DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning

2020 ◽  
Vol 36 (19) ◽  
pp. 4894-4901 ◽  
Author(s):  
Yi Shi ◽  
Zehua Guo ◽  
Xianbin Su ◽  
Luming Meng ◽  
Mingxuan Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
T Cell ◽  
Distribution Patterns ◽  
Supplementary Information ◽  
Sparse Learning ◽  
Mhc I ◽  
3D Genome ◽  
Immunogenic Peptides ◽  
New Perspective ◽  
Personalized Cancer

Abstract Motivation The mutations of cancers can encode the seeds of their own destruction, in the form of T-cell recognizable immunogenic peptides, also known as neoantigens. It is computationally challenging, however, to accurately prioritize the potential neoantigen candidates according to their ability of activating the T-cell immunoresponse, especially when the somatic mutations are abundant. Although a few neoantigen prioritization methods have been proposed to address this issue, advanced machine learning model that is specifically designed to tackle this problem is still lacking. Moreover, none of the existing methods considers the original DNA loci of the neoantigens in the perspective of 3D genome which may provide key information for inferring neoantigens’ immunogenicity. Results In this study, we discovered that DNA loci of the immunopositive and immunonegative MHC-I neoantigens have distinct spatial distribution patterns across the genome. We therefore used the 3D genome information along with an ensemble pMHC-I coding strategy, and developed a group feature selection-based deep sparse neural network model (DNN-GFS) that is optimized for neoantigen prioritization. DNN-GFS demonstrated increased neoantigen prioritization power comparing to existing sequence-based approaches. We also developed a webserver named deepAntigen (http://yishi.sjtu.edu.cn/deepAntigen) that implements the DNN-GFS as well as other machine learning methods. We believe that this work provides a new perspective toward more accurate neoantigen prediction which eventually contribute to personalized cancer immunotherapy. Availability and implementation Data and implementation are available on webserver: http://yishi.sjtu.edu.cn/deepAntigen. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Utilizing TAPBPR to promote exogenous peptide loading onto cell surface MHC I molecules

2018 ◽  
Vol 115 (40) ◽  
pp. E9353-E9361 ◽  
Author(s):  
F. Tudor Ilca ◽  
Andreas Neerincx ◽  
Mark R. Wills ◽  
Maike de la Roche ◽  
Louise H. Boyle
Keyword(s):  
Plasma Membrane ◽  
T Cell ◽  
Cell Surface ◽  
Cell Receptor ◽  
Target Cells ◽  
Intact Cells ◽  
Mhc I ◽  
Immunogenic Peptides ◽  
Presentation Pathway ◽  
Peptide Exchange

The repertoire of peptides displayed at the cell surface by MHC I molecules is shaped by two intracellular peptide editors, tapasin and TAPBPR. While cell-free assays have proven extremely useful in identifying the function of both of these proteins, here we explored whether a more physiological system could be developed to assess TAPBPR-mediated peptide editing on MHC I. We reveal that membrane-associated TAPBPR targeted to the plasma membrane retains its ability to function as a peptide editor and efficiently catalyzes peptide exchange on surface-expressed MHC I molecules. Additionally, we show that soluble TAPBPR, consisting of the luminal domain alone, added to intact cells, also functions as an effective peptide editor on surface MHC I molecules. Thus, we have established two systems in which TAPBPR-mediated peptide exchange on MHC class I can be interrogated. Furthermore, we could use both plasma membrane-targeted and exogenous soluble TAPBPR to display immunogenic peptides on surface MHC I molecules and consequently induce T cell receptor engagement, IFN-γ secretion, and T cell-mediated killing of target cells. Thus, we have developed an efficient way to by-pass the natural antigen presentation pathway of cells and load immunogenic peptides of choice onto cells. Our findings highlight a potential therapeutic use for TAPBPR in increasing the immunogenicity of tumors in the future.

scholarly journals PLGA Nanoparticles Co-encapsulating NY-ESO-1 Peptides and IMM60 Induce Robust CD8 and CD4 T Cell and B Cell Responses

2021 ◽  
Vol 12 ◽  
Author(s):  
Yusuf Dölen ◽  
Uzi Gileadi ◽  
Ji-Li Chen ◽  
Michael Valente ◽  
Jeroen H. A. Creemers ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Responses ◽  
Plga Nanoparticles ◽  
Inkt Cell ◽  
Cell Responses ◽  
Immunogenic Peptides ◽  
High Doses ◽  
Personalized Cancer ◽  
Antibody Levels

Tumor-specific neoantigens can be highly immunogenic, but their identification for each patient and the production of personalized cancer vaccines can be time-consuming and prohibitively expensive. In contrast, tumor-associated antigens are widely expressed and suitable as an off the shelf immunotherapy. Here, we developed a PLGA-based nanoparticle vaccine that contains both the immunogenic cancer germline antigen NY-ESO-1 and an α-GalCer analog IMM60, as a novel iNKT cell agonist and dendritic cell transactivator. Three peptide sequences (85–111, 117–143, and 157–165) derived from immunodominant regions of NY-ESO-1 were selected. These peptides have a wide HLA coverage and were efficiently processed and presented by dendritic cells via various HLA subtypes. Co-delivery of IMM60 enhanced CD4 and CD8 T cell responses and antibody levels against NY-ESO-1 in vivo. Moreover, the nanoparticles have negligible systemic toxicity in high doses, and they could be produced according to GMP guidelines. Together, we demonstrated the feasibility of producing a PLGA-based nanovaccine containing immunogenic peptides and an iNKT cell agonist, that is activating DCs to induce antigen-specific T cell responses.

Molecular mechanism of TLR4 mediated T cell immune effect in transfusion-induced acute lung injury based on Slit2/Robo4 signaling pathway

2020 ◽  
Vol 13 ◽  
Author(s):  
Kun Xiao ◽  
Fei Zhao ◽  
WenJie Xie ◽  
Jian Ding ◽  
XiaoAn Gong ◽  
...  
Keyword(s):  
T Cell ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Lung Tissue ◽  
Acute Injury ◽  
Tissue Homogenate ◽  
Control Group ◽  
Pathological Features ◽  
Mhc I ◽  
Immune Effect

Objective: To explore and investigate the molecular mechanism of TLR4 mediated T cell immune effect in transfusion-induced acute injury based on SLIT2/ROBO4 signaling pathway. Methods: Sixty C57/BL6 male mice (Wild type, WT) aged 8 to 10 weeks were randomly divided into 5 groups: 1) normal type WT, 2) LPS control group of WT type lipopolysaccharide, 3) WT type TRALI group (LPS + MHC-I mAb), 4) (TLR4 antibody) lipopolysaccharide LPS control group, 5) (TLR4 antibody) TRALI group (LPS + MHC-I mAb). Mice were dosed with LPS (0.1 mg / kg), and MHC-I mAb (2 mg / kg) was injected into the tail vein 24 hours later for modeling. After 2 hours, mice were sacrificed and experimental samples were collected. HE staining was performed to detect pathological features. The myeloperoxidase (MPO) activity and the level of IL-2, IL-6, TNF, IFN-γ, IL-17A as well as IL-10 were measured in the lung tissue homogenate supernatant. Blood, spleen single cell suspension and bronchoalveolar lavage fluid (BALF) were collected to detect the ratio of Treg and Th17 cells by flow cytometry, respectively. RT-PCR and WB indicated the mRNA or protein expression of CDH5 (Cadherin-5), SLIT2 and ROBO4 in mouse lung tissue and pulmonary vascular tissue respectively. Results: TLR4 mAb treatment decreases the pathological features of LPS induced ALI model in vivo. And so does the MPO activity as well as the level of proinflammatory factors in the lung tissue. TLR4 exerts its function through the changes of Treg/Th17 ratio via SLIT2/ROBO4 signaling pathway and downregulating CDH5 and SETSIP in ALI model. Conclusion: TLR4 mediates immune response in LPS induced ALI model through SLIT2/ROBO4 signaling pathway.

scholarly journals NetCleave: an open-source algorithm for predicting C-terminal antigen processing for MHC-I and MHC-II

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pep Amengual-Rigo ◽  
Victor Guallar
Keyword(s):  
Open Source ◽  
Antigen Processing ◽  
High Accuracy ◽  
Biological Processes ◽  
Mhc I ◽  
Mhc Ii ◽  
Prediction Tools ◽  
Immunogenic Peptides ◽  
Physicochemical Descriptors ◽  
Peptide Presentation

AbstractAntigens presented on the cell surface have been subjected to multiple biological processes. Among them, C-terminal antigen processing constitutes one of the main bottlenecks of the peptide presentation pathways, as it delimits the peptidome that will be subjected downstream. Here, we present NetCleave, an open-source and retrainable algorithm for the prediction of the C-terminal antigen processing for both MHC-I and MHC-II pathways. NetCleave architecture consists of a neural network trained on 46 different physicochemical descriptors of the cleavage site amino acids. Our results demonstrate that prediction of C-terminal antigen processing achieves high accuracy on MHC-I (AUC of 0.91), while it remains challenging for MHC-II (AUC of 0.66). Moreover, we evaluated the performance of NetCleave and other prediction tools for the evaluation of four independent immunogenicity datasets (H2-Db, H2-Kb, HLA-A*02:01 and HLA-B:07:02). Overall, we demonstrate that NetCleave stands out as one of the best algorithms for the prediction of C-terminal processing, and we provide one of the first evidence that C-terminal processing predictions may help in the discovery of immunogenic peptides.

scholarly journals Modelling the interplay between the CD4$$^{+}$$/CD8$$^{+}$$ T-cell ratio and the expression of MHC-I in tumours

2021 ◽  
Vol 83 (1) ◽  
Author(s):  
Christian John Hurry ◽  
Alexander Mozeika ◽  
Alessia Annibale
Keyword(s):  
Immune Response ◽  
T Cell ◽  
Critical Level ◽  
Cell Infiltration ◽  
Cytotoxic T Cell ◽  
Mhc I ◽  
Cell Ratio ◽  
T Cell Infiltration ◽  
Immunological Mechanisms ◽  
Tcr Repertoire

AbstractDescribing the anti-tumour immune response as a series of cellular kinetic reactions from known immunological mechanisms, we create a mathematical model that shows the CD4$$^{+}$$ + /CD8$$^{+}$$ + T-cell ratio, T-cell infiltration and the expression of MHC-I to be interacting factors in tumour elimination. Methods from dynamical systems theory and non-equilibrium statistical mechanics are used to model the T-cell dependent anti-tumour immune response. Our model predicts a critical level of MHC-I expression which determines whether or not the tumour escapes the immune response. This critical level of MHC-I depends on the helper/cytotoxic T-cell ratio. However, our model also suggests that the immune system is robust against small changes in this ratio. We also find that T-cell infiltration and the specificity of the intra-tumour TCR repertoire will affect the critical MHC-I expression. Our work suggests that the functional form of the time evolution of MHC-I expression may explain the qualitative behaviour of tumour growth seen in patients.

scholarly journals Differences in TCR repertoire and T cell activation underlie the divergent outcomes of antitumor immune responses in tumor-eradicating versus tumor-progressing hosts

2021 ◽  
Vol 9 (1) ◽  
pp. e001615
Author(s):  
Rachel A Woolaver ◽  
Xiaoguang Wang ◽  
Alexandra L Krinsky ◽  
Brittany C Waschke ◽  
Samantha M Y Chen ◽  
...  
Keyword(s):  
T Cell ◽  
Mouse Model ◽  
Immune Responses ◽  
Single Cell ◽  
T Cell Activation ◽  
Antitumor Immunity ◽  
Cell Activation ◽  
Tcr Repertoire ◽  
Underlying Mechanisms ◽  
Personalized Cancer

BackgroundAntitumor immunity is highly heterogeneous between individuals; however, underlying mechanisms remain elusive, despite their potential to improve personalized cancer immunotherapy. Head and neck squamous cell carcinomas (HNSCCs) vary significantly in immune infiltration and therapeutic responses between patients, demanding a mouse model with appropriate heterogeneity to investigate mechanistic differences.MethodsWe developed a unique HNSCC mouse model to investigate underlying mechanisms of heterogeneous antitumor immunity. This model system may provide a better control for tumor-intrinsic and host-genetic variables, thereby uncovering the contribution of the adaptive immunity to tumor eradication. We employed single-cell T-cell receptor (TCR) sequencing coupled with single-cell RNA sequencing to identify the difference in TCR repertoire of CD8 tumor-infiltrating lymphocytes (TILs) and the unique activation states linked with different TCR clonotypes.ResultsWe discovered that genetically identical wild-type recipient mice responded heterogeneously to the same squamous cell carcinoma tumors orthotopically transplanted into the buccal mucosa. While tumors initially grew in 100% of recipients and most developed aggressive tumors, ~25% of recipients reproducibly eradicated tumors without intervention. Heterogeneous antitumor responses were dependent on CD8 T cells. Consistently, CD8 TILs in regressing tumors were significantly increased and more activated. Single-cell TCR-sequencing revealed that CD8 TILs from both growing and regressing tumors displayed evidence of clonal expansion compared with splenic controls. However, top TCR clonotypes and TCR specificity groups appear to be mutually exclusive between regressing and growing TILs. Furthermore, many TCRα/TCRβ sequences only occur in one recipient. By coupling single-cell transcriptomic analysis with unique TCR clonotypes, we found that top TCR clonotypes clustered in distinct activation states in regressing versus growing TILs. Intriguingly, the few TCR clonotypes shared between regressors and progressors differed greatly in their activation states, suggesting a more dominant influence from tumor microenvironment than TCR itself on T cell activation status.ConclusionsWe reveal that intrinsic differences in the TCR repertoire of TILs and their different transcriptional trajectories may underlie the heterogeneous antitumor immune responses in different hosts. We suggest that antitumor immune responses are highly individualized and different hosts employ different TCR specificities against the same tumors, which may have important implications for developing personalized cancer immunotherapy.

132 CAR macrophages (CAR-M) elicit a systemic anti-tumor immune response and synergize with PD1 blockade in immunocompetent mouse models of HER2+ solid tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A145-A145
Author(s):  
Stefano Pierini ◽  
Rashid Gabbasov ◽  
Linara Gabitova ◽  
Yumi Ohtani ◽  
Michael Klichinsky
Keyword(s):  
Immune Response ◽  
Overall Survival ◽  
Animal Model ◽  
T Cell ◽  
Cancer Cells ◽  
Solid Tumors ◽  
Tumor Model ◽  
Epitope Spreading ◽  
Mhc I ◽  
Single Tumor

BackgroundDespite the remarkable efficacy achieved by CAR-T therapy in hematologic malignancies, application in solid tumors has been challenging. We previously developed human CAR-M and demonstrated that adoptive cell transfer of CAR-M into xenograft models of human cancer controls tumor progression and improves overall survival [1]. Given that CAR-M are professional antigen presenting cells, we developed an immunocompetent animal model to evaluate the potential for induction of a systemic anti-tumor immune response.MethodsMurine bone marrow-derived macrophages were engineered to express an anti-HER2 CAR using the chimeric adenoviral vector Ad5f35. CAR-M were phenotypically and functionally evaluated in vitro and in syngeneic models. To evaluate CAR-M efficacy in an immunocompetent animal model, BALB/c mice were engrafted with CT26-HER2+ tumors (single-tumor model) and were treated with intratumoral CAR-HER2 or untransduced (UTD) macrophages. To evaluate epitope spreading, we simultaneously engrafted BALB/c mice with CT26-HER2+ and CT26-Wt tumors on opposite flanks (dual-tumor model), and treated mice with CAR-M or controls into the CT26-HER2+ tumor only. Peripheral and tumor-infiltrating immune cells were phenotypically and functionally characterized.ResultsIn addition to efficient gene delivery, Ad5f35 transduction promoted a pro-inflammatory (M1) phenotype in murine macrophages. CAR-M, but not control UTD macrophages, phagocytosed HER2+ target cancer cells. Anti-HER2 CAR-M eradicated HER2+ murine CT26 colorectal and human AU-565 breast cancer cells in a dose-dependent manner. CAR-M increased MHC-I and MHC-II expression on tumor cells and promoted tumor-associated antigen presentation and T cell activation. In vivo, CAR-M treatment led to tumor regression and improved overall survival in the CT26-HER2+ single-tumor model. In the dual-tumor model, CAR-M treatment cleared 75% of CT26-HER2+ tumors and inhibited the growth rate of contralateral CT26-WT tumors, demonstrating an abscopal effect. CAR-M treatment led to increased infiltration of intratumoral CD4+ and CD8+ T, NK, and dendritic cells – as well as an increase in T cell responsiveness to the CT26 MHC-I antigen gp70, indicating enhanced epitope spreading. Given the impact CAR-M had on endogenous T-cell immunity, we evaluated the combination of CAR-M and anti-PD1 in the CT26-HER2 model and found that the combination further enhanced tumor control and overall survival.ConclusionsThese results demonstrate that CAR-M therapy induces epitope spreading via activation of endogenous T cells, orchestrating a systemic immune response against solid tumors. Moreover, our findings provide rationale for the combination of CAR-M with immune checkpoint inhibitors. The anti-HER2 CAR-M CT-0508 will be evaluated in an upcoming Phase I clinical trial.ReferenceKlichinsky M, Ruella M, Shestova O, et al. Human chimeric antigen receptor macrophages for cancer immunotherapy. Nat Biotechnol 2020;38(8):947–953.

418 A phase 1, dose escalation and dose expansion study of SQZ PBMC HPV as monotherapy and in combination with atezolizumab in HLA-A*02+ Patients with HPV16+ recurrent, or metastatic solid tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A444-A444
Author(s):  
Cathy Eng ◽  
Joaquina Baranda ◽  
Matthew Taylor ◽  
Michael Gordon ◽  
Ursula Matulonis ◽  
...  
Keyword(s):  
T Cell ◽  
Solid Tumors ◽  
Cancer Vaccine ◽  
Phase 1 ◽  
T Cell Responses ◽  
Cd8 T Cell ◽  
Dose Effect ◽  
Statistical Hypothesis ◽  
Mhc I ◽  
Cell Responses

BackgroundSQZ-PBMC-HPV is a therapeutic cancer vaccine created with Cell Squeeze®, a proprietary cell-engineering system. SQZ-PBMC-HPV is a novel cancer vaccine generated from peripheral blood mononuclear cells (PBMC) squeezed with HPV16 E6 and E7 antigens, resulting in delivery into the cytosol. The resulting antigen presenting cells (APCs) provide enhanced antigen presentation on MHC-I to potentially elicit robust, antigen-specific CD8+ T cell responses. Importantly, SQZ-PBMC-HPV are neither genetically modified nor immune effector cells.Studies in MHC-I knockout mice demonstrated that activation of antigen specific CD8+ tumor infiltrating lymphocytes (TILs) was a direct effect of cytosolic antigen delivery to PBMCs. In the murine TC-1 tumor model, tumor regression correlated with an influx of HPV16-specific CD8+ TILs. In vitro studies with human volunteer PBMCs demonstrated that each subset is capable of inducing CD8+ T cell responses. The Phase 1 study includes a significant biomarker program to investigate whether pharmacodynamic effects observed in non-clinical studies correlate with potential clinical benefit. Immunogenic and pharmacodynamic endpoints include Elispot assays to measure frequency of interferon gamma secreting cells, as well as quantification and characterization of TILs and tumor microenvironment. In addition, various cytokine responses and circulating cell-free HPV16 DNA levels in plasma are measured.MethodsSQZ-PBMC-HPV-101 (NCT04084951) is open for enrollment to HLA A*02+ patients with HPV16+ recurrent, locally advanced or metastatic solid tumors and includes escalation cohorts for monotherapy and in combination with atezolizumab. After initial demonstration of safety, the study assesses dose effect by testing different cell dose levels, the effect of prolonged antigen priming in Cycle 1 [APC administration on Day 1 only compared to Days 1 and 2 (double priming)] and the impact of treatment duration to identify the optimal dose regimen. The cycle length is 3 weeks, and patients will receive SQZ-PBMC-HPV for up to 1 year or until available autologous drug product is exhausted. Atezolizumab will be administered for up to 1 year. Eligible patients including but not limited to anal, cervical and head and neck tumors will undergo a single leukapheresis at the study site. The manufacturing process includes a maturation step and takes less than 24 hours. The vein-to-vein time for the 1st administration is approximately one week. Patients must have a lesion that can be biopsied with acceptable clinical risk and agree to have a fresh biopsy at Screening and on study. A Study Safety Committee is in place. No formal statistical hypothesis testing will be performed.ResultsN/AConclusionsN/ATrial RegistrationNCT04084951Ethics ApprovalThe study is registered on clinicaltrials.gov was approved by the Ethics Board of all institution listed as recruiting.

scholarly journals CXCL14 suppresses human papillomavirus-associated head and neck cancer through antigen-specific CD8+ T-cell responses by upregulating MHC-I expression

Oncogene ◽  
2019 ◽  
Vol 38 (46) ◽  
pp. 7166-7180 ◽  
Author(s):  
Joseph A. Westrich ◽  
Daniel W. Vermeer ◽  
Alexa Silva ◽  
Stephanie Bonney ◽  
Jennifer N. Berger ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Human Papillomavirus ◽  
T Cell ◽  
Head And Neck ◽  
Neck Cancer ◽  
T Cell Responses ◽  
Cd8 T Cell ◽  
Mhc I ◽  
Cell Responses

scholarly journals Accurate estimation of isoelectric point of protein and peptide based on amino acid sequences

2015 ◽  
Vol 32 (6) ◽  
pp. 821-827 ◽  
Author(s):  
Enrique Audain ◽  
Yassel Ramos ◽  
Henning Hermjakob ◽  
Darren R. Flower ◽  
Yasset Perez-Riverol
Keyword(s):  
Machine Learning ◽  
Isoelectric Point ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Basis Set ◽  
Superior Performance ◽  
Supplementary Information ◽  
Training Dataset ◽  
Accurate Estimation ◽  
Prediction Methods

Abstract Motivation: In any macromolecular polyprotic system—for example protein, DNA or RNA—the isoelectric point—commonly referred to as the pI—can be defined as the point of singularity in a titration curve, corresponding to the solution pH value at which the net overall surface charge—and thus the electrophoretic mobility—of the ampholyte sums to zero. Different modern analytical biochemistry and proteomics methods depend on the isoelectric point as a principal feature for protein and peptide characterization. Protein separation by isoelectric point is a critical part of 2-D gel electrophoresis, a key precursor of proteomics, where discrete spots can be digested in-gel, and proteins subsequently identified by analytical mass spectrometry. Peptide fractionation according to their pI is also widely used in current proteomics sample preparation procedures previous to the LC-MS/MS analysis. Therefore accurate theoretical prediction of pI would expedite such analysis. While such pI calculation is widely used, it remains largely untested, motivating our efforts to benchmark pI prediction methods. Results: Using data from the database PIP-DB and one publically available dataset as our reference gold standard, we have undertaken the benchmarking of pI calculation methods. We find that methods vary in their accuracy and are highly sensitive to the choice of basis set. The machine-learning algorithms, especially the SVM-based algorithm, showed a superior performance when studying peptide mixtures. In general, learning-based pI prediction methods (such as Cofactor, SVM and Branca) require a large training dataset and their resulting performance will strongly depend of the quality of that data. In contrast with Iterative methods, machine-learning algorithms have the advantage of being able to add new features to improve the accuracy of prediction. Contact: [email protected] Availability and Implementation: The software and data are freely available at https://github.com/ypriverol/pIR. Supplementary information: Supplementary data are available at Bioinformatics online.

Sign in / Sign up

Export Citation Format

Share Document