Recombinant ClearColi™-derived outer membrane vesicles as an effective carrier for development of neoepitope-based vaccine candidate against colon carcinoma.

BACKGROUND: Colorectal carcinoma (CRC) is the third most common cancer worldwide, with high clonal heterogeneity due to somatic mutations. Poly neoepitope vaccines can inhibit the tumor's escape from the immune system. However, they have rapid clearance and low immunogenicity. Bacteria-derived recombinant outer membrane vesicles (OMVs) have gained increased attention as ideal cancer vaccine candidates due to their unique adjuvant properties and ability to carry antigens. Herein, the benefits of OMV-based and polyneoepitope-based vaccines were combined to obtain a functional individualized cancer vaccine. METHODS: OMVs and rOMVs displaying CT26 polytopes were isolated from ClearColi™ and recombinant ClearColi™ containing pET-22b (ClyA-CT26 polytope) by the AS (70 %) + UDF method. BALB/c mice were immunized with OMVs (40 µg) and rOMVs (20 and 40 µg) and subcutaneously challenged with CT26 cells. Then, IgG1 and IgG2a antibodies specific for CT26 M90 and CT26 polytope, the stimulated IFN-γ, TNF-α, and IL-10 cytokines and the stimulated CTL responses by measuring granzyme B were evaluated. To investigate whether pooled sera and pooled splenocytes are indicators of individual responses, pooled and individual methods for determining the elicited immunity were compared. Additionally, the ability of OMVs and rOMVs (20 and 40 µg) to prevent tumor growth against the CT26 challenge was investigated. RESULTS: Immunization with rOMVs displaying CT26 polytopes induced a higher titer of CT26 polytope- and CT26 M90 peptide-specific IgG2a than IgG1 antibodies in a dose-dependent manner, thus directing immunity to Th1. The antibody responses determined by pooled sera can be used as indicators of individual responses. In addition, both OMVs and rOMVs displaying CT26 polytopes could induce tumor-suppressing cytokines (IFN-γ and TNF-α). The ability of rOMVs displaying CT26 polytopes to induce these cytokines was higher than OMVs in a dose-dependent way. The results of the granzyme B assay were also in agreement with the cytokine assay. The survival of mice after the CT26 challenge was 100 % in the OMVs and rOMVs groups, and inhibition of tumor growth was significantly higher by rOMVs (40 µg) compared to OMVs. CONCLUSION: The bioengineered OMVs displaying CT26 neoepitopes have the potential for the development of personalized tumor vaccines. Our results can provide new insights for developing rOMV-based vaccines displaying polytopes against diseases containing highly variable antigens.

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies.

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

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.

iPSC-induced neurons with the V337M MAPT mutation are selectively vulnerable to caspase-mediated cleavage of tau and apoptotic cell death.

BACKGROUND: Tau post-translational modifications (PTMs) result in the gradual build-up of abnormal tau and neuronal degeneration in tauopathies, encompassing variants of frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). Tau proteolytically cleaved by active caspases, including caspase-6, may be neurotoxic and prone to self-aggregation. Also, our recent findings show that caspase-6 truncated tau represents a frequent and understudied aspect of tau pathology in AD in addition to phospho-tau pathology. In AD and Pick's disease, a large percentage of caspase-6 associated cleaved-tau positive neurons lack phospho-tau, suggesting that many vulnerable neurons to tau pathology go undetected when using conventional phospho-tau antibodies and possibly will not respond to phospho-tau based therapies. Therefore, therapeutic strategies against caspase cleaved-tau pathology could be necessary to modulate the extent of tau abnormalities in AD and other tauopathies. METHODS: To understand the timing and progression of caspase activation, tau cleavage, and neuronal death, we created two mAbs targeting caspase-6 tau cleavage sites and probed postmortem brain tissue from an individual with FTLD due to the V337M MAPT mutation. We then assessed tau cleavage and apoptotic stress response in cortical neurons derived from induced pluripotent stem cells (iPSCs) carrying the FTD-related V337M MAPT mutation. Finally, we evaluated the neuroprotective effects of caspase inhibitors in these iPSC-derived neurons. RESULTS: FTLD V337M MAPT postmortem brain showed positivity for both cleaved tau mAbs and active caspase-6. Relative to isogenic wild-type MAPT controls, V337M MAPT neurons cultured for 3 months post-differentiation showed a time-dependent increase in pathogenic tau in the form of caspase-cleaved tau, phospho-tau, and higher levels of tau oligomers. Accumulation of toxic tau species in V337M MAPT neurons was correlated with increased vulnerability to pro-apoptotic stress. Notably, this mutation-associated cell death was pharmacologically rescued by the inhibition of effector caspases. CONCLUSIONS: Our results suggest an upstream, time-dependent accumulation of caspase-6 cleaved tau in V337M MAPT neurons promoting neurotoxicity. These processes can be reversed by caspase inhibition. These results underscore the potential of developing caspase-6 inhibitors as therapeutic agents for FTLD and other tauopathies. Additionally, they highlight the promise of using caspase-cleaved tau as biomarkers for these conditions.

In Silico Design of CT26 Polytope and its Surface Display by ClearColi™-Derived Outer Membrane Vesicles as a Cancer Vaccine Candidate Against Colon Carcinoma.

Simultaneous targeting of several mutations can be useful in colorectal cancer (CRC) due to its heterogeneity and presence of somatic mutations. As CT26 mutations and expression profiles resemble those of human CRC, we focused on designing a polyepitope vaccine based on CT26 neoepitopes. Due to its low immunogenicity, outer membrane vesicles (rOMV) as an antigen delivery system and adjuvant was applied. Herein, based on previous experimental and our in silico studies four CT26 neoepitopes with the ability to bind MHC-I and MHC-II, TCR, and induce IFN-α production were selected. To increase their immunogenicity, the gp70 and PADRE epitopes were added. The order of the neoepitopes was determined through 3D structure analysis using ProSA, Verify 3D, ERRAT, and Ramachandran servers. The stable peptide-protein docking between the selected epitopes and MHC alleles strengthen our prediction. The CT26 polytope vaccine sequence was fused to the C-terminal of cytolysin A (ClyA) anchor protein and rOMVs were isolated from endotoxin-free ClearColi™ strain. The results of the C-ImmSim server showed that the ClyA-CT26 polytope vaccine could induce T and B cells immunity.The ClyA-CT26 polytope was characterized as a soluble, stable, immunogen, and non-allergen vaccine and optimized for expression in ClearColi™ 24 h after induction with 1 mM IPTG at 25 °C. Western blot analysis confirmed the expression of ClyA-CT26 polytope by ClearColi™ and also on ClearColi™-derived rOMVs. In conclusion, we found that ClearColi™-derived rOMVs with CT26 polytope can deliver CRC neoantigens and induce antitumor immunity, but in vivo immunological studies are needed to confirm vaccine efficacy.

The immune response behind peptide vaccination in diffuse midline glioma.

A first-in-human trial demonstrated that a vaccine targeting the histone mutation H3K27M can induce an immune response, in a mutation-specific manner, in patients with diffuse midline glioma. In a recent study by Boschert et al., the same group now dissects the functional immune response triggered after effective vaccination of one of the patients, who has been in remission for over 3 years. The H3K27M peptide vaccine, named H3-vac, induces a CD4+ T-cell-specific immune response in this patient and expands the repertoire of polyclonal H3K27M-specific T-cell receptors. A clonal H3K27M-reactive B-cell population was also detected in the patient's cerebrospinal fluid. Importantly, the immune response is induced across various human leukocyte antigen alleleotypes, indicating the potential efficacy of the vaccine in diverse populations. By exploring in detail the immune response linked to this patient's long-term survival, the authors prove peptide vaccinations as a viable therapeutic approach. This paves the way for personalised therapies harnessing immunogenic T- and B-cell responses against different tumour types.

Cartilage Collagen Neoepitope C2C Expression in the Articular Cartilage and Its Relation to Joint Tissue Damage in Patients with Knee Osteoarthritis.

Pathological cleavage of type II collagen (Col2) and generation of Col2 neoepitopes can serve as useful molecular markers of the progression of osteoarthritis (OA). One of such potential biomarkers is type II collagen neoepitope C2C. The aim of this study was to correlate the degree of articular cartilage damage in OA patients with C2C expression in histological samples of tissues removed during total knee replacement. Cartilage samples were obtained from 27 patients ranging in age from 55 to 66 years. In each patient, medial and lateral tibia plateau samples were analyzed according to the OARSI histopathology grading system. The C2C expression was evaluated on histological slides by semi-quantitative analysis using ImageJ Fiji 2.14.0 software. Spearman's rank correlation analysis revealed a positive weak correlation (rho = 0.289, p = 0.0356) between the histological grade of tissue damage and the percentage of C2C staining. In addition, a highly significant positive correlation (rho = 0.388, p = 0.0041) was discovered between the osteoarthritis score (combining the histological grade of damage with the OA macroscopic stage) and the percentage of C2C staining in the samples. The C2C expression was detected in all the regions of the articular cartilage (i.e., the superficial zone, mid zone, deep zone and tidemark area, and the zone of calcified cartilage). Our findings imply that local expression of C2C correlates with the articular cartilage damage in OA-affected knees. This confirms that C2C can be used as a prospective marker for assessing pathological changes in the OA course and OA clinical trials.

Neo-epitope detection identifies extracellular matrix turnover in systemic inflammation and sepsis: an exploratory study.

BACKGROUND: Sepsis is associated with high morbidity and mortality, primarily due to systemic inflammation-induced tissue damage, resulting organ failure, and impaired recovery. Regulated extracellular matrix (ECM) turnover is crucial for maintaining tissue homeostasis in health and in response to disease-related changes in the tissue microenvironment. Conversely, uncontrolled turnover can contribute to tissue damage. Systemic Inflammation is implicated to play a role in the regulation of ECM turnover, but the relationship between the two is largely unclear. METHODS: We performed an exploratory study in 10 healthy male volunteers who were intravenously challenged with 2 ng/kg lipopolysaccharide (LPS, derived from Escherichia coli) to induce systemic inflammation. Plasma samples were collected before (T0) and after (T 1 h, 3 h, 6 h and 24 h) the LPS challenge. Furthermore, plasma was collected from 43 patients with septic shock on day 1 of ICU admission. Circulating neo-epitopes of extracellular matrix turnover, including ECM degradation neo-epitopes of collagen type I (C1M), type III (C3M), type IV (C4Ma3), and type VI (C6M), elastin (ELP-3) and fibrin (X-FIB), as well as the ECM synthesis neo-epitopes of collagen type III (PRO-C3), collagen type IV (PRO-C4) and collagen type VI (PRO-C6) were measured by ELISA. Patient outcome data were obtained from electronic patient records. RESULTS: Twenty-four hours after LPS administration, all measured ECM turnover neo-epitopes, except ELP-3, were increased compared to baseline levels. In septic shock patients, concentrations of all measured ECM neo-epitopes were higher compared to healthy controls. In addition, concentrations of C6M, ELP-3 and X-FIB were higher in patients with septic shock who ultimately did not survive (N = 7) compared to those who recovered (N = 36). CONCLUSION: ECM turnover is induced in a model of systemic inflammation in healthy volunteers and was observed in patients with septic shock. Understanding interactions between systemic inflammation and ECM turnover may provide further insight into mechanisms underlying acute and persistent organ failure in sepsis.

Idiopathic pulmonary fibrosis (IPF): Diagnostic routes using novel biomarkers.

Idiopathic pulmonary fibrosis (IPF) diagnosis is still the diagnosis of exclusion. Differentiating from other forms of interstitial lung diseases (ILDs) is essential, given the various therapeutic approaches. The IPF course is now unpredictable for individual patients, although some genetic factors and several biomarkers have already been associated with various IPF prognoses. Since its early stages, IPF may be asymptomatic, leading to a delayed diagnosis. The present review critically examines the recent literature on molecular biomarkers potentially useful in IPF diagnostics. The examined biomarkers are grouped into breath and sputum biomarkers, serologically assessed extracellular matrix neoepitope markers, and oxidative stress biomarkers in lung tissue. Fibroblasts and complete blood count have also gained recent interest in that respect. Although several biomarker candidates have been profiled, there has yet to be a single biomarker that proved specific to the IPF disease. Nevertheless, various IPF biomarkers have been used in preclinical and clinical trials to verify their predictive and monitoring potential.

FusionVAC22_01: a phase I clinical trial evaluating a DNAJB1-PRKACA fusion transcript-based peptide vaccine combined with immune checkpoint inhibition for fibrolamellar hepatocellular carcinoma and other tumor entities carrying the oncogenic driver fusion.

The DNAJB1-PRKACA fusion transcript was identified as the oncogenic driver of tumor pathogenesis in fibrolamellar hepatocellular carcinoma (FL-HCC), also known as fibrolamellar carcinoma (FLC), as well as in other tumor entities, thus representing a broad target for novel treatment in multiple cancer entities. FL-HCC is a rare primary liver tumor with a 5-year survival rate of only 45%, which typically affects young patients with no underlying primary liver disease. Surgical resection is the only curative treatment option if no metastases are present at diagnosis. There is no standard of care for systemic therapy. Peptide-based vaccines represent a low side-effect approach relying on specific immune recognition of tumor-associated human leucocyte antigen (HLA) presented peptides. The induction (priming) of tumor-specific T-cell responses against neoepitopes derived from gene fusion transcripts by peptide-vaccination combined with expansion of the immune response and optimization of immune function within the tumor microenvironment achieved by immune-checkpoint-inhibition (ICI) has the potential to improve response rates and durability of responses in malignant diseases. The phase I clinical trial FusionVAC22_01 will enroll patients with FL-HCC or other cancer entities carrying the DNAJB1-PRKACA fusion transcript that are locally advanced or metastatic. Two doses of the DNAJB1-PRKACA fusion-based neoepitope vaccine Fusion-VAC-XS15 will be applied subcutaneously (s.c.) with a 4-week interval in combination with the anti-programmed cell death-ligand 1 (PD-L1) antibody atezolizumab starting at day 15 after the first vaccination. Anti-PD-L1 will be applied every 4 weeks until end of the 54-week treatment phase or until disease progression or other reason for study termination. Thereafter, patients will enter a 6 months follow-up period. The clinical trial reported here was approved by the Ethics Committee II of the University of Heidelberg (Medical faculty of Mannheim) and the Paul-Ehrlich-Institute (P-00540). Clinical trial results will be published in peer-reviewed journals. Trial registration numbers: EU CT Number: 2022-502869-17-01 and ClinicalTrials.gov Registry (NCT05937295).

IMPROVE: a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition.

Background: Mutation-derived neoantigens are critical targets for tumor rejection in cancer immunotherapy, and better tools for neoepitope identification and prediction are needed to improve neoepitope targeting strategies. Computational tools have enabled the identification of patient-specific neoantigen candidates from sequencing data, but limited data availability has hindered their capacity to predict which of the many neoepitopes will most likely give rise to T cell recognition. Method: To address this, we make use of experimentally validated T cell recognition towards 17,500 neoepitope candidates, with 467 being T cell recognized, across 70 cancer patients undergoing immunotherapy. Results: We evaluated 27 neoepitope characteristics, and created a random forest model, IMPROVE, to predict neoepitope immunogenicity. The presence of hydrophobic and aromatic residues in the peptide binding core were the most important features for predicting neoepitope immunogenicity. Conclusion: Overall, IMPROVE was found to significantly advance the identification of neoepitopes compared to other current methods.

Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes.

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

A Serological Neoepitope Biomarker of Neutrophil Elastase-Degraded Calprotectin, Associated with Neutrophil Activity, Identifies Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease More Effectively Than Total Calprotectin.

Neutrophil activation can release neutrophil extracellular traps (NETs) in acute inflammation. NETs result in the release of human neutrophil elastase (HNE) and calprotectin, where the former can degrade the latter and generate protein fragments associated with neutrophil activity. We investigated this in chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) using the novel neoepitope biomarker CPa9-HNE, quantifying a specific HNE-mediated fragment of calprotectin in serum. CPa9-HNE was compared to total calprotectin. Initially, CPa9-HNE was measured in healthy (n = 39), COPD (n = 67), and IPF (n = 16) serum using a neoepitope-specific competitive enzyme-linked immunosorbent assay. Then, a head-to-head comparison of CPa9-HNE and total calprotectin, a non-neoepitope, was conducted in healthy (n = 19), COPD (n = 25), and IPF (n = 19) participants. CPa9-HNE levels were significantly increased in COPD (p < 0.0001) and IPF subjects (p = 0.0001) when compared to healthy participants. Additionally, CPa9-HNE distinguished IPF (p < 0.0001) and COPD (p < 0.0001) from healthy participants more effectively than total calprotectin for IPF (p = 0.0051) and COPD (p = 0.0069). Here, CPa9-HNE also distinguished IPF from COPD (p = 0.045) participants, which was not observed for total calprotectin (p = 0.98). Neutrophil activity was significantly higher, as assessed via serum CPa9-HNE, for COPD and IPF compared to healthy participants. Additionally, CPa9-HNE exceeded the ability of non-neoepitope calprotectin serum measurements to separate healthy from lung disease and even COPD from IPF participants, indicating that neutrophil activity is essential for both COPD and IPF.

SIGANEO: Similarity network with GAN enhancement for immunogenic neoepitope prediction.

Target selection of the personalized cancer neoantigen vaccine, which is highly dependent on computational prediction algorithms, is crucial for its clinical efficacy. Due to the limited number of experimentally validated immunogenic neoepitopes as well as the complexity of neoantigens in eliciting T cell response, the accuracy of neoepitope immunogenicity prediction methods requires persistent efforts for improvement. We present a deep learning framework for neoepitope immunogenicity prediction - SIGANEO by integrating GAN-like network with similarity network to address issues of missing values and limited data concerning neoantigen prediction. This framework exhibits superior performance over competing machine-learning-based neoantigen prediction algorithms over an independent test dataset from TESLA consortium. Particularly for the clinical setting of neoantigen vaccine where only the top 10 and 20 predictions are selected for vaccine production, SIGANEO achieves significantly better accuracy for predicting experimentally validated neoepitopes. Our work demonstrates that deep learning techniques can greatly boost the accuracy of target identification for cancer neoantigen vaccine.

Immunological analysis of hybrid neoantigen peptide encompassing class I/II neoepitope-pulsed dendritic cell vaccine.

Neoantigens/ are tumor-specific antigens that evade central immune tolerance mechanisms in the thymus. Long-term tumor-specific cytotoxic T lymphocyte activity maintenance requires class II antigen-reactive CD4+ T cells. We had previously shown that intranodal vaccination with class I neoantigen peptide-pulsed dendritic cells (DCs) induced a robust immune response in a subset of patients with metastatic cancer. The present study aimed to perform a detailed ex vivo analysis of immune responses in four patients receiving an intranodal hybrid human leukocyte antigen class II neoantigen peptide encompassing a class I neoantigen epitope (hybrid neoantigen)-pulsed DC vaccine. After vaccination, strong T-cell reactions against the hybrid class II peptide and the class I-binding neoantigen peptide were observed in all four patients. We found that hybrid class II neoantigen peptide-pulsed DCs stimulated CD4+ T cells via direct antigen presentation and CD8+ T cells via cross-presentation. Further, we demonstrated that hybrid class II peptides encompassing multiple class I neoantigen epitope-pulsed DCs could present multiple class I peptides to CD8+ T cells via cross-presentation. Our findings provide insight into the mechanisms underlying hybrid neoantigen-pulsed DC vaccine therapy and suggest future neoantigen vaccine design.

A robust deep learning workflow to predict CD8 + T-cell epitopes.

BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies. However, the identification of antigens recognised by T-cells is low-throughput and laborious. To overcome some of these limitations, computational methods for predicting CD8 + T-cell epitopes have emerged. Despite recent developments, most immunogenicity algorithms struggle to learn features of peptide immunogenicity from small datasets, suffer from HLA bias and are unable to reliably predict pathology-specific CD8 + T-cell epitopes. METHODS: We developed TRAP (T-cell recognition potential of HLA-I presented peptides), a robust deep learning workflow for predicting CD8 + T-cell epitopes from MHC-I presented pathogenic and self-peptides. TRAP uses transfer learning, deep learning architecture and MHC binding information to make context-specific predictions of CD8 + T-cell epitopes. TRAP also detects low-confidence predictions for peptides that differ significantly from those in the training datasets to abstain from making incorrect predictions. To estimate the immunogenicity of pathogenic peptides with low-confidence predictions, we further developed a novel metric, RSAT (relative similarity to autoantigens and tumour-associated antigens), as a complementary to 'dissimilarity to self' from cancer studies. RESULTS: TRAP was used to identify epitopes from glioblastoma patients as well as SARS-CoV-2 peptides, and it outperformed other algorithms in both cancer and pathogenic settings. TRAP was especially effective at extracting immunogenicity-associated properties from restricted data of emerging pathogens and translating them onto related species, as well as minimising the loss of likely epitopes in imbalanced datasets. We also demonstrated that the novel metric termed RSAT was able to estimate immunogenic of pathogenic peptides of various lengths and species. TRAP implementation is available at: https://github.com/ChloeHJ/TRAP . CONCLUSIONS: This study presents a novel computational workflow for accurately predicting CD8 + T-cell epitopes to foster a better understanding of antigen-specific T-cell response and the development of effective clinical therapeutics.

A serologically assessed neo-epitope biomarker of cellular fibronectin degradation is related to pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by excessive extracellular matrix (ECM) remodeling, herein ECM degradation. Fibronectin (FN) is an important component of the ECM that is produced by multiple cell types, including fibroblasts. Extra domain B (EDB) is specific for a cellular FN isoform which is found in the ECM. We sought to develop a non-invasive test to investigate whether matrix metalloproteinase 8 (MMP-8) degradation of EDB in cellular FN results in a specific protein fragment that can be assessed serologically and if levels relate to pulmonary fibrosis. METHOD: Cellular FN was cleaved in vitro by MMP-8 and a protein fragment was identified by mass spectrometry. A monoclonal antibody (mAb) was generated, targeting a neo-epitope originating from EDB in cellular FN. Utilizing this mAb, a neo-epitope specific enzyme-linked immunosorbent assay (FN-EDB) was developed and technically validated. Serum FN-EDB was assessed in an IPF cohort (n = 98), registered at clinicaltrials.gov (NCT02818712), and in healthy controls (n = 35). RESULTS: The FN-EDB assay had high specificity for the MMP-8 degraded neo-epitope and was technically robust. FN-EDB serum levels were not influenced by age, sex, ethnicity, or BMI. Moreover, FN-EDB serum levels were significantly higher in IPF patients (median 31.38 [IQR 25.79-46.84] ng/mL) as compared to healthy controls (median 28.05 [IQR 21.58-33.88] ng/mL, p = 0.023). CONCLUSION: We developed the neo-epitope specific FN-EDB assay, a competitive ELISA, as a tool for serological assessment of MMP-8 mediated degradation of EDB in cellular FN. This study indicates that degradation of EDB in cellular FN is elevated in IPF and warrants further investigation.

Circular RNAs as a potential source of neoepitopes in cancer.

Neoepitopes have attracted much attention as targets for immunotherapy against cancer. Therefore, efficient neoepitope screening technology is an essential step in the development of personalized vaccines. Circular RNAs (circRNAs) are generated by back-splicing and have a single-stranded continuous circular structure. So far, various circRNAs have been poorly characterized, though new evidence suggests that a few translated circRNAs may play a role in cancer. In the present study, circRNA was used as a source of neoepitope, a novel strategy as circRNA-derived neoepitopes have never been previously explored. The present study reports CIRC_neo (circRNA-derived neoepitope prediction pipeline), which is a comprehensive and automated bioinformatic pipeline for the prediction of circRNA-derived neoepitopes from RNA sequencing data. The computational prediction from sequencing data requires complex computational workflows to identify circRNAs, derive the resulting peptides, infer the types of human leukocyte antigens (HLA I and HLA II) in patients, and predict the neoepitopes binding to these antigens. The present study proposes a novel source of neoepitopes. The study focused on cancer-specific circRNAs, which have greatly expanded the source pool for neoepitope discovery. The statistical analysis of different features of circRNA-derived neoepitopes revealed that circRNAs could produce long proteins or truncated proteins. Because the peptides were completely foreign to the human body, they could be highly immunogenic. Importantly, circRNA-derived neoepitopes capable of binding to HLA were discovered. In the current study, circRNAs were systematically analyzed, revealing potential targets and novel research clues for cancer diagnosis, treatment, and prospective personalized vaccine research.

Phenotypic plasticity and reduced tissue retention of exhausted tumor-infiltrating T cells following neoadjuvant immunotherapy in head and neck cancer.

Neoadjuvant immunotherapies (NITs) have led to clinical benefits in several cancers. Characterization of the molecular mechanisms underlying responses to NIT may lead to improved treatment strategies. Here we show that exhausted, tumor-infiltrating CD8+ T (Tex) cells display local and systemic responses to concurrent neoadjuvant TGF-ß and PD-L1 blockade. NIT induces a significant and selective increase in circulating Tex cells associated with reduced intratumoral expression of the tissue-retention marker CD103. TGF-ß-driven CD103 expression on CD8+ T cells is reversed following TGF-ß neutralization in vitro, implicating TGF-ß in T cell tissue retention and impaired systemic immunity. Transcriptional changes implicate T cell receptor signaling and glutamine metabolism as important determinants of enhanced or reduced Tex treatment response, respectively. Our analysis illustrates physiological and metabolic changes underlying T cell responses to NIT, highlighting the interplay between immunosuppression, tissue retention, and systemic anti-tumor immunity and suggest antagonism of T cell tissue retention as a promising neoadjuvant treatment strategy.

Salivary biglycan-neo-epitope-BGN262: A novel surrogate biomarker for equine osteoarthritic sub-chondral bone sclerosis and to monitor the effect of short-term training and surface arena.

Objective: We aimed to delineate a novel soluble Biglycan Neo-epitope-BGN262 in saliva from young reference and osteoarthritic horses in conjunction with the influence of short-term training exercise, riding surface hardness, circadian rhythm, and feeding on its soluble levels. Design: A custom-made inhibition ELISA was used for the quantification of BGN262 in saliva. Cohort 1: A cross-sectional study comprising reference (N â€‹= â€‹19) and OA horses (N â€‹= â€‹9) with radiographically classified subchondral bone sclerosis. Receiver operating characteristic curve analysis was performed to evaluate the robustness of BGN262. Cohorts 2 (N â€‹= â€‹5) & 3 (N â€‹= â€‹7): Longitudinal studies of sampling during a short-term training exercise (sand-fibre) and a cross-over design of short-training exercise on 2 different riding arenas (sand and sand-fibre), respectively. Capillary western immunoassay was used to determine the BGN262 molecular size in a selection of saliva samples collected from cohort 1. Results: Cohort 1: Salivary BGN262 levels were significantly higher in the OA group. The Receiver operating characteristic curve analysis showed an area under the curve of 0.8304 [0.6386 to 1.022], indicating a good separation from the reference group. Cohorts 2 & 3: Salivary BGN262 levels significantly changed during the exercise on sand and sand-fibre arena, with a trend towards higher levels for sand-fibre. The size of the BGN262 fragment determined by Capillary western assay was 18 â€‹kDa. Conclusions: The data presented show saliva BGN262 levels as a novel biomarker in evaluating the influence of exercise, and interaction with riding arenas alongside assessing osteoarthritis severity.