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.

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.

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.

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.

Dynamic publication media with the COPASI R Connector (CoRC).

In this article we show how dynamic publication media and the COPASI R Connector (CoRC) can be combined in a natural and synergistic way to communicate (biochemical) models. Dynamic publication media are becoming a popular tool for authors to effectively compose and publish their work. They are built from templates and the final documents are created dynamically. In addition, they can also be interactive. Working with dynamic publication media is made easy with the programming environment R via its integration with tools such as R Markdown, Jupyter and Shiny. Additionally, the COmplex PAthway SImulator COPASI (http://www.copasi.org), a widely used biochemical modelling toolkit, is available in R through the use of the COPASI R Connector (CoRC, https://jpahle.github.io/CoRC). Models are a common tool in the mathematical biosciences, in particular kinetic models of biochemical networks in (computational) systems biology. We focus on three application areas of dynamic publication media and CoRC: Documentation (reproducible workflows), Teaching (creating self-paced lessons) and Science Communication (immersive and engaging presentation). To illustrate these, we created six dynamic document examples in the form of R Markdown and Jupyter notebooks, hosted on the platforms GitHub, shinyapps.io, Google Colaboratory. Having code and output in one place, creating documents in template-form and the option of interactivity make the combination of dynamic documents and CoRC a versatile tool. All our example documents are freely available at https://jpahle.github.io/DynamiCoRC under the Creative Commons BY 4.0 licence.

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.