optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Meeting report: Considerations for trial design and endpoints in licensing therapeutic HPV16/18 vaccines to prevent cervical cancer.

Cervical cancer is a major cause of morbidity and mortality globally with a disproportionate impact on women in low- and middle-income countries. In 2021, the World Health Organization (WHO) called for increased vaccination, screening, and treatment to eliminate cervical cancer. However, even with widespread rollout of human papillomavirus (HPV) prophylactic vaccines, millions of women who previously acquired HPV infections will remain at risk for progression to cancer for decades to come. The development and licensing of an affordable, accessible therapeutic HPV vaccine, designed to clear or control carcinogenic HPV and/or to induce regression precancer could significantly contribute to the elimination efforts, particularly benefiting those who missed out on the prophylactic vaccine. One barrier to development of such vaccines is clarity around the regulatory pathway for licensure. In Washington, D.C. on September 12-13, 2023, a meeting was convened to provide input and guidance on trial design with associated ethical and regulatory considerations. This report summarizes the discussion and conclusions from the meeting. Expert presentation topics included the current state of research, potential regulatory challenges, WHO preferred product characteristics, modeling results of impact of vaccine implementation, epidemiology and natural history of HPV infection, immune responses related to viral clearance and/or precancer regression including potential biomarkers, and ethical considerations. Panel discussions were held to explore specific trial design recommendations to support the licensure process for two vaccine indications: (1) treatment of prevalent HPV infection or (2) treatment of cervical precancers. Discussion covered inclusion/exclusion criteria, study endpoints, sample size and power, safety, study length, and additional data needed, which are reported here. Further research of HPV natural history is needed to address identified gaps in regulatory guidance, especially for therapeutic vaccines intended to treat existing HPV infections.

Transcriptome-based identification of tumor-reactive and bystander CD8+ T cell receptor clonotypes in human pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is generally refractory to immune checkpoint blockade, although patients with genetically unstable tumors can show modest therapeutic benefit. We previously demonstrated the presence of tumor-reactive CD8+ T cells in PDAC samples. Here, we charted the tumor-infiltrating T cell repertoire in PDAC by combining single-cell transcriptomics with functional testing of T cell receptors (TCRs) for reactivity against autologous tumor cells. On the basis of a comprehensive dataset including 93 tumor-reactive and 65 bystander TCR clonotypes, we delineated a gene signature that effectively distinguishes between these T cell subsets in PDAC, as well as in other tumor indications. This revealed a high frequency of tumor-reactive TCR clonotypes in three genetically unstable samples. In contrast, the T cell repertoire in six genetically stable PDAC tumors was largely dominated by bystander T cells. Nevertheless, multiple tumor-reactive TCRs were successfully identified in each of these samples, thereby providing a perspective for personalized immunotherapy in this treatment-resistant indication.

Characterization of DoTc2 4510-Identifying HPV16 Presence in a Cervical Carcinoma Cell Line Previously Considered to Be HPV-Negative.

Cervical cancer is the fourth leading cause of cancer deaths in women, with over 340,000 women dying from this disease in 2020. Almost all cases have an underlying persistent infection with an oncogenic high-risk type of human papillomavirus (HPV), mainly HPV16. While cervical squamous cell carcinoma is hardly ever HPV-negative, a small subset of adenocarcinoma exhibits absence of HPV, even after disproval of false-negative testing results due to low viral load. This proportion is evident in many cervical cancer studies and is reflected in the repertoire of model cell lines commonly used in research. As the viral origin of cervical cancer makes it a disease preventable and potentially treatable by immunotherapeutic approaches, it is the focus of many studies. For pertinent research, both a broad set of HPV-infected cervical carcinoma models are required, as well as stringent negative controls. A ubiquitously used HPV-negative cervical adenocarcinoma cell line is C-33A. Another cervical cancer cell line is available for purchase from the American Type Culture Collection (ATCC), namely DoTc2 4510, described to be HPV-negative and thus as a model for a rare gynecological malignancy. Here, we present findings proving that DoTc2 4510 is, in fact, an HPV16-positive cell line. This we assessed using a highly sensitive nested multiplex PCR protocol adapted for the identification of 12 carcinogenic HPV types and a second PCR targeting the HPV16 oncogenes E6 and E7. Subsequently, the protein expression of E6 and E7 was examined, as well as the expression of their target proteins p53, p21, and p16INK4a, to assess E6/E7 functionality. Finally, to attest to the survival dependence of DoTc2 4510 cells on HPV16, we performed an HPV16 E6/E7-targeted siRNA knock-down, which indeed led to senescence induction. Together, these findings demonstrate that DoTc2 4510 is an HPV16-transformed cell line.

Definition and Characterization of SOX11-Derived T Cell Epitopes towards Immunotherapy of Glioma.

The transcription factor SOX11 is a tumor-associated antigen with low expression in normal cells, but overexpression in glioblastoma (GBM). So far, conventional surgery, chemotherapy, and radiotherapy have not substantially improved the dismal prognosis of relapsed/refractory GBM patients. Immunotherapy is considered a promising strategy against GBM, but there is a fervent need for better immunotargets in GBM. To this end, we performed an in silico prediction study on SOX11, which primarily yielded ten promising HLA-A*0201-restricted peptides derived from SOX11. We defined a novel peptide FMACSPVAL, which had the highest score according to in silico prediction (6.02 nM by NetMHC-4.0) and showed an exquisite binding affinity to the HLA-A*0201 molecule in the peptide-binding assays. In the IFN-γ ELISPOT assays, FMACSPVAL demonstrated a high efficiency for generating SOX11-specific CD8+ T cells. Nine out of thirty-two healthy donors showed a positive response to SOX11, as assessed by the ELISPOT assays. Therefore, this novel antigen peptide epitope seems to be promising as a target for T cell-based immunotherapy in GBM. The adoptive transfer of in vitro elicited SOX11-specific CD8+ T cells constitutes a potential approach for the treatment of GBM patients.

Development of an Orthotopic HPV16-Dependent Base of Tongue Tumor Model in MHC-Humanized Mice.

Head and neck squamous cell carcinomas (HNSCC) caused by infections with high-risk human papillomaviruses (HPV) are responsible for an increasing number of head and neck cancers, particularly in the oropharynx. Despite the significant biological differences between HPV-driven and HPV-negative HNSCC, treatment strategies are similar and not HPV targeted. HPV-driven HNSCC are known to be more sensitive to treatment, particularly to radiotherapy, which is at least partially due to HPV-induced immunogenicity. The development of novel therapeutic strategies that are specific for HPV-driven cancers requires tumor models that reflect as closely as possible the characteristics and complexity of human tumors and their response to treatment. Current HPV-positive cancer models lack one or more hallmarks of their human counterpart. This study presents the development of a new HPV16 oncoprotein-dependent tumor model in MHC-humanized mice, modeling the major biologic features of HPV-driven tumors and presenting HLA-A2-restricted HPV16 epitopes. Furthermore, this model was developed to be orthotopic (base of tongue). Thus, it also reflects the correct tumor microenvironment of HPV-driven HNSCC. The cancer cells are implanted in a manner that allows the exact control of the anatomical location of the developing tumor, thereby homogenizing tumor growth. In conclusion, the new model is suited to study HPV16-specific therapeutic vaccinations and other immunotherapies, as well as tumor-targeted interventions, such as surgery or radiotherapy, or a combination of all these modalities.

MediMer: a versatile do-it-yourself peptide-receptive MHC class I multimer platform for tumor neoantigen-specific T cell detection.

Peptide-loaded MHC class I (pMHC-I) multimers have revolutionized our capabilities to monitor disease-associated T cell responses with high sensitivity and specificity. To improve the discovery of T cell receptors (TCR) targeting neoantigens of individual tumor patients with recombinant MHC molecules, we developed a peptide-loadable MHC class I platform termed MediMer. MediMers are based on soluble disulfide-stabilized ß2-microglobulin/heavy chain ectodomain single-chain dimers (dsSCD) that can be easily produced in large quantities in eukaryotic cells and tailored to individual patients' HLA allotypes with only little hands-on time. Upon transient expression in CHO-S cells together with ER-targeted BirA biotin ligase, biotinylated dsSCD are purified from the cell supernatant and are ready to use. We show that CHO-produced dsSCD are free of endogenous peptide ligands. Empty dsSCD from more than 30 different HLA-A,B,C allotypes, that were produced and validated so far, can be loaded with synthetic peptides matching the known binding criteria of the respective allotypes, and stored at low temperature without loss of binding activity. We demonstrate the usability of peptide-loaded dsSCD multimers for the detection of human antigen-specific T cells with comparable sensitivities as multimers generated with peptide-tethered ß2m-HLA heavy chain single-chain trimers (SCT) and wild-type peptide-MHC-I complexes prior formed in small-scale refolding reactions. Using allotype-specific, fluorophore-labeled competitor peptides, we present a novel dsSCD-based peptide binding assay capable of interrogating large libraries of in silico predicted neoepitope peptides by flow cytometry in a high-throughput and rapid format. We discovered rare T cell populations with specificity for tumor neoepitopes and epitopes from shared tumor-associated antigens in peripheral blood of a melanoma patient including a so far unreported HLA-C*08:02-restricted NY-ESO-1-specific CD8+ T cell population. Two representative TCR of this T cell population, which could be of potential value for a broader spectrum of patients, were identified by dsSCD-guided single-cell sequencing and were validated by cognate pMHC-I multimer staining and functional responses to autologous peptide-pulsed antigen presenting cells. By deploying the technically accessible dsSCD MHC-I MediMer platform, we hope to significantly improve success rates for the discovery of personalized neoepitope-specific TCR in the future by being able to also cover rare HLA allotypes.

Effects of hypoxia on antigen presentation and T cell-based immune recognition of HPV16-transformed cells.

Attempts to develop a therapeutic vaccine against human papillomavirus (HPV)-induced malignancies have mostly not been clinically successful to date. One reason may be the hypoxic microenvironment present in most tumors, including cervical cancer. Hypoxia dysregulates the levels of human leukocyte antigen (HLA) class I molecules in different tumor entities, impacts the function of cytotoxic T cells, and leads to decreased protein levels of the oncoproteins E6 and E7 in HPV-transformed cells. Therefore, we investigated the effect of hypoxia on the presentation of HPV16 E6- and E7-derived epitopes in cervical cancer cells and its effect on epitope-specific T cell cytotoxicity. Hypoxia induced downregulation of E7 protein levels in all analyzed cell lines, as assessed by Western blotting. However, contrary to previous reports, no perturbation of antigen processing and presentation machinery (APM) components and HLA-A2 surface expression upon hypoxia treatment was detected by mass spectrometry and flow cytometry, respectively. Cytotoxicity assays performed in hypoxic conditions showed differential effects on the specific killing of HPV16-positive cervical cancer cells by epitope-specific CD8+ T cell lines in a donor- and peptide-specific manner. Effects of hypoxia on the expression of PD-L1 were ruled out by flow cytometry analysis. Altogether, our results under hypoxia show a decreased expression of E6 and E7, but an intact APM, and epitope- and donor-dependent effects on T cell cytotoxicity towards HPV16-positive target cells. This suggests that successful immunotherapies can be developed for hypoxic HPV-induced cervical cancer, with careful choice of target epitopes, and ideally in combination with hypoxia-alleviating measures.

The Importance of Being Presented: Target Validation by Immunopeptidomics for Epitope-Specific Immunotherapies.

Presentation of tumor-specific or tumor-associated peptides by HLA class I molecules to CD8+ T cells is the foundation of epitope-centric cancer immunotherapies. While often in silico HLA binding predictions or in vitro immunogenicity assays are utilized to select candidates, mass spectrometry-based immunopeptidomics is currently the only method providing a direct proof of actual cell surface presentation. Despite much progress in the last decade, identification of such HLA-presented peptides remains challenging. Here we review typical workflows and current developments in the field of immunopeptidomics, highlight the challenges which remain to be solved and emphasize the importance of direct target validation for clinical immunotherapy development.

Light contamination in stable isotope-labelled internal peptide standards is frequent and a potential source of false discovery and quantitation error in proteomics.

In mass spectrometry-based proteomics, heavy internal standards are used to validate target peptide detections and to calibrate peptide quantitation. Here, we report light contamination present in heavy labelled synthetic peptides of high isotopic enrichment. Application of such peptides as assay-internal standards potentially compromises the detection and quantitation especially of low abundant cellular peptides. Therefore, it is important to adopt guidelines to prevent false-positive identifications of endogenous light peptides as well as errors in their quantitation from biological samples.

The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution.

The immune system can recognize and attack cancer cells, especially those with a high load of mutation-induced neoantigens. Such neoantigens are abundant in DNA mismatch repair (MMR)-deficient, microsatellite-unstable (MSI) cancers. MMR deficiency leads to insertion/deletion (indel) mutations at coding microsatellites (cMS) and to neoantigen-inducing translational frameshifts. Here, we develop a tool to quantify frameshift mutations in MSI colorectal and endometrial cancer. Our results show that frameshift mutation frequency is negatively correlated to the predicted immunogenicity of the resulting peptides, suggesting counterselection of cell clones with highly immunogenic frameshift peptides. This correlation is absent in tumors with Beta-2-microglobulin mutations, and HLA-A*02:01 status is related to cMS mutation patterns. Importantly, certain outlier mutations are common in MSI cancers despite being related to frameshift peptides with functionally confirmed immunogenicity, suggesting a possible driver role during MSI tumor evolution. Neoantigens resulting from shared mutations represent promising vaccine candidates for prevention of MSI cancers.

Inducing Immunity Where It Matters: Orthotopic HPV Tumor Models and Therapeutic Vaccinations.

Anogenital and oropharyngeal cancers caused by human papillomavirus (HPV) infections account for 4.5% of all cancer cases worldwide. So far, only the initial infection with selected high-risk types can be prevented by prophylactic vaccination. Already existing persistent HPV infections, however, can currently only be treated by surgical removal of resulting lesions. Therapeutic HPV vaccination, promoting cell-based anti-HPV immunity, would be ideal to eliminate and protect against HPV-induced lesions and tumors. A multitude of vaccination approaches has been tested to date, many of which led to high amounts of HPV-specific T cells in vivo. However, growing evidence suggests that not the induction of systemic but of local immunity is paramount for tackling mucosal infections and tumors. Therefore, recent therapeutic vaccination studies have focused on how to induce tissue-resident T cells in the anogenital and oropharyngeal mucosa. These approaches include direct mucosal vaccinations and influencing the migration of systemic T cells toward the mucosa. The efficacy of these new vaccination approaches is best tested in vivo by utilizing orthotopic tumor models, i.e. HPV-positive tumors being located in the animal's mucosa. In line with this, we here review existing HPV tumor models and describe two novel tumorigenic cell lines for the MHC-humanized mouse model A2.DR1. These were used for the establishment of an HPV16 E6/E7-positive vaginal tumor model, suitable for testing therapeutic vaccines containing HLA-A2-restricted HPV16-derived epitopes. The newly developed MHC-humanized orthotopic HPV16-positive tumor model is likely to improve the translatability of in vivo findings to the clinical setting.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 × 10-16), including CD8+ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.

Enhanced Radiation Sensitivity of Human Papillomavirus-Driven Head and Neck Cancer: Focus on Immunological Aspects.

Head and neck squamous cell carcinomas (HNSCC), emerging in the mucosa of the upper aerodigestive tract, are associated with either the classical risk factors, tobacco and alcohol consumption, or with infections with high-risk types of the human papillomavirus (HPV). Depending on the involvement of HPV, HNSCC follow different pathways of carcinogenesis and show distinct clinical presentations regarding survival, prognosis and treatment response. For instance, HPV-driven HNSCC exhibit an enhanced radiation response compared to their typically radioresistant HPV-negative counterparts. Although radiosensitivity of HNSCC has been studied by many research groups, the major causes for the difference in radiation responses between HPV-driven and HPV-negative HNSCC are still an open question. In this mini review, we discuss the reported cellular and immunological factors involved in the enhanced radiation response in HPV-driven HNSCC, focusing on the vital role of the immune response in the outcome of HNSCC radiotherapy.

Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC-Peptide Binding Data Set.

Knowing whether a protein can be processed and the resulting peptides presented by major histocompatibility complex (MHC) is highly important for immunotherapy design. MHC ligands can be predicted by in silico peptide-MHC class-I binding prediction algorithms. However, prediction performance differs considerably, depending on the selected algorithm, MHC class-I type, and peptide length. We evaluated the prediction performance of 13 algorithms based on binding affinity data of 8- to 11-mer peptides derived from the HPV16 E6 and E7 proteins to the most prevalent human leukocyte antigen (HLA) types. Peptides from high to low predicted binding likelihood were synthesized, and their HLA binding was experimentally verified by in vitro competitive binding assays. Based on the actual binding capacity of the peptides, the performance of prediction algorithms was analyzed by calculating receiver operating characteristics (ROC) and the area under the curve (AROC). No algorithm outperformed others, but different algorithms predicted best for particular HLA types and peptide lengths. The sensitivity, specificity, and accuracy of decision thresholds were calculated. Commonly used decision thresholds yielded only 40% sensitivity. To increase sensitivity, optimal thresholds were calculated, validated, and compared. In order to make maximal use of prediction algorithms available online, we developed MHCcombine, a web application that allows simultaneous querying and output combination of up to 13 prediction algorithms. Taken together, we provide here an evaluation of peptide-MHC class-I binding prediction tools and recommendations to increase prediction sensitivity to extend the number of potential epitopes applicable as targets for immunotherapy.

A non-functional neoepitope specific CD8+ T-cell response induced by tumor derived antigen exposure in vivo.

Cancer-associated mutations, mostly single nucleotide variations, can act as neoepitopes and prime targets for effective anti-cancer T-cell immunity. T cells recognizing cancer mutations are critical for the clinical activity of immune checkpoint blockade (ICB) and they are potent vaccine antigens. High frequencies of mutation-specific T cells are rarely spontaneously induced. Hence, therapies that broaden the tumor specific T-cell response are of interest. Here, we analyzed neoepitope-specific CD8+ T-cell responses mounted either spontaneously or after immunotherapy regimens, which induce local tumor inflammation and cell death, in mice bearing tumors of the widely used colon carcinoma cell line CT26. A comprehensive immune reactivity screening of 2474 peptides covering 628 transcribed CT26 point mutations was conducted. All tested treatment regimens were found to induce a single significant CD8+ T-cell response against a non-synonymous D733A point mutation in the Smc3 gene. Surprisingly, even though Smc3 D733A turned out to be the immune-dominant neoepitope in CT26 tumor bearing mice, neither T cells specific for this neoepitope nor their T cell receptors (TCRs) were able to recognize or lyse tumor cells. Moreover, vaccination with the D733A neoepitope did not result in anti-tumoral activity despite induction of specific T cells. This is to our knowledge the first report that neoepitope specific CD8+ T cells primed by tumor-released antigen exposure in vivo can be functionally irrelevant.

Therapeutic vaccination using minimal HPV16 epitopes in a novel MHC-humanized murine HPV tumor model.

Therapeutic vaccination as a treatment option for HPV-induced cancers is actively pursued because the two HPV proteins E6 and E7 represent ideal targets for immunotherapy, as they are non-self and expressed in all tumor stages. MHC-humanized mice are valuable tools for the study of therapeutic cancer vaccines - given the availability of a suitable tumor model. Here, we present for the first time an HPV16 tumor model suitable for fully MHC-humanized A2.DR1 mice, PAP-A2 cells, which in contrast to existing HPV16 tumor models allows the exclusive study of HLA-A2- and DR1-mediated immune responses, without any interfering murine MHC-presented epitopes. We used several HPV16 epitopes that were shown to be presented on human cervical cancer cells by mass spectrometry for therapeutic anti-tumor vaccination in the new tumor model. All epitopes were immunogenic when rendered amphiphilic by incorporation into a molecule containing stearic acids. Prophylactic and therapeutic vaccination experiments with the epitope E7/11-19 demonstrated that effective immune responses could be induced with these vaccination approaches in A2.DR1 mice. Interestingly, the combination of E7/11-19 with other immunogenic HPV16 E6/E7 epitopes caused a reduction of vaccine efficacy, although all tested combinations resulted in a survival benefit. In summary, we present the first HPV16 tumor model for exclusive studies of HLA-A2-mediated anti-HPV tumor immune responses and show anti-tumor efficacy of minimal epitope vaccines.

MHCflurry: Open-Source Class I MHC Binding Affinity Prediction.

Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry's prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices.

A Targeted LC-MS Strategy for Low-Abundant HLA Class-I-Presented Peptide Detection Identifies Novel Human Papillomavirus T-Cell Epitopes.

For rational design of therapeutic vaccines, detailed knowledge about target epitopes that are endogenously processed and truly presented on infected or transformed cells is essential. Many potential target epitopes (viral or mutation-derived), are presented at low abundance. Therefore, direct detection of these peptides remains a challenge. This study presents a method for the isolation and LC-MS3 -based targeted detection of low-abundant human leukocyte antigen (HLA) class-I-presented peptides from transformed cells. Human papillomavirus (HPV) was used as a model system, as the HPV oncoproteins E6 and E7 are attractive therapeutic vaccination targets and expressed in all transformed cells, but present at low abundance due to viral immune evasion mechanisms. The presented approach included preselection of target antigen-derived peptides by in silico predictions and in vitro binding assays. The peptide purification process was tailored to minimize contaminants after immunoprecipitation of HLA-peptide complexes, while keeping high isolation yields of low-abundant target peptides. The subsequent targeted LC-MS3 detection allowed for increased sensitivity, which resulted in successful detection of the known HLA-A2-restricted epitope E711-19 and ten additional E7-derived peptides on the surface of HPV16-transformed cells. T-cell reactivity was shown for all the 11 detected peptides in ELISpot assays, which shows that detection by our approach has high predictive value for immunogenicity. The presented strategy is suitable for validating even low-abundant candidate epitopes to be true immunotherapy targets.