Investigation of Chelating Agents for the Removal of Thorium from Human Teeth upon Nuclear Contamination.

Thorium-232 (232Th) is a radioactive heavy metal that is of increasing interest as a source of nuclear energy. However, upon nuclear incidents, the ingestion or inhalation of Th in major quantities can contribute to chemical and radiological health problems, including accumulation in the bone tissue and an increased risk of developing pancreatic, lung, and hematopoietic cancers. The major mineral component of the bone is hydroxyapatite (HAP)─also the major mineral component of the teeth. As such, the teeth are the first site of exposure upon oral ingestion of Th-contaminated materials, and Th can pose a potential risk to teeth development. In essence, in the case of human contamination, it is critical to identify effective chelating agents capable of removing Th. Using a batch study methodology, this present work investigates the uptake and the removal of Th from synthetic HAP and from teeth samples by diethylenetriamine pentaacetate (DTPA), ethylenediaminetetraacetic acid (EDTA), and other promising chelating agents. Th uptake over synthetic HAP exceeds 98% at physiological pH with <1 min of contact time and uptake exceeds 90% across the entire pH range. Regarding teeth, over 1 mg Th uptaken per gram of tooth is observed after 24 h. The overall effectiveness of chelating agents for the removal of Th from is as follows: DTPA > EDTA > NaF/mouthwash/3,4,3-LI(1,2-HOPO); this trend was observed both in synthetic HAP and Th-impregnated teeth samples.

The immunopeptidome landscape associated with T cell infiltration, inflammation and immune editing in lung cancer.

One key barrier to improving efficacy of personalized cancer immunotherapies that are dependent on the tumor antigenic landscape remains patient stratification. Although patients with CD3+CD8+ T cell-inflamed tumors typically show better response to immune checkpoint inhibitors, it is still unknown whether the immunopeptidome repertoire presented in highly inflamed and noninflamed tumors is substantially different. We surveyed 61 tumor regions and adjacent nonmalignant lung tissues from 8 patients with lung cancer and performed deep antigen discovery combining immunopeptidomics, genomics, bulk and spatial transcriptomics, and explored the heterogeneous expression and presentation of tumor (neo)antigens. In the present study, we associated diverse immune cell populations with the immunopeptidome and found a relatively higher frequency of predicted neoantigens located within HLA-I presentation hotspots in CD3+CD8+ T cell-excluded tumors. We associated such neoantigens with immune recognition, supporting their involvement in immune editing. This could have implications for the choice of combination therapies tailored to the patient's mutanome and immune microenvironment.

Improved NGS-based detection of microsatellite instability using tumor-only data.

Microsatellite instability (MSI) is a molecular signature of mismatch repair deficiency (dMMR), a predictive marker of immune checkpoint inhibitor therapy response. Despite its recognized pan-cancer value, most methods only support detection of this signature in colorectal cancer. In addition to the tissue-specific differences that impact the sensitivity of MSI detection in other tissues, the performance of most methods is also affected by patient ethnicity, tumor content, and other sample-specific properties. These limitations are particularly important when only tumor samples are available and restrict the performance and adoption of MSI testing. Here we introduce MSIdetect, a novel solution for NGS-based MSI detection. MSIdetect models the impact of indel burden and tumor content on read coverage at a set of homopolymer regions that we found are minimally impacted by sample-specific factors. We validated MSIdetect in 139 Formalin-Fixed Paraffin-Embedded (FFPE) clinical samples from colorectal and endometrial cancer as well as other more challenging tumor types, such as glioma or sebaceous adenoma or carcinoma. Based on analysis of these samples, MSIdetect displays 100% specificity and 96.3% sensitivity. Limit of detection analysis supports that MSIdetect is sensitive even in samples with relatively low tumor content and limited microsatellite instability. Finally, the results obtained using MSIdetect in tumor-only data correlate well (R=0.988) with what is obtained using tumor-normal matched pairs, demonstrating that the solution addresses the challenges posed by MSI detection from tumor-only data. The accuracy of MSI detection by MSIdetect in different cancer types coupled with the flexibility afforded by NGS-based testing will support the adoption of MSI testing in the clinical setting and increase the number of patients identified that are likely to benefit from immune checkpoint inhibitor therapy.

Sensitive identification of neoantigens and cognate TCRs in human solid tumors.

The identification of patient-specific tumor antigens is complicated by the low frequency of T cells specific for each tumor antigen. Here we describe NeoScreen, a method that enables the sensitive identification of rare tumor (neo)antigens and of cognate T cell receptors (TCRs) expressed by tumor-infiltrating lymphocytes. T cells transduced with tumor antigen-specific TCRs identified by NeoScreen mediate regression of established tumors in patient-derived xenograft mice.

Identification of tumor antigens with immunopeptidomics.

The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.

Cell-autonomous inflammation of BRCA1-deficient ovarian cancers drives both tumor-intrinsic immunoreactivity and immune resistance via STING.

In this study, we investigate mechanisms leading to inflammation and immunoreactivity in ovarian tumors with homologous recombination deficiency (HRD). BRCA1 loss is found to lead to transcriptional reprogramming in tumor cells and cell-intrinsic inflammation involving type I interferon (IFN) and stimulator of IFN genes (STING). BRCA1-mutated (BRCA1mut) tumors are thus T cell inflamed at baseline. Genetic deletion or methylation of DNA-sensing/IFN genes or CCL5 chemokine is identified as a potential mechanism to attenuate T cell inflammation. Alternatively, in BRCA1mut cancers retaining inflammation, STING upregulates VEGF-A, mediating immune resistance and tumor progression. Tumor-intrinsic STING elimination reduces neoangiogenesis, increases CD8+ T cell infiltration, and reverts therapeutic resistance to dual immune checkpoint blockade (ICB). VEGF-A blockade phenocopies genetic STING loss and synergizes with ICB and/or poly(ADP-ribose) polymerase (PARP) inhibitors to control the outgrowth of Trp53-/-Brca1-/- but not Brca1+/+ ovarian tumors in vivo, offering rational combinatorial therapies for HRD cancers.

Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction.

Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity-from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes.

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes.

Predictions of epitopes presented by class II human leukocyte antigen molecules (HLA-II) have limited accuracy, restricting vaccine and therapy design. Here we combined unbiased mass spectrometry with a motif deconvolution algorithm to profile and analyze a total of 99,265 unique peptides eluted from HLA-II molecules. We then trained an epitope prediction algorithm with these data and improved prediction of pathogen and tumor-associated class II neoepitopes.

Correction: Tumour-reactive T cell subsets in the microenvironment of ovarian cancer.

Since the publication of this paper, the authors noticed that the funding information was not complete. The correct funding information is now shown in the Acknowledgements section. Acknowledgements The studies were supported by grants from the OvaCure Foundation, the Danish Cancer Society Research Foundation, the Anticancer Fund, Aase og Ejnar Danielsens Foundation and the Independent Research Fund Denmark (grant number DFF-4183-00597).

Tumour-reactive T cell subsets in the microenvironment of ovarian cancer.

BACKGROUND: Solid malignancies are frequently infiltrated with T cells. The success of adoptive cell transfer (ACT) with expanded tumour-infiltrating lymphocytes (TILs) in melanoma warrants its testing in other cancer types. In this preclinical study, we investigated whether clinical-grade TILs could be manufactured from ovarian cancer (OC) tumour specimens. METHODS: Thirty-four tumour specimens were obtained from 33 individual patients with OC. TILs were analysed for phenotype, antigen specificity and functionality. RESULTS: Minimally expanded TILs (Young TILs) were successfully established from all patients. Young TILs contained a high frequency of CD3+ cells with a variable CD4/CD8 ratio. TILs could be expanded to clinical numbers. Importantly, recognition of autologous tumour cells was demonstrated in TILs in >50% of the patients. We confirmed with mass spectrometry the presentation of multiple tumour antigens, including peptides derived from the cancer-testis antigen GAGE, which could be recognised by antigen-specific TILs. Antigen-specific TILs could be isolated and further expanded in vitro. CONCLUSION: These findings support the hypothesis that patients with OC can benefit from ACT with TILs and led to the initiation of a pilot clinical trial at our institution . TRIAL REGISTRATION: clinicaltrials.gov: NCT02482090.

High-Throughput, Fast, and Sensitive Immunopeptidomics Sample Processing for Mass Spectrometry.

Comprehensive knowledge of the HLA class I and class II peptides presented to T cells is crucial for designing innovative therapeutics against cancer and other diseases. So far, methodologies for recovery of HLA class I and II peptides for subsequent mass spectrometry-based analysis have been a major limitation. In this chapter we describe a detailed protocol for a high-throughput, reproducible, and sensitive immunoaffinity-purification of HLA-I and HLA-II peptides from up to 96 samples in a plate format, suitable for tissue samples and cell lines. Our methodology reduces sample handling, has a competitive peptide yield, and can be completed within 5 h. This simplified pipeline is applicable for basic and clinical applications.

Estimating the Contribution of Proteasomal Spliced Peptides to the HLA-I Ligandome.

Spliced peptides are short protein fragments spliced together in the proteasome by peptide bond formation. True estimation of the contribution of proteasome-spliced peptides (PSPs) to the global human leukocyte antigen (HLA) ligandome is critical. A recent study suggested that PSPs contribute up to 30% of the HLA ligandome. We performed a thorough reanalysis of the reported results using multiple computational tools and various validation steps and concluded that only a fraction of the proposed PSPs passes the quality filters. To better estimate the actual number of PSPs, we present an alternative workflow. We performed de novo sequencing of the HLA-peptide spectra and discarded all de novo sequences found in the UniProt database. We checked whether the remaining de novo sequences could match spliced peptides from human proteins. The spliced sequences were appended to the UniProt fasta file, which was searched by two search tools at a false discovery rate (FDR) of 1%. We find that 2-6% of the HLA ligandome could be explained as spliced protein fragments. The majority of these potential PSPs have good peptide-spectrum match properties and are predicted to bind the respective HLA molecules. However, it remains to be shown how many of these potential PSPs actually originate from proteasomal splicing events.

High-throughput and Sensitive Immunopeptidomics Platform Reveals Profound Interferonγ-Mediated Remodeling of the Human Leukocyte Antigen (HLA) Ligandome.

Comprehensive knowledge of the human leukocyte antigen (HLA) class-I and class-II peptides presented to T-cells is crucial for designing innovative therapeutics against cancer and other diseases. However methodologies for their purification for mass-spectrometry analysis have been a major limitation. We designed a novel high-throughput, reproducible and sensitive method for sequential immuno-affinity purification of HLA-I and -II peptides from up to 96 samples in a plate format, suitable for both cell lines and tissues. Our methodology drastically reduces sample-handling and can be completed within five hours. We challenged our methodology by extracting HLA peptides from multiple replicates of tissues (n = 7) and cell lines (n = 21, 108 cells per replicate), which resulted in unprecedented depth, sensitivity and high reproducibility (Pearson correlations up to 0.98 and 0.97 for HLA-I and HLA-II). Because of the method's achieved sensitivity, even single measurements of peptides purified from 107 B-cells resulted in the identification of more than 1700 HLA-I and 2200 HLA-II peptides. We demonstrate the feasibility of performing drug-screening by using ovarian cancer cells treated with interferon gamma (IFNγ). Our analysis revealed an augmented presentation of chymotryptic-like and longer ligands associated with IFNγ induced changes of the antigen processing and presentation machinery. This straightforward method is applicable for basic and clinical applications.

Deciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity.

The precise identification of Human Leukocyte Antigen class I (HLA-I) binding motifs plays a central role in our ability to understand and predict (neo-)antigen presentation in infectious diseases and cancer. Here, by exploiting co-occurrence of HLA-I alleles across ten newly generated as well as forty public HLA peptidomics datasets comprising more than 115,000 unique peptides, we show that we can rapidly and accurately identify many HLA-I binding motifs and map them to their corresponding alleles without any a priori knowledge of HLA-I binding specificity. Our approach recapitulates and refines known motifs for 43 of the most frequent alleles, uncovers new motifs for 9 alleles that up to now had less than five known ligands and provides a scalable framework to incorporate additional HLA peptidomics studies in the future. The refined motifs improve neo-antigen and cancer testis antigen predictions, indicating that unbiased HLA peptidomics data are ideal for in silico predictions of neo-antigens from tumor exome sequencing data. The new motifs further reveal distant modulation of the binding specificity at P2 for some HLA-I alleles by residues in the HLA-I binding site but outside of the B-pocket and we unravel the underlying mechanisms by protein structure analysis, mutagenesis and in vitro binding assays.

A Case for a Human Immuno-Peptidome Project Consortium.

A multidisciplinary group of researchers gathered at the Hönggerberg Campus at ETH Zurich, Switzerland, for the first meeting on the Human Immuno-Peptidome Project (https://hupo.org/human-immuno-peptidome-project/). The long-term goal of this project is to map the entire repertoire of peptides presented by human leukocyte antigen molecules using mass spectrometry technologies, and make its robust analysis accessible to any immunologist. Here we outline the specific challenges identified toward this goal, and within this framework, describe the structure of a multipronged program aimed at addressing these challenges and implementing solutions at a community-wide level. Pillars of that program are: (1) method and technology development, (2) standardization, (3) effective data sharing, and (4) education. If successful, this community-driven endeavor might provide a roadmap toward new paradigms in immunology.

Regulation of lymphangiogenesis in the diaphragm by macrophages and VEGFR-3 signaling.

Lymphatic vessels play important roles in fluid drainage and in immune responses, as well as in pathological processes including cancer progression and inflammation. While the molecular regulation of the earliest lymphatic vessel differentiation and development has been investigated in much detail, less is known about the control and timing of lymphatic vessel maturation in different organs, which often occurs postnatally. We investigated the time course of lymphatic vessel development on the pleural side of the diaphragmatic muscle in mice, the so-called submesothelial initial diaphragmatic lymphatic plexus. We found that this lymphatic network develops largely after birth and that it can serve as a reliable and easily quantifiable model to study physiological lymphangiogenesis in vivo. Lymphangiogenic growth in this tissue was highly dependent on vascular endothelial growth factor receptor (VEGFR)-3 signaling, whereas VEGFR-1 and -2 signaling was dispensable. During diaphragm development, macrophages appeared first in a linearly arranged pattern, followed by ingrowth of lymphatic vessels along these patterned lines. Surprisingly, ablation of macrophages in colony-stimulating factor-1 receptor (Csf1r)-deficient mice and by treatment with a CSF-1R-blocking antibody did not inhibit the general lymphatic vessel development in the diaphragm but specifically promoted branch formation of lymphatic sprouts. In agreement with these findings, incubation of cultured lymphatic endothelial cells with conditioned medium from P7 diaphragmatic macrophages significantly reduced LEC sprouting. These results indicate that the postnatal diaphragm provides a suitable model for studies of physiological lymphangiogenic growth and maturation, and for the identification of modulators of lymphatic vessel growth.

DeepCAGE transcriptomics identify HOXD10 as a transcription factor regulating lymphatic endothelial responses to VEGF-C.

Lymphangiogenesis plays a crucial role during development, in cancer metastasis and in inflammation. Activation of VEGFR-3 (also known as FLT4) by VEGF-C is one of the main drivers of lymphangiogenesis, but the transcriptional events downstream of VEGFR-3 activation are largely unknown. Recently, we identified a wave of immediate early transcription factors that are upregulated in human lymphatic endothelial cells (LECs) within the first 30 to 80 min after VEGFR-3 activation. Expression of these transcription factors must be regulated by additional pre-existing transcription factors that are rapidly activated by VEGFR-3 signaling. Using transcription factor activity analysis, we identified the homeobox transcription factor HOXD10 to be specifically activated at early time points after VEGFR-3 stimulation, and to regulate expression of immediate early transcription factors, including NR4A1. Gain- and loss-of-function studies revealed that HOXD10 is involved in LECs migration and formation of cord-like structures. Furthermore, HOXD10 regulates expression of VE-cadherin, claudin-5 and NOS3 (also known as e-NOS), and promotes lymphatic endothelial permeability. Taken together, these results reveal an important and unanticipated role of HOXD10 in the regulation of VEGFR-3 signaling in lymphatic endothelial cells, and in the control of lymphangiogenesis and permeability.

In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging.

Techniques to image lymphatic vessel function in either animal models or in the clinic are limited. In particular, imaging methods that can provide robust outcome measures for collecting lymphatic vessel function are sorely needed. In this study, we aimed to develop a method to visualize and quantify collecting lymphatic vessel function in mice, and to establish an in vivo system for evaluation of contractile agonists and antagonists using near-infrared fluorescence imaging. The flank collecting lymphatic vessel in mice was exposed using a surgical technique and a near-infrared tracer was infused into the inguinal lymph node. Collecting lymphatic vessel contractility and valve function could be easily visualized after the infusion. A diameter tracking method was established and the diameter of the vessel was found to closely correlate to near-infrared fluorescence signal. Phasic contractility measures of frequency and amplitude were established using an automated algorithm. The methods were validated by tracking the vessel response to topical application of a contractile agonist, prostaglandin F2α, and by demonstrating the potential of the technique for non-invasive evaluation of modifiers of lymphatic function. These new methods will enable high-resolution imaging and quantification of collecting lymphatic vessel function in animal models and may have future clinical applications.