scholarly journals The Cancer Epitope Database and Analysis Resource: A Blueprint for the Establishment of a New Bioinformatics Resource for Use by the Cancer Immunology Community

2021 ◽  
Vol 12 ◽  
Author(s):  
Zeynep Koşaloğlu-Yalçın ◽  
Nina Blazeska ◽  
Hannah Carter ◽  
Morten Nielsen ◽  
Ezra Cohen ◽  
...  

Recent years have witnessed a dramatic rise in interest towards cancer epitopes in general and particularly neoepitopes, antigens that are encoded by somatic mutations that arise as a consequence of tumorigenesis. There is also an interest in the specific T cell and B cell receptors recognizing these epitopes, as they have therapeutic applications. They can also aid in basic studies to infer the specificity of T cells or B cells characterized in bulk and single-cell sequencing data. The resurgence of interest in T cell and B cell epitopes emphasizes the need to catalog all cancer epitope-related data linked to the biological, immunological, and clinical contexts, and most importantly, making this information freely available to the scientific community in a user-friendly format. In parallel, there is also a need to develop resources for epitope prediction and analysis tools that provide researchers access to predictive strategies and provide objective evaluations of their performance. For example, such tools should enable researchers to identify epitopes that can be effectively used for immunotherapy or in defining biomarkers to predict the outcome of checkpoint blockade therapies. We present here a detailed vision, blueprint, and work plan for the development of a new resource, the Cancer Epitope Database and Analysis Resource (CEDAR). CEDAR will provide a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature and provide easily accessible epitope and T cell/B cell target prediction and analysis tools. The curated cancer epitope data will provide a transparent benchmark dataset that can be used to assess how well prediction tools perform and to develop new prediction tools relevant to the cancer research community.

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1509-1509
Author(s):  
Katsuyoshi Takata ◽  
Lauren C. Chong ◽  
Avinash Thakur ◽  
Tomohiro Aoki ◽  
Anja Mottok ◽  
...  

Background: The tumor-associated antigen PRAME is over-expressed in several types of cancer and is currently investigated as a therapeutic target for T-cell immunotherapy. Our previous integrative genomic study in diffuse large B-cell lymphoma (DLBCL) identified PRAME deletion to be correlated with patient outcome and an immunologically "cold" tumor microenvironment. However, it remains an open question whether PRAME expression significantly contributes to differential treatment outcomes and tumor microenvironment crosstalk across various B-cell lymphoma subtypes. Material and Methods: We performed an immunohistochemical (IHC) screen in a large cohort of B-cell lymphomas (de novo DLBCL; N=347, follicular lymphoma (FL); N= 166, mantle cell lymphoma (MCL); N= 180), and classical Hodgkin lymphoma (HL); N= 166) to assess PRAME expression as a prognostic biomarker. Moreover, to investigate PRAME-expression associated tumor microenvironment composition and function, we correlated PRAME IHC results with single cell RNA sequencing data of more than 127,000 cells from 22 HL tissue specimens. Results: PRAME IHC analysis revealed frequent PRAME over-expression in HL (115/166, 69%), followed by DLBCL (104/319, 33%), FL (13/166, 8%), and MCL (14/180, 8%). Interestingly, only HL showed a significant treatment outcome correlation, whereas other B-cell lymphoma subtypes did not. Specifically, using a previously published HL cohort (Steidl et al, NEJM 2010) PRAME-negative Hodgkin Reed Sternberg (HRS) cells indicated significantly shorter overall survival (P = 0.008) and disease-specific survival (P = 0.042 ). To characterize PRAME-specific microenvironment composition and function in HL, we analyzed T-, B-, NK-cell, and macrophage subsets in PRAME-positive (17 of 22 cases) vs -negative (5 of 22 cases) tumor samples using single cell RNA sequencing data. From 22 expression-based microenvironment cell clusters that were annotated and assigned to a cell type based on gene expression, all three CD4 helper T-cell clusters were de-enriched in PRAME-negative samples, and the CD4 non-Treg proportion was significantly lower in PRAME-negative samples (P = 0.049). Strikingly, when focusing on phenotypic features of cells within the CD4 non-Treg T-cell cluster, CXCL13 was identified as the most up-regulated gene in PRAME-negative samples. When interrogating published HRS cell transcriptome data (Steidl et al, Blood 2012), immune response pathways including chemokine receptors and chemokine ligands were up-regulated in PRAME-negative HRS cell samples. Of specific interest, CXCR5, the cognate receptor for CXCL13, was significantly upregulated as a member of the chemokine pathway (P = 0.0086) in PRAME-negative HRS cell samples. These results suggest that crosstalk between CXCL13 (produced in the microenvironment) and CXCR5 (expressed on HRS cells) contributes to tumor maintenance in PRAME-negative HL. Finally, to explore potential therapeutic approaches for PRAME-negative HL cells, we focused on 3 HL-derived cell lines (L540, L591, DEV) with low PRAME expression and exposed these lines to DNMT or HDAC inhibitors. DNMT inhibitor treatment showed clear restoration of PRAME expression in a dose dependent manner, but no restoration was found by HDAC inhibitor treatment. To investigate the effect of DNA methylation in transcriptional regulation of PRAME in HL cells, we performed bisulfite sequencing in the PRAME CpG promoter region in PRAME down-regulated (L540, L591, DEV) and up-regulated (HD-LM2, KMH-2, L1236) cell lines and found hypermethylation in PRAME low vs high cell lines. Moreover, the CpG promoter region was significantly demethylated by DNMT inhibitor treatment in cell lines with low PRAME expression. Conclusion: We discovered that PRAME protein expression was correlated with outcome in HL and identified specific T-cell subsets in PRAME-negative patients. PRAME restoration by DNMT inhibitors might represent a new therapeutic avenue in combination with modern immunotherapies, such as PRAME-specific T-cell therapy or PD1 inhibition. Disclosures Scott: Roche/Genentech: Research Funding; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Celgene: Consultancy. Steidl:Nanostring: Patents & Royalties: Filed patent on behalf of BC Cancer; Bristol-Myers Squibb: Research Funding; Roche: Consultancy; Seattle Genetics: Consultancy; Bayer: Consultancy; Juno Therapeutics: Consultancy; Tioma: Research Funding.


2020 ◽  
Author(s):  
Parvez Slathia ◽  
Preeti Sharma,

<p>The world is currently battling the Covid-19 pandemic for which there is no therapy available. Prophylactic measures like vaccines can effectively thwart the disease burden. The current methods of detection are PCR based and require skilled manpower to operate. The availability of cheap and ready to use diagnostics like serological methods can ease the detection of SARS-CoV-2 virus. In the current study, immunoinformatics tools have been used to predict T and B cell epitopes present in all the proteins of this virus. NetMHCPan, NetCTL and NetMHCII servers were used for T cell epitope prediction while BepiPred and ABCPred were used for B cell epitope prediction. Population coverage analysis for T cell epitopes revealed that these could provide protection to the people throughout world. The T cell epitopes can exclusively used for vaccine design whereas B cell epitopes can be used for both vaccine design and developing diagnostic kits. </p> <p> </p>


2020 ◽  
Author(s):  
Parvez Slathia ◽  
Preeti Sharma,

<p>The world is currently battling the Covid-19 pandemic for which there is no therapy available. Prophylactic measures like vaccines can effectively thwart the disease burden. The current methods of detection are PCR based and require skilled manpower to operate. The availability of cheap and ready to use diagnostics like serological methods can ease the detection of SARS-CoV-2 virus. In the current study, immunoinformatics tools have been used to predict T and B cell epitopes present in all the proteins of this virus. NetMHCPan, NetCTL and NetMHCII servers were used for T cell epitope prediction while BepiPred and ABCPred were used for B cell epitope prediction. Population coverage analysis for T cell epitopes revealed that these could provide protection to the people throughout world. The T cell epitopes can exclusively used for vaccine design whereas B cell epitopes can be used for both vaccine design and developing diagnostic kits. </p> <p> </p>


2019 ◽  
Author(s):  
Sinu Paul ◽  
Nathan P. Croft ◽  
Anthony W. Purcell ◽  
David C. Tscharke ◽  
Alessandro Sette ◽  
...  

AbstractT cell epitope candidates are commonly identified using computational prediction tools in order to enable applications such as vaccine design, cancer neoantigen identification, development of diagnostics and removal of unwanted immune responses against protein therapeutics. Most T cell epitope prediction tools are based on machine learning algorithms trained on MHC binding or naturally processed MHC ligand elution data. The ability of currently available tools to predict T cell epitopes has not been comprehensively evaluated. In this study, we used a recently published dataset that systematically defined T cell epitopes recognized in vaccinia virus (VACV) infected mice, considering both peptides predicted to bind MHC or experimentally eluted from infected cells, making this the most comprehensive dataset of T cell epitopes mapped in a complex pathogen. We evaluated the performance of all currently publicly available computational T cell epitope prediction tools to identify these major epitopes from all peptides encoded in the VACV proteome. We found that all methods were able to improve epitope identification above random, with the best performance achieved by neural network-based predictions trained on both MHC binding and MHC ligand elution data (NetMHCPan-4.0 and MHCFlurry). Impressively, these methods were able to capture more than half of the major epitopes in the top 0.04% (N = 277) of peptides in the VACV proteome (N = 767,788). These performance metrics provide guidance for immunologists as to which prediction methods to use. In addition, this benchmark was implemented in an open and easy to reproduce format, providing developers with a framework for future comparisons against new tools.Author summaryComputational prediction tools are used to screen peptides to identify potential T cell epitope candidates. These tools, developed using machine learning methods, save time and resources in many immunological studies including vaccine discovery and cancer neoantigen identification. In addition to the already existing methods several epitope prediction tools are being developed these days but they lack a comprehensive and uniform evaluation to see which method performs best. In this study we did a comprehensive evaluation of publicly accessible MHC I restricted T cell epitope prediction tools using a recently published dataset of Vaccinia virus epitopes. We found that methods based on artificial neural network architecture and trained on both MHC binding and ligand elution data showed very high performance (NetMHCPan-4.0 and MHCFlurry). This benchmark analysis will help immunologists to choose the right prediction method for their desired work and will also serve as a framework for tool developers to evaluate new prediction methods.


2016 ◽  
Author(s):  
Tanushree Jaitly ◽  
Niels Schaft ◽  
Jan Doerrie ◽  
Stefanie Gross ◽  
Beatrice Schuler-Thurner ◽  
...  

In aggressive solid tumors like melanoma, a strategy for therapy personalization can be achieved by combining high-throughput data on the patient’s specific tumor mutation and expression profiles. A remarkable case is dendritic cell-based immunotherapy, where tumor epitopes identified from the patient’s specific mutation profiles are loaded on patient-derived mature dendritic cells to stimulate cytotoxic T cell mediated anticancer immunity. Here we present a personalized computational pipeline for the selection of tumor-specific epitopes based on 1) patient specific haplotype; 2) cancer associated mutations; and 3) expression profiles of mutation carrying genes. We applied our workflow to one melanoma patient. Specifically, we analyzed tumor whole exome sequencing and RNA sequencing data to first detect tumor-specific mutations followed by epitope prediction based on the patient’s HLA haplotype and filtering of epitopes using expression profile and binding affinity. We performed docking studies to predict the best set of epitopes targeting the patient’s alleles. The proposed workflow enables us to find personalized tumor-specific epitopes for stimulating cytotoxic T-cell responses.


2021 ◽  
Vol 948 (1) ◽  
pp. 012080
Author(s):  
S Pambudi ◽  
D Irawan ◽  
A Danny ◽  
T Widayanti ◽  
Tarwadi

Abstract The identification of human Non-Structural-1 (NS1) protein epitopes will help us better understand Dengue virus (DENV) immunopathogenesis. In this study, several online and offline bioinformatic prediction tools were exploited to predict and analyze T-cell and B-cell epitopes of DENV NS1 consensus sequences originated from Indonesian clinical isolates. We identified a potential peptide at NS1155--163 (VEDYGFGIF) which interact with MHC-I allele HLA-B*40:01 and showed high binding affinity (IC50) scores ranging between 63.8 nM to 183.9 nM for all Indonesian DENV serotypes. Furthermore, we have succeeded identified a region at the C-terminal of Indonesian DENV NS1 protein between 325--344 as part of discontinuous antigenic epitope which conserved for all serotypes. Our analyses showed this region could induce strong and persistent antibody against all DENV serotypes by interacting with MHC-I molecule and also recognized by B-cell receptor. The identification of DENV NS1 T-cell and B-cell epitopes may help in the development of a new vaccine, drug discovery, and diagnostic system to help eradicate dengue infection.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4105-4105
Author(s):  
Keisuke Kataoka ◽  
Hiroaki Miyoshi ◽  
Yasunori Kogure ◽  
Yasuharu Sato ◽  
Kenji Nishida ◽  
...  

Abstract Immune checkpoint blockade using anti-PD-1 or anti-PD-L1 antibodies is a highly promising therapy that can induce a durable anti-tumor response and a long-term remission in many patients with multiple cancer types. In particular, the excellent efficacy of anti-PD-1 antibody has been reported in advanced cases with classical Hodgkin lymphoma (cHL), of which high frequency of genetic lesions involving PD-L1 and/or PD-L2 somatic alterations is a defining feature, suggesting a close link between the relevant genetic lesions and the efficacy of anti-PD-1/PD-L1 therapy. In addition to cHL, several subtypes of B-cell lymphomas are shown to have structural variations (SVs) involving PD-1 ligands, such as gene amplification and chromosomal translocation causing promoter replacement. Moreover, recently we reported unique SVs disrupting the 3′-untranslated region (UTR) of PD-L1 in a diversity of cancers, including adult T-cell leukemia/lymphoma (ATL) and diffuse large B-cell lymphoma (DLBCL). However, the comprehensive landscape of PD-L1 and PD-L2 alterations in non-Hodgkin lymphomas has not been fully elucidated. Therefore, in this study, we interrogated PD-L1 and PD-L2 genetic aberrations and characterized their features in a variety of non-Hodgkin lymphomas. To do this, lymphoma-derived DNA was captured for the entire region of PD-L1 and PD-L2 genes including their exons, introns, and 3′- and 5′-untranslated regions (UTRs) and subjected to high-throughput DNA sequencing. More than 300 samples from different lymphoma subtypes were analyzed, including DLBCL, follicular lymphoma, mantle cell lymphoma, MALT lymphoma, primary mediastinal B-cell lymphoma, peripheral T-cell lymphoma-not otherwise specified, and cutaneous T-cell lymphoma. We also analyzed publicly available sequencing data as well as our own data for lymphomas, which included Burkitt and angioimmunoblastic T-cell lymphomas as well. PD-L1/PD-L2-involving SVs were most frequently observed in PMBCL, accounting for 26.3% of the cases, but widely observed in various B- and T-cell lymphomas at varying but generally low frequencies. However, in contrast to PD-L1-involving SVs, which were found in both B- and T-cell lymphomas, PD-L2-involving SVs were exclusively seen in B-cell lymphomas. Depending on samples, different SV types were observed, including deletion, inversion, tandem duplication, and translocation, but most of SVs resulted in a truncation of the 3'-UTR of the PD-L1 or PD-L2 genes. Unlike previous reports, we rarely found those SVs that translocate PD-L1/PD-L2 to an ectopic regulatory element. Of particular interest were those cases in which multiple, independent SVs that converged to PD-L1 and PD-L2, were observed in a single tumor sample, underscoring the importance of PD-L1 and PD-L2 SVs in clonal selection and expansion of these tumors Given that PD-L1-involving SVs are detected not only in aggressive lymphomas but also in a variety of solid cancers, we hypothesized that PD-L2 genetic alterations are also present in other human cancers. However, no PD-L2-involving SVs were identified among > 10,000 cancer samples from 32 tumor panels, for which RNA sequencing data were available from the Cancer Genome Atlas (TCGA). These results suggest that PD-L1 is affected in a broad spectrum of human malignancies, whereas PD-L2 SVs are a characteristic alteration of B-cell lymphomas, which is consistent with their expression patterns. Based on these findings, we assessed whether disruption of PD-L2 3'-UTR also induces PD-L2 overexpression as seen for that of PD-L1 3'-UTR. When introduced in T2 human B and T lymphoblast hybrid cell line using the CRISPR/Cas9 system, SVs involving an almost entire PD-L2 3'-UTR sequence actually induced a significant elevation of PD-L2 expression, confirming the relevance of 3'-UTR in the regulation of PD-L2 expression. Taken together, our findings clarified the entire picture of PD-L1/PD-L2-involving SVs ligands in B- and T-cell lymphomas. Detection of these SVs might help the identification of patients with non-Hodgkin lymphomas who potentially benefit from PD-1/PD-L1 blockade therapy. Disclosures Kataoka: Kyowa Hakko Kirin: Honoraria; Boehringer Ingelheim: Honoraria; Yakult: Honoraria. Izutsu:Abbvie: Research Funding; Gilead: Research Funding; Celgene: Research Funding; Janssen Pharmaceutical K.K.: Honoraria; Eisai: Honoraria; Kyowa Hakko Kirin: Honoraria; Chugai Pharmaceutical: Honoraria, Research Funding; Takeda Pharmaceutical: Honoraria; Mundipharma KK: Research Funding. Ohshima:Kyowa Hakko Kirin Co., Ltd.: Research Funding, Speakers Bureau; CHUGAI PHARMACEUTICAL CO.,LTD.: Research Funding, Speakers Bureau. Ogawa:Kan research institute: Consultancy, Research Funding; Takeda Pharmaceuticals: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding.


2007 ◽  
Vol 20 (2) ◽  
pp. 75-82 ◽  
Author(s):  
Jason A. Greenbaum ◽  
Pernille Haste Andersen ◽  
Martin Blythe ◽  
Huynh-Hoa Bui ◽  
Raul E. Cachau ◽  
...  

2020 ◽  
Vol 37 (1) ◽  
Author(s):  
Bilal Ahmed Khan ◽  
Saif Ullah ◽  
Amanullah Lail ◽  
Saeed Khan

Background & Objectives: The Chikungunya virus (CHIKV) transmitted to the humans through Aedes species of the mosquitoes. In December 2016, a severe outbreak reported from Pakistan. However, there is no vaccine or anti-viral treatment currently available so host immune response against CHIKV gained significant interest. Therefore, this study was conducted to identify the mutations in CHIKV E2 region of currently circulating Pakistani strains & determine their potential immunogenicity in Pakistani population. Methods: It was a cross sectional study in which a total of 60 CHIKV PCR positive samples were collected from Molecular Department of Pathology, Dow University of Health Sciences (DUHS), Karachi during November 2017 to February 2018. CHIKV E2 gene was amplified by PCR & sequenced. Sequences were analyzed by using bioinformatic tools followed by epitope prediction in E2 sequences by In-silico immunoinformatic approach. Results: Several single nucleotide variations (SNVs) were identified in Pakistani isolates with six novel mutations in E2 sequences. Immunoinformatic analyses showed more proteasomal sites, CTL & B-Cell epitopes in Pakistani strains with respect to S27 prototype with 69.4% population coverage against these epitopes in Pakistan. The study also identified key mutations responsible for generation of unique epitopes and HLA restriction in Pakistani isolates. The strain specific mutations revealed the current outbreak was caused by ESCA.IOL lineage of CHIKV. Conclusion: The evolution of E2 protein in Pakistani strains has increased its immunogenicity in comparison to ancestral s27 strain. The identification of most immunogenic and conserved epitopes with high population coverage has high potential to be used in vaccine development against these local strains. doi: https://doi.org/10.12669/pjms.37.1.3236 How to cite this:Khan BA, Saifullah, Lail A, Khan S. Sub-genomic analysis of Chikungunya virus E2 mutations in Pakistani isolates potentially modulating B-cell & T-Cell immune response. Pak J Med Sci. 2021;37(1):93-98. doi: https://doi.org/10.12669/pjms.37.1.3236 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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