Mass spectrometric identification of immunogenic SARS-CoV-2 epitopes and cognate TCRs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID-19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally if not more important than humoral responses in mediating recovery and immune protection. One major challenge in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities. Our studies find that, in contrast to current convention, "immunodominant" SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined empirically by directly analyzing peptides eluted from the naturally processed peptide-major histocompatibility complex (MHC) and then validating immunogenicity by determining whether such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes derived from not only structural but also nonstructural genes in regions highly conserved among SARS-CoV-2 strains, including recently recognized variants. Finally, there are no reported T cell receptor-engineered T cell technology that can redirect T cell specificity to recognize and kill SARS-CoV-2 target cells. We report here several SARS-CoV-2 epitopes defined by mass spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity, and demonstrate engineered TCR-redirected killing.

Altered human alveolar bone gene expression in type 2 diabetes-A cross-sectional study.

OBJECTIVE: The objective of this cross-sectional study is to investigate alveolar bone gene expression in health and diabetes through ribonucleic acid (RNA) sequencing and bioinformatics analysis. BACKGROUND: It is relatively unknown how type 2 diabetes modulates gene expression in alveolar bone in humans. Clinical concern regarding increased implant failure rate in patients with diabetes has been discussed in the literature. Previous studies in animal models and humans have suggested an imbalance between the genes regulating bone formation with data suggesting bone resorption in diabetes. However, there is lack of data regarding a comprehensive gene expression from human alveolar bone in diabetes. METHODS: Alveolar bone was collected from healthy and type 2 diabetic subjects undergoing periodontal and implant surgeries. The homogenized RNA sample was then extracted and analyzed for quantity and quality. RNA samples were further purified using ribosomal RNA depletion technique and processed for RNA sequencing and analysis. Expression levels for mRNAs were performed by calculating FPKM ([total_exon_fragments/mapped reads (millions) × exon length (kB)]), and differentially expressed mRNAs were selected with log2 (fold change) >1 or log2 (fold change) ≤1 and with a parametric F test comparing nested linear models. RESULTS: Eighteen bone samples (10 healthy, 8 patients with diabetes) were analyzed for gene expression. The mean age and HbA1c% of healthy versus diabetic subjects were as follows: age (55.3 ± 17.5 vs 63.9 ± 8.7 years) and HbA1c% (5.6 ± 0.29 vs 7.3 ± 2.4), respectively. Sequencing analysis showed that expression of genes that regulate bone turnover like TGFB1, LTBP4, IGF1, BMP2, BMP4, BMP6, SMAD1, RUNX2, MCSF, and THRA was significantly downregulated in diabetes samples compared with healthy controls with overall reduced expression of genes in the bone regulation pathway in patients with diabetes. Bioinformatics analysis for the altered genes highlighted several pathways related to bone homeostasis and inflammation in diabetes. Periodontitis did not affect the gene expression pattern based on diabetes status. CONCLUSIONS: Altered expression of genes due to downregulation of certain pathways that are involved in bone turnover and inflammation suggests that overall wound healing and bone homeostasis may be compromised in type 2 diabetes.

Combination of PD-1 Inhibitor and OX40 Agonist Induces Tumor Rejection and Immune Memory in Mouse Models of Pancreatic Cancer.

BACKGROUND & AIMS: Advanced pancreatic ductal adenocarcinoma (PDAC) is resistant to therapy, including immune checkpoint inhibitors. We evaluated the effects of a neutralizing antibody against programmed cell death 1 (PD-1) and an agonist of OX40 (provides a survival signal to activated T cells) in mice with pancreatic tumors. METHODS: We performed studies in C57BL/6 mice (controls), KrasG12D/+;Trp53R172H/+;Pdx-1-Cre (KPC) mice, and mice with orthotopic tumors grown from Panc02 cells, KrasG12D;P53flox/flox;PDX-1-Cre;Luciferase (KPC-Luc) cells, or mT4 cells. After tumors developed, mice were given injections of control antibody or anti-OX40 and/or anti-PD-1 antibody. Some mice were then given injections of antibodies against CD8, CD4, or NK1.1 to deplete immune cells, and IL4 or IL7RA to block cytokine signaling. Bioluminescence imaging was used to monitor tumor growth. Tumor tissues collected and single-cell suspensions were analyzed by time of flight mass spectrometry analysis. Mice that were tumor-free 100 days after implantation of orthotopic tumors were rechallenged with PDAC cells (KPC-Luc or mT4) and survival was measured. Median levels of PD-1 and OX40 mRNAs in PDACs were determined from The Cancer Genome Atlas and compared with patient survival times. RESULTS: In mice with orthotopic tumors, all those given control antibody or anti-PD-1 died within 50 days, whereas 43% of mice given anti-OX40 survived for 225 days; almost 100% of mice given the combination of anti-PD-1 and anti-OX40 survived for 225 days, and tumors were no longer detected. KPC mice given control antibody, anti-PD-1, or anti-OX40 had median survival times of 50 days or less, whereas mice given the combination of anti-PD-1 and anti-OX40 survived for a median 88 days. Mice with orthotopic tumors that were given the combination of anti-PD-1 and anti-OX40 and survived 100 days were rechallenged with a second tumor; those rechallenged with mT4 cells survived an additional median 70 days and those rechallenged with KPC-Luc cells survived long term, tumor free. The combination of anti-PD-1 and anti-OX40 did not slow tumor growth in mice with antibody-mediated depletion of CD4+ T cells. Mice with orthotopic tumors given the combination of anti-PD-1 and anti-OX40 that survived after complete tumor rejection were rechallenged with KPC-Luc cells; those with depletion of CD4+ T cells before the rechallenge had uncontrolled tumor growth. Furthermore, KPC orthotopic tumors from mice given the combination contained an increased number of CD4+ T cells that expressed CD127 compared with mice given control antibody. The combination of agents reduced the proportion of T-regulatory and exhausted T cells and decreased T-cell expression of GATA3; tumor size was negatively associated with numbers of infiltrating CD4+ T cells, CD4+CD127+ T cells, and CD8+CD127+ T cells, and positively associated with numbers of CD4+PD-1+ T cells, CD4+CD25+ T cells, and CD8+PD-1+ T cells. PDACs with high levels of OX40 and low levels of PD-1 were associated with longer survival times of patients. CONCLUSIONS: Pancreatic tumors appear to evade the immune response by inducing development of immune-suppressive T cells. In mice, the combination of anti-PD-1 inhibitory and anti-OX40 agonist antibodies reduces the proportion of T-regulatory and exhausted T cells in pancreatic tumors and increases numbers of memory CD4+ and CD8+ T cells, eradicating all detectable tumor. This information can be used in development of immune-based combination therapies for PDAC.

Response envelope analysis for quantitative evaluation of drug combinations.

MOTIVATION: The concept of synergy between two agents, over a century old, is important to the fields of biology, chemistry, pharmacology and medicine. A key step in drug combination analysis is the selection of an additivity model to identify combination effects including synergy, additivity and antagonism. Existing methods for identifying and interpreting those combination effects have limitations. RESULTS: We present here a computational framework, termed response envelope analysis (REA), that makes use of 3D response surfaces formed by generalized Loewe Additivity and Bliss Independence models of interaction to evaluate drug combination effects. Because the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-exclusive), a response envelope defined by them provides a quantitatively stringent additivity model for identifying combination effects without knowing the inhibition mechanism. As a demonstration, we apply REA to representative published data from large screens of anticancer and antibiotic combinations. We show that REA is more accurate than existing methods and provides more consistent results in the context of cross-experiment evaluation. AVAILABILITY AND IMPLEMENTATION: The open-source software package associated with REA is available at: https://github.com/4dsoftware/rea. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SoS Notebook: an interactive multi-language data analysis environment.

Motivation: Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking. Results: We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications. Availability and implementation: SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license.

A Multivariate Mixture Model to Estimate the Accuracy of Glycosaminoglycan Identifications Made by Tandem Mass Spectrometry (MS/MS) and Database Search.

We present a statistical model to estimate the accuracy of derivatized heparin and heparan sulfate (HS) glycosaminoglycan (GAG) assignments to tandem mass (MS/MS) spectra made by the first published database search application, GAG-ID. Employing a multivariate expectation-maximization algorithm, this statistical model distinguishes correct from ambiguous and incorrect database search results when computing the probability that heparin/HS GAG assignments to spectra are correct based upon database search scores. Using GAG-ID search results for spectra generated from a defined mixture of 21 synthesized tetrasaccharide sequences as well as seven spectra of longer defined oligosaccharides, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly, ambiguously, and incorrectly assigned heparin/HS GAGs. This analysis makes it possible to filter large MS/MS database search results with predictable false identification error rates.

GAG-ID: Heparan Sulfate (HS) and Heparin Glycosaminoglycan High-Throughput Identification Software.

Heparin and heparan sulfate are very large linear polysaccharides that undergo a complex variety of modifications and are known to play important roles in human development, cell-cell communication and disease. Sequencing of highly sulfated glycosaminoglycan oligosaccharides like heparin and heparan sulfate by liquid chromatography-tandem mass spectrometry (LC-MS/MS) remains challenging because of the presence of multiple isomeric sequences in a complex mixture of oligosaccharides, the difficulties in separation of these isomers, and the facile loss of sulfates in MS/MS. We have previously introduced a method for structural sequencing of heparin/heparan sulfate oligosaccharides involving chemical derivatizations that replace labile sulfates with stable acetyl groups. This chemical derivatization scheme allows the use of reversed phase LC for high-resolution separation and MS/MS for sequencing of isomeric heparan sulfate oligosaccharides. However, because of the large number of analytes present in complex mixtures of heparin/HS oligosaccharides, the resulting LC-MS/MS data sets are large and cannot be annotated with existing glycomics software because of the specifically designed chemical derivatization strategy. We have developed a tool, called GAG-ID, to automate the interpretation of derivatized heparin/heparan sulfate LC-MS/MS data based on a modified multivariate hypergeometric distribution to weight the annotation of more intense peaks. The software is tested on a LC-MS/MS data set collected from a mixture of 21 synthesized heparan sulfate tetrasaccharides. By testing the discrimination of scoring with this system, we show that stratifying peaks into different intensity classes benefits the discrimination of scoring, and GAG-ID is able to properly assign all 21 synthetic tetrasaccharides in a defined mixture from a single LC-MS/MS run.

Integrated Approach to Identify Heparan Sulfate Ligand Requirements of Robo1.

An integrated methodology is described to establish ligand requirements for heparan sulfate (HS) binding proteins based on a workflow in which HS octasaccharides are produced by partial enzymatic degradation of natural HS followed by size exclusion purification, affinity enrichment using an immobilized HS-binding protein of interest, putative structure determination of isolated compounds by a hydrophilic interaction chromatography-high-resolution mass spectrometry platform, and chemical synthesis of well-defined HS oligosaccharides for structure-activity relationship studies. The methodology was used to establish the ligand requirements of human Roundabout receptor 1 (Robo1), which is involved in a number of developmental processes. Mass spectrometric analysis of the starting octasaccharide mixture and the Robo1-bound fraction indicated that Robo1 has a preference for a specific set of structures. Further analysis was performed by sequential permethylation, desulfation, and pertrideuteroacetylation followed by online separation and structural analysis by MS/MS. Sequences of tetrasaccharides could be deduced from the data, and by combining the compositional and sequence data, a putative octasaccharide ligand could be proposed (GlA-GlcNS6S-IdoA-GlcNS-IdoA2S-GlcNS6S-IdoA-GlcNAc6S). A modular synthetic approach was employed to prepare the target compound, and binding studies by surface plasmon resonance (SPR) confirmed it to be a high affinity ligand for Robo1. Further studies with a number of tetrasaccharides confirmed that sulfate esters at C-6 are critical for binding, whereas such functionalities at C-2 substantially reduce binding. High affinity ligands were able to reverse a reduction in endothelial cell migration induced by Slit2-Robo1 signaling.

De Novo Sequencing of Complex Mixtures of Heparan Sulfate Oligosaccharides.

Here, we describe the first sequencing method of a complex mixture of heparan sulfate tetrasaccharides by LC-MS/MS. Heparin and heparan sulfate (HS) are linear polysaccharides that are modified in a complex manner by N- and O-sulfation, N-acetylation, and epimerization of the uronic acid. Heparin and HS are involved in various essential cellular communication processes. The structural analysis of these glycosaminoglycans is challenging due to the lability of their sulfate groups, the high heterogeneity of modifications, and the epimerization of the uronic acids. While advances in liquid chromatography (LC) and mass spectrometry (MS) have enabled compositional profiling of HS oligosaccharide mixtures, online separation and detailed structural analysis of isomeric and epimeric HS mixtures has not been achieved. Here, we report the development and evaluation of a chemical derivatization and tandem mass spectrometry method that can separate and identify isomeric and epimeric structures from complex mixtures. A series of well-defined synthetic HS tetrasaccharides varying in sulfation patterns and uronic acid epimerization were analyzed by chemical derivatization and LC-MS/MS. These synthetic compounds made it possible to establish relationships between HS structure, chromatographic behavior and MS/MS fragmentation characteristics. Using the analytical characteristics determined through the analysis of the synthetic HS tetrasaccharide standards, an HS tetrasacharide mixture derived from natural sources was successfully sequenced. This method represents the first sequencing of complex mixtures of HS oligosaccharides, an essential milestone in the analysis of structure-function relationships of these carbohydrates.

An interpretable ML model to characterize patient-specific HLA-I antigen presentation.

Personalized immunotherapy holds the promise of revolutionizing cancer prevention and treatment. However, selecting HLA-bound peptide targets that are specific to patient tumors has been challenging due to a lack of patient-specific antigen presentation models. Here, we present epiNB, a white-box, positive-example-only, semi-supervised method based on Naïve Bayes formulation, with information content-based feature selection, to achieve accurate modeling using Mass Spectrometry data eluted from mono-allelic cell lines and patient-derived cell lines. In addition to achieving state-of-the-art accuracy, epiNB yields novel insights into the structural properties, such as interactions of peptide positions, that appear important for modeling personalized, tumor-specific antigen presentation. epiNB uses substantially less parameters than neural networks, does not require hyperparameter tweaking and can efficiently train and run on our web portal (https://epinbweb.streamlit.app/) or a regular PC/laptop, making it easily applicable in translational settings.

Harnessing the synergy of perfusable muscle flap matrix and adipose-derived stem cells for prevascularization and macrophage polarization to reconstruct volumetric muscle loss.

Muscle flaps must have a strong vascular network to support a large tissue volume and ensure successful engraftment. We developed porcine stomach musculofascial flap matrix (PDSF) comprising extracellular matrix (ECM) and intact vasculature. PDSF had a dominant vascular pedicle, microcirculatory vessels, a nerve network, well-retained 3-dimensional (3D) nanofibrous ECM structures, and no allo- or xenoantigenicity. In-depth proteomic analysis demonstrated that PDSF was composed of core matrisome proteins (e.g., collagens, glycoproteins, proteoglycans, and ECM regulators) that, as shown by Gene Ontology term enrichment analysis, are functionally related to musculofascial biological processes. Moreover, PDSF-human adipose-derived stem cell (hASC) synergy not only induced monocytes towards IL-10-producing M2 macrophage polarization through the enhancement of hASCs' paracrine effect but also promoted the proliferation and interconnection of both human skeletal muscle myoblasts (HSMMs) and human umbilical vein endothelial cells (HUVECs) in static triculture conditions. Furthermore, PDSF was successfully prevascularized through a dynamic perfusion coculture of hASCs and HUVECs, which integrated with PDSF and induced the maturation of vascular networks in vitro. In a xenotransplantation model, PDSF demonstrated myoconductive and immunomodulatory properties associated with the predominance of M2 macrophages and regulatory T cells. In a volumetric muscle loss (VML) model, prevascularized PDSF augmented neovascularization and constructive remodeling, which was characterized by the predominant infiltration of M2 macrophages and significant musculofascial tissue formation. These results indicate that hASCs' integration with PDSF enhances the cells' dual function in immunomodulation and angiogenesis. Owing in part to this PDSF-hASC synergy, our platform shows promise for vascularized muscle flap engineering for VML reconstruction.

CRISPR/Cas9 screen uncovers functional translation of cryptic lncRNA-encoded open reading frames in human cancer.

Emerging evidence suggests that cryptic translation within long noncoding RNAs (lncRNAs) may produce novel proteins with important developmental/physiological functions. However, the role of this cryptic translation in complex diseases (e.g., cancer) remains elusive. Here, we applied an integrative strategy combining ribosome profiling and CRISPR/Cas9 screening with large-scale analysis of molecular/clinical data for breast cancer (BC) and identified estrogen receptor α-positive (ER+) BC dependency on the cryptic ORFs encoded by lncRNA genes that were upregulated in luminal tumors. We confirmed the in vivo tumor-promoting function of an unannotated protein, GATA3-interacting cryptic protein (GT3-INCP) encoded by LINC00992, the expression of which was associated with poor prognosis in luminal tumors. GTE-INCP was upregulated by estrogen/ER and regulated estrogen-dependent cell growth. Mechanistically, GT3-INCP interacted with GATA3, a master transcription factor key to mammary gland development/BC cell proliferation, and coregulated a gene expression program that involved many BC susceptibility/risk genes and impacted estrogen response/cell proliferation. GT3-INCP/GATA3 bound to common cis regulatory elements and upregulated the expression of the tumor-promoting and estrogen-regulated BC susceptibility/risk genes MYB and PDZK1. Our study indicates that cryptic lncRNA-encoded proteins can be an important integrated component of the master transcriptional regulatory network driving aberrant transcription in cancer, and suggests that the "hidden" lncRNA-encoded proteome might be a new space for therapeutic target discovery.

CRISPR-Cas9-based functional interrogation of unconventional translatome reveals human cancer dependency on cryptic non-canonical open reading frames.

Emerging evidence suggests that cryptic translation beyond the annotated translatome produces proteins with developmental or physiological functions. However, functions of cryptic non-canonical open reading frames (ORFs) in cancer remain largely unknown. To fill this gap and systematically identify colorectal cancer (CRC) dependency on non-canonical ORFs, we apply an integrative multiomic strategy, combining ribosome profiling and a CRISPR-Cas9 knockout screen with large-scale analysis of molecular and clinical data. Many such ORFs are upregulated in CRC compared to normal tissues and are associated with clinically relevant molecular subtypes. We confirm the in vivo tumor-promoting function of the microprotein SMIMP, encoded by a primate-specific, long noncoding RNA, the expression of which is associated with poor prognosis in CRC, is low in normal tissues and is specifically elevated in CRC and several other cancer types. Mechanistically, SMIMP interacts with the ATPase-forming domains of SMC1A, the core subunit of the cohesin complex, and facilitates SMC1A binding to cis-regulatory elements to promote epigenetic repression of the tumor-suppressive cell cycle regulators encoded by CDKN1A and CDKN2B. Thus, our study reveals a cryptic microprotein as an important component of cohesin-mediated gene regulation and suggests that the 'dark' proteome, encoded by cryptic non-canonical ORFs, may contain potential therapeutic or diagnostic targets.

Charge-based interactions through peptide position 4 drive diversity of antigen presentation by human leukocyte antigen class I molecules.

Human leukocyte antigen class I (HLA-I) molecules bind and present peptides at the cell surface to facilitate the induction of appropriate CD8+ T cell-mediated immune responses to pathogen- and self-derived proteins. The HLA-I peptide-binding cleft contains dominant anchor sites in the B and F pockets that interact primarily with amino acids at peptide position 2 and the C-terminus, respectively. Nonpocket peptide-HLA interactions also contribute to peptide binding and stability, but these secondary interactions are thought to be unique to individual HLA allotypes or to specific peptide antigens. Here, we show that two positively charged residues located near the top of peptide-binding cleft facilitate interactions with negatively charged residues at position 4 of presented peptides, which occur at elevated frequencies across most HLA-I allotypes. Loss of these interactions was shown to impair HLA-I/peptide binding and complex stability, as demonstrated by both in vitro and in silico experiments. Furthermore, mutation of these Arginine-65 (R65) and/or Lysine-66 (K66) residues in HLA-A*02:01 and A*24:02 significantly reduced HLA-I cell surface expression while also reducing the diversity of the presented peptide repertoire by up to 5-fold. The impact of the R65 mutation demonstrates that nonpocket HLA-I/peptide interactions can constitute anchor motifs that exert an unexpectedly broad influence on HLA-I-mediated antigen presentation. These findings provide fundamental insights into peptide antigen binding that could broadly inform epitope discovery in the context of viral vaccine development and cancer immunotherapy.

Hypoxia acts as an environmental cue for the human tissue-resident memory T cell differentiation program.

Tissue-resident memory T cells (TRM) provide frontline defense against infectious diseases and contribute to antitumor immunity; however, aside from the necessity of TGF-ß, knowledge regarding TRM-inductive cues remains incomplete, particularly for human cells. Oxygen tension is an environmental cue that distinguishes peripheral tissues from the circulation, and here, we demonstrate that differentiation of human CD8+ T cells in the presence of hypoxia and TGF-ß1 led to the development of a TRM phenotype, characterized by a greater than 5-fold increase in CD69+CD103+ cells expressing human TRM hallmarks and enrichment for endogenous human TRM gene signatures, including increased adhesion molecule expression and decreased expression of genes involved in recirculation. Hypoxia and TGF-ß1 synergized to produce a significantly larger population of TRM phenotype cells than either condition alone, and comparison of these cells from the individual and combination conditions revealed distinct phenotypic and transcriptional profiles, indicating a programming response to milieu rather than a mere expansion. Our findings identify a likely previously unreported cue for the TRM differentiation program and can enable facile generation of human TRM phenotype cells in vitro for basic studies and translational applications such as adoptive cellular therapy.

In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19.

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally, if not more important than humoral responses in mediating recovery and immune-protection. One of the major challenges in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities and consensus data. Our studies find that, in contrast to current dogma, 'immunodominant' SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes.

Immunogenic SARS-CoV2 Epitopes Defined by Mass Spectrometry.

SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, T cell responses are important in mediating recovery and immune-protection. The identification of immunogenic epitopes that can elicit a meaningful T cell response can be elusive. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes; however, our previous studies find that 'immunodominant' SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing SARS-CoV-2. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined by directly analyzing peptides eluted from the peptide-MHC complex and then validating immunogenicity empirically by determining if such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes of SARS-CoV-2 derived not only from structural but also non-structural genes in regions highly conserved among SARS-CoV-2 strains including recently recognized variants. We report here, for the first time, several novel SARS-CoV-2 epitopes from membrane glycol-protein (MGP) and non-structure protein-13 (NSP13) defined by mass-spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity to induce T cell response. SIGNIFICANCE STATEMENT: Current state of the art uses putative epitope peptides based on in silico prediction algorithms to evaluate the T cell response among COVID-19 patients. However, none of these peptides have been tested for immunogenicity, i.e. the ability to elicit a T cell response capable of recognizing endogenously presented peptide. In this study, we used MHC immune-precipitation, acid elution and tandem mass spectrometry to define the SARS-CoV-2 immunopeptidome for membrane glycol-protein and the non-structural protein. Furthermore, taking advantage of a highly robust endogenous T cell (ETC) workflow, we verify the immunogenicity of these MS-defined peptides by in vitro generation of MGP and NSP13 peptide-specific T cells and confirm T cell recognition of MGP or NSP13 endogenously expressing cell lines.

Novel Anaplastic Thyroid Cancer PDXs and Cell Lines: Expanding Preclinical Models of Genetic Diversity.

CONTEXT: Anaplastic thyroid cancer (ATC) is a rare, aggressive, and deadly disease. Robust preclinical thyroid cancer models are needed to adequately develop and study novel therapeutic agents. Patient-derived xenograft (PDX) models may resemble patient tumors by recapitulating key genetic alterations and gene expression patterns, making them excellent preclinical models for drug response evaluation. OBJECTIVE: We developed distinct ATC PDX models concurrently with cell lines and characterized them in vitro and in vivo. METHODS: Fresh thyroid tumor from patients with a preoperative diagnosis of ATC was surgically collected and divided for concurrent cell line and PDX model development. Cell lines were created by generating single cells through enzymatic digestion. PDX models were developed following direct subcutaneous implantation of fresh tumor on the flank of immune compromised/athymic mice. RESULTS: Six ATC PDX models and 4 cell lines were developed with distinct genetic profiles. Mutational characterization showed one BRAF/TP53/CDKN2A, one BRAF/CDKN2A, one BRAF/TP53, one TP53 only, one TERT-promoter/HRAS, and one TERT-promoter/KRAS/TP53/NF2/NFE2L2 mutated phenotype. Hematoxylin-eosin staining comparing the PDX models to the original patient surgical specimens show remarkable resemblance, while immunohistochemistry stains for important biomarkers were in full concordance (cytokeratin, TTF-1, PAX8, BRAF). Short tandem repeats DNA fingerprinting analysis of all PDX models and cell lines showed strong concordance with the original tumor. PDX successful establishment rate was 32%. CONCLUSION: We have developed and characterized 6 novel ATC PDX models with 4 matching cell lines. Each PDX model harbors a distinct genetic profile, making them excellent tools for preclinical therapeutic trials.

Neoantigen vaccination induces clinical and immunologic responses in non-small cell lung cancer patients harboring EGFR mutations.

BACKGROUND: Neoantigen (NeoAg) peptides displayed at the tumor cell surface by human leukocyte antigen molecules show exquisite tumor specificity and can elicit T cell mediated tumor rejection. However, few NeoAgs are predicted to be shared between patients, and none to date have demonstrated therapeutic value in the context of vaccination. METHODS: We report here a phase I trial of personalized NeoAg peptide vaccination (PPV) of 24 stage III/IV non-small cell lung cancer (NSCLC) patients who had previously progressed following multiple conventional therapies, including surgery, radiation, chemotherapy, and tyrosine kinase inhibitors (TKIs). Primary endpoints of the trial evaluated feasibility, tolerability, and safety of the personalized vaccination approach, and secondary trial endpoints assessed tumor-specific immune reactivity and clinical responses. Of the 16 patients with epidermal growth factor receptor (EGFR) mutations, nine continued TKI therapy concurrent with PPV and seven patients received PPV alone. RESULTS: Out of 29 patients enrolled in the trial, 24 were immunized with personalized NeoAg peptides. Aside from transient rash, fatigue and/or fever observed in three patients, no other treatment-related adverse events were observed. Median progression-free survival and overall survival of the 24 vaccinated patients were 6.0 and 8.9 months, respectively. Within 3-4 months following initiation of PPV, seven RECIST-based objective clinical responses including one complete response were observed. Notably, all seven clinical responders had EGFR-mutated tumors, including four patients that had continued TKI therapy concurrently with PPV. Immune monitoring showed that five of the seven responding patients demonstrated vaccine-induced T cell responses against EGFR NeoAg peptides. Furthermore, two highly shared EGFR mutations (L858R and T790M) were shown to be immunogenic in four of the responding patients, all of whom demonstrated increases in peripheral blood neoantigen-specific CD8+ T cell frequencies during the course of PPV. CONCLUSIONS: These results show that personalized NeoAg vaccination is feasible and safe for advanced-stage NSCLC patients. The clinical and immune responses observed following PPV suggest that EGFR mutations constitute shared, immunogenic neoantigens with promising immunotherapeutic potential for large subsets of NSCLC patients. Furthermore, PPV with concurrent EGFR inhibitor therapy was well tolerated and may have contributed to the induction of PPV-induced T cell responses.

Vestigial-like 1 is a shared targetable cancer-placenta antigen expressed by pancreatic and basal-like breast cancers.

Cytotoxic T lymphocyte (CTL)-based cancer immunotherapies have shown great promise for inducing clinical regressions by targeting tumor-associated antigens (TAA). To expand the TAA landscape of pancreatic ductal adenocarcinoma (PDAC), we performed tandem mass spectrometry analysis of HLA class I-bound peptides from 35 PDAC patient tumors. This identified a shared HLA-A*0101 restricted peptide derived from co-transcriptional activator Vestigial-like 1 (VGLL1) as a putative TAA demonstrating overexpression in multiple tumor types and low or absent expression in essential normal tissues. Here we show that VGLL1-specific CTLs expanded from the blood of a PDAC patient could recognize and kill in an antigen-specific manner a majority of HLA-A*0101 allogeneic tumor cell lines derived not only from PDAC, but also bladder, ovarian, gastric, lung, and basal-like breast cancers. Gene expression profiling reveals VGLL1 as a member of a unique group of cancer-placenta antigens (CPA) that may constitute immunotherapeutic targets for patients with multiple cancer types.