the control empty vector (data not shown) altered HLA class I (W6/32) and HLA-DR expression at the cell surface. Moreover, HLA subtype-specific antibodies (kindly provided by Dr. D.L. Roelen, HLA genotyping laboratory LUMC, Leiden) confirmed normal HLA subtype expression by BRAF^V600E transduced SB, MLA (Figure S10) and JY cells (data not shown). We also included an HLA-A^*01/HLA-A^*24 bearing BRAF^V600E mutated colon carcinoma cell line (HT29) with earlier confirmed HLA (72–74) and BRAF^V600E protein (75, 76) expression in our analysis. Using parallel reaction monitoring (PRM)-based targeted peptidomics (77), the 11mer neopeptide KIGDFGLATEK was not detected in the HLA class I peptidomes of both BRAF^V600E expressing cell lines expressing HLA-A^*03:01 or HLA-A^*11:01 (Table 3). Notably, neither the 11mer BRAF wildtype peptide KIGDFGLATVK was detected in HLA class I peptides isolated from the mock or BRAF^V600E transduced SB and MLA EBV-LCL. In contrast, the 10mer BRAF wildtype peptide KIGDFGLATV was detected in the HLA class I peptidomes of 3/3 BRAF^V600E transduced and 2/2 mock transduced cell lines expressing HLA-A^*02:01 (Table 3).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.