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Jensen MF, Nielsen M. Enhancing TCR specificity predictions by combined pan- and peptide-specific training, loss-scaling, and sequence similarity integration. eLife 2024; 12:RP93934. [PMID: 38437160 PMCID: PMC10942633 DOI: 10.7554/elife.93934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024] Open
Abstract
Predicting the interaction between Major Histocompatibility Complex (MHC) class I-presented peptides and T-cell receptors (TCR) holds significant implications for vaccine development, cancer treatment, and autoimmune disease therapies. However, limited paired-chain TCR data, skewed towards well-studied epitopes, hampers the development of pan-specific machine-learning (ML) models. Leveraging a larger peptide-TCR dataset, we explore various alterations to the ML architectures and training strategies to address data imbalance. This leads to an overall improved performance, particularly for peptides with scant TCR data. However, challenges persist for unseen peptides, especially those distant from training examples. We demonstrate that such ML models can be used to detect potential outliers, which when removed from training, leads to augmented performance. Integrating pan-specific and peptide-specific models alongside with similarity-based predictions, further improves the overall performance, especially when a low false positive rate is desirable. In the context of the IMMREP22 benchmark, this modeling framework attained state-of-the-art performance. Moreover, combining these strategies results in acceptable predictive accuracy for peptides characterized with as little as 15 positive TCRs. This observation places great promise on rapidly expanding the peptide covering of the current models for predicting TCR specificity. The NetTCR 2.2 model incorporating these advances is available on GitHub (https://github.com/mnielLab/NetTCR-2.2) and as a web server at https://services.healthtech.dtu.dk/services/NetTCR-2.2/.
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Affiliation(s)
- Mathias Fynbo Jensen
- Department of Health Technology, Section for Bioinformatics, Technical University of DenmarkLyngbyDenmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of DenmarkLyngbyDenmark
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2
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Wan YTR, Koşaloğlu‐Yalçın Z, Peters B, Nielsen M. A large-scale study of peptide features defining immunogenicity of cancer neo-epitopes. NAR Cancer 2024; 6:zcae002. [PMID: 38288446 PMCID: PMC10823584 DOI: 10.1093/narcan/zcae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Revised: 01/03/2024] [Accepted: 01/12/2024] [Indexed: 01/31/2024] Open
Abstract
Accurate prediction of immunogenicity for neo-epitopes arising from a cancer associated mutation is a crucial step in many bioinformatics pipelines that predict outcome of checkpoint blockade treatments or that aim to design personalised cancer immunotherapies and vaccines. In this study, we performed a comprehensive analysis of peptide features relevant for prediction of immunogenicity using the Cancer Epitope Database and Analysis Resource (CEDAR), a curated database of cancer epitopes with experimentally validated immunogenicity annotations from peer-reviewed publications. The developed model, ICERFIRE (ICore-based Ensemble Random Forest for neo-epitope Immunogenicity pREdiction), extracts the predicted ICORE from the full neo-epitope as input, i.e. the nested peptide with the highest predicted major histocompatibility complex (MHC) binding potential combined with its predicted likelihood of antigen presentation (%Rank). Key additional features integrated into the model include assessment of the BLOSUM mutation score of the neo-epitope, and antigen expression levels of the wild-type counterpart which is often reflecting a neo-epitope's abundance. We demonstrate improved and robust performance of ICERFIRE over existing immunogenicity and epitope prediction models, both in cross-validation and on external validation datasets.
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Affiliation(s)
- Yat-tsai Richie Wan
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, DK 28002, Denmark
| | - Zeynep Koşaloğlu‐Yalçın
- Center for Infectious Disease and Vaccine Research, La Jolla Institute of Immunology, La Jolla, CA 92037, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute of Immunology, La Jolla, CA 92037, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, DK 28002, Denmark
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3
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Taksoee-Vester CA, Mikolaj K, Petersen OBB, Vejlstrup NG, Christensen AN, Feragen A, Nielsen M, Svendsen MBS, Tolsgaard MG. Role of AI-assisted automated cardiac biometrics in screening for fetal coarctation of aorta. Ultrasound Obstet Gynecol 2024. [PMID: 38339776 DOI: 10.1002/uog.27608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024]
Abstract
OBJECTIVES Although there have been remarkable strides in fetal medicine and prenatal diagnosis of congenital heart disease, a significant percentage of newborns with isolated coarctation of the aorta (CoA) - around 60 percent - are still not identified prior to birth. The prenatal detection of CoA has been shown to have a notable impact on the survival rates of affected infants. To this end, the implementation of artificial intelligence (AI) in fetal ultrasound may represent a groundbreaking advancement. Our hypothesis is that leveraging automated cardiac biometric measurements with AI during the 18-22-week anomaly scan will enhance the identification of fetuses that are at risk of developing CoA. METHODS We have developed an AI model capable of identifying standard cardiac planes and conducting automated cardiac biometric measurements. Our data consisted of pregnancy ultrasound image and outcome data spanning from 2008 to 2018 and collected from four distinct regions in Denmark. The CoA cases from the period were paired with healthy controls in a ratio of 1:100 and matched on gestational ages of ±2 days. The cardiac biometrics on the four-chamber view and three vessel view were included in a logistic regression-based prediction model. To assess the predictive capabilities, we visualized sensitivity and specificity on Receiver Operating Characteristic (ROC) curves. RESULTS At the 18-22 week scan, the right ventricle (RV)area and length, left ventricle (LV) width, and the ratios of RV/LV areas and main pulmonary artery/ascending aorta diameters showed significant differences with z-scores above 0.7 when comparing subjects with a postnatal diagnosis of CoA (n=73) and healthy controls (n=7300). Using logistic regression and backward feature selection, our prediction model produced a ROC curve with an AUC (Area Under the Curve) of 0.96 and a specificity of 88.9% at a sensitivity level of 90.4%. CONCLUSION The integration of AI technology with automated cardiac biometric measurements conducted during the 18-22-week anomaly scan in fetal medicine has the potential to substantially enhance the screening for fetal CoA and subsequently the rate of CoA detection. Future research should clarify how AI technology can be used to aid in screening and detection of congenital heart anomalies to improve neonatal outcomes. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- C A Taksoee-Vester
- University of Copenhagen, Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, Denmark
- Center of Fetal Medicine, Dept. of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Denmark
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Denmark
| | - K Mikolaj
- Technical University of Denmark, Lyngby, Denmark
| | - O B B Petersen
- University of Copenhagen, Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, Denmark
- Center of Fetal Medicine, Dept. of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - N G Vejlstrup
- Dept. of Cardiology, Copenhagen University Hospital, Rigshospitalet, Denmark
| | | | - A Feragen
- Technical University of Denmark, Lyngby, Denmark
| | - M Nielsen
- University of Copenhagen, Dept. of Computer Science, Denmark
| | - M B S Svendsen
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Denmark
| | - M G Tolsgaard
- University of Copenhagen, Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, Denmark
- Center of Fetal Medicine, Dept. of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Denmark
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Denmark
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Høie MH, Gade FS, Johansen J, Würtzen C, Winther O, Nielsen M, Marcatili P. DiscoTope-3.0: improved B-cell epitope prediction using inverse folding latent representations. Front Immunol 2024; 15:1322712. [PMID: 38390326 PMCID: PMC10882062 DOI: 10.3389/fimmu.2024.1322712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/08/2024] [Indexed: 02/24/2024] Open
Abstract
Accurate computational identification of B-cell epitopes is crucial for the development of vaccines, therapies, and diagnostic tools. However, current structure-based prediction methods face limitations due to the dependency on experimentally solved structures. Here, we introduce DiscoTope-3.0, a markedly improved B-cell epitope prediction tool that innovatively employs inverse folding structure representations and a positive-unlabelled learning strategy, and is adapted for both solved and predicted structures. Our tool demonstrates a considerable improvement in performance over existing methods, accurately predicting linear and conformational epitopes across multiple independent datasets. Most notably, DiscoTope-3.0 maintains high predictive performance across solved, relaxed and predicted structures, alleviating the need for experimental structures and extending the general applicability of accurate B-cell epitope prediction by 3 orders of magnitude. DiscoTope-3.0 is made widely accessible on two web servers, processing over 100 structures per submission, and as a downloadable package. In addition, the servers interface with RCSB and AlphaFoldDB, facilitating large-scale prediction across over 200 million cataloged proteins. DiscoTope-3.0 is available at: https://services.healthtech.dtu.dk/service.php?DiscoTope-3.0.
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Affiliation(s)
- Magnus Haraldson Høie
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Frederik Steensgaard Gade
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Julie Maria Johansen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Charlotte Würtzen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Ole Winther
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
- Center for Genomic Medicine, Rigshospitalet (Copenhagen University Hospital), Copenhagen, Denmark
- Department of Biology, Bioinformatics Centre, University of Copenhagen, Copenhagen, Denmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Paolo Marcatili
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
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5
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Yankilevich P, Nazerai L, Willis SC, Schmiegelow K, De Zio D, Nielsen M. An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome. Cancer Immunol Immunother 2024; 73:22. [PMID: 38279992 PMCID: PMC10821971 DOI: 10.1007/s00262-023-03610-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/07/2023] [Indexed: 01/29/2024]
Abstract
Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is increasing, and consequently, the need for data analysis pipelines is likewise growing. Most NGS data analysis solutions to date do not support mouse data or require highly specific configuration for their use. Here, we present a genome analysis pipeline for mouse tumour NGS data including the whole-genome sequence (WGS) data analysis flow for somatic variant discovery, and the RNA-seq data flow for differential expression, functional analysis and neoantigen prediction. The pipeline is based on standards and best practices and integrates mouse genome references and annotations. In a recent study, the pipeline was applied to demonstrate the efficacy of low dose 6-thioguanine (6TG) treatment on low-mutation melanoma in a pre-clinical mouse model. Here, we further this study and describe in detail the pipeline and the results obtained in terms of tumour mutational burden (TMB) and number of predicted neoantigens, and correlate these with 6TG effects on tumour volume. Our pipeline was expanded to include a neoantigen analysis, resulting in neopeptide prediction and MHC class I antigen presentation evaluation. We observed that the number of predicted neoepitopes were more accurate indicators of tumour immune control than TMB. In conclusion, this study demonstrates the usability of the proposed pipeline, and suggests it could be an essential robust genome analysis platform for future mouse genomic analysis.
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Affiliation(s)
- Patricio Yankilevich
- Bioinformatics Core Facility, Instituto de Investigación en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina.
| | - Loulieta Nazerai
- Melanoma Research Team, Danish Cancer Institute, Copenhagen, Denmark
- Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Shona Caroline Willis
- Melanoma Research Team, Danish Cancer Institute, Copenhagen, Denmark
- Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Kjeld Schmiegelow
- Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Daniela De Zio
- Melanoma Research Team, Danish Cancer Institute, Copenhagen, Denmark
- Department of Cancer and Inflammation Research, Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, Lyngby, Denmark.
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Liao H, Barra C, Zhou Z, Peng X, Woodhouse I, Tailor A, Parker R, Carré A, Borrow P, Hogan MJ, Paes W, Eisenlohr LC, Mallone R, Nielsen M, Ternette N. MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer. Nat Commun 2024; 15:661. [PMID: 38253617 PMCID: PMC10803737 DOI: 10.1038/s41467-023-44460-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 12/14/2023] [Indexed: 01/24/2024] Open
Abstract
Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.
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Affiliation(s)
- Hanqing Liao
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | | | - Zhicheng Zhou
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
| | - Xu Peng
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
| | - Isaac Woodhouse
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Arun Tailor
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Robert Parker
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Alexia Carré
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
| | - Persephone Borrow
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Michael J Hogan
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Wayne Paes
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK
| | - Laurence C Eisenlohr
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, 75014, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, 75014, Paris, France
| | | | - Nicola Ternette
- The Jenner Institute, University of Oxford, Oxford, OX3 7BN, UK.
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7DQ, UK.
- University of Utrecht, Department of Pharmaceutical Sciences, 3584 CH, Utrecht, The Netherlands.
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7
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Egholm Bruun Jensen E, Reynisson B, Barra C, Nielsen M. New light on the HLA-DR immunopeptidomic landscape. J Leukoc Biol 2024:qiae007. [PMID: 38214568 DOI: 10.1093/jleuko/qiae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 12/18/2023] [Accepted: 12/27/2023] [Indexed: 01/13/2024] Open
Abstract
The set of peptides processed and presented by MHC class II molecules define the immunopeptidome, and its characterisation holds keys to understanding essential properties of the immune system. High-throughput mass spectrometry techniques enable interrogation of the diversity and complexity of the immunopeptidome at an unprecedented scale. Here, we analysed a large set of MS-immunopeptidomics data from 40 donors, 221 samples, covering 30 unique HLA-DR molecules. We identified likely co-immunoprecipitated HLA-DR irrelevant contaminants using state-of-the-art prediction methods and unveiled novel light on the properties of HLA antigen processing and presentation. The ligandome (HLA binders) was enriched in 15-mer peptides, and the contaminome (non-binders) in longer peptides. Classification of singletons and nested sets showed that the first were enriched in contaminants. Investigating the source protein location of ligands revealed that only contaminants shared a positional bias. Regarding subcellular localisation, nested peptides were found to predominantly be of endo-lysosomal whereas singletons shared an equal distribution between the cytosolic and endo-lysosomal origin. According to antigen processing signatures, no significant differences were observed between the cytosolic and endo-lysosomal ligands. Further, the sensitivity of MS-immunopeptidomics was investigated by analysing overlap and saturation between biological MS-replica, concluding that at least 5 replicas are needed to identify 80% of the immunopeptidome. Moreover, the overlap in immunopeptidome between donors was found to be very low both in terms of peptides and source proteins, the latter indicating a critical HLA bias in the antigen sampling in the HLA antigen presentation. Finally, the complementarity between MS and in-silico approaches for comprehensively sampling the immunopeptidome was demonstrated.
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Affiliation(s)
| | - Birkir Reynisson
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Carolina Barra
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, B 1650 HMP, Buenos Aires, Argentina
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Terlouw D, Boot A, Ducarmon QR, Nooij S, Jessurun MA, van Leerdam ME, Tops CM, Langers AMJ, Morreau H, van Wezel T, Nielsen M. Colibactin mutational signatures in NTHL1 tumor syndrome and MUTYH associated polyposis patients. Genes Chromosomes Cancer 2024; 63:e23208. [PMID: 37795928 DOI: 10.1002/gcc.23208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 10/06/2023] Open
Abstract
Polyketide synthase (pks) island harboring Escherichia coli are, under the right circumstances, able to produce the genotoxin colibactin. Colibactin is a risk factor for the development of colorectal cancer and associated with mutational signatures SBS88 and ID18. This study explores colibactin-associated mutational signatures in biallelic NTHL1 and MUTYH patients. Targeted Next Generation Sequencing (NGS) was performed on colorectal adenomas and carcinomas of one biallelic NTHL and 12 biallelic MUTYH patients. Additional fecal metagenomics and genome sequencing followed by mutational signature analysis was conducted for the NTHL1 patient. Targeted NGS of the NTHL1 patient showed somatic APC variants fitting SBS88 which was confirmed using WGS. Furthermore, fecal metagenomics revealed pks genes. Also, in 1 out of 11 MUTYH patient a somatic variant was detected fitting SBS88. This report shows that colibactin may influence development of colorectal neoplasms in predisposed patients.
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Affiliation(s)
- D Terlouw
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - A Boot
- Department of Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore
| | - Q R Ducarmon
- Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands
| | - S Nooij
- Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands
| | - M A Jessurun
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - M E van Leerdam
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands
| | - C M Tops
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - A M J Langers
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands
| | - H Morreau
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - T van Wezel
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - M Nielsen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
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Friborg J, Jensen K, Eriksen JG, Samsøe E, Maare C, Farhadi M, Sibolt P, Nielsen M, Andersen M, Holm AIS, Skyt P, Smulders B, Johansen J, Overgaard J, Grau C, Hansen CR. Considerations for study design in the DAHANCA 35 trial of protons versus photons for head and neck cancer. Radiother Oncol 2024; 190:109958. [PMID: 37871751 DOI: 10.1016/j.radonc.2023.109958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 08/10/2023] [Accepted: 09/26/2023] [Indexed: 10/25/2023]
Abstract
Proton radiotherapy offers a dosimetric advantage compared to photon therapy in sparing normal tissue, but the clinical evidence for toxicity reductions in the treatment of head and neck cancer is limited. The Danish Head and Neck Cancer Group (DAHANCA) has initiated the DAHANCA 35 randomised trial to clarify the value of proton therapy (NCT04607694). The DAHANCA 35 trial is performed in an enriched population of patients selected by an anticipated benefit of proton therapy to reduce the risk of late dysphagia or xerostomia based on normal tissue complication probability (NTCP) modelling. We present our considerations on the trial design and a test of the selection procedure conducted before initiating the randomised study.
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Affiliation(s)
- J Friborg
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark; Department of Oncology, Rigshospitalet, Denmark. %
| | - K Jensen
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark
| | - J G Eriksen
- Department of Oncology, Aarhus University Hospital, Denmark; Aarhus University Hospital, Department of Experimental Clinical Oncology, Denmark
| | - E Samsøe
- Department of Oncology, Zealand University Hospital Næstved, Denmark
| | - C Maare
- Department of Oncology, Copenhagen University Hospital - Herlev and Gentofte, Denmark
| | - M Farhadi
- Department of Oncology, Zealand University Hospital Næstved, Denmark
| | - P Sibolt
- Department of Oncology, Copenhagen University Hospital - Herlev and Gentofte, Denmark
| | - M Nielsen
- Department of Oncology, Aalborg University Hospital, Denmark
| | - M Andersen
- Department of Oncology, Aalborg University Hospital, Denmark
| | - A I S Holm
- Department of Oncology, Aarhus University Hospital, Denmark
| | - P Skyt
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark
| | - B Smulders
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark; Department of Oncology, Rigshospitalet, Denmark
| | - J Johansen
- Department of Oncology, Odense University Hospital, Denmark
| | - J Overgaard
- Aarhus University Hospital, Department of Experimental Clinical Oncology, Denmark
| | - C Grau
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark
| | - C R Hansen
- Danish Center of Particle Therapy, Aarhus University Hospital, Denmark; Department of Oncology, Odense University Hospital, Denmark; Institute of Clinical Research, University of Southern Denmark, Denmark
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Marrama D, Chronister WD, Westernberg L, Vita R, Koşaloğlu-Yalçın Z, Sette A, Nielsen M, Greenbaum JA, Peters B. PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins. BMC Bioinformatics 2023; 24:485. [PMID: 38110863 PMCID: PMC10726511 DOI: 10.1186/s12859-023-05606-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 12/06/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions. The utility of such tools is critical in applications ranging from identifying conservation across viral epitopes, identifying putative epitope targets for allergens, and finding matches for cancer-associated neoepitopes to examine the role of tolerance in tumor recognition. RESULTS We defined a set of benchmarks that reflect the different practical applications of short peptide sequence matching. We evaluated a suite of existing methods for speed and recall and developed a new tool, PEPMatch. The tool uses a deterministic k-mer mapping algorithm that preprocesses proteomes before searching, achieving a 50-fold increase in speed over methods such as the Basic Local Alignment Search Tool (BLAST) without compromising recall. PEPMatch's code and benchmark datasets are publicly available. CONCLUSIONS PEPMatch offers significant speed and recall advantages for peptide sequence matching. While it is of immediate utility for immunologists, the developed benchmarking framework also provides a standard against which future tools can be evaluated for improvements. The tool is available at https://nextgen-tools.iedb.org , and the source code can be found at https://github.com/IEDB/PEPMatch .
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Affiliation(s)
- Daniel Marrama
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - William D Chronister
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - Luise Westernberg
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - Randi Vita
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - Zeynep Koşaloğlu-Yalçın
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - Alessandro Sette
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
- University of California San Diego School of Medicine, La Jolla, San Diego, CA, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Jason A Greenbaum
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA
| | - Bjoern Peters
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, San Diego, CA, USA.
- University of California San Diego School of Medicine, La Jolla, San Diego, CA, USA.
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11
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Nielsen M, Monberg T, Sundvold V, Albieri B, Hovgaard D, Petersen MM, Krarup-Hansen A, Met Ö, Camilio K, Clancy T, Stratford R, Sveinbjornsson B, Rekdal Ø, Junker N, Svane IM. LTX-315 and adoptive cell therapy using tumor-infiltrating lymphocytes generate tumor specific T cells in patients with metastatic soft tissue sarcoma. Oncoimmunology 2023; 13:2290900. [PMID: 38125722 PMCID: PMC10732595 DOI: 10.1080/2162402x.2023.2290900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
LTX-315 is an oncolytic peptide that elicits both local and systemic immune responses upon intratumoral injection. In the present pilot trial, we treated patients with metastatic soft tissue sarcoma with the combination of LTX-315 and adoptive T-cell therapy using in vitro expanded tumor-infiltrating lymphocytes. Six heavily pretreated patients were included in the trial and treated with LTX-315 of which four patients proceeded to adoptive T-cell therapy. Overall, the treatment was considered safe with only expected and manageable toxicity. The best overall clinical response was stable disease for 208 days, and in this patient, we detected tumor-reactive T cells in the blood that lasted until disease progression. In three patients T-cell reactivity against in silico predicted neoantigens was demonstrated. Additionally, de novo T-cell clones were generated and expanded in the blood following LTX-315 injections. In conclusion, this pilot study provides proof that it is feasible to combine LTX-315 and adoptive T-cell therapy, and that this treatment can induce systemic immune responses that resulted in stabilization of the disease in sarcoma patients with otherwise progressive disease. Further optimization of the treatment protocol is warranted to increase clinical activity. ClinicalTrials.gov Identifier: NCT03725605.
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Affiliation(s)
- Morten Nielsen
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Tine Monberg
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | | | - Benedetta Albieri
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Dorrit Hovgaard
- Department of Orthopedic Surgery, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Michael Mørk Petersen
- Department of Orthopedic Surgery, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Özcan Met
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | | | | | | | | | | | - Niels Junker
- Department of Oncology, Herlev and Gentofte Hospital, Herlev, Denmark
| | - Inge Marie Svane
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
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12
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Nilsson JB, Kaabinejadian S, Yari H, Kester MG, van Balen P, Hildebrand WH, Nielsen M. Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. Sci Adv 2023; 9:eadj6367. [PMID: 38000035 PMCID: PMC10672173 DOI: 10.1126/sciadv.adj6367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/25/2023] [Indexed: 11/26/2023]
Abstract
Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4+ T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR because of limited availability of immunopeptidomics data for HLA-DQ and HLA-DP while not taking into account alternative peptide binding modes. We present an update to the NetMHCIIpan prediction method, which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across all loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes.
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Affiliation(s)
- Jonas B. Nilsson
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Saghar Kaabinejadian
- Pure MHC LLC, Oklahoma City, OK, USA
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Hooman Yari
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Michel G. D. Kester
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - Peter van Balen
- Department of Hematology, Leiden University Medical Center, Leiden, Netherlands
| | - William H. Hildebrand
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
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13
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Foos G, Blazeska N, Nielsen M, Carter H, Kosaloglu-Yalcin Z, Peters B, Sette A. A meta-analysis of epitopes in prostate-specific antigens identifies opportunities and knowledge gaps. Hum Immunol 2023; 84:578-589. [PMID: 37679223 DOI: 10.1016/j.humimm.2023.08.145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 08/16/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND The Cancer Epitope Database and Analysis Resource (CEDAR) is a newly developed repository of cancer epitope data from peer-reviewed publications, which includes epitope-specific T cell, antibody, and MHC ligand assays. Here we focus on prostate cancer as our first cancer category to demonstrate the capabilities of CEDAR, and to shed light on the advances of epitope-related prostate cancer research. RESULTS The meta-analysis focused on a subset of data describing epitopes from 8 prostate-specific (PS) antigens. A total of 460 epitopes were associated with these proteins, 187 T cell, 109B cell, and 271 MHC ligand epitopes. The number of epitopes was not correlated with the length of the protein; however, we found a significant positive correlation between the number of references per specific PS antigen and the number of reported epitopes. Forty-four different class I and 27 class II restrictions were found, with the most epitopes described for HLA-A*02:01 and HLA-DRB1*01:01. Cytokine assays were mostly limited to IFNg assays and a very limited number of tetramer assays were performed. Monoclonal and polyclonal B cell responses were balanced, with the highest number of epitopes studied in ELISA/Western blot assays. Additionally, epitopes were generically described as associated with prostate cancer, with little granularity specifying diseases state. We found that in vivo and tumor recognition assays were sparse, and the number of epitopes with annotated B/T cell receptor information were limited. Potential immunodominant regions were identified by the use of the ImmunomeBrowser tool. CONCLUSION CEDAR provides a comprehensive repository of epitopes related to prostate-specific antigens. This inventory of epitope data with its wealth of searchable T cell, B cell and MHC ligand information provides a useful tool for the scientific community. At the same time, we identify significant knowledge gaps that could be addressed by experimental analysis.
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Affiliation(s)
- Gabriele Foos
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
| | - Nina Blazeska
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
| | - Morten Nielsen
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, CP 1650 San Martín, Argentina; Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Hannah Carter
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Zeynep Kosaloglu-Yalcin
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA; Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego (UCSD), La Jolla, CA 92037, USA
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology (LJI), La Jolla, CA 92037, USA; Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego (UCSD), La Jolla, CA 92037, USA.
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14
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Li Y, Sackett PW, Nielsen M, Barra C. NetAllergen, a random forest model integrating MHC-II presentation propensity for improved allergenicity prediction. Bioinform Adv 2023; 3:vbad151. [PMID: 37901344 PMCID: PMC10603389 DOI: 10.1093/bioadv/vbad151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 09/28/2023] [Accepted: 10/13/2023] [Indexed: 10/31/2023]
Abstract
Motivation Allergy is a pathological immune reaction towards innocuous protein antigens. Although only a narrow fraction of plant or animal proteins induce allergy, atopic disorders affect millions of children and adults and cost billions in healthcare systems worldwide. In silico predictors can aid in the development of more innocuous food sources. Previous allergenicity predictors used sequence similarity, common structural domains, and amino acid physicochemical features. However, these predictors strongly rely on sequence similarity to known allergens and fail to predict protein allergenicity accurately when similarity diminishes. Results To overcome these limitations, we collected allergens from AllergenOnline, a curated database of IgE-inducing allergens, carefully removed allergen redundancy with a novel protein partitioning pipeline, and developed a new allergen prediction method, introducing MHC presentation propensity as a novel feature. NetAllergen outperformed a sequence similarity-based BLAST baseline approach, and previous allergenicity predictor AlgPred 2 when similarity to known allergens is limited. Availability and implementation The web service NetAllergen and the datasets are available at https://services.healthtech.dtu.dk/services/NetAllergen-1.0/.
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Affiliation(s)
- Yuchen Li
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Copenhagen 2800, Denmark
| | - Peter Wad Sackett
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Copenhagen 2800, Denmark
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Copenhagen 2800, Denmark
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martin 1650, Argentina
| | - Carolina Barra
- Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Copenhagen 2800, Denmark
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15
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Brincker M, Jensen I, Rechner LA, Schut DA, Johansen TS, Nielsen M, Thomsen JB. Multi-center comparison between proton and photon plans for mediastinal lymphomas. Acta Oncol 2023; 62:1251-1255. [PMID: 37624751 DOI: 10.1080/0284186x.2023.2251089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023]
Affiliation(s)
- Mads Brincker
- Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Ingelise Jensen
- Department of Medical Physics, Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Laura Ann Rechner
- Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Oncology, Radiotherapy Research Unit, Herlev and Gentofte Hospital, University of Copenhagen, Herlev, Denmark
| | - Deborah Anne Schut
- Department of Oncology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | - Morten Nielsen
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
| | - Jakob Borup Thomsen
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
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16
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Montemurro A, Povlsen HR, Jessen LE, Nielsen M. Benchmarking data-driven filtering for denoising of TCRpMHC single-cell data. Sci Rep 2023; 13:16147. [PMID: 37752190 PMCID: PMC10522655 DOI: 10.1038/s41598-023-43048-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 09/18/2023] [Indexed: 09/28/2023] Open
Abstract
Pairing of the T cell receptor (TCR) with its cognate peptide-MHC (pMHC) is a cornerstone in T cell-mediated immunity. Recently, single-cell sequencing coupled with DNA-barcoded MHC multimer staining has enabled high-throughput studies of T cell specificities. However, the immense variability of TCR-pMHC interactions combined with the relatively low signal-to-noise ratio in the data generated using current technologies are complicating these studies. Several approaches have been proposed for denoising single-cell TCR-pMHC specificity data. Here, we present a benchmark evaluating two such denoising methods, ICON and ITRAP. We applied and evaluated the methods on publicly available immune profiling data provided by 10x Genomics. We find that both methods identified approximately 75% of the raw data as noise. We analyzed both internal metrics developed for the purpose and performance on independent data using machine learning methods trained on the raw and denoised 10x data. We find an increased signal-to-noise ratio comparing the denoised to the raw data for both methods, and demonstrate an overall superior performance of the ITRAP method in terms of both data consistency and performance. In conclusion, this study demonstrates that Improving the data quality from high throughput studies of TCRpMHC-specificity by denoising is paramount in increasing our understanding of T cell-mediated immunity.
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Affiliation(s)
- Alessandro Montemurro
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800, Kgs. Lyngby, Denmark
| | - Helle Rus Povlsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800, Kgs. Lyngby, Denmark
| | - Leon Eyrich Jessen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800, Kgs. Lyngby, Denmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800, Kgs. Lyngby, Denmark.
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17
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Eltschkner S, Mellinger S, Buus S, Nielsen M, Paulsson KM, Lindkvist-Petersson K, Westerdahl H. The structure of songbird MHC class I reveals antigen binding that is flexible at the N-terminus and static at the C-terminus. Front Immunol 2023; 14:1209059. [PMID: 37483599 PMCID: PMC10360169 DOI: 10.3389/fimmu.2023.1209059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/08/2023] [Indexed: 07/25/2023] Open
Abstract
Long-distance migratory animals such as birds and bats have evolved to withstand selection imposed by pathogens across the globe, and pathogen richness is known to be particularly high in tropical regions. Immune genes, so-called Major Histocompatibility Complex (MHC) genes, are highly duplicated in songbirds compared to other vertebrates, and this high MHC diversity has been hypothesised to result in a unique adaptive immunity. To understand the rationale behind the evolution of the high MHC genetic diversity in songbirds, we determined the structural properties of an MHC class I protein, Acar3, from a long-distance migratory songbird, the great reed warbler Acrocephalus arundinaceus (in short: Acar). The structure of Acar3 was studied in complex with pathogen-derived antigens and shows an overall antigen presentation similar to human MHC class I. However, the peptides bound to Acar3 display an unusual conformation: Whereas the N-terminal ends of the peptides display enhanced flexibility, the conformation of their C-terminal halves is rather static. This uncommon peptide-binding mode in Acar3 is facilitated by a central Arg residue within the peptide-binding groove that fixes the backbone of the peptide at its central position, and potentially permits successful interactions between MHC class I and innate immune receptors. Our study highlights the importance of investigating the immune system of wild animals, such as birds and bats, to uncover unique immune mechanisms which may neither exist in humans nor in model organisms.
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Affiliation(s)
- Sandra Eltschkner
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
- Molecular Ecology and Evolution Lab, Department of Biology, Lund University, Lund, Sweden
| | - Samantha Mellinger
- Molecular Ecology and Evolution Lab, Department of Biology, Lund University, Lund, Sweden
| | - Soren Buus
- Department of Experimental Immunology, Institute of International Health, Immunology and Microbiology, Copenhagen, Denmark
| | - Morten Nielsen
- Immunoinformatics and Machine Learning, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Kajsa M. Paulsson
- Antigen Presentation, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Karin Lindkvist-Petersson
- Medical Structural Biology, Department of Experimental Medical Science, Lund University, Lund, Sweden
- LINXS - Institute of Advanced Neutron and X-ray Science, Lund University, Lund, Sweden
| | - Helena Westerdahl
- Molecular Ecology and Evolution Lab, Department of Biology, Lund University, Lund, Sweden
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18
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Povlsen HR, Bentzen AK, Kadivar M, Jessen LE, Hadrup SR, Nielsen M. Improved T cell receptor antigen pairing through data-driven filtering of sequencing information from single cells. eLife 2023; 12:e81810. [PMID: 37133356 PMCID: PMC10156162 DOI: 10.7554/elife.81810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 03/13/2023] [Indexed: 05/04/2023] Open
Abstract
Novel single-cell-based technologies hold the promise of matching T cell receptor (TCR) sequences with their cognate peptide-MHC recognition motif in a high-throughput manner. Parallel capture of TCR transcripts and peptide-MHC is enabled through the use of reagents labeled with DNA barcodes. However, analysis and annotation of such single-cell sequencing (SCseq) data are challenged by dropout, random noise, and other technical artifacts that must be carefully handled in the downstream processing steps. We here propose a rational, data-driven method termed ITRAP (improved T cell Receptor Antigen Paring) to deal with these challenges, filtering away likely artifacts, and enable the generation of large sets of TCR-pMHC sequence data with a high degree of specificity and sensitivity, thus outputting the most likely pMHC target per T cell. We have validated this approach across 10 different virus-specific T cell responses in 16 healthy donors. Across these samples, we have identified up to 1494 high-confident TCR-pMHC pairs derived from 4135 single cells.
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Affiliation(s)
- Helle Rus Povlsen
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
| | - Amalie Kai Bentzen
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
| | - Mohammad Kadivar
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
| | - Leon Eyrich Jessen
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
| | - Sine Reker Hadrup
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
| | - Morten Nielsen
- Department of Health Technology at Technical University of DenmarkKongens LyngbyDenmark
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19
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Nilsson JB, Kaabinejadian S, Yari H, Peters B, Barra C, Gragert L, Hildebrand W, Nielsen M. Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome. Commun Biol 2023; 6:442. [PMID: 37085710 PMCID: PMC10121683 DOI: 10.1038/s42003-023-04749-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 03/23/2023] [Indexed: 04/23/2023] Open
Abstract
Human leukocyte antigen (HLA) class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and β-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific mass spectrometry immunopeptidomics data. The analysis demonstrates highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants reveals a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study furthers our understanding of HLA-DQ specificities and casts light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available at https://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2 .
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Affiliation(s)
| | - Saghar Kaabinejadian
- Pure MHC, LLC, Oklahoma City, OK, USA
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Hooman Yari
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, 92037, California, USA
| | - Carolina Barra
- Department of Health Technology, Technical University of Denmark, DK-2800, Lyngby, Denmark
| | - Loren Gragert
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, New Orleans, LA, 70112, USA
| | - William Hildebrand
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800, Lyngby, Denmark.
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20
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Nazerai L, Willis SC, Yankilevich P, Di Leo L, Bosisio FM, Frias A, Bertolotto C, Nersting J, Thastrup M, Buus S, Thomsen AR, Nielsen M, Rohrberg KS, Schmiegelow K, De Zio D. Thiopurine 6TG treatment increases tumor immunogenicity and response to immune checkpoint blockade. Oncoimmunology 2022; 12:2158610. [PMID: 36545256 PMCID: PMC9762757 DOI: 10.1080/2162402x.2022.2158610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Immune-checkpoint inhibitors (ICI) are highly effective in reinvigorating T cells to attack cancer. Nevertheless, a large subset of patients fails to benefit from ICI, partly due to lack of the cancer neoepitopes necessary to trigger an immune response. In this study, we used the thiopurine 6-thioguanine (6TG) to induce random mutations and thus increase the level of neoepitopes presented by tumor cells. Thiopurines are prodrugs which are converted into thioguanine nucleotides that are incorporated into DNA (DNA-TG), where they can induce mutation through single nucleotide mismatching. In a pre-clinical mouse model of a mutation-low melanoma cell line, we demonstrated that 6TG induced clinical-grade DNA-TG integration resulting in an improved tumor control that was strongly T cell dependent. 6TG exposure increased the tumor mutational burden, without affecting tumor cell proliferation and cell death. Moreover, 6TG treatment re-shaped the tumor microenvironment by increasing T and NK immune cells, making the tumors more responsive to immune-checkpoint blockade. We further validated that 6TG exposure improved tumor control in additional mouse models of melanoma. These findings have paved the way for a phase I/II clinical trial that explores whether treatment with thiopurines can increase the proportion of otherwise treatment-resistant cancer patients who may benefit from ICI therapy (NCT05276284).
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Affiliation(s)
- Loulieta Nazerai
- Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark,Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Shona Caroline Willis
- Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark,Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Patricio Yankilevich
- Bioinformatics Core Facility, Instituto de Investigación En Biomedicina de Buenos Aires (Ibioba), Buenos Aires, Argentina
| | - Luca Di Leo
- Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark
| | | | - Alex Frias
- Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Corine Bertolotto
- Universite Côte d’Azur, Nice, France,INSERM, Biology and Pathologies of melanocytes, team1, Equipe labellisée Ligue 2020, Centre Méditerranéen de Médecine Moléculaire, Nice, France
| | - Jacob Nersting
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Maria Thastrup
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Soren Buus
- Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark
| | - Allan Randrup Thomsen
- Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, Lyngby, Denmark
| | | | - Kjeld Schmiegelow
- Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Daniela De Zio
- Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark,Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark,CONTACT Daniela De Zio Melanoma Research Team, Danish Cancer Society Research Center, Copenhagen, Denmark
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21
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Montemurro A, Jessen LE, Nielsen M. NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions. Front Immunol 2022; 13:1055151. [PMID: 36561755 PMCID: PMC9763291 DOI: 10.3389/fimmu.2022.1055151] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
T cell receptors (TCR) define the specificity of T cells and are responsible for their interaction with peptide antigen targets presented in complex with major histocompatibility complex (MHC) molecules. Understanding the rules underlying this interaction hence forms the foundation for our understanding of basic adaptive immunology. Over the last decade, efforts have been dedicated to developing assays for high throughput identification of peptide-specific TCRs. Based on such data, several computational methods have been proposed for predicting the TCR-pMHC interaction. The general conclusion from these studies is that the prediction of TCR interactions with MHC-peptide complexes remains highly challenging. Several reasons form the basis for this including scarcity and quality of data, and ill-defined modeling objectives imposed by the high redundancy of the available data. In this work, we propose a framework for dealing with this redundancy, allowing us to address essential questions related to the modeling of TCR specificity including the use of peptide- versus pan-specific models, how to best define negative data, and the performance impact of integrating of CDR1 and 2 loops. Further, we illustrate how and why it is strongly recommended to include simple similarity-based modeling approaches when validating an improved predictive power of machine learning models, and that such validation should include a performance evaluation as a function of "distance" to the training data, to quantify the potential for generalization of the proposed model. The conclusion of the work is that, given current data, TCR specificity is best modeled using peptide-specific approaches, integrating information from all 6 CDR loops, and with negative data constructed from a combination of true and mislabeled negatives. Comparing such machine learning models to similarity-based approaches demonstrated an increased performance gain of the former as the "distance" to the training data was increased; thus demonstrating an improved generalization ability of the machine learning-based approaches. We believe these results demonstrate that the outlined modeling framework and proposed evaluation strategy form a solid basis for investigating the modeling of TCR specificities and that adhering to such a framework will allow for faster progress within the field. The final devolved model, NetTCR-2.1, is available at https://services.healthtech.dtu.dk/service.php?NetTCR-2.1.
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Affiliation(s)
- Alessandro Montemurro
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs., Lyngby, Denmark
| | - Leon Eyrich Jessen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs., Lyngby, Denmark
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, DTU, 2800 Kgs., Lyngby, Denmark,Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina,*Correspondence: Morten Nielsen,
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22
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Daca-Alvarez M, Martí M, Spinelli A, de Miranda NFFC, Palles C, Vivas A, Lachtford A, Monahan K, Szczepkowski M, Tarnowski W, Makkai-Popa ST, Vidal R, López I, Hurtado E, Jiménez F, Jiménez-Toscano M, Álvaro E, Sanz G, Ballestero A, Melone S, Brandáriz L, Prieto I, García-Olmo D, Ocaña T, Moreira R, Moreno L, Carballal S, Moreira L, Pellisé M, González-Sarmiento R, Holowatyj AN, Perea J, Balaguer F, Martínez M, Moreno V, Ruffinelli JCJC, Inglada-Pérez L, Rueda J, Castellano V, Hernández-Villafranca S, Escanciano M, Cavero A, Portugal V, Domenech M, Jiménez L, Peligros I, Rey C, Zorrilla J, Cuatrecasas M, Sánchez A, Rivero-Sanchez L, Iglesias M, de Molina AR, Colmenarejo G, Espinosa-Salinas I, Fernández L, de Cedrón MG, Corchete L, García JL, García P, Hernández A, Martel A, Pérez J, Burdaspal A, de Fuenmayor M, Forero A, Rubio I, Fernández J, Pastor E, Villafañe A, Alonso O, Encinas S, Teijo A, Pastor C, Arredondo J, Baixauli J, Ceniceros L, Rodriguez J, Sánchez C, Die J, Fernández J, Ocaña J, Dziakova J, Picazo S, Sanz R, Suárez M, Alcazar J, García J, Urioste M, Malats N, Estudillo L, Pérez-Pérez J, Espín E, Marinello F, Kraft M, Landolfi S, Pares B, Verdaguer M, Valverde I, Narváez C, Borycka K, Gellert R, Kołacin D, Ziółkowski B, Curley H, Tomlinson I, Foppa C, Maroli A, Abdulrahman M, Nielsen M, Azagra J, Pascotto B, Ali M, Anele C, Faiz O, Uryszek M, Aseem R, Pawa N. Familial component of early-onset colorectal cancer: opportunity for prevention. Br J Surg 2022; 109:1319-1325. [PMID: 36108087 DOI: 10.1093/bjs/znac322] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND Individuals with a non-syndromic family history of colorectal cancer are known to have an increased risk. There is an opportunity to prevent early-onset colorectal cancer (age less than 50 years) (EOCRC) in this population. The aim was to explore the proportion of EOCRC that is preventable due to family history of colorectal cancer. METHODS This was a retrospective multicentre European study of patients with non-hereditary EOCRC. The impact of the European Society of Gastrointestinal Endoscopy (ESGE), U.S. Multi-Society Task Force (USMSTF), and National Comprehensive Cancer Network (NCCN) guidelines on prevention and early diagnosis was compared. Colorectal cancer was defined as potentially preventable if surveillance colonoscopy would have been performed at least 5 years before the age of diagnosis of colorectal cancer, and diagnosed early if colonoscopy was undertaken between 1 and 4 years before the diagnosis. RESULTS Some 903 patients with EOCRC were included. Criteria for familial colorectal cancer risk in ESGE, USMSTF, and NCCN guidelines were met in 6.3, 9.4, and 30.4 per cent of patients respectively. Based on ESGE, USMSTF, and NCCN guidelines, colorectal cancer could potentially have been prevented in 41, 55, and 30.3 per cent of patients, and diagnosed earlier in 11, 14, and 21.1 per cent respectively. In ESGE guidelines, if surveillance had started 10 years before the youngest relative, there would be a significant increase in prevention (41 versus 55 per cent; P = 0.010). CONCLUSION ESGE, USMSTF, and NCCN criteria for familial colorectal cancer were met in 6.3, 9.4, and 30.4 per cent of patients with EOCRC respectively. In these patients, early detection and/or prevention could be achieved in 52, 70, and 51.4 per cent respectively. Early and accurate identification of familial colorectal cancer risk and increase in the uptake of early colonoscopy are key to decreasing familial EOCRC.
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Affiliation(s)
- Maria Daca-Alvarez
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Marc Martí
- Department of Surgery, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Antonino Spinelli
- Division of Colon and Rectal Surgery, Humanitas Research Hospital, Humanitas University, Rozzano, Italy
| | | | - Claire Palles
- Gastrointestinal Cancer Genetics Laboratory, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Alfredo Vivas
- Department of Surgery, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Andrew Lachtford
- Polyposis Registry and Family Cancer Clinic, St Mark's Hospital, London, UK
| | - Kevin Monahan
- Polyposis Registry and Family Cancer Clinic, St Mark's Hospital, London, UK.,Department of Gastroenterology, West Middlesex University Hospital, London, UK
| | - Marek Szczepkowski
- Clinical Department of Colorectal, General and Oncological Surgery, Centre of Postgraduate Medical Education, Bielanski Hospital, Warsaw, Poland
| | - Wieslaw Tarnowski
- Department of Surgery, Centre of Postgraduate Medical Education, Orlowski Hospital, Warsaw, Poland
| | | | - Rosario Vidal
- Medical Oncology Department, Hospital Universitario de Salamanca, Salamanca, Spain
| | - Irene López
- Department of Surgery, Hospital MD Anderson, Madrid, Spain
| | - Elena Hurtado
- Department of Surgery, Hospital Universitario Gregorio Marañon, Madrid, Spain
| | - Fernando Jiménez
- Department of Surgery, Hospital Galdakao-Usansolo, Vizcaya, Spain
| | | | - Edurne Álvaro
- Department of Surgery, Hospital Universitario Infanta Leonor, Madrid, Spain
| | - Gonzalo Sanz
- Department of Surgery, Hospital Clínico San Carlos, Madrid, Spain
| | - Araceli Ballestero
- Department of Surgery, Hospital Universitario Ramon y Cajal, Madrid, Spain
| | - Sirio Melone
- Department of Surgery, Hospital Universitario Fundación Alcorcón, Madrid, Spain
| | - Lorena Brandáriz
- Department of Surgery, Hospital Universitario General de Villalba, Madrid, Spain
| | - Isabel Prieto
- Department of Surgery, Hospital Universitario La Paz, Madrid, Spain
| | - Damián García-Olmo
- Department of Surgery, Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain
| | - Teresa Ocaña
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Rebeca Moreira
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Lorena Moreno
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Sabela Carballal
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Leticia Moreira
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Maria Pellisé
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Rogelio González-Sarmiento
- Molecular Medicine Unit, Department of Medicine, Biomedical Research Institute of Salamanca (IBSAL), Institute of Molecular and Cellular Biology of Cancer (IBMCC), University of Salamanca-SACYL-CSIC, Salamanca, Spain
| | - Andreana N Holowatyj
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - José Perea
- Molecular Medicine Unit, Department of Medicine, Biomedical Research Institute of Salamanca (IBSAL), Institute of Molecular and Cellular Biology of Cancer (IBMCC), University of Salamanca-SACYL-CSIC, Salamanca, Spain
| | - Francesc Balaguer
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
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23
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Connelley T, Nicastri A, Sheldrake T, Vrettou C, Fisch A, Reynisson B, Buus S, Hill A, Morrison I, Nielsen M, Ternette N. Immunopeptidomic Analysis of BoLA-I and BoLA-DR Presented Peptides from Theileria parva Infected Cells. Vaccines (Basel) 2022; 10:vaccines10111907. [PMID: 36423003 PMCID: PMC9699068 DOI: 10.3390/vaccines10111907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/16/2022] Open
Abstract
The apicomplexan parasite Theileria parva is the causative agent of East Coast fever, usually a fatal disease for cattle, which is prevalent in large areas of eastern, central, and southern Africa. Protective immunity against T. parva is mediated by CD8+ T cells, with CD4+ T-cells thought to be important in facilitating the full maturation and development of the CD8+ T-cell response. T. parva has a large proteome, with >4000 protein-coding genes, making T-cell antigen identification using conventional screening approaches laborious and expensive. To date, only a limited number of T-cell antigens have been described. Novel approaches for identifying candidate antigens for T. parva are required to replace and/or complement those currently employed. In this study, we report on the use of immunopeptidomics to study the repertoire of T. parva peptides presented by both BoLA-I and BoLA-DR molecules on infected cells. The study reports on peptides identified from the analysis of 13 BoLA-I and 6 BoLA-DR datasets covering a range of different BoLA genotypes. This represents the most comprehensive immunopeptidomic dataset available for any eukaryotic pathogen to date. Examination of the immunopeptidome data suggested the presence of a large number of coprecipitated and non-MHC-binding peptides. As part of the work, a pipeline to curate the datasets to remove these peptides was developed and used to generate a final list of 74 BoLA-I and 15 BoLA-DR-presented peptides. Together, the data demonstrated the utility of immunopeptidomics as a method to identify novel T-cell antigens for T. parva and the importance of careful curation and the application of high-quality immunoinformatics to parse the data generated.
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Affiliation(s)
- Timothy Connelley
- The Roslin Institute, The Royal (Dick) School of Veterinary Science, The University of Edinburgh, Edinburgh EH25 9RG, UK
- Correspondence:
| | - Annalisa Nicastri
- The Jenner Institute, Nuffield Department of Medicine, The University of Oxford, Oxford OX3 7BN, UK
| | - Tara Sheldrake
- The Roslin Institute, The Royal (Dick) School of Veterinary Science, The University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Christina Vrettou
- The Roslin Institute, The Royal (Dick) School of Veterinary Science, The University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Andressa Fisch
- Ribeirão Preto College of Nursing, University of São Paulo, Av Bandeirantes, Ribeirão Preto 3900, Brazil
| | - Birkir Reynisson
- Department of Health Technology, Technical University of Denmark, DK-2800 Copenhagen, Denmark
| | - Soren Buus
- Laboratory of Experimental Immunology, Department of Immunology and Microbiology, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Adrian Hill
- The Jenner Institute, Nuffield Department of Medicine, The University of Oxford, Oxford OX3 7BN, UK
| | - Ivan Morrison
- The Roslin Institute, The Royal (Dick) School of Veterinary Science, The University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Copenhagen, Denmark
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martín CP1650, Argentina
| | - Nicola Ternette
- The Jenner Institute, Nuffield Department of Medicine, The University of Oxford, Oxford OX3 7BN, UK
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24
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Clifford J, Høie MH, Deleuran S, Peters B, Nielsen M, Marcatili P. BepiPred‐3.0: Improved B‐cell epitope prediction using protein language models. Protein Sci 2022; 31:e4497. [DOI: 10.1002/pro.4497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/13/2022]
Affiliation(s)
- Joakim Clifford
- Department of Health Technology Technical University of Denmark Kgs. Lyngby Denmark
| | | | - Sebastian Deleuran
- Department of Health Technology Technical University of Denmark Kgs. Lyngby Denmark
| | | | - Morten Nielsen
- Department of Health Technology Technical University of Denmark Kgs. Lyngby Denmark
| | - Paolo Marcatili
- Department of Health Technology Technical University of Denmark Kgs. Lyngby Denmark
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25
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Koşaloğlu-Yalçın Z, Blazeska N, Vita R, Carter H, Nielsen M, Schoenberger S, Sette A, Peters B. The Cancer Epitope Database and Analysis Resource (CEDAR). Nucleic Acids Res 2022; 51:D845-D852. [PMID: 36250634 PMCID: PMC9825495 DOI: 10.1093/nar/gkac902] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/26/2022] [Accepted: 10/07/2022] [Indexed: 01/30/2023] Open
Abstract
We established The Cancer Epitope Database and Analysis Resource (CEDAR) to catalog all epitope data in the context of cancer. The specific molecular targets of adaptive T cell and B cell immune responses are referred to as epitopes. Epitopes derived from cancer antigens are of high relevance as they are recognized by anti-cancer immune cells. Detailed knowledge of the molecular characteristic of cancer epitopes and associated metadata is relevant to understanding and planning prophylactic and therapeutic applications and accurately characterizing naturally occurring immune responses and cancer immunopathology. CEDAR provides a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature and serves as a companion site to the Immune Epitope Database (IEDB), which is focused on infectious, autoimmune, and allergic diseases. CEDAR is freely accessible at https://cedar.iedb.org/.
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Affiliation(s)
| | - Nina Blazeska
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Randi Vita
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Hannah Carter
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Morten Nielsen
- Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark,Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martín, Argentina
| | - Stephen Schoenberger
- Laboratory of Cellular Immunology, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Alessandro Sette
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA,Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA,Department of Medicine, University of California San Diego, La Jolla, CA, USA
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26
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Garcia Alvarez HM, Koşaloğlu-Yalçın Z, Peters B, Nielsen M. The role of antigen expression in shaping the repertoire of HLA presented ligands. iScience 2022; 25:104975. [PMID: 36060059 PMCID: PMC9437844 DOI: 10.1016/j.isci.2022.104975] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 07/21/2022] [Accepted: 08/14/2022] [Indexed: 11/26/2022] Open
Abstract
Human leukocyte antigen (HLA) presentation of peptides is a prerequisite of T cell immune activation. The understanding of the rules defining this event has large implications for our knowledge of basic immunology and for the rational design of immuno-therapeutics and vaccines. Historically, most of the available prediction methods have been solely focused on the information related to antigen processing and presentation. Recent work has, however, demonstrated that method performance can be boosted by integrating information related to antigen abundance. Here we expand on these later findings and develop an extended version of NetMHCpan, called NetMHCpanExp, integrating information on antigen abundance from RNA-Seq experiments. In line with earlier works, the model demonstrates improved performance for both HLA ligand and cancer neoantigen epitope prediction. Optimal results are obtained by use of sample-specific abundance information but also reference datasets can be applied with a limited performance drop. The developed tool is available at https://services.healthtech.dtu.dk/service.php?NetMHCpanExp-1.0.
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Affiliation(s)
- Heli M Garcia Alvarez
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, CP 1650 San Martín, Argentina
| | - Zeynep Koşaloğlu-Yalçın
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, 92037 CA, USA
| | - Bjoern Peters
- Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, 92037 CA, USA.,Department of Medicine, University of California, San Diego, La Jolla, 92093 CA, USA
| | - Morten Nielsen
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, CP 1650 San Martín, Argentina.,Department of Health Technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
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27
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Ma Y, Liu F, Li B, Peng K, Zhou H, Xu Y, Qiao D, Deng L, Tian G, Nielsen M, Wang M. Identification and assessment of TCR-T cells targeting an epitope conserved in SARS-CoV-2 variants for the treatment of COVID-19. Int Immunopharmacol 2022; 112:109283. [PMID: 36201943 PMCID: PMC9515335 DOI: 10.1016/j.intimp.2022.109283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/09/2022] [Accepted: 09/22/2022] [Indexed: 11/28/2022]
Abstract
Background Coronavirus disease 2019 (COVID-19) continues to be a major global public health challenge, with the emergence of variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current vaccines or monoclonal antibodies may not well be protect against infection with new SARS-CoV-2 variants. Unlike antibody-based treatment, T cell-based therapies such as TCR-T cells can target epitopes that are highly conserved across different SARS-CoV-2 variants. Reportedly, T cell-based immunity alone can restrict SARS-CoV-2 replication. Methods In this study, we identified two TCRs targeting the RNA-dependent RNA polymerase (RdRp) protein in CD8 + T cells. Functional evaluation by transducing these TCRs into CD8 + or CD4 + T cells confirmed their specificity. Results Combinations of inflammatory and anti-inflammatory cytokines secreted by CD8 + and CD4 + T cells can help control COVID-19 in patients. Moreover, the targeted epitope is highly conserved in all emerged SARS-CoV-2 variants, including the Omicron. It is also conserved in the seven coronaviruses that infect humans and more broadly in the subfamily Coronavirinae. Conclusions The pan-genera coverage of mutant epitopes from the Coronavirinae subfamily by the two TCRs highlights the unique strengths of TCR-T cell therapies in controlling the ongoing pandemic and in preparing for the next coronavirus outbreak.
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28
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Nielsen M, Presti M, Sztupinszki Z, Jensen AWP, Draghi A, Chamberlain CA, Schina A, Yde CW, Wojcik J, Szallasi Z, Crowther MD, Svane IM, Donia M. Co-existing alterations of MHC class I antigen presentation and IFNγ signaling mediate acquired resistance of melanoma to post-PD-1 immunotherapy. Cancer Immunol Res 2022; 10:1254-1262. [PMID: 35969233 DOI: 10.1158/2326-6066.cir-22-0326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/25/2022] [Accepted: 08/03/2022] [Indexed: 11/16/2022]
Abstract
Responses to immunotherapy can be very durable but acquired resistance leading to tumor progression often occurs. We investigated a patient with melanoma resistant to anti-PD-1 who participated in the CA224-020 clinical trial (NCT01968109) and had further progression after an initial objective response to anti-PD-1 plus anti-LAG-3. We found consecutive acquisition of beta-2 microglobulin (B2M) loss and impaired Janus Kinase 1 (JAK1) signaling that co-existed in progressing tumor cells. Functional analyses revealed a pan T cell immune escape phenotype, where distinct alterations mediated independent immune resistance to tumor killing by autologous CD8+ tumor-infiltrating lymphocytes (TILs) (B2M loss) and CD4+ TILs (impaired JAK1 signaling). These findings shed light on the complexity of acquired resistance to immunotherapy in the post anti-PD-1 setting, indicating that co-existing altered pathways can lead to pan T cell immune escape.
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Affiliation(s)
- Morten Nielsen
- Copenhagen University Hospital, Herlev and Gentofte, Herlev, Copenhagen, Denmark
| | - Mario Presti
- Copenhagen University Hospital, Herlev and Gentofte, Herlev, Denmark
| | | | | | - Arianna Draghi
- Copenhagen University Hospital, Herlev and Gentofte, Herlev, Denmark
| | | | - Aimilia Schina
- Herlev and Gentofte Hospital, University of Copenhagen, Herlev, Denmark
| | | | - John Wojcik
- Bristol-Myers Squibb (United States), Princeton, NJ, United States
| | | | | | | | - Marco Donia
- Copenhagen University Hospital, Herlev and Gentofte, Herlev, Denmark
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29
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Trevizani R, Yan Z, Greenbaum JA, Sette A, Nielsen M, Peters B. A comprehensive analysis of the IEDB MHC class-I automated benchmark. Brief Bioinform 2022; 23:6632617. [PMID: 35794711 DOI: 10.1093/bib/bbac259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/27/2022] [Accepted: 06/05/2022] [Indexed: 11/12/2022] Open
Abstract
In 2014, the Immune Epitope Database automated benchmark was created to compare the performance of the MHC class I binding predictors. However, this is not a straightforward process due to the different and non-standardized outputs of the methods. Additionally, some methods are more restrictive regarding the HLA alleles and epitope sizes for which they predict binding affinities, while others are more comprehensive. To address how these problems impacted the ranking of the predictors, we developed an approach to assess the reliability of different metrics. We found that using percentile-ranked results improved the stability of the ranks and allowed the predictors to be reliably ranked despite not being evaluated on the same data. We also found that given the rate new data are incorporated into the benchmark, a new method must wait for at least 4 years to be ranked against the pre-existing methods. The best-performing tools with statistically indistinguishable scores in this benchmark were NetMHCcons, NetMHCpan4.0, ANN3.4, NetMHCpan3.0 and NetMHCpan2.8. The results of this study will be used to improve the evaluation and display of benchmark performance. We highly encourage anyone working on MHC binding predictions to participate in this benchmark to get an unbiased evaluation of their predictors.
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Affiliation(s)
- Raphael Trevizani
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, California 92037, USA.,Fiocruz Ceará, Fundação Oswaldo Cruz, Rua São José s/n, Precabura, Eusébio/CE, Brazil
| | - Zhen Yan
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, California 92037, USA
| | - Jason A Greenbaum
- Bioinformatics Core, La Jolla Institute for Immunology, La Jolla, California 92037, USA
| | - Alessandro Sette
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, California 92037, USA.,Department of Medicine, University of California San Diego, La Jolla, California 92093, USA
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.,Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, B1650 Buenos Aires, Argentina
| | - Bjoern Peters
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, California 92037, USA.,Department of Medicine, University of California San Diego, La Jolla, California 92093, USA
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Nielsen M, Monberg T, Albieri B, Sundvold V, Rekdal O, Junker N, Svane IM. LTX-315 and adoptive cell therapy using tumor-infiltrating lymphocytes in patients with metastatic soft tissue sarcoma. J Clin Oncol 2022. [DOI: 10.1200/jco.2022.40.16_suppl.11567] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
11567 Background: Adoptive cell transfer (ACT) with tumor-infiltrating lymphocytes (TILs) is a potent treatment that can induce complete and durable tumor regression as documented in patients with metastatic melanoma. To our knowledge, ACT has not been utilized for patients with metastatic soft-tissue sarcoma (STS). LTX-315 is an oncolytic peptide that has been shown to increase TILs in malignant tumors after intratumoral injection. In this trial, patients with metastatic sarcoma were treated with the combination of LTX-315 and TIL - based ACT. Methods: Patients with progressive metastatic STS after a minimum of one systemic treatment were eligible for inclusion. In step 1, patients received up to five treatments over 2-3 weeks with LTX-315 injections. Afterwards, the injected tumor was surgically removed, and TILs were expanded in vitro. In step 2, patients received preparative chemotherapy followed by infusion of the expanded TILs, and follow-up treatment with subcutaneous IL-2. The impact of LTX-315 on tumor microenvironment was assessed by immunohistochemistry (IHC) on biopsies collected before and after injections. Clinical effect of the treatment was assessed by follow-up CT-scans using RECIST 1.1. Exploratory analyses aimed at identifying tumor reactive T cells in the expanded TILs and in peripheral blood (PBMC) in the patients before and after treatment. Expanded TILs or PBMC were cocultured with autologous tumor or selected neo-peptides and reactivity was assessed by measurement by Elispot or flow cytometry. Results: Six patients received intratumoral injections with LTX-315. In 3 out of 5 samples available for IHC, increased infiltration of CD4+ cells following LTX-315 injections was observed. Four patients received the full treatment with both LTX-315 injections and ACT. Total number of infused cells was 44-63x109, comprising 0,4-52% CD8+ T cells. Treatment was tolerated with manageable toxicity. After completed treatment, all four patients had stable disease as best overall response. Two patients with leiomyosarcoma and solitary fibrous tumor had stable disease for 25 and 20 weeks, respectively. In these two patients, and one additional patient, Elispot analyses showed presence of tumor-reactive cells in the PBMC following treatment. Conclusions: This trial demonstrates that the combination of LTX-315 and ACT is feasible and tolerable with manageable toxicity. CD4+ and CD8+ TILs can be expanded in vitro from sarcomas that have been pretreated with the oncolytic peptide LTX-315. Furthermore, the data suggest that LTX-315 can modulate the tumor microenvironment in sarcomas, thus potentially affect the expanded TILs that can be used for ACT. Further optimization of the treatment schedule will position LTX-315 as technology to invoke tumor specific T cells that can be cultured and infused as part of an adoptive transfer regimen for several subtypes of soft tissue sarcoma. Clinical trial information: NCT03725605.
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Affiliation(s)
- Morten Nielsen
- National Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital, Herlev, Denmark, Herlev, Denmark
| | - Tine Monberg
- National Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital, Herlev, Denmark, Herlev, Denmark
| | - Benedetta Albieri
- National Center for Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital, Herlev, Denmark, Herlev, Denmark
| | | | | | - Niels Junker
- Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Inge Marie Svane
- Department of Haematology and Department of Oncology, Herlev University Hospital, Herlev, Denmark
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31
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Høie MH, Kiehl EN, Petersen B, Nielsen M, Winther O, Nielsen H, Hallgren J, Marcatili P. NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning. Nucleic Acids Res 2022; 50:W510-W515. [PMID: 35648435 PMCID: PMC9252760 DOI: 10.1093/nar/gkac439] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/04/2022] [Accepted: 05/27/2022] [Indexed: 11/23/2022] Open
Abstract
Recent advances in machine learning and natural language processing have made it possible to profoundly advance our ability to accurately predict protein structures and their functions. While such improvements are significantly impacting the fields of biology and biotechnology at large, such methods have the downside of high demands in terms of computing power and runtime, hampering their applicability to large datasets. Here, we present NetSurfP-3.0, a tool for predicting solvent accessibility, secondary structure, structural disorder and backbone dihedral angles for each residue of an amino acid sequence. This NetSurfP update exploits recent advances in pre-trained protein language models to drastically improve the runtime of its predecessor by two orders of magnitude, while displaying similar prediction performance. We assessed the accuracy of NetSurfP-3.0 on several independent test datasets and found it to consistently produce state-of-the-art predictions for each of its output features, with a runtime that is up to to 600 times faster than the most commonly available methods performing the same tasks. The tool is freely available as a web server with a user-friendly interface to navigate the results, as well as a standalone downloadable package.
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Affiliation(s)
- Magnus Haraldson Høie
- Department of Health Technology, Technical University of Denmark, DK Lyngby, Denmark
| | - Erik Nicolas Kiehl
- Department of Health Technology, Technical University of Denmark, DK Lyngby, Denmark
| | - Bent Petersen
- Center for Evolutionary Hologenomics, GLOBE Institute, University of Copenhagen, Denmark.,Centre of Excellence for Omics-Driven Computational Biodiscovery (COMBio), Faculty of Applied Sciences, AIMST University, Kedah, Malaysia
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, DK Lyngby, Denmark
| | - Ole Winther
- Section for Cognitive Systems, DTU Compute, Technical University of Denmark (DTU), Denmark.,Center for Genomic Medicine, Rigshospitalet (Copenhagen University Hospital), Copenhagen, Denmark.,Department of Biology, Bioinformatics Centre, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Nielsen
- Department of Health Technology, Technical University of Denmark, DK Lyngby, Denmark
| | | | - Paolo Marcatili
- Department of Health Technology, Technical University of Denmark, DK Lyngby, Denmark
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Olloni A, Hansen O, Kristiansen C, Edvardsson L, Nielsen M, Jeppesen S, Schytte T. PO-1140 Survival after stereotactic radiosurgery for brain metastases – A single-institution experience. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03104-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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33
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Nowicka-Matus K, Friborg J, Hansen C, Andersen E, Bernsdorf M, Elstrøm U, Farhadi M, Grau C, Eriksen J, Johansen J, Nielsen M, Petersen J, Samsøe E, Sibolt P, Smulders B, Jensen K. OC-0089 Acute toxicities in proton therapy of head-neck cancer – a matched analysis of DAHANCA 35 pilot data. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)02465-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Josipovic M, van Overeem Felter M, Ottosson W, Worm E, Sand H, Nielsen M, Bjørn Nielsen T, Slot Thing R, Fredberg Persson G. PO-1659 Participation in clinical trials improved harmonization of dosimetric parameters applied in SBRT. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03623-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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35
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Vedaa Ø, Djupedal ILR, Svensen E, Waage S, Bjorvatn B, Pallesen S, Lie SA, Nielsen M, Harris A. Health-promoting work schedules: protocol for a large-scale cluster randomised controlled trial on the effects of a work schedule without quick returns on sickness absence among healthcare workers. BMJ Open 2022; 12:e058309. [PMID: 35428642 PMCID: PMC9014074 DOI: 10.1136/bmjopen-2021-058309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
INTRODUCTION In shift work, quick returns refer to transitions between two shifts with less than 11 hours available rest time. Twenty-three per cent of employees in European countries reported having quick returns. Quick returns are related to short sleep duration, fatigue, sleepiness, work-related accidents and sickness absence. The present study is the first randomised controlled trial (RCT) to investigate the effect of a work schedule without quick returns for 6 months, compared with a work schedule that maintains quick returns during the same time frame. METHODS AND ANALYSIS A parallel-group cluster RCT in a target sample of more than 4000 healthcare workers at Haukeland University Hospital in Norway will be conducted. More than 70 hospital units will be assessed for eligibility and randomised to a work schedule without quick returns for 6 months or continue with a schedule that maintains quick returns. The primary outcome is objective records of sickness absence; secondary outcomes are questionnaire data (n≈4000 invited) on sleep and functioning, physical and psychological health, work-related accidents and turnover intention. For a subsample, sleep diaries and objective sleep registrations with radar technology (n≈ 50) will be collected. ETHICS AND DISSEMINATION The study protocol was approved by the Regional Committee for Medical and Health Research Ethics in Western Norway (2020/200386). Findings from the trial will be disseminated in peer-reviewed journals and presented at national and international conferences. Exploratory analyses of potential mediators and moderators will be reported. User-friendly outputs will be disseminated to relevant stakeholders, unions and other relevant societal groups. TRIAL REGISTRATION NUMBER NCT04693182.
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Affiliation(s)
- Øystein Vedaa
- Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Development, St Olavs University Hospital, Trondheim, Norway
- Department of Psychosocial Science, University of Bergen, Bergen, Norway
| | - Ingebjørg Louise Rockwell Djupedal
- Department of Health Promotion, Norwegian Institute of Public Health, Bergen, Norway
- Department of Psychosocial Science, University of Bergen, Bergen, Norway
| | - Erling Svensen
- Department of Human Resources, Haukeland University Hospital, Bergen, Norway
| | - Siri Waage
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway
| | - Bjørn Bjorvatn
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway
| | - Ståle Pallesen
- Department of Psychosocial Science, University of Bergen, Bergen, Norway
- Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway
- Optentia at the Vaal Triangle Campus of the North-West University, Vanderbijlpark, South Africa
| | - Stein Atle Lie
- Department of Clinical Dentistry, University of Bergen, Bergen, Norway
| | - Morten Nielsen
- Department of Psychosocial Science, University of Bergen, Bergen, Norway
- Department of Work Psychology and Physiology, National Institute of Occupational Health, Oslo, Norway
| | - Anette Harris
- Department of Psychosocial Science, University of Bergen, Bergen, Norway
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Nielsen M, Ternette N, Barra C. The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome. Expert Rev Proteomics 2022; 19:77-88. [PMID: 35390265 DOI: 10.1080/14789450.2022.2064278] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION The comprehensive collection of peptides presented by Major Histocompatibility Complex (MHC) molecules on the cell surface is collectively known as the immunopeptidome. The analysis and interpretation of such data sets holds great promise for furthering our understanding of basic immunology and adaptive immune activation and regulation, and for direct rational discovery of T cell antigens and the design of T-cell based therapeutics and vaccines. These applications are however challenged by the complex nature of immunopeptidome data. AREAS COVERED Here, we describe the benefits and shortcomings of applying liquid chromatography-tandem mass spectrometry (MS) to obtain large scale immunopeptidome data sets and illustrate how the accurate analysis and optimal interpretation of such data is reliant on the availability of refined and highly optimized machine learning approaches. EXPERT OPINION Further we demonstrate how the accuracy of immunoinformatics prediction methods within the field of MHC antigen presentation has benefited greatly from the availability of MS-immunopeptidomics data, and exemplify how optimal antigen discovery is best performed in a synergistic combination of MS experiments and such in silico models trained on large scale immunopeptidomics data.
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Affiliation(s)
- Morten Nielsen
- Department of Health technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Nicola Ternette
- Centre for Cellular and Molecular Physiology, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - Carolina Barra
- Department of Health technology, Technical University of Denmark, DK-2800 Lyngby, Denmark
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Khilji MS, Faridi P, Pinheiro-Machado E, Hoefner C, Dahlby T, Aranha R, Buus S, Nielsen M, Klusek J, Mandrup-Poulsen T, Pandey K, Purcell AW, Marzec MT. Defective Proinsulin Handling Modulates the MHC I Bound Peptidome and Activates the Inflammasome in β-Cells. Biomedicines 2022; 10:biomedicines10040814. [PMID: 35453564 PMCID: PMC9024965 DOI: 10.3390/biomedicines10040814] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/23/2022] [Accepted: 03/28/2022] [Indexed: 12/04/2022] Open
Abstract
How immune tolerance is lost to pancreatic β-cell peptides triggering autoimmune type 1 diabetes is enigmatic. We have shown that loss of the proinsulin chaperone glucose-regulated protein (GRP) 94 from the endoplasmic reticulum (ER) leads to mishandling of proinsulin, ER stress, and activation of the immunoproteasome. We hypothesize that inadequate ER proinsulin folding capacity relative to biosynthetic need may lead to an altered β-cell major histocompatibility complex (MHC) class-I bound peptidome and inflammasome activation, sensitizing β-cells to immune attack. We used INS-1E cells with or without GRP94 knockout (KO), or in the presence or absence of GRP94 inhibitor PU-WS13 (GRP94i, 20 µM), or exposed to proinflammatory cytokines interleukin (IL)-1β or interferon gamma (IFNγ) (15 pg/mL and 10 ng/mL, respectively) for 24 h. RT1.A (rat MHC I) expression was evaluated using flow cytometry. The total RT1.A-bound peptidome analysis was performed on cell lysates fractionated by reverse-phase high-performance liquid chromatography (RP-HPLC), followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The nucleotide-binding oligomerization domain, leucine rich repeat and pyrin domain containing protein (NLRP1), nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (IκBα), and (pro) IL-1β expression and secretion were investigated by Western blotting. GRP94 KO increased RT1.A expression in β-cells, as did cytokine exposure compared to relevant controls. Immunopeptidome analysis showed increased RT1.A-bound peptide repertoire in GRP94 KO/i cells as well as in the cells exposed to cytokines. The GRP94 KO/cytokine exposure groups showed partial overlap in their peptide repertoire. Notably, proinsulin-derived peptide diversity increased among the total RT1.A peptidome in GRP94 KO/i along with cytokines exposure. NLRP1 expression was upregulated in GRP94 deficient cells along with decreased IκBα content while proIL-1β cellular levels declined, coupled with increased secretion of mature IL-1β. Our results suggest that limiting β-cell proinsulin chaperoning enhances RT1.A expression alters the MHC-I peptidome including proinsulin peptides and activates inflammatory pathways, suggesting that stress associated with impeding proinsulin handling may sensitize β-cells to immune-attack.
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Affiliation(s)
- Muhammad Saad Khilji
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (M.S.K.); (C.H.); (T.M.-P.)
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3168, Australia; (R.A.); (K.P.)
- Department of Physiology, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan
| | - Pouya Faridi
- Department of Medicine, School of Clinical Sciences, Monash Univesity, Clayton, VIC 3168, Australia;
| | - Erika Pinheiro-Machado
- Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9713 Groningen, The Netherlands;
| | - Carolin Hoefner
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (M.S.K.); (C.H.); (T.M.-P.)
| | - Tina Dahlby
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zürich, 8603 Zürich, Switzerland;
| | - Ritchlynn Aranha
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3168, Australia; (R.A.); (K.P.)
| | - Søren Buus
- Department of Immunology and Microbiology, University of Copenhagen, 2200 Copenhagen, Denmark;
| | - Morten Nielsen
- Department of Health Technology, Section for Bioinformatics, Technical University of Denmark, 2800 Lyngby, Denmark;
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, San Martín CP1650, Argentina
| | - Justyna Klusek
- Laboratory of Medical Genetics, Department of Surgical Medicine, Collegium Medicum, Jan Kochanowski University, 25-369 Kielce, Poland;
| | - Thomas Mandrup-Poulsen
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (M.S.K.); (C.H.); (T.M.-P.)
| | - Kirti Pandey
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3168, Australia; (R.A.); (K.P.)
| | - Anthony W. Purcell
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3168, Australia; (R.A.); (K.P.)
- Correspondence: (A.W.P.); (M.T.M.); Tel.: +61-39-902-9265 (A.W.P.); +45-25-520-256 (M.T.M.)
| | - Michal T. Marzec
- Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark; (M.S.K.); (C.H.); (T.M.-P.)
- Institute of Health Sciences, Collegium Medicum, Jan Kochanowski University, 25-002 Kielce, Poland
- Correspondence: (A.W.P.); (M.T.M.); Tel.: +61-39-902-9265 (A.W.P.); +45-25-520-256 (M.T.M.)
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Wright DW, Harvey WT, Hughes J, Cox M, Peacock TP, Colquhoun R, Jackson B, Orton R, Nielsen M, Hsu NS, Harrison EM, de Silva TI, Rambaut A, Peacock SJ, Robertson DL, Carabelli AM. Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer. Virus Evol 2022; 8:veac023. [PMID: 35502202 PMCID: PMC9037374 DOI: 10.1093/ve/veac023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/03/2022] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
COG-UK Mutation Explorer (COG-UK-ME, https://sars2.cvr.gla.ac.uk/cog-uk/-last accessed date 16 March 2022) is a web resource that displays knowledge and analyses on SARS-CoV-2 virus genome mutations and variants circulating in the UK, with a focus on the observed amino acid replacements that have an antigenic role in the context of the human humoral and cellular immune response. This analysis is based on more than 2 million genome sequences (as of March 2022) for UK SARS-CoV-2 data held in the CLIMB-COVID centralised data environment. COG-UK-ME curates these data and displays analyses that are cross-referenced to experimental data collated from the primary literature. The aim is to track mutations of immunological importance that are accumulating in current variants of concern and variants of interest that could alter the neutralising activity of monoclonal antibodies (mAbs), convalescent sera, and vaccines. Changes in epitopes recognised by T cells, including those where reduced T cell binding has been demonstrated, are reported. Mutations that have been shown to confer SARS-CoV-2 resistance to antiviral drugs are also included. Using visualisation tools, COG-UK-ME also allows users to identify the emergence of variants carrying mutations that could decrease the neutralising activity of both mAbs present in therapeutic cocktails, e.g. Ronapreve. COG-UK-ME tracks changes in the frequency of combinations of mutations and brings together the curated literature on the impact of those mutations on various functional aspects of the virus and therapeutics. Given the unpredictable nature of SARS-CoV-2 as exemplified by yet another variant of concern, Omicron, continued surveillance of SARS-CoV-2 remains imperative to monitor virus evolution linked to the efficacy of therapeutics.
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Affiliation(s)
- Derek W Wright
- MRC-University of Glasgow Centre for Virus
Research, University of Glasgow, Garscube Campus, 464 Bearsden Road,
Glasgow G61 1QH, UK
| | | | - Joseph Hughes
- MRC-University of Glasgow Centre for Virus
Research, University of Glasgow, Garscube Campus, 464 Bearsden Road,
Glasgow G61 1QH, UK
| | - MacGregor Cox
- Department of Medicine, University of
Cambridge, Addenbrookes Hospital, Hills Road, Cambridge CB2 0QQ,
UK
| | - Thomas P Peacock
- Department of Infectious Disease, St Mary’s
Medical School, Imperial College London, Praed Street, London,
Westminster W2 1NY, UK
| | - Rachel Colquhoun
- Institute of Evolutionary Biology, University of
Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
- MRC-University of Glasgow Centre for Virus
Research, University of Glasgow, Garscube Campus, 464 Bearsden Road,
Glasgow G61 1QH, UK
| | - Ben Jackson
- Institute of Evolutionary Biology, University of
Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
| | - Richard Orton
- MRC-University of Glasgow Centre for Virus
Research, University of Glasgow, Garscube Campus, 464 Bearsden Road,
Glasgow G61 1QH, UK
| | - Morten Nielsen
- Department of Health Technology, Technical
University of Denmark, Lyngby DK-2800, Denmark
| | - Nienyun Sharon Hsu
- The Florey Institute for Host-Pathogen
Interactions and Department of Infection, Immunity and Cardiovascular Disease, Medical
School, University of Sheffield, Beech Hill Road, Sheffield S10 2RX,
UK
| | | | - Ewan M Harrison
- Department of Medicine, University of
Cambridge, Addenbrookes Hospital, Hills Road, Cambridge CB2 0QQ,
UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton
CB10 1SA, UK
- Department of Public Health and Primary Care,
University of Cambridge, Worts Causeway, Cambridge CB1 8RN, UK
| | - Thushan I de Silva
- The Florey Institute for Host-Pathogen
Interactions and Department of Infection, Immunity and Cardiovascular Disease, Medical
School, University of Sheffield, Beech Hill Road, Sheffield S10 2RX,
UK
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of
Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
| | - Sharon J Peacock
- Department of Medicine, University of
Cambridge, Addenbrookes Hospital, Hills Road, Cambridge CB2 0QQ,
UK
| | - David L Robertson
- MRC-University of Glasgow Centre for Virus
Research, University of Glasgow, Garscube Campus, 464 Bearsden Road,
Glasgow G61 1QH, UK
| | - Alessandro M Carabelli
- Department of Medicine, University of
Cambridge, Addenbrookes Hospital, Hills Road, Cambridge CB2 0QQ,
UK
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Kaabinejadian S, Barra C, Alvarez B, Yari H, Hildebrand WH, Nielsen M. Accurate MHC Motif Deconvolution of Immunopeptidomics Data Reveals a Significant Contribution of DRB3, 4 and 5 to the Total DR Immunopeptidome. Front Immunol 2022; 13:835454. [PMID: 35154160 PMCID: PMC8826445 DOI: 10.3389/fimmu.2022.835454] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/10/2022] [Indexed: 01/23/2023] Open
Abstract
Mass spectrometry (MS) based immunopeptidomics is used in several biomedical applications including neo-epitope discovery in oncology, next-generation vaccine development and protein-drug immunogenicity assessment. Immunopeptidome data are highly complex given the expression of multiple HLA alleles on the cell membrane and presence of co-immunoprecipitated contaminants. The absence of tools that deal with these challenges effectively and guide the analysis and interpretation of this complex type of data is currently a major bottleneck for the large-scale application of this technique. To resolve this, we here present the MHCMotifDecon that benefits from state-of-the-art HLA class-I and class-II predictions to accurately deconvolute immunopeptidome datasets and assign individual ligands to the most likely HLA molecule, allowing to identify and characterize HLA binding motifs while discarding co-purified contaminants. We have benchmarked the tool against other state-of-the-art methods and illustrated its application on experimental datasets for HLA-DR demonstrating a previously underappreciated role for HLA-DRB3/4/5 molecules in defining HLA class II immune repertoires. With its ease of use, MHCMotifDecon can efficiently guide interpretation of immunopeptidome datasets, serving the discovery of novel T cell targets. MHCMotifDecon is available at https://services.healthtech.dtu.dk/service.php?MHCMotifDecon-1.0.
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Affiliation(s)
- Saghar Kaabinejadian
- Pure MHC, LLC., Oklahoma City, OK, United States.,Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Carolina Barra
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Bruno Alvarez
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina
| | - Hooman Yari
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - William H Hildebrand
- Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Morten Nielsen
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.,Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina
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Hansen O, Boes MB, Schytte T, Nielsen TB, Jeppesen SS, Nielsen M. Survival after palliative radiotherapy in nondisseminated nonsmall cell lung cancer treated with 30 Gy in 10 fractions or 39 Gy in 13 fractions using conformal technique. Acta Oncol 2022; 61:193-196. [PMID: 34986733 DOI: 10.1080/0284186x.2021.2022205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Olfred Hansen
- Department of Oncology, Odense University Hospital Odense, Denmark
- Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Mette Boye Boes
- Department of Oncology, Odense University Hospital Odense, Denmark
| | - Tine Schytte
- Department of Oncology, Odense University Hospital Odense, Denmark
- Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Tine Bjørn Nielsen
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
| | - Stefan Starup Jeppesen
- Department of Oncology, Odense University Hospital Odense, Denmark
- Academy of Geriatric Cancer Research (AgeCare), Odense University Hospital, Odense, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Morten Nielsen
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
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Held MK, Hansen O, Schytte T, Hansen KH, Bahij R, Nielsen M, Nielsen TB, Jeppesen SS. Outcomes of prophylactic cranial irradiation in patients with small cell lung cancer in the modern era of baseline magnetic resonance imaging of the brain. Acta Oncol 2022; 61:185-192. [PMID: 34583620 DOI: 10.1080/0284186x.2021.1974553] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
BACKGROUND For decades many patients with small cell lung cancer (SCLC) have been offered prophylactic cranial irradiation (PCI) to prevent brain metastases (BM). However, the role of PCI is debated in the modern era of increased brain magnetic resonance imaging (MRI) availability. BM in SCLC patients may respond to chemotherapy, and if a negative MRI is used in the decision to use of PCI in the treatment strategy, the timing of brain MRI may be crucial when evaluating the effect of PCI. This retrospective study investigates the impact of PCI outcomes in patients with SCLC staged with brain MRI prior to chemotherapy. MATERIALS AND METHODS This study included 245 patients diagnosed SCLC/mixed NSCLC-SCLC treated between 2012 and 2019. The population was analyzed separately for limited disease (LS-SCLC) and extensive disease (ES-SCLC). Patients were divided into groups based on baseline brain MRI prior to chemotherapy and PCI. The primary endpoint was time to symptomatic BM. Secondary endpoints were overall survival (OS), and progression-free survival (PFS). RESULTS In patients with LS-SCLC staged with brain MRI the probability of developing symptomatic BM at one year was 4% vs. 22% (p < 0.05), median OS was 55 vs. 24 months (p < 0.05), and median PFS was 30 vs. 10 months (p < 0.05) with and without PCI, respectively. No differences in probability of symptomatic BM and survival outcomes were observed in ES-SCLC. In a multivariate regression analysis, no variables were statistically significant associated with the risk of developing symptomatic BM in patients with LS-SCLC and ES-SCLC. For patients with ES-SCLC staged with brain MRI, PS (HR = 3.33, CI; 1.41-7.89, p < 0.05) was associated with poor survival. CONCLUSION This study found that PCI in LS-SCLC patients staged with brain MRI had lower incidence of symptomatic BM and improved survival outcomes suggesting PCI as standard of care. Similar benefit of PCI in patients with ES-SCLC was not found.
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Affiliation(s)
- Mads Kjaergaard Held
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | - Olfred Hansen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
- Academy of Geriatric Cancer Research (AgeCare), Odense, Denmark
| | - Tine Schytte
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | | | - Rana Bahij
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | - Morten Nielsen
- Department of Oncology, Odense University Hospital, Odense, Denmark
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
| | - Tine Bjørn Nielsen
- Department of Oncology, Odense University Hospital, Odense, Denmark
- Laboratory of Radiation Physics, Odense University Hospital, Odense, Denmark
| | - Stefan Starup Jeppesen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
- Academy of Geriatric Cancer Research (AgeCare), Odense, Denmark
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Gueniche A, Nielsen M. Introduction to probiotic fractions and Vichy volcanic mineralizing water: two key ingredients for stressed skin. J Eur Acad Dermatol Venereol 2022; 36 Suppl 2:3-4. [PMID: 34979588 DOI: 10.1111/jdv.17783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 10/18/2021] [Accepted: 11/02/2021] [Indexed: 11/29/2022]
Affiliation(s)
- A Gueniche
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - M Nielsen
- Laboratoires Vichy, Levallois Perret, France
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Gueniche A, Valois A, Salomao Calixto L, Sanchez Hevia O, Labatut F, Kerob D, Nielsen M. A dermocosmetic formulation containing Vichy volcanic mineralizing water, Vitreoscilla filiformis extract, niacinamide, hyaluronic acid, and vitamin E regenerates and repairs acutely stressed skin. J Eur Acad Dermatol Venereol 2022; 36 Suppl 2:26-34. [PMID: 34979590 DOI: 10.1111/jdv.17785] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 10/11/2021] [Indexed: 11/28/2022]
Abstract
The exposome has an impact on skin from life-long exposure. Acute short-term exposure to exposome stressors can also alter skin functions such as skin physical barrier and immune defenses, leading to skin dryness, sensitivity, flares of inflammatory skin conditions, or viral reactivations. Probiotics are defined as live microorganisms, which, when administered in adequate amounts, confer a health benefit on the host. An extract produced by lysing Vitreoscilla filiformis (VfeV) cultured in Vichy volcanic mineralizing water (VVMW) has properties of probiotic fractions. In this review, we present in vivo and ex vivo studies with a dermocosmetic formulation containing 80% VVMW, 5% VfeV, 4% niacinamide (vitamin B3), 0.4% hyaluronic acid, and 0.2% vitamin E (M89PF) to evaluate the clinical efficacy in preventing and repairing stressed skin. Skin barrier benefits of M89PF were shown in studies after the skin was exposed to sudden thermal changes, after skin irritation by tape stripping, and in sleep-deprived women. M89PF significantly accelerated skin renewal compared to untreated skin. Skin antioxidant defense activity of M89PF was shown after exposure to stress from UVA plus cigarette smoke aggression. Skin microbiome recovery after acute stress from a harsh cleanser was significantly better in M89PF-treated skin compared to bare skin. Clinical benefits of M89PF on correcting clinical signs of stressed skin were shown in both Caucasian and Asian women exposed to a stressful lifestyle and various external (pollution, tobacco smoking, solar radiation) and internal (poor sleep, stressful work, unbalanced diet, and alcohol consumption) exposome factors. M89PF also showed depigmenting properties on dark spots in Asian women. Further clinical studies are now warranted to evaluate the efficacy of M89PF as adjuvant care to prevent and repair skin barrier disruption and reinforce skin defenses in skin exposed to acute stresses.
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Affiliation(s)
- A Gueniche
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - A Valois
- L'Oréal Research & Innovation, Chevilly Larue, France
| | | | | | - F Labatut
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - D Kerob
- Laboratoires Vichy, Levallois Perret, France
| | - M Nielsen
- Laboratoires Vichy, Levallois Perret, France
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Gueniche A, Valois A, Kerob D, Rasmont V, Nielsen M. A combination of Vitreoscilla filiformis extract and Vichy volcanic mineralizing water strengthens the skin defenses and skin barrier. J Eur Acad Dermatol Venereol 2022; 36 Suppl 2:16-25. [PMID: 34979591 DOI: 10.1111/jdv.17786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/03/2021] [Accepted: 09/27/2021] [Indexed: 11/28/2022]
Abstract
Probiotics are live microorganisms, which, when administered in adequate amounts, confer a health benefit on the host. Semiactive, non-replicating bacteria or extracts used in dermocosmetics have interesting properties for skin quality. Vitreoscilla filiformis is cultured by a fermentation process to obtain an extract. It is considered as a probiotic fraction and topical application of this extract has shown activity to strengthen the skin physical barrier function and maintain good homeostasis of skin defenses. Vichy volcanic mineralizing water (VVMW) is a pure, highly mineralized water that has been shown to strengthen the skin against exposome aggressions. This manuscript reviews properties of probiotic fractions used in skin care, especially studies on an extract of V. filiformis grown in a medium containing VVMW (VfeV) and evaluated in combination with VVMW. Skin barrier function: In normal human epidermal keratinocyte cultures, the combination of 10% VVMW and 0.002% VfeV significantly increased transglutaminase, filaggrin, involucrin, claudin-1, and zonula occludens-1 in comparison with the controls. Antimicrobial peptide defenses: The combination of 16.7% VVMW and 0.1% VfeV increased the expression of β-defensin-4A and S100A7. Skin immune defense functions: In lipopolysaccharide-stimulated peripheral blood mononuclear cells, the combination of 16.7% VVMW and 0.1% VfeV down-regulated IL-8, TNF-α, IL-12/IL-23p40, and increased IL10 and IL-10/IL-12 ratio compared to the control. Additionally, the combination of 79% VVMW plus 5% VfeV protected Langerhans cells in skin explants exposed to ultraviolet radiation. In conclusion, the combination of VfeV plus VVMW has properties to strengthen the skin barrier by stimulating skin differentiation and tight junctions, biochemical defenses by stimulating antimicrobial peptides, and cellular immune defenses by increasing the IL-10/IL-12 ratio and by protecting Langerhans cells challenged by ultraviolet radiation.
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Affiliation(s)
- A Gueniche
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - A Valois
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - D Kerob
- Laboratoires Vichy, Levallois Perret, France
| | - V Rasmont
- Laboratoires Vichy, Levallois Perret, France
| | - M Nielsen
- Laboratoires Vichy, Levallois Perret, France
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Rasmont V, Valois A, Gueniche A, Sore G, Kerob D, Nielsen M, Berardesca E. Vichy volcanic mineralizing water has unique properties to strengthen the skin barrier and skin defenses against exposome aggressions. J Eur Acad Dermatol Venereol 2022; 36 Suppl 2:5-15. [PMID: 34979589 DOI: 10.1111/jdv.17784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/16/2021] [Indexed: 01/04/2023]
Abstract
Exposome aggressions are known to weaken certain skin functions, such as skin barrier and skin defense functions. Vichy volcanic mineralizing water (VVMW) percolates through volcanic and magmatic rocks in the Auvergne region in France to create a pure, highly mineralized water containing 15 minerals for a total mineral concentration of 5.2 g/L. Here, we provide an overview of the main results of in vitro and ex vivo studies (keratinocyte cultures, 3D reconstructed skin model, skin explants) and clinical studies to evaluate the effect of VVMW on key skin functions to help elucidate how it counteracts exposome aggressions on the skin. Properties to strengthen the skin barrier: VVMW stimulated the synthesis of tight junction proteins and keratinocyte differentiation markers in vitro. In clinical studies, VVMW accelerated cell turnover and improved skin hydration. Properties to strengthen skin antioxidant defense: VVMW stimulated the expression of antioxidant defense markers and had a higher stimulatory effect than a competitor thermal water on the expression of superoxide dismutase, catalase, and glutathione peroxidase in keratinocytes in vitro. In vivo, VVMW restored endogenous catalase activity after exposure to UVA radiation. Anti-inflammatory action: VVMW reduced substance P-induced inflammation ex vivo and lactic acid-induced stinging in vivo. Topical application of VVMW in subjects with sensitive skin showed soothing and decongestant effects by reducing skin dryness and erythema. After sodium lauryl sulfate -induced skin barrier disruption, recovery from redness and erythema was faster following application of VVMW compared to a competitor water or untreated skin. These studies illustrate that VVMW has unique properties to repair and regenerate the skin barrier, as well as to strengthen antioxidant and immune defenses, which help protect the skin against exposome aggressions.
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Affiliation(s)
- V Rasmont
- Laboratoires Vichy, Levallois Perret, France
| | - A Valois
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - A Gueniche
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - G Sore
- L'Oréal Research & Innovation, Chevilly Larue, France
| | - D Kerob
- Laboratoires Vichy, Levallois Perret, France
| | - M Nielsen
- Laboratoires Vichy, Levallois Perret, France
| | - E Berardesca
- Phillip Frost Department of Dermatology, University of Miami, Miami, FL, USA
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Sand H, Nielsen M. Quality assurance for automatic 4D-CT mid-ventilation selection. Phys Med 2021. [DOI: 10.1016/s1120-1797(22)00385-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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Kristensen NP, Heeke C, Tvingsholm SA, Borch A, Draghi A, Crowther MD, Carri I, Munk KK, Holm JS, Bjerregaard AM, Bentzen AK, Marquard AM, Szallasi Z, McGranahan N, Andersen R, Nielsen M, Jönsson GB, Donia M, Svane IM, Hadrup SR. Neoantigen-reactive CD8+ T cells affect clinical outcome of adoptive transfer with tumor-infiltrating lymphocytes in melanoma. J Clin Invest 2021; 132:150535. [PMID: 34813506 PMCID: PMC8759789 DOI: 10.1172/jci150535] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 11/18/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Neoantigen-driven recognition and T cell-mediated killing contribute to tumor clearance following adoptive cell therapy (ACT) with Tumor-Infiltrating Lymphocytes (TILs). Yet, how diversity, frequency, and persistence of expanded neoepitope-specific CD8+ T cells derived from TIL infusion products affect patient outcome is not fully determined. METHODS Using barcoded pMHC multimers, we provide a comprehensive mapping of CD8+ T cells recognizing neoepitopes in TIL infusion products and blood samples from 26 metastatic mela-noma patients who received ACT. RESULTS We identified 106 neoepitopes within TIL infusion products corresponding to 1.8% of all predicted neoepitopes. We observed neoepitope-specific recognition to be virtually devoid in TIL infusion products given to patients with progressive disease outcome. Moreover, we found that the frequency of neoepitope-specific CD8+ T cells in TIL infusion products correlated with in-creased survival, and that detection of engrafted CD8+ T cells in post-treatment (i.e. originating from the TIL infusion product) were unique to responders of TIL-ACT. Finally, we found that a transcriptional signature for lymphocyte activity within the tumor microenvironment was associated with a higher frequency of neoepitope-specific CD8+ T cells in the infusion product. CONCLUSIONS These data support previous case studies of neoepitope-specific CD8+ T cells in melanoma, and indicate that successful TIL-ACT is associated with an expansion of neoepitope-specific CD8+ T cells. FUNDING NEYE Foundation; European Research Council; Lundbeck Foundation Fellowship; Carlsberg Foundation.
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Affiliation(s)
- Nikolaj Pagh Kristensen
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Christina Heeke
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Siri A Tvingsholm
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Annie Borch
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Arianna Draghi
- Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | | | - Ibel Carri
- Instituto de Investigaciones Biotecnológicas, Universidad Nacional de San Martín, Buenos Aires, Argentina
| | - Kamilla K Munk
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Jeppe Sejerø Holm
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Anne-Mette Bjerregaard
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Amalie Kai Bentzen
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Andrea M Marquard
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Zoltan Szallasi
- Danish Cancer Society Research Center, Danish Cancer Society, Copenhagen, Denmark
| | | | - Rikke Andersen
- Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Morten Nielsen
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
| | - Göran B Jönsson
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Marco Donia
- Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Inge Marie Svane
- Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Sine Reker Hadrup
- Department of Health Technology, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark
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Nielsen TB, Brink C, Jeppesen SS, Schytte T, Hansen O, Nielsen M. Tumour motion analysis from planning to end of treatment course for a large cohort of peripheral lung SBRT targets. Acta Oncol 2021; 60:1407-1412. [PMID: 34643168 DOI: 10.1080/0284186x.2021.1949036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND The aim is to quantify and analyse tumour motion during a course of treatment for lung SBRT patients. MATERIAL AND METHODS Peak-to-peak motion of 483 tumours in 441 patients treated with peripheral lung SBRT at a single institution over a two year period was measured on planning CT and at all treatment fractions. Planning 4D-CT scans were analysed using our clinical workflow involving deformable propagation of the delineated target to all phases. Similarly, acquisition of the 4D-CBCT data followed the clinical workflow based on XVI 5.0 available on Elekta linacs. Differences and correlations of the peak-to-peak motion on the planning CT and at treatment were analysed. RESULTS On the planning CT, a total of 81.4% of the tumours had a peak-to-peak motion <10 mm, and 96.1% had <20 mm. The largest motion was observed in the CC direction, with largest amplitude for tumours located in the caudal posterior part of the lung. The difference in amplitude in CC between planning CT and first fraction had a mean and standard deviation of 0.3 mm and 3.5 mm, respectively, and the largest differences were observed in the caudal posterior part of the lung. Patients with a difference in tumour motion amplitude exceeding two standard deviations (>7 mm) at the first fraction were evaluated individually, and they all had poor 4DCT image quality. The difference between the first and second/third fractions had a mean and standard deviation of 0.4 mm/0.5 mm and 2.0 mm/1.9 mm. CONCLUSION Tumour motion at first treatment was similar to motion at planning, and motion at subsequent treatments was very similar to motion at first treatment. Large tumour motions are located towards the caudal posterior tumour locations. Patients with poor 4D-CT image quality should be closely followed at the first treatment to verify the motion.
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Affiliation(s)
- Tine Bjørn Nielsen
- Department of Oncology, Laboratory of Radiation Physics, Odense University Hospital, Odense C, Denmark
| | - Carsten Brink
- Department of Oncology, Laboratory of Radiation Physics, Odense University Hospital, Odense C, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | | | - Tine Schytte
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | - Olfred Hansen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | - Morten Nielsen
- Department of Oncology, Laboratory of Radiation Physics, Odense University Hospital, Odense C, Denmark
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Morrison WI, Aguado A, Sheldrake TA, Palmateer NC, Ifeonu OO, Tretina K, Parsons K, Fenoy E, Connelley T, Nielsen M, Silva JC. CD4 T Cell Responses to Theileria parva in Immune Cattle Recognize a Diverse Set of Parasite Antigens Presented on the Surface of Infected Lymphoblasts. J Immunol 2021; 207:1965-1977. [PMID: 34507950 DOI: 10.4049/jimmunol.2100331] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/22/2021] [Indexed: 12/23/2022]
Abstract
Parasite-specific CD8 T cell responses play a key role in mediating immunity against Theileria parva in cattle (Bos taurus), and there is evidence that efficient induction of these responses requires CD4 T cell responses. However, information on the antigenic specificity of the CD4 T cell response is lacking. The current study used a high-throughput system for Ag identification using CD4 T cells from immune animals to screen a library of ∼40,000 synthetic peptides representing 499 T. parva gene products. Use of CD4 T cells from 12 immune cattle, representing 12 MHC class II types, identified 26 Ags. Unlike CD8 T cell responses, which are focused on a few dominant Ags, multiple Ags were recognized by CD4 T cell responses of individual animals. The Ags had diverse properties, but included proteins encoded by two multimember gene families: five haloacid dehalogenases and five subtelomere-encoded variable secreted proteins. Most Ags had predicted signal peptides and/or were encoded by abundantly transcribed genes, but neither parameter on their own was reliable for predicting antigenicity. Mapping of the epitopes confirmed presentation by DR or DQ class II alleles and comparison of available T. parva genome sequences demonstrated that they included both conserved and polymorphic epitopes. Immunization of animals with vaccine vectors expressing two of the Ags demonstrated induction of CD4 T cell responses capable of recognizing parasitized cells. The results of this study provide detailed insight into the CD4 T cell responses induced by T. parva and identify Ags suitable for use in vaccine development.
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Affiliation(s)
- W Ivan Morrison
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom;
| | - Adriana Aguado
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
| | - Tara A Sheldrake
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
| | - Nicholas C Palmateer
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD
| | - Olukemi O Ifeonu
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD
| | - Kyle Tretina
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD
| | - Keith Parsons
- Institute for Animal Health, Berkshire, United Kingdom
| | - Emilio Fenoy
- Biotechnological Research Institute, National University of San Martin, Buenos Aires, Argentina
| | - Timothy Connelley
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
| | - Morten Nielsen
- Biotechnological Research Institute, National University of San Martin, Buenos Aires, Argentina.,Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark; and
| | - Joana C Silva
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD.,Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD
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Draghi A, Chamberlain CA, Khan S, Papp K, Lauss M, Soraggi S, Radic HD, Presti M, Harbst K, Gokuldass A, Kverneland A, Nielsen M, Westergaard MCW, Andersen MH, Csabai I, Jönsson G, Szallasi Z, Svane IM, Donia M. Rapid Identification of the Tumor-Specific Reactive TIL Repertoire via Combined Detection of CD137, TNF, and IFNγ, Following Recognition of Autologous Tumor-Antigens. Front Immunol 2021; 12:705422. [PMID: 34707600 PMCID: PMC8543011 DOI: 10.3389/fimmu.2021.705422] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 09/23/2021] [Indexed: 11/13/2022] Open
Abstract
Detecting the entire repertoire of tumor-specific reactive tumor-infiltrating lymphocytes (TILs) is essential for investigating their immunological functions in the tumor microenvironment. Current in vitro assays identifying tumor-specific functional activation measure the upregulation of surface molecules, de novo production of antitumor cytokines, or mobilization of cytotoxic granules following recognition of tumor-antigens, yet there is no widely adopted standard method. Here we established an enhanced, yet simple, method for identifying simultaneously CD8+ and CD4+ tumor-specific reactive TILs in vitro, using a combination of widely known and available flow cytometry assays. By combining the detection of intracellular CD137 and de novo production of TNF and IFNγ after recognition of naturally-presented tumor antigens, we demonstrate that a larger fraction of tumor-specific and reactive CD8+ TILs can be detected in vitro compared to commonly used assays. This assay revealed multiple polyfunctionality-based clusters of both CD4+ and CD8+ tumor-specific reactive TILs. In situ, the combined detection of TNFRSF9, TNF, and IFNG identified most of the tumor-specific reactive TIL repertoire. In conclusion, we describe a straightforward method for efficient identification of the tumor-specific reactive TIL repertoire in vitro, which can be rapidly adopted in most cancer immunology laboratories.
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Affiliation(s)
- Arianna Draghi
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Christopher Aled Chamberlain
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Shawez Khan
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Krisztian Papp
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Martin Lauss
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
- Lund University Cancer Centre, Lund University, Lund, Sweden
| | - Samuele Soraggi
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
| | - Haja Dominike Radic
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Mario Presti
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Katja Harbst
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
- Lund University Cancer Centre, Lund University, Lund, Sweden
| | - Aishwarya Gokuldass
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Anders Kverneland
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Morten Nielsen
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | | | - Mads Hald Andersen
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Istvan Csabai
- Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Göran Jönsson
- Division of Oncology and Pathology, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
- Lund University Cancer Centre, Lund University, Lund, Sweden
| | | | - Inge Marie Svane
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
| | - Marco Donia
- National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, Herlev, Denmark
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