The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma

Bauer, Jens; Köhler, Natalie; Maringer, Yacine; Bucher, Philip; Bilich, Tatjana; Zwick, Melissa; Dicks, Severin; Nelde, Annika; Dubbelaar, Marissa; Scheid, Jonas; Wacker, Marcel; Heitmann, Jonas S.; Schroeder, Sarah; Rieth, Jonas; Denk, Monika; Richter, Marion; Klein, Reinhild; Bonzheim, Irina; Luibrand, Julia; Holzer, Ursula; Ebinger, Martin; Brecht, Ines B.; Bitzer, Michael; Boerries, Melanie; Feucht, Judith; Salih, Helmut R.; Rammensee, Hans-Georg; Hailfinger, Stephan; Walz, Juliane S.

doi:10.1038/s41467-022-33746-3

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Published: 27 October 2022

The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma

Nature Communications volume 13, Article number: 6401 (2022) Cite this article

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Abstract

The DNAJB1-PRKACA fusion transcript is the oncogenic driver in fibrolamellar hepatocellular carcinoma, a lethal disease lacking specific therapies. This study reports on the identification, characterization, and immunotherapeutic application of HLA-presented neoantigens specific for the DNAJB1-PRKACA fusion transcript in fibrolamellar hepatocellular carcinoma. DNAJB1-PRKACA-derived HLA class I and HLA class II ligands induce multifunctional cytotoxic CD8⁺ and T-helper 1 CD4⁺ T cells, and their cellular processing and presentation in DNAJB1-PRKACA expressing tumor cells is demonstrated by mass spectrometry-based immunopeptidome analysis. Single-cell RNA sequencing further identifies multiple T cell receptors from DNAJB1-PRKACA-specific T cells. Vaccination of a fibrolamellar hepatocellular carcinoma patient, suffering from recurrent short interval disease relapses, with DNAJB1-PRKACA-derived peptides under continued Poly (ADP-ribose) polymerase inhibitor therapy induces multifunctional CD4⁺ T cells, with an activated T-helper 1 phenotype and high T cell receptor clonality. Vaccine-induced DNAJB1-PRKACA-specific T cell responses persist over time and, in contrast to various previous treatments, are accompanied by durable relapse free survival of the patient for more than 21 months post vaccination. Our preclinical and clinical findings identify the DNAJB1-PRKACA protein as source for immunogenic neoepitopes and corresponding T cell receptors and provide efficacy in a single-patient study of T cell-based immunotherapy specifically targeting this oncogenic fusion.

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Introduction

T cell-based immunotherapies, comprising immune checkpoint inhibitors (ICIs), CAR-T cells, and bispecific T cell engager antibodies achieved a breakthrough in the treatment of malignant disease^1,2,3,4,5, adoptive T cell transfer and vaccination strategies hold further promise^6,7,8,9,10. However, these therapies, which rely on the rejection of cancer cells through recognition of tumor antigens and T cell-mediated cytotoxicity are still only available and effective in small subsets of cancer patients and single tumor entities. One main problem for the development of antigen-specific immunotherapies is the lack of suitable target structures that show natural, highly frequent, and tumor-exclusive presentation on the cell surface of tumor cells and are recognized by the immune system¹¹. Tumor antigens are represented by HLA-independent surface molecules or by HLA class I- and HLA class II-presented T cell epitopes, originating from intracellular proteins¹². In terms of the latter, neoepitopes arising from tumor-specific mutations have been identified in recent years as the main specificity of anti-cancer T cell responses induced by ICIs, and were in turn suggested as prime candidates for T cell-based immunotherapy approaches^13,14,15. In line, response to ICIs correlates with high tumor somatic mutational burden, and neoepitope-based immunotherapies have been applied in individual tumor patients^16,17,18. However, patient/tumor-specificity and intratumoral heterogeneity of somatic mutations, as well as the limited number of somatic mutations that are ultimately translated, processed, and presented as HLA-restricted neoepitopes on the tumor cells^{8,13,19,20,21} restrict the broad applicability of these antigens in particular in low-mutational burden cancer entities²². Recently, fusion transcripts, whose products often represent clonal oncogenic drivers, were identified as the source of highly immunogenic neoepitopes, and T cell responses against such fusion protein-derived neoepitopes were detected in patients receiving ICIs and correlated with treatment response²³.

The DNAJB1-PRKACA fusion transcript links exon 1 of the DnaJ homolog subfamily B member 1 gene (DNAJB1) to exon 2–10 of the cAMP-dependent protein kinase catalytic subunit alpha gene (PRKACA)²⁴. In FL-HCC, the DNAJB1-PRKACA fusion transcript is detectable in 100% of patients and has been identified as the oncogenic driver in tumor pathogenesis^25,26 indicating expression of the fusion transcript in all tumor cells. FL-HCC is a devastating tumor disease with a 5-year survival of only 45%, which typically affects children and young adults with no history of primary liver disease. The frequency of FL-HCC diagnosis is continuously increasing to ∼5% of all liver cancers today^27,28. To date, surgical resection is the only effective therapy if the cancer is diagnosed before the occurrence of metastases, and long-term survival is jeopardized by tumor recurrence calling for the development of specific treatment options for FL-HCC patients^26,29. The oncogenic fusion protein DNAJB1-PRKACA represents an attractive target for the development of novel therapies for this devastating tumor disease. Moreover, the recent identification of other cancer entities that express the DNAJB1-PRKACA fusion transcript gives the prospect that targeting the fusion protein might improve treatment options in multiple cancer entities³⁰.

Here, we show that the DNAJB1-PRKACA fusion transcript is a prime source for broadly applicable neoepitopes and provide the first evidence for their efficacy in immunotherapy approaches in an FL-HCC patient.

Results

The DNAJB1-PRKACA fusion gene is a source of HLA class I and HLA class II neoantigens and induces DNAJB1-PRKACA-specific CD4⁺and CD8⁺ T cells

To identify potential DNAJB1-PRKACA fusion gene-specific HLA ligands an in silico prediction was conducted based on the DNAJB1-PRKACA protein sequence (NCBI accession 4WB7_A). The in silico prediction workflow using the algorithm NetMHCIIpan identified nine unique binding cores of nine amino acid (AA) lengths for a total of 1290 different HLA class II alleles within the 24 AA fusion region of the DNAJB1-PRKACA protein (Fig. 1a, b). 83.5% of these alleles represent HLA-DP combinations, 11.6% and 5.0% are HLA-DQ or HLA-DR combinations, respectively. Focusing on the population frequencies of the top four alleles covered by the fusion region (HLA-DPA1*02:02-DPB1*05:01, HLA-DPA1*01:03-DPB1*05:01, HLA-DPA1*02:01-DPB1*05:01, and HLA-DPA1*01:03-DPB1*09:01) in a publicly available HLA-DP, -DQ, and -DR allele typed population (Japan pop 17; http://www.allelefrequencies.net), 41.4%, 39.1%, 17.9%, and 12.5% of the donors were calculated to carry the respective allotype, suggesting very broad applicability of this fusion neoepitope based on its’ predicted promiscuous HLA binding. The core sequence RYGEEVKEF, located directly in the middle of the fusion transcript (5 AAs on exon 1 (DNAJB1), 4 AAs on exon 2 (PRKACA)) is predicted to bind to the majority of different HLA class II alleles (60.52% of possible allele/binding core combinations). For HLA class I, 13 DNAJB1-PRKACA-derived HLA ligands were identified for the 20 most frequent HLA class I allotypes of the European population, using a prediction workflow combining the algorithms SYFPEITHI and NetMHCpan (Fig. 1c, Table 1). These 13 HLA class I allotypes within the 22 AA peptide KREIFDRYGEEVKEFLAKAKED (P_II-1), spanning the fusion region of the DNAJB1-PRKACA protein, cover 96.6% and 93.8% of the European and world population with at least one HLA allotype, respectively (Fig. 1d, Supplementary Fig. S1a). Of note, the HLA class II-binding core RYGEEVKEF was also predicted as HLA class I ligand binding the alleles HLA-A*24:02, -C*04:01, -C*06:02, and -C*07:02.

**Fig. 1: Prediction of DNAJB1-PRKACA fusion protein-derived HLA class I and HLA class II ligands and characterization of DNAJB1-PRKACA-derived T cell epitopes.**

Table 1 Predicted DNAJB1-PRKACA fusion protein-derived HLA class I ligands

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Cellular presentation of DNAJB1-PRKACA-derived HLA-presented peptides was shown by liquid chromatography–coupled tandem mass spectrometry (LC–MS/MS) of differentiated and maturated monocyte-derived dendritic cells (moDCs; Supplementary Fig. S1b) from healthy volunteers (HV) loaded with the isotope-labeled 22 AA peptide P_II-1. The mass spectrometric (MS) identified fragment ion spectra of the experimentally eluted P_II-1 were validated using the synthetic peptide (Supplementary Fig. S1c). P_II-1 and 12 shorter length variants were identified by MS and predicted to bind to the HLA-DP allele DPA1*01:03-DPB1*05:01 of the respective HV6 with the best NetMHCIIpan binding rank of 0.74 for the binding core RYGEEVKEF (Fig. 1b, Table 2, Supplementary Table 1). De novo priming of CD4⁺ T cells from HVs with P_II-1-loaded mature moDCs induced multifunctional P_II-1-specific CD4⁺ T cells, which showed expression of CD107a and CD154 as well as production of interleukin-2 (IL-2), interferon-γ (IFN-γ), and tumor necrosis factor (TNF) upon P_II-1 stimulation (Fig. 1e). Refolding of the DNAJB1-PRKACA protein fusion-derived ligands RYGEEVKEF (P_A*24, SYFPEITHI score of 74.19% and NetMHCpan rank of 0.018), and EIFDRYGEEV (P_A*68/A*02, A*68:02 NetMHCpan rank of 0.106) was conducted to an HLA-A*24:02-P_A*24 monomer and HLA-A*68:02-P_A*68/A*02 monomer, respectively. These monomers were used to build artificial antigen-presenting cells (aAPCs) for aAPC-based priming of CD8⁺ T cells of HVs to validate their immunogenicity. aAPC-based priming induced P_A*24-specific and P_A*68/A*02-specific CD8⁺ T cells with frequencies of up to 15.7% (median 4.1%) and 1.1% (median 0.7%) peptide-specific T cells, respectively (Fig. 1f, g, Supplementary Fig. S1d, e, Table 1). Flow cytometry-based functional characterization of P_A*24-specific and P_A*68/A*02-specific CD8⁺ T cells showed a polyfunctional phenotype reflected by IFN-γ, TNF, and CD107a production/expression (Fig. 1h, i).

Table 2 HLA class II-presented length variants of P_II-1 as identified by MS

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In-depth characterization of DNAJB1-PRKACA fusion protein-specific CD8⁺ T cells and single-cell TCR sequencing

We further conducted an in-depth characterization of P_A*24-specific CD8⁺ T cells using single-cell RNA-sequencing analysis of flow cytometry-based bulk sorted P_A*24-specific CD8⁺ T cells of HV 1 and HV2 which showed a high expression of cytotoxicity markers comprising amongst others GNLY, GZMA, GZMB, GZMK, PRF1, and NKG7, paired with a low expression of the exhaustion marker PDCD1 (Fig. 2a). P_A*24-specific CD8⁺ T cells specifically lysed P_A*24-loaded autologous CD8⁻ cells in vitro with up to 82.4% lysis of target cells in comparison to unspecific effector cells at various effector to target ratios (Fig. 2b). Single-cell T cell receptor (TCR) sequencing of the P_A*24-specific CD8⁺ T cell bulks from the two HVs showed high clonality of one dominant TCR clone for HV2 and two clones for HV1 (Supplementary Fig. S2a, b and Supplementary Table 2). There was no overlap of the V(D)J genes of the three TCR clones, but the complementary determining region (CDR) 3-β sequences of the main clone from HV1 and HV2 shared a high sequence identity and similarity of 69.2% and 76.9%, respectively (Fig. 2c, Supplementary Fig. S2c). The CDR3-α sequence of the main TCR clone of HV1 showed, in terms of physiochemical properties of the AA sequences, opposing characteristics regarding chemical groups in comparison to the target peptide P_A*24, which could not be observed in the CDR3-α motif cluster of a negative control dataset of published TCR sequences (Supplementary Fig. S2d).

**Fig. 2: In-depth characterization of DNAJB1-PRKACA-specific CD8⁺ T cells and single-cell TCR sequencing.**

Doxycycline-inducible DNAJB1-PRKACA fusion gene expression leads to cellular processing and presentation of DNAJB1-PRKACA-derived HLA class I- and HLA class II-restricted peptides

Three HLA class I-expressing hepatocellular carcinoma (HCC) cell lines (HLE, SMMC-7721, and HepG2; Supplementary Table 3) were transduced with an expression construct that allowed the Doxycycline (Dox)-dependent expression of the DNAJB1-PRKACA fusion protein (Fig. 3a, b, Supplementary Fig. S3a). Subsequent MS-based immunopeptidome analysis revealed up to 3688 different HLA class I ligands (mean 2787; Fig. 3c). Twenty unique HLA class I ligands derived from the DNAJB1-PRKACA fusion protein were identified in the three HCC cell lines with two ligands spanning the fusion region (Fig. 3d, Supplementary Fig. S3b). The two cellular processed and presented DNAJB1-PRKACA-derived neoepitopes EIFDRYGEEV (P_A*68/A*02) and IFDRYGEEV (P_C*04/C*05) identified on SMMC-7721 and HepG2 were predicted to bind to the HLA allotypes HLA-A*68:02 and HLA-C*04:01, respectively, and were validated by comparative spectra analysis using synthetic peptides (Figs. 1c, 3e, Table 1). Of note, the C-terminal AA of P_A*68/A*02 and P_C*04/C*05 spanning the fusion region leads to altered HLA presentation of the ligands due to a change in the HLA binding motif anchor position. The corresponding wild-type (WT) peptides would display a glycine at the C-terminal end (EIFDRYGEEG (P_A*68/A*02-WT) and IFDRYGEEG (P_C*04/C*05-WT)), which do not allow HLA class I presentation of the two WT-peptides on the respective as well as on any other HLA allotype according to netMHC-4.0 and SYFPEITHI predictions. To investigate the processing and presentation of DNAJB1-PRKACA-derived HLA class II peptides, mature moDCs of three HVs were incubated with lysate of the HLE cell line after activation of DNAJB1-PRKACA fusion gene expression (Supplementary Fig. S3c). MS-based immunopeptidome analysis of these moDCs revealed up to 8293 different HLA class II peptides (mean 5956; Fig. 3f). Thirteen unique peptides derived from the DNAJB1-PRKACA fusion protein were identified with one peptide EVKEFLAKAKEDFLKK (P_II-2) spanning the fusion region (Figs. 1b and 3g). The DNAJB1-PRKACA-derived neoepitope P_II-2 was predicted to bind to the HLA allele DRB1*13:02 of the respective HV3 (Fig.1b, Supplementary Table 1). The experimental fragment ion spectrum of the P_II-2 peptide was validated with an isotope-labeled synthetic peptide (Fig. 3h). No HLA class I or HLA class II ligands derived either from the two proteins DNAJB1 and PRKACA or the fusion protein were identified in the respective negative controls.

**Fig. 3: Mass spectrometry-based identification of naturally presented DNAJB1-PRKACA-derived HLA class I and HLA class II ligands.**

Personalized DNAJB1-PRKACA-derived peptide vaccine induces long-lasting DNAJB1-PRKACA-specific immune response and shows favorable clinical outcome in a FL-HCC patient

A personalized DNAJB1-PRKACA-derived peptide vaccine was designed for a young patient with histologically confirmed FL-HCC (FL-HCC01), who suffered from multiple tumor relapses after receiving an early liver transplant (LTx), due to unresectable FL-HCC not responsive to chemotherapy (Fig. 4a and Supplementary Fig. S4a). The mTOR inhibitor everolimus was applied for post-transplant immunosuppression. Poly (ADP-ribose) polymerase (PARP) inhibition was initiated based on detectable alterations in the DNA damage response (DDR) pathway (ATM and CHEK2, germline variant, BRCA2 and BAP1 somatic deletion)³¹, but without achieving a durable remission. Recurrent tumor manifestations were resected or treated with radiotherapy. Based on the prevalence of the DNAJB1-PRKACA fusion gene (confirmed by Sanger sequencing) a vaccine consisting of three short allotype-matching HLA class I ligands (EIFDRYGEEV (P_A*68/A*02), EEVKEFLAKA (P_B*44), and IFDRYGEEV (P_C*04/C*05)), together with the long peptide KREIFDRYGEEVKEFLAKAKED (P_II-1) predicted to bind to the HLA-DP allotype DPA1*01:03-DPB1*06:01 of FL-HCC01 was composed (Supplementary Fig. S4b and Supplementary Tables 1 and 4). The vaccine was applied twice within a 6-week interval and adjuvanted with the toll-like receptor (TLR) 1/2 agonist XS15 (Pam₃Cys-GDPKHPKSF) emulsified in Montanide^TM ISA51 VG to endorse activation and maturation of antigen-presenting cells and prevent vaccine peptides from immediate degradation, thereby enabling induction of an effective and potent T cell response^32,33,34,35. The patient mounted a profound T cell response targeting the P_II-1 peptide documented 6 weeks after the second vaccination, as analyzed by IFN-γ enzyme-linked immunospot (ELISPOT) assay after in vitro stimulation with the vaccine cocktail peptides (1 mean spot count prior to vaccination versus 872 spot counts post second vaccination; Fig. 4b, c and Supplementary Fig. S4c). In addition, a weak induction of an IFN-γ T cell response was detected after P_B*44 stimulation in the ELISPOT assay (0 mean spot count prior to vaccination versus 56 spot counts post second vaccination). Flow cytometry-based characterization of the P_B*44- and P_II-1-directed T cell responses revealed T helper 1 (Th1) phenotype CD4⁺ T cells with specific expression of IFN-γ and TNF, whereas no CD8⁺ T cell-driven response against the P_II-1 or the P_B*44 was observed, suggesting the P_B*44-induced IFN-γ T cell response in the ELISPOT assay as cross-reactivity to the shared binding core of the long P_II-1 (Fig. 4d, e). No T cell responses targeting the P_A*68/A*02 and P_C*04/C*05 were observed. Longitudinal IFN-γ ELISPOT assays showed the persistence of P_II-1-specific T cells over time with a constant intensity of response (770 mean spot count) 18 months after the second vaccination (Fig. 4c and Supplementary Fig. S4c). In contrast to the disease prior to vaccination, where the patient regularly suffered from relapses (time to next relapse 2.5–5.0 months (median 3.0 months)), up to now no disease relapse was observed (21 months after the second vaccination) pointing to the clinical efficacy of vaccine-induced DNAJB1-PRKACA-specific T cell responses.

**Fig. 4: FL-HCC patient vaccinated with a personalized DNAJB1-PRKACA-derived peptide vaccine.**

In order to identify the vaccine-induced T cell clones expanding in FL-HCC01 post-vaccination, combined single-cell RNA and single-cell TCR sequencing utilizing 10x Genomics single-cell immune profiling was performed. Unsupervised clustering of single-cell RNA sequencing data from vaccine-induced P_II-1-reactive CD4⁺ T cells after in vitro expansion, followed by flow-cytometry-based bulk sort of CD4⁺ T cells, showed three defined T cell clusters: (I) cytokine and chemokine-expressing activated T cells defined by high expression of IFNG, TNF, GZMB (encoding granzyme B), CCL3, and CCL4 (Fig. 5a–c), (II) T cells exhibiting an exhausted or late effector profile with an expression of PDCD1, LAG3, HAVCR2, and CTLA4 (Fig. 5a, b and Supplementary Fig. S5a), and (III) naïve resting T cells defined by expression of SELL (encoding CD62L), CCR7, and TCF7 (Fig. 5a, b and Supplementary Fig. S5b). In agreement, functional enrichment for the hallmarks of cancer gene sets “TNF signaling via NF-κB” and “inflammatory response” showed an increased gene expression in the cytokine and chemokine expressing activated T cell cluster (Fig. 5d), indicating that this cluster comprised the CD4⁺ T cells reactive to the P_II-1. As expected, VDJ sequencing revealed a high TCR clonality in the activated T cell cluster with 74.2% of cells assigned to large clones (clonality ≥ 4), compared to the naïve resting (1.3%) or exhausted T cell clusters (31.4%) (Fig. 5e and Supplementary Fig. S5c). In total, 10 defined TCR clones were identified, of which eight were predominantly assigned to the activated T cell cluster (Fig. 5f, Supplementary Table 5). The high similarity of physiochemical properties and hydrophilicity of the AA sequences was observed for the CDR3-α/-β sequences of the ten expanded TCR clones, especially for positions four and five of the CDR3-α sequences with opposing characteristics regarding chemical groups in comparison to the target peptide core-binding motif (Fig. 5g, Supplementary Fig. S5d and Supplementary Table 5). By clustering the CDR3-α/-β sequences distinct motif plots were generated for the 10 expanded TCR clones in comparison to the naïve unexpanded TCRs, which showed a specific preference for basic AAs on position five of the CDR3-α sequence which could not be observed in the unexpanded clones (no significant Pearson correlation coefficient to the negative cluster). Specific differences (no significant motif correlation) between the expanded clones and the negative dataset were also observed for position six of the CDR3-α cluster and position six, seven, and eight of the CDR3-β motif (Fig. 5h).

**Fig. 5: Single-cell RNA sequencing of vaccine-induced P_II-1 specific CD4⁺ T cells.**

Discussion

T cell recognition of HLA-presented antigens plays a central role in the immune surveillance of malignant disease^36,37. Numerous immunotherapeutic approaches aim to utilize respective tumor antigens to therapeutically induce an anti-tumor T cell response^7,8,17,18. This study reports on the identification and characterization of immunogenic neoantigens derived from the DNAJB1-PRKACA fusion transcript, which is the oncogenic driver in all patients suffering from FL-HCC^24,25. Neoepitopes derived from oncogenic gene fusions have been suggested as a superior category of tumor antigens²³. This has been attributed to (I) the clonal expression of oncogenic driver gene fusions^23,38, (II) the higher degree of sequence alteration compared to somatic point mutations, resulting in increased immunogenicity³⁹, and (III) limited down-regulated-based immune escape⁴⁰. In contrast to other fusion transcripts^41,42,43, the DNAJB1-PRKACA fusion generates a defined and unique protein sequence that allows an off-the-shelf application of DNAJB1-PRKACA-derived neoepitopes in cancer immunotherapy. We validated the DNAJB1-PRKACA fusion protein as a source of immunogenic HLA class I and HLA class II-binding antigens inducing both CD8⁺ and CD4⁺ T cell responses, which is required for effective anti-cancer immunity^44,45. Furthermore, we proved the cellular processing and HLA-restricted presentation of DNAJB1-PRKACA neoepitopes, which is an indispensable prerequisite for therapeutically used tumor antigens in particular regarding the distorted correlation between gene expression and HLA-restricted antigen presentation, with only a small fraction of alterations on DNA level resulting in an HLA-presented neoepitope on the tumor cell surface^13,22,46,47. However, for the immunogenic neoepitope P_A*24 natural processing and presentation could not be validated in the DNAJB1-PRKACA transduced HCC cell lines, within the sensitivity limitation of the current state-of-the-art mass spectrometry-based immunopeptidomics. The sensitivity of shotgun mass spectrometric discovery approaches is, even in the context of immense technical improvements in the last decades, still limited⁴⁸. Therefore, we cannot exclude the low-level presentation of the P_A*24.

We further report on the clinical application of a DNAJB1-PRKACA neoepitope-based personalized peptide vaccine adjuvanted with the TLR1/2 agonist XS15³² and Montanide^TM ISA51 VG in a single FL-HCC patient. We observed profound and long-lasting DNAJB1-PRKACA-specific T cell responses showing a clonal expansion of activated CD4⁺ T cells, despite ongoing mTOR inhibition-based immunosuppression with contradictory reported effects on T cells^49,50. Follow-up data until month 18 after vaccination showed the persistence of profound DNAJB1-PRKACA-specific T cell responses. This is in line with the induction of long-term virus-specific T cell responses observed upon XS15-adjuvanted multi-peptide vaccination with our CoVac-1 COVID19 vaccine candidate³⁵. Induction of long-lasting T cell responses was mirrored by so far relapse-free survival of the patient, indicating, in line with other tumor vaccines^17,18, a potential of DNAJB1-PRKACA-based vaccines to combat residual tumor cells. Peptide vaccination of the FL-HCC patient was applied under continued PARP inhibitor treatment, which started 5 months prior to vaccination and did not prevent the occurrence of relapse applied as a single substance. The combination of PARP inhibition and DNAJB1-PRKACA neoepitope-based peptide vaccine could have positively affected the vaccination response and the prolonged relapse-free survival of the FL-HCC patient based on the beneficial impact of DNA-damaging agents on tumor immunogenicity, which was previously reported for the combination of PARP inhibition and ICIs^51,52. We could not detect any vaccine-induced CD8⁺ T cell responses against the DNAJB1-PRKACA fusion protein. Thus, tumor immune surveillance and relapse-free survival observed in the patient after vaccination might be mediated by DNAJB1-PRKACA-specific CD4⁺ T cells alone⁵³, or accompanied by undetected CD8⁺ T cells recognizing other tumor antigens that were induced by the CD4⁺ T cells via epitope spreading⁵⁴. Moreover, the in vitro expansion of patient-derived T cells prior to characterization by flow cytometry and single-cell RNA sequencing might have impacted the phenotypes of these cells.

This low side-effect peptide vaccine represents so far the only DNAJB1-PRKACA-targeted therapy³⁰ and might in the future be applied within combinatorial treatment approaches comprising newly developed small molecules targeting the kinase activity of PRKACA³⁰ and/or ICIs. Combination with the latter is supported by (I) the high expression of PD-L1 in FL-HCC⁵⁵, (II) the detection and response correlation of fusion protein-specific T cells in patients receiving ICIs²³, and (III) the first promising clinical results of neoepitope-based vaccines in combination with ICIs^17,18. Beyond the design of vaccines, DNAJB1-PRKACA-derived neoepitopes could serve as targets for the development of therapeutic approaches using adoptive T cell transfer and TCR engineering. For this purpose, we identified multiple TCRs from in vitro and in vivo induced DNAJB1-PRKACA-specific T cells displaying a unique basic AA motif of the CDR3-α sequence with opposing characteristics regarding chemical groups in comparison to the target peptide core-binding motif⁵⁶.

FL-HCC is a rare tumor disease; however recent reports state that the number of FL-HCC cases might be significantly under-diagnosed^57,58, suggesting a growing number of cases in the future. Furthermore, recent advances in genome sequence analysis^59,60 enable the identification of further cancer entities that express the DNAJB1-PRKACA fusion transcript³⁰. This study identifies the DNAJB1-PRKACA fusion transcript as a prime source for broadly applicable neoepitopes and provides evidence for their immunotherapeutic efficacy in a single FL-HCC patient. Open questions remain if future off-the-shelf T cell-based immunotherapies targeting the DNAJB1-PRKACA fusion will be able to overcome the immunosuppressive microenvironment and other escape mechanisms of tumors⁶¹ to natural immune surveillance and which of the multiple predicted HLA allotypes give rise to DNAJB1-PRKACA neoepitopes in vivo and thus which patients will profit from, e.g. a neoepitope-based vaccine. These issues will be addressed in an upcoming clinical trial evaluating the here-defined DNAJB1-PRKACA neoepitopes adjuvanted with the TLR1/2 agonist XS15 emulsified in Montanide^TM ISA51 VG^32,35 in combination with the PD-L1 antibody atezolizumab in a Phase I vaccine study, recruiting patients with various malignant disease expressing the DNAJB1-PRKACA fusion transcript.

Methods

The study was performed according to the guidelines of the ethics committee at the medical faculty of the Eberhard-Karls-University and at the University Hospital Tübingen (713/2018B02, 406/2019BO2).

Patients and blood samples

Peripheral blood mononuclear cells (PBMCs) from the FL-HCC patient (n = 1) as well as PBMCs from healthy volunteers (HVs, n = 11) were isolated by density gradient centrifugation and stored at −80 °C until further use for subsequent T cell-based assays. Informed consent was obtained in accordance with the Declaration of Helsinki protocol, and donors were not financially compensated. The study was performed according to the guidelines of the local ethics committees (713/2018B02, 406/2019BO2). HLA typing was carried out by the Department of Hematology and Oncology, Tübingen, Germany (Supplementary Table 1).

Personalized peptide vaccine

The personalized vaccine developed and produced by the Good Manufacturing Practices (GMP) Peptide Laboratory of the Department of Immunology, University Tübingen, Germany, is a peptide-based vaccine containing four DNAJB1-PRKACA-derived peptides (Supplementary Table 4) and the adjuvant lipopeptide synthetic TLR1/2 ligand XS15⁸ (manufactured by Bachem AG, Bubendorf, Switzerland) emulsified in Montanide^TM ISA51 VG⁹ (manufactured by Seppic, Paris, France). Vaccine peptides (250 µg/peptide) and XS15 (50 µg) are prepared as a water–oil emulsion 1:1 with Montanide^TM ISA51 VG to yield an injectable volume of 500 µl. Following disclosure and written consent, the patient received a subcutaneous injection of the personalized vaccine in the lower abdomen. The treatment of the patient was performed within a compassionate use program (expanded access) for personalized peptide vaccination under the project: clinicaltrials.gov NCT05014607. The local Ethics Committee (406/2019BO2) and the regulatory authority (Regierungspräsidium Tübingen) approved the project which was conducted under the German Drug Law §13 paragraph 2b. The patient gave written informed consent for vaccine treatment, sequential blood analysis for immunomonitoring, as well as publishing of the related data.

Detection of DNAJB1-PRKACA transcript and sequencing

RNA was extracted from macrodissected 5 µm paraffin sections using the Maxwell® RSC RNA FFPE Kit and the Maxwell® RSC Instrument (Promega, Madison, WI, USA) according to the manufacturer’s instructions. Reverse transcription of RNA and polymerase chain reaction (PCR) of the DNAJB1-PRKACA breakpoint region (forward primer 5′-GTTCAAGGAGATCGCTGAGG-3′, reverse primer 5′- TTCCCGGTCTCCTTGTGTTT-3′) was performed using the QIAGEN OneStep RT-PCR Kit according to the manufacturer’s instructions (Qiagen, Hilden, Germany). To visualize the detection of the DNAJB1-PRKACA fusion, the PCR product was run on an agarose gel. For sequencing, the PCR product was purified (AMPure, Beckman Coulter, Brea, CA, USA) and aliquots were used for the sequencing reaction with 1 μM of the forward or reverse primer and 2 μl of GenomeLab DTCS-Quick Start Master Mix (Beckman Coulter, Brea, CA, USA) in a final volume of 10 μl according to the manufacturer’s protocol. Sequencing reactions were purified (CleanSEQ, Beckman Coulter, Brea, CA, USA) and analyzed in a GenomeLab GeXP Genetic Analysis System, and evaluated by the GenomeLab GeXP software (Beckman Coulter, Brea, CA, USA).

Histology and immunohistochemistry

Tissue specimens were obtained during the routine diagnostic procedure, fixed in 4% formalin, and embedded in paraffin (FFPE). 1.5–3.0 µm-thick sections were cut by using a microtome and stained with haematoxylin and eosin (HE) or with Masson’s trichrome as additional routine staining for liver specimens. Immunohistochemistry was performed on an automated immunostainer (VENTANA BenchMark ULTRA, Ventana Medical Systems, Oro Valley, AZ, USA) according to in-house protocols. Slides were stained by using CK7 (1:2000, Clone OV-TL 12/30, Agilent Dako, Santa Clara, CA, USA) and hepatocyte paraffin1 (Hepar1) (1:1000, Clone OCH1E5, Agilent Dako, Santa Clara, CA, USA) as primary antibodies. Slide scans of the hepatectomy specimen were produced by using the Ventana Scanner DP200 (Ventana Medical Systems, Oro Valley, AZ, USA).

In silico prediction of DNAJB1-PRKACA-derived HLA class I and HLA class II ligands

HLA class I DNAJB1-PRKACA ligand prediction was performed for all possible 8–12 AA long peptide sequences spanning the fusion region using SYFPEITHI 1.0⁶² and NetMHCpan 4.1⁶³ for the 20 most frequent HLA class I allotypes in the European population (tools.iedb.org). HLA class II DNAJB1-PRKACA ligand prediction was performed for all possible 15 AA long peptide sequences spanning the fusion region using NetMHCIIpan 4.0⁶³ with all listed allele combinations.

Quantification of HLA surface expression

HLA surface expression of HCC cell lines was analyzed using the QIFIKIT bead-based quantitative flow cytometric assay (Dako, K0078) according to the manufacturer’s instructions as described before⁶⁴. In brief, samples were stained with the pan-HLA class I-specific monoclonal antibody (mAb) W6/32 (produced in-house) or IgG isotype control (BioLegend, 400202). Flow cytometric analysis was performed on a FACSCanto II Analyzer (BD).

Doxycycline-inducible DNAJB1-PRKACA fusion gene expression in HCC cell lines

The HCC cell lines HLE (obtained from the Japan Collection of Research Bioresources (JCRB) Cell Bank), SMMC-7721 (obtained from Woodland Pharmaceuticals), and HepG2 (obtained from the American Type Culture Collection (ATCC)) were cultivated in Gibco Dulbecco’s Modified Eagle Medium supplemented with 10% fetal calf serum (FCS), penicillin, streptomycin (all from Merck) and plasmocin (Invivogen) at 37 °C and 5% CO₂ in a humidified atmosphere. The SMMC-7721 cell line is under the list of known misidentified cell lines maintained by the International Cell Line Authentication Committee; however, the cell line was selected due to the specific HLA type and was validated by HLA typing. The DNAJB1-PRKACA coding sequence was synthesized by Thermo Fisher, cloned into the pENTR^TM plasmid, and transferred by directional TOPO cloning (pENTR^TM/D-TOPO^TM cloning kit, Invitrogen) into the pInducer20 (Addgene #44012) destination vector. Lentiviral particles were produced in HEK293T cells (obtained from the DSMZ) by calcium-phosphate transfection of the helper plasmids psPAX2, pMD2.G, and either the empty or the DNAJB1-PRKACA coding pInducer20. The transduced HCC cell lines were selected with G418 (Invivogen) for at least 2 weeks. To induce the expression of DNAJB1-PRKACA, the transduced HCC cell lines were treated with 1 µg/ml Doxycycline (Dox) for 24 h (AppliChem). To validate the DNAJB1-PRKACA expression, cells were lysed in lysis buffer (50 mM Tris–HCl pH 7.4, 150 mM NaCl, 1% Triton X-100, 50 mM NaF, 10 mM Na₄P₂O₇, 10 mM Na₄V₂O₇ and complete protease inhibitor cocktail (Roche)). SDS–PAGE and immunoblotting were performed as described previously⁶⁵. For immunoblotting the primary antibodies anti-PKAα cat (1:1000 dilution, Santa Cruz, clone A-2, Cat# sc-28315, RRID:AB_628136), anti-GAPDH (1:2000 dilution, Cell Signaling, clone D16H11, Cat# 5174, RRID:AB_10622025), and anti-Tubulin (1:2000 dilution, Merck, clone DM1A, Cat# 05-829, RRID:AB_310035) were used. HRP-coupled goat anti-rabbit or goat anti-mouse (both Jackson ImmunoResearch) secondary antibodies were used for visualization. Uncropped and unprocessed scans are supplied in the Source Data file.

Isolation of HLA ligands

HLA class I and HLA class II molecules were isolated by standard immunoaffinity purification⁶⁶ using the pan-HLA class I-specific mAb W6/32, the pan-HLA class II-specific mAb Tü-39, and the HLA-DR-specific mAb L243 (all produced in-house) to extract HLA ligands.

Analysis of HLA ligands by liquid chromatography–coupled tandem mass spectrometry (LC–MS/MS)

Peptide samples were separated by reversed-phase liquid chromatography (nanoUHPLC, UltiMate 3000 RSLCnano, Thermo Fisher, Waltham, MA, USA) and subsequently analyzed in an online coupled Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher). Samples were analyzed in three technical replicates. Sample volumes of 5 µl with shares of 20% were injected onto a 75 µm × 2 cm trapping column (Thermo Fisher) at 4 µl/min for 5.75 min. Peptide separation was subsequently performed at 50 °C and a flow rate of 300 nL/min on a 50 µm × 25 cm separation column (PepMap C18, Thermo Fisher) applying a gradient ranging from 2.4% to 32.0% of ACN over the course of 90 min. Eluting peptides were ionized by nanospray ionization and analyzed in the mass spectrometer implementing a top speed (3 s) HCD (Higher-energy C-trap dissociation) method generating fragment spectra with a resolution of 30,000, a mass range limited to 235–1151m/z, and positive charge states 2–5 selected for fragmentation.

Data processing

Data processing was performed as described previously⁶⁷. The Proteome Discoverer (v1.4, Thermo Fisher) was used to integrate the search results of the SequestHT search engine (University of Washington⁶⁸) against the human proteome (Swiss-Prot database, 20,279 reviewed protein sequences, September 27, 2013) accompanied by the complete sequence of the DNAJB1-PRKACA fusion protein. Precursor mass tolerance was set to 5 ppm and fragment mass tolerance was set to 0.02 Da. Oxidized methionine was allowed as a dynamic modification. The false discovery rate (FDR, estimated by the Percolator algorithm 2.04⁶⁹) was limited to 5% for HLA class I and 1% for HLA class II. HLA class I annotation was performed using SYFPEITHI 1.0⁶² and NetMHCpan 4.1⁶³.

Spectrum validation

Spectrum validation of the experimentally eluted peptides was performed by computing the similarity of the spectra with corresponding synthetic peptides measured in a complex matrix. The spectral correlation was calculated between the MS/MS spectra of the eluted and the synthetic peptide⁷⁰.

Amplification of peptide-specific T cells and IFN-γ ELISPOT assay

PBMCs were pulsed either with 1 µg/ml or with 5 µg/ml of HLA class I or HLA class II peptide, respectively. Irrelevant peptides with the respective HLA restrictions were used as negative control (YLLPAIVHI for HLA-A*02 (source protein: DDX5_HUMAN), and ETVITVDTKAAGKGK for HLA class II (source protein: FLNA_HUMAN)). Cells were cultured for 12 days adding 20 U/ml IL-2 (Novartis, Basel, Switzerland) on days 2, 5, and 7. Peptide-stimulated PBMCs were analyzed by IFN-γ enzyme-linked immunospot (ELISPOT) assay on day 12⁶⁷, with anti-IFN-γ antibody (clone 1-D1K, 2 µg/mL, MabTech), anti-IFN-γ biotinylated detection antibody (clone 7 B6 1, 0.3 µg/mL, MabTech), ExtrAvidin-Alkaline Phosphatase (1:1000 dilution, Sigma-Aldrich) and BCIP/NBT (5 bromo 4-chloro 3 indolyl-phosphate/nitro-blue tetrazolium chloride, Sigma-Aldrich). Spots were counted using an ImmunoSpot S6 analyzer (CTL, Cleveland, OH, USA) and T cell responses were considered positive if >10 spots/500,000 cells were counted, and the mean spot count was at least three-fold higher than the mean spot count of the negative control.

Refolding

Biotinylated HLA:peptide complexes were manufactured as described previously⁷¹ and tetramerized using PE-conjugated streptavidin (Invitrogen) at a 4:1 molar ratio.

Induction of peptide-specific CD8⁺ T cells with aAPCs

Priming of peptide-specific cytotoxic T lymphocytes was conducted using aAPCs as described previously⁷². In detail, 800,000 streptavidin-coated microspheres (Bangs Laboratories, Fishers, IN, USA) were loaded with 200 ng biotinylated HLA:peptide monomer and 600 ng biotinylated anti-human CD28 monoclonal antibody (clone 9.3, in-house production). CD8⁺ T cells were cultured with 4.8 U/µl IL-2 (R&D Systems, Minneapolis, MN, USA) and 1.25 ng/ml IL-7 (PromoKine, Heidelberg, Germany). Weekly stimulation with aAPCs (200,000 aAPCs per 1 × 10⁶ CD8⁺ T cells) and 5 ng/ml IL-12 (PromoKine) was performed for four cycles.

Cytokine, surface marker and tetramer staining

Functionality of peptide-specific CD4⁺ and CD8⁺ T cells was analyzed by surface marker and intracellular cytokine staining (ICS) as described previously^73,74. Cells were pulsed with 10 μg/ml of respective peptide and incubated with 10 μg/ml Brefeldin A (Sigma-Aldrich, Saint Louis, MO, USA) and 10 μg/ml GolgiStop (BD, Franklin Lakes, NJ, USA) for 12–16 h. Staining was performed using Cytofix/Cytoperm (BD), Aqua live/dead (1:400 dilution, Invitrogen), APC/Cy7 anti-human CD4 (1:100 dilution, BioLegend, Cat# 300518, RRID: AB_314086), PE/Cy7 anti-human CD8 (1:400 dilution, Beckman Coulter, Cat# 737661, RRID: AB_1575980), Pacific Blue anti-human TNF (1:120 dilution, BioLegend, Cat# 502920, RRID: AB_528965), FITC anti-human CD107a (1:100 dilution, BioLegend, Cat# 328606, RRID: AB_1186036), APC anti-human IL-2 (1:40 dilution, BioLegend, Cat# 500309, RRID: AB_315096), and PE anti-human IFN-γ mAB (1:200 dilution, BioLegend, Cat# 506507, RRID: AB_315440). PMA and ionomycin (Sigma-Aldrich) served as a positive control. Negative control peptides with matching HLA restrictions were used: YLLPAIVHI for HLA-A*02 (source protein: DDX5_HUMAN), KYPENFFLL for HLA-A*24 (source protein: PP1G_HUMAN), EEFGRAFSF for HLA-B*44 (source protein: HLA-DP_HUMAN), and ETVITVDTKAAGKGK for HLA class II (source protein: FLNA_HUMAN). Gating strategies applied for the analyses of flow cytometry-acquired data are provided in Supplementary Figs. S6, S7, and S8.

The frequency of peptide-specific CD8⁺ T cells after aAPC-based priming was determined by Aqua live/dead (1:400 dilution, Invitrogen), PE/Cy7 anti-human CD8 (1:400 dilution, Beckman Coulter, Cat# 737661, RRID: AB_1575980) and HLA:peptide tetramer-PE staining. Cells of the same donor primed with an irrelevant control peptide TYSEKTTLF (source protein: MUC16_HUMAN) and stained with the tetramer containing the test peptide were used as a negative control. The priming was considered successful if the frequency of peptide-specific CD8⁺ T cells was ≥0.1% of CD8⁺ T cells within the viable single cell population and at least three-fold higher than the frequency of peptide-specific CD8⁺ T cells in the negative control. The same evaluation criteria were applied to ICS results. Samples were analyzed on a FACS Canto II cytometer (BD). The gating strategy applied for tetramer staining analysis of flow cytometry-acquired data is provided in Supplementary Fig. S9.

Cytotoxicity assays

Peptide-specific CD8⁺ T cells were analyzed for their capacity to induce peptide-specific target cell lysis in the flow cytometry-based VITAL assay²². Autologous CD8⁻ target cells were either loaded with the P_A*24 peptide or the HLA-matched negative peptide KYPENFFLL (source protein: PP1G_HUMAN) and labeled with CFSE or FarRed (Life Technologies, Carlsbad, CA, USA), respectively. The P_A*24-specific effector cells were added in the indicated effector-to-target ratios. Specific lysis of peptide-loaded CD8⁻ target cells was calculated relative to control targets.

Induction of peptide-specific CD4⁺ T cells with peptide-loaded moDCs

For the differentiation of monocyte-derived dendritic cells (moDCs) CD14⁺ cells were isolated from PBMC using magnetic-activated cell sorting (MACS; Miltenyi, Bergisch Gladbach, Germany), and subsequently cultivated in X-VIVO^TM 15 serum-free hematopoietic cell medium supplemented with penicillin, streptomycin, GM-CSF (1000 IU/ml; Miltenyi, Bergisch Gladbach, Germany), and IL-4 (400 IU/ml; Miltenyi, Bergisch Gladbach, Germany) at 37 °C and 5% CO₂ in a humidified atmosphere for seven days. Differentiated moDCs were maturated by adding LPS (100 ng/ml; Invivogen, Toulouse, France) to the cell culture medium for 24 h and checked for cell surface marker expression using FITC anti-human CD80 (1:40 dilution, Biolegend, Cat# 305206), BV711 anti-human HLA-DR (1:100 dilution, Biolegend, Cat# 307644), and BV605 anti-human CD86 (1:400 dilution, Biolegend, Cat# 374214). The gating strategy applied for the analysis of flow cytometry-acquired data is provided in Supplementary Fig. S10. Mature moDCs were incubated with the P_II-1 peptide for 2 h prior to CD4⁺ T cell stimulation. CD4⁺ cells were isolated from PBMC of the same healthy volunteer (HV) using MACS and subsequently cultivated with penicillin, streptomycin, IL-2 (10 U/ml; R&D Systems, Minneapolis, MN, USA), and IL-7 (2.5 ng/ml; PromoKine, Heidelberg, Germany), at 37 °C and 5% CO₂ in a humidified atmosphere. Cultured CD4⁺ cells were stimulated weekly for a total of four weeks with peptide-loaded mature moDCs and IL-12 (5 ng/ml; PromoKine, Heidelberg, Germany). The functionality of peptide-specific CD4⁺ T cells was analyzed by ICS.

Antigen loading of mature moDCs

For the generation of tumor lysate, HCC cell lines transduced with the empty or the DNAJB1-PRKACA coding plasmid were treated with IFN-γ and Dox for 24 h. The treated cells were harvested, washed with PBS, subjected to five freeze–thaw cycles, irradiated with 30 Gy, and sonicated for 2 min. The clear supernatant was then added to the cell culture medium of maturated moDCs of HV3, HV4, and HV5 for 24 h, and the antigen-loaded mature moDCs were subsequently harvested for HLA immunoprecipitation.

Software and statistical analysis

The HLA allotype distribution and population coverage of the European and world population were calculated with the IEDB population coverage tool (www.iedb.org). All figures and statistical analyses were generated using GraphPad Prism 9.2.0 (GraphPad Software). P values of <0.05 were considered statistically significant. All flow cytometry-acquired data were analyzed with FlowJo 10.0.8 (FlowJo™ Software).

Single-cell immune profiling

Peptide-specific CD8⁺ T cells of HVs induced by in vitro aAPC-based priming or in vitro amplified bulk memory CD4⁺ T cells of the FL-HCC patient were sorted by fluorescence-activated cell sorting (FACS), counted, and washed in 0.04% BSA/PBS according to the 10× Genomics cell preparation protocol. Single cells were partitioned into Gel Beads-in-Emulsion (GEMs) together with 10× barcoded Gel Beads and reverse transcriptase enzymatic reaction using the Chromium Controller instrument (10× Genomics, Pleasanton, CA, USA). Single-cell gene expression libraries and single-cell T-cell receptor (VDJ) libraries were then prepared using the Chromium Next GEM Single Cell 5′Kit v2 (10× Genomics, Pleasanton, CA, USA) and the Chromium Single Cell Human TCR Amplification Kit (10× Genomics, Pleasanton, CA, USA) according to the manufacturer’s instructions. Libraries were pooled and sequenced on a NextSeq 550 (Illumina, San Diego, CA, USA) at 28,806, 138,975, and 3519 mean reads per cell, respectively. Samples were demultiplexed using bcl2fastq version 2.20.0.422 (Illumina, San Diego, CA, USA). Barcode processing, alignment, VDJ annotation, and single-cell 5′gene counting were performed using Cell Ranger Software version 6.0.1 (10× Genomics, Pleasanton, CA, USA). Further data processing, visualization, and analysis were done using scanpy and scirpy^75,76 for each sample separately. Cells with unique gene counts <200 and without VDJ sequence associated, as well as cells with >10% of mitochondrial genes, were removed from the analysis, keeping 474 cells (FL-HCC01), 115 cells (HV1), and 3338 cells (HV2), respectively. Data was log-normalized to a size factor of 10,000. Only highly variable genes were considered for linear dimensional reduction and were defined by a minimum mean expression of 0.0125, a maximum mean expression of 3, and a minimum dispersion of 0.5. The effect of total counts was regressed out and counts were scaled to unit variance and zero mean for each gene. The dimensionality reduction was done using principal component analysis (PCA). The neighborhood graph and UMAP embedding were computed using the rapids implementation of the UMAP algorithm⁷⁷ for 10 neighbors and the first 10 principal components (n_neighbors = 10, n_PC = 10). Unsupervised clustering was performed using the rapids implementation of the Louvain algorithm. Functional enrichment for the hallmarks of cancer gene sets⁷⁸ was performed using the decoupler’s run_ora function with default parameters⁷⁹. This analysis was performed on the log normalized counts of all genes present in more than one cell for each sample.

Clustering of CDR3-α and CDR3-β

Clustering of variable sequences of CDR3-α and CDR3-β was conducted using GibbsCluster 2.0⁸⁰ with MHC class I configurations and a specified core size of the smallest variable sequence in the positive dataset. The negative dataset of not binding CD3 sequences of CD8⁺ T cells to the HLA class I target peptide was retrieved from the VDJdb database (https://vdjdb.cdr3.net) containing only human sequences associated with HLA-A*24:02. For the HLA class II target peptide sequences of CD4⁺ T cells that did not show an in vitro response was defined as a negative dataset. The underlying position-specific scoring matrixes (PSSMs) of the clustering were used to conduct the position-wise Pearson correlation between positive and negative datasets. Correlation significance was assessed using the Pearson correlation test. Similarity and identity of variable CD3 sequences were computed using a pairwise sequence alignment by ClustalW with standard configurations (https://www.ebi.ac.uk/Tools/msa/clustalo/).

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The mass spectrometry proteomics data generated in this study have been deposited in the ProteomeXchange Consortium database via the PRIDE⁸¹ partner repository under dataset identifier PXD029882. The single-cell RNA sequencing data generated in this study have been deposited in the NCBI’s Gene Expression Omnibus database with the dataset identifier GSE210337. The remaining data are available within the Article, Supplementary Information or Source Data file. Source data are provided with this paper.

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Acknowledgements

We thank Richard Schaad, Ulrike Schmidt, Ulrich Wulle, Beate Pömmerl, and Claudia Falkenburger for technical support and the Flow Cytometry Core Facility Tübingen for cell sorting. This work was supported by the Deutsche Forschungsgemeinschaft under Germany’s Excellence Strategy (Grant EXC2180-390900677 (H.-G.R., H.R.S., and J.S.W.), and CIBSS—EXC 2189—Project ID 390939984 (N.K.)), the German Cancer Consortium (DKTK) (H.-G.R., H.R.S., M. Boerries, and J.S.W.), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, Grant WA4608/1-2 (J.S.W.); CRC/TRR167-Project ID 259373024/Z01 (M. Boerries); CRC1160-Project ID 256073931/Z02 (M. Boerries); CRC 1453-Project ID 431984000/S1 (M. Boerries); SFB1479-Project ID 441891347/S1 (M. Boerries); and SFB-1479 – Project ID: 441891347 (N.K.)), the Wilhelm Sander Stiftung (Grant 2016.177.3 (J.S.W.)), the José Carreras Leukämie-Stiftung (Grant DJCLS 05R/2017 (J.S.W.)), the Bundesministerium für Bildung und Forschung (BMBF, FKZ:01KI20130 (J.S.W.); FKZ:16LW0005 (J.S.W.); FKZ:01DP21014 (J.S.W.); FKZ 01ZZ1801B (M. Boerries)), the Else Kröner Fresenius Stiftung, Translatorik Programm (Grant 2022_EKTP03 (J.S.W.)), the Deutsche Krebshilfe (German Cancer Aid, 70114948 (J.S.W.)), the Zentren für Personalisierte Medizin (ZPM, (M. Boerries, J.S.W.)), the Applied Clinical Research program (AKF, (J.S.W.)), and the Fortüne Program of the University of Tübingen (Fortüne number 2451-0-0 (S.S.)).

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Open Access funding enabled and organized by Projekt DEAL.

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Authors and Affiliations

Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
Jens Bauer, Yacine Maringer, Tatjana Bilich, Annika Nelde, Marissa Dubbelaar, Jonas Scheid, Marcel Wacker, Sarah Schroeder, Jonas Rieth, Monika Denk, Marion Richter & Juliane S. Walz
Department of Immunology, Institute for Cell Biology, University of Tübingen, Tübingen, Germany
Jens Bauer, Yacine Maringer, Tatjana Bilich, Annika Nelde, Marissa Dubbelaar, Jonas Scheid, Marcel Wacker, Sarah Schroeder, Jonas Rieth, Monika Denk, Marion Richter, Hans-Georg Rammensee & Juliane S. Walz
Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Tübingen, Germany
Jens Bauer, Yacine Maringer, Philip Bucher, Tatjana Bilich, Annika Nelde, Marissa Dubbelaar, Marcel Wacker, Jonas S. Heitmann, Michael Bitzer, Judith Feucht, Helmut R. Salih, Hans-Georg Rammensee, Stephan Hailfinger & Juliane S. Walz
Department of Internal Medicine I, Medical Center - University of Freiburg, Faculty of Medicine, Albert Ludwigs University, Freiburg, Germany
Natalie Köhler & Melissa Zwick
CIBSS – Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
Natalie Köhler
Department of Pediatric Hematology and Oncology, University Children’s Hospital, University of Tübingen, Tübingen, Germany
Philip Bucher, Ursula Holzer, Martin Ebinger, Ines B. Brecht & Judith Feucht
Faculty of Biology, Albert-Ludwigs-Universität, Freiburg, Germany
Melissa Zwick & Severin Dicks
Institute of Medical Bioinformatics and Systems Medicine, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
Severin Dicks & Melanie Boerries
Quantitative Biology Center (QBiC), University of Tübingen, Tübingen, Germany
Marissa Dubbelaar & Jonas Scheid
Clinical Collaboration Unit Translational Immunology, German Cancer Consortium (DKTK), Department of Internal Medicine, University Hospital Tübingen, Tübingen, Germany
Jonas S. Heitmann, Helmut R. Salih & Juliane S. Walz
Department of Otorhinolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
Sarah Schroeder
German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner site Tübingen, Tübingen, Germany
Monika Denk, Marion Richter, Michael Bitzer, Hans-Georg Rammensee & Juliane S. Walz
Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tübingen, Tübingen, Germany
Reinhild Klein
Department of Pathology and Neuropathology, University Hospital Tübingen, Tübingen, Germany
Irina Bonzheim & Julia Luibrand
Department of Internal Medicine I, University Hospital Tübingen, Tübingen, Germany
Michael Bitzer
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ) Partner Site, Freiburg, Germany
Melanie Boerries
Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
Stephan Hailfinger

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Jens Bauer
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Natalie Köhler
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Philip Bucher
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Jonas Scheid
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Marcel Wacker
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Sarah Schroeder
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Jonas Rieth
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Martin Ebinger
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Ines B. Brecht
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Michael Bitzer
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Judith Feucht
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Contributions

J.B. and J.S.W. designed the study. H.-G.R., H.R.S., S.H., M. Boerries, and N.K. provided feedback on the study design. J.B., A.N., and M.W. performed immunopeptidome experiments. J.B., Y.M., T.B., and J.R. conducted in vitro T cell experiments. M.Z., S.D., and N.K. conducted single-cell RNA sequencing. P.B., S.H., J.F., and J.B. created the DNAJB1-PRKACA fusion gene, expression model. J.B., S.D., M. Dubbelaar, and J.S. conducted data analyses. M. Denk and M.R. conducted the production of the peptide vaccine. S.S., R.K., I.B.B., J.L., U.H., M.E., I.B., J.S.H., M. Bitzer, and J.S.W. conducted patient data and sample collection as well as medical evaluation and analysis. J.B. created the figures. J.B. and J.S.W. drafted the manuscript. All authors supported the review of the manuscript.

Corresponding author

Correspondence to Juliane S. Walz.

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Competing interests

J.B., N.K., Y.M., M.Z., S.D., M. Boerries, and J.S.W. are listed as inventors on a patent related to the DNAJB1-PRKACA T cell epitopes and TCRs (Peptides and antigen binding proteins for use in immunotherapy against fibrolamellar HCC and other cancers, Application number: EP21214728.4). H.-G.R. is listed as an inventor on a patent related to the adjuvant XS15 (Adjuvant for the induction of a cellular immune response: DE102016005550.2). The other authors declare no competing interests.

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Bauer, J., Köhler, N., Maringer, Y. et al. The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma. Nat Commun 13, 6401 (2022). https://doi.org/10.1038/s41467-022-33746-3

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Received: 29 July 2022
Accepted: 30 September 2022
Published: 27 October 2022
DOI: https://doi.org/10.1038/s41467-022-33746-3

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