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Robert PA, Akbar R, Frank R, Pavlović M, Widrich M, Snapkov I, Slabodkin A, Chernigovskaya M, Scheffer L, Smorodina E, Rawat P, Mehta BB, Vu MH, Mathisen IF, Prósz A, Abram K, Olar A, Miho E, Haug DTT, Lund-Johansen F, Hochreiter S, Haff IH, Klambauer G, Sandve GK, Greiff V. Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. Nat Comput Sci 2022; 2:845-865. [PMID: 38177393 DOI: 10.1038/s43588-022-00372-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 11/09/2022] [Indexed: 01/06/2024]
Abstract
Machine learning (ML) is a key technology for accurate prediction of antibody-antigen binding. Two orthogonal problems hinder the application of ML to antibody-specificity prediction and the benchmarking thereof: the lack of a unified ML formalization of immunological antibody-specificity prediction problems and the unavailability of large-scale synthetic datasets to benchmark real-world relevant ML methods and dataset design. Here we developed the Absolut! software suite that enables parameter-based unconstrained generation of synthetic lattice-based three-dimensional antibody-antigen-binding structures with ground-truth access to conformational paratope, epitope and affinity. We formalized common immunological antibody-specificity prediction problems as ML tasks and confirmed that for both sequence- and structure-based tasks, accuracy-based rankings of ML methods trained on experimental data hold for ML methods trained on Absolut!-generated data. The Absolut! framework has the potential to enable real-world relevant development and benchmarking of ML strategies for biotherapeutics design.
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Affiliation(s)
- Philippe A Robert
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
| | - Rahmad Akbar
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Robert Frank
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | | | - Michael Widrich
- ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria
| | - Igor Snapkov
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Andrei Slabodkin
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | | | - Eva Smorodina
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Puneet Rawat
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Brij Bhushan Mehta
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Mai Ha Vu
- Department of Linguistics and Scandinavian Studies, University of Oslo, Oslo, Norway
| | | | - Aurél Prósz
- Danish Cancer Society Research Center, Translational Cancer Genomics, Copenhagen, Denmark
| | - Krzysztof Abram
- The Novo Nordisk Foundation Center for Biosustainability, Autoflow, DTU Biosustain and IT University of Copenhagen, Copenhagen, Denmark
| | - Alex Olar
- Department of Complex Systems in Physics, Eötvös Loránd University, Budapest, Hungary
| | - Enkelejda Miho
- Institute of Medical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
- aiNET GmbH, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Sepp Hochreiter
- ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria
- Institute of Advanced Research in Artificial Intelligence (IARAI), Vienna, Austria
| | | | - Günter Klambauer
- ELLIS Unit Linz and LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria
| | | | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
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Weber CR, Rubio T, Wang L, Zhang W, Robert PA, Akbar R, Snapkov I, Wu J, Kuijjer ML, Tarazona S, Conesa A, Sandve GK, Liu X, Reddy ST, Greiff V. Reference-based comparison of adaptive immune receptor repertoires. Cell Rep Methods 2022; 2:100269. [PMID: 36046619 PMCID: PMC9421535 DOI: 10.1016/j.crmeth.2022.100269] [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] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 04/01/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022]
Abstract
B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.
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Affiliation(s)
- Cédric R. Weber
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Teresa Rubio
- Laboratory of Neurobiology, Centro Investigación Príncipe Felipe, Valencia, Spain
| | - Longlong Wang
- BGI-Shenzhen, Shenzhen, China
- BGI-Education Center, University of Chinese Academy of Sciences, Shenzhen, China
| | - Wei Zhang
- BGI-Shenzhen, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Hong Kong, China
| | - Philippe A. Robert
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Rahmad Akbar
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Igor Snapkov
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | | | - Marieke L. Kuijjer
- Centre for Molecular Medicine Norway, University of Oslo, Oslo, Norway
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
- Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sonia Tarazona
- Departamento de Estadística e Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València, Valencia, Spain
| | - Ana Conesa
- Institute for Integrative Systems Biology, Spanish National Research Council, Valencia, Spain
| | - Geir K. Sandve
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Xiao Liu
- BGI-Shenzhen, Shenzhen, China
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
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Akbar R, Robert PA, Weber CR, Widrich M, Frank R, Pavlović M, Scheffer L, Chernigovskaya M, Snapkov I, Slabodkin A, Mehta BB, Miho E, Lund-Johansen F, Andersen JT, Hochreiter S, Hobæk Haff I, Klambauer G, Sandve GK, Greiff V. In silico proof of principle of machine learning-based antibody design at unconstrained scale. MAbs 2022; 14:2031482. [PMID: 35377271 PMCID: PMC8986205 DOI: 10.1080/19420862.2022.2031482] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [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: 12/15/2022] Open
Abstract
Generative machine learning (ML) has been postulated to become a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing arbitrarily large numbers of antibody sequences for their most critical design parameters: paratope, epitope, affinity, and developability. To address this challenge, we leveraged a lattice-based antibody-antigen binding simulation framework, which incorporates a wide range of physiological antibody-binding parameters. The simulation framework enables the computation of synthetic antibody-antigen 3D-structures, and it functions as an oracle for unrestricted prospective evaluation and benchmarking of antibody design parameters of ML-generated antibody sequences. We found that a deep generative model, trained exclusively on antibody sequence (one dimensional: 1D) data can be used to design conformational (three dimensional: 3D) epitope-specific antibodies, matching, or exceeding the training dataset in affinity and developability parameter value variety. Furthermore, we established a lower threshold of sequence diversity necessary for high-accuracy generative antibody ML and demonstrated that this lower threshold also holds on experimental real-world data. Finally, we show that transfer learning enables the generation of high-affinity antibody sequences from low-N training data. Our work establishes a priori feasibility and the theoretical foundation of high-throughput ML-based mAb design.
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Affiliation(s)
- Rahmad Akbar
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Philippe A Robert
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Michael Widrich
- Ellis Unit Linz and Lit Ai Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria
| | - Robert Frank
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | | | | | - Maria Chernigovskaya
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Igor Snapkov
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Andrei Slabodkin
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Brij Bhushan Mehta
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Enkelejda Miho
- Institute of Medical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Fridtjof Lund-Johansen
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
| | - Jan Terje Andersen
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway.,Institute of Clinical Medicine, Department of Pharmacology, University of Oslo, Oslo, Norway
| | - Sepp Hochreiter
- Ellis Unit Linz and Lit Ai Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria.,Institute of Advanced Research in Artificial Intelligence (IARAI), Austria
| | | | - Günter Klambauer
- Ellis Unit Linz and Lit Ai Lab, Institute for Machine Learning, Johannes Kepler University Linz, Linz, Austria
| | | | - Victor Greiff
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Norway
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Slabodkin A, Chernigovskaya M, Mikocziova I, Akbar R, Scheffer L, Pavlović M, Bashour H, Snapkov I, Mehta BB, Weber CR, Gutierrez-Marcos J, Sollid LM, Haff IH, Sandve GK, Robert PA, Greiff V. Individualized VDJ recombination predisposes the available Ig sequence space. Genome Res 2021; 31:2209-2224. [PMID: 34815307 PMCID: PMC8647828 DOI: 10.1101/gr.275373.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/20/2021] [Indexed: 11/25/2022]
Abstract
The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire and, consequently, (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also nongenetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.
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Affiliation(s)
- Andrei Slabodkin
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Ivana Mikocziova
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Rahmad Akbar
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Lonneke Scheffer
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Milena Pavlović
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Habib Bashour
- School of Life Sciences, University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Igor Snapkov
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Brij Bhushan Mehta
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
| | | | - Ludvig M Sollid
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | | | | | - Philippe A Robert
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, 0372 Oslo, Norway
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Jareid M, Snapkov I, Holden M, Busund LTR, Lund E, Nøst TH. The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort. PLoS One 2021; 16:e0256442. [PMID: 34449791 PMCID: PMC8396762 DOI: 10.1371/journal.pone.0256442] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 08/06/2021] [Indexed: 11/22/2022] Open
Abstract
Epithelial ovarian cancer (EOC) has a 5-year relative survival of 50%, partly because markers of early-stage disease are not available in current clinical diagnostics. The aim of the present study was to investigate whether EOC is associated with transcriptional profiles in blood collected up to 7 years before diagnosis. For this, we used RNA-stabilized whole blood, which contains circulating immune cells, from a sample of EOC cases from the population-based Norwegian Women and Cancer (NOWAC) postgenome cohort. We explored case-control differences in gene expression in all EOC (66 case-control pairs), as well as associations between gene expression and metastatic EOC (56 pairs), serous EOC (45 pairs, 44 of which were metastatic), and interval from blood sample collection to diagnosis (≤3 or >3 years; 34 and 31 pairs, respectively). Lastly, we assessed differential expression of genes associated with EOC in published functional genomics studies that used blood samples collected from newly diagnosed women. After adjustment for multiple testing, this nested case-control study revealed no significant case-control differences in gene expression in all EOC (false discovery rate q>0.96). With the exception of a few probes, the log2 fold change values obtained in gene-wise linear models were below ±0.2. P-values were lowest in analyses of metastatic EOC (80% of which were serous EOC). No common transcriptional profile was indicated by interval to diagnosis; when comparing the 100 genes with the lowest p-values in gene-wise tests in samples collected ≤3 and >3 years before EOC diagnosis, no overlap in these genes was observed. Among 86 genes linked to ovarian cancer in previous publications, our data contained expression values for 42, and of these, tests of LIME1, GPR162, STAB1, and SKAP1, resulted in unadjusted p<0.05. Although limited by sample size, our findings indicated less variation in blood gene expression between women with similar tumor characteristics.
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Affiliation(s)
- Mie Jareid
- Faculty of Health Sciences, Department of Community Medicine, UiT – The Arctic University of Norway, Tromsø, Norway
- * E-mail:
| | - Igor Snapkov
- Department of Immunology, Oslo University Hospital Rikshospitalet and University of Oslo, Oslo, Norway
| | | | - Lill-Tove Rasmussen Busund
- Faculty of Health Sciences, Department of Medical Biology, UiT – The Arctic University of Norway, Tromsø, Norway
| | - Eiliv Lund
- Faculty of Health Sciences, Department of Community Medicine, UiT – The Arctic University of Norway, Tromsø, Norway
- Cancer Registry of Norway, Oslo, Norway
| | - Therese Haugdahl Nøst
- Faculty of Health Sciences, Department of Community Medicine, UiT – The Arctic University of Norway, Tromsø, Norway
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Öjlert ÅK, Nebdal D, Snapkov I, Olsen V, Kidman J, Greiff V, Chee J, Helland Å. Dynamic changes in the T cell receptor repertoire during treatment with radiotherapy combined with an immune checkpoint inhibitor. Mol Oncol 2021; 15:2958-2968. [PMID: 34402187 PMCID: PMC8564644 DOI: 10.1002/1878-0261.13082] [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] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/26/2021] [Accepted: 08/13/2021] [Indexed: 02/01/2023] Open
Abstract
Previous studies have indicated a synergistic effect between radiotherapy and immunotherapy. A better understanding of how this combination affects the immune system can help to clarify its role in the treatment of metastatic cancer. We performed T cell receptor (TCR) sequencing on 46 sequentially collected samples from 15 patients with stage IV non-small cell lung cancer, receiving stereotactic body radiotherapy combined with a programmed cell death ligand-1 (PD-L1) inhibitor. TCR repertoire diversity was assessed using Rényi diversity curves and the Shannon diversity index. TCR clones were tracked over time. We found decreasing or stable diversity in the best responders, and an increase in diversity at progression in patients with an initial response. Expansion of TCR clones was more often seen in responders. Several patients also developed new clones of high abundance. This seemed to be more related to radiotherapy than to immune checkpoint blockade. In summary, we observed similar dynamics in the TCR repertoire as have been described with immunotherapy alone. In addition, the occurrence of new unique clones of high abundance after radiotherapy may indicate that radiotherapy functions as a personalized cancer vaccine.
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Affiliation(s)
- Åsa Kristina Öjlert
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Norway
| | - Daniel Nebdal
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Norway
| | - Igor Snapkov
- Department of Immunology, University of Oslo, Norway
| | - Vibeke Olsen
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Norway
| | - Joel Kidman
- National Centre for Asbestos Related Diseases, Institute of Respiratory Health, University of Western Australia, Perth, WA, Australia.,School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia
| | - Victor Greiff
- Department of Immunology, University of Oslo, Norway
| | - Jonathan Chee
- National Centre for Asbestos Related Diseases, Institute of Respiratory Health, University of Western Australia, Perth, WA, Australia.,School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia
| | - Åslaug Helland
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Norway.,Department of Clinical Medicine, University of Oslo, Norway.,Department of Oncology, Oslo University Hospital, Norway
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Akbar R, Robert PA, Pavlović M, Jeliazkov JR, Snapkov I, Slabodkin A, Weber CR, Scheffer L, Miho E, Haff IH, Haug DTT, Lund-Johansen F, Safonova Y, Sandve GK, Greiff V. A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding. Cell Rep 2021; 34:108856. [PMID: 33730590 DOI: 10.1016/j.celrep.2021.108856] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [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: 03/12/2020] [Revised: 11/29/2020] [Accepted: 02/22/2021] [Indexed: 12/16/2022] Open
Abstract
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo antibody and (neo-)epitope design. A fundamental premise for the predictability of antibody-antigen binding is the existence of paratope-epitope interaction motifs that are universally shared among antibody-antigen structures. In a dataset of non-redundant antibody-antigen structures, we identify structural interaction motifs, which together compose a commonly shared structure-based vocabulary of paratope-epitope interactions. We show that this vocabulary enables the machine learnability of antibody-antigen binding on the paratope-epitope level using generative machine learning. The vocabulary (1) is compact, less than 104 motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible.
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Affiliation(s)
- Rahmad Akbar
- Department of Immunology, University of Oslo, Oslo, Norway.
| | | | - Milena Pavlović
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway; K.G. Jebsen Centre for Coeliac Disease Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Igor Snapkov
- Department of Immunology, University of Oslo, Oslo, Norway
| | | | - Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Lonneke Scheffer
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway
| | - Enkelejda Miho
- Institute of Medical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | | | | | | | - Yana Safonova
- Computer Science and Engineering Department, University of California, San Diego, La Jolla, CA, USA
| | - Geir K Sandve
- Department of Informatics, University of Oslo, Oslo, Norway; Centre for Bioinformatics, University of Oslo, Norway; K.G. Jebsen Centre for Coeliac Disease Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway.
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Weber CR, Akbar R, Yermanos A, Pavlović M, Snapkov I, Sandve GK, Reddy ST, Greiff V. immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking. Bioinformatics 2020; 36:3594-3596. [PMID: 32154832 PMCID: PMC7334888 DOI: 10.1093/bioinformatics/btaa158] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [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: 09/09/2019] [Revised: 02/03/2020] [Accepted: 03/04/2020] [Indexed: 11/14/2022] Open
Abstract
Summary B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full-length variable region immune receptor sequences by tuning the following immune receptor features: (i) species and chain type (BCR, TCR, single and paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis, such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis and machine learning methods for motif detection. Availability and implementation The package is available via https://github.com/GreiffLab/immuneSIM and on CRAN at https://cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https://immuneSIM.readthedocs.io. Contact sai.reddy@ethz.ch or victor.greiff@medisin.uio.no Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Cédric R Weber
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Rahmad Akbar
- Department of Immunology, University of Oslo, 0372 Oslo, Norway
| | - Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Milena Pavlović
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Igor Snapkov
- Department of Immunology, University of Oslo, 0372 Oslo, Norway
| | - Geir K Sandve
- Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Sai T Reddy
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Victor Greiff
- Department of Immunology, University of Oslo, 0372 Oslo, Norway
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Lund E, Nakamura A, Snapkov I, Thalabard JC, Olsen KS, Holden L, Holden M. Each pregnancy linearly changes immune gene expression in the blood of healthy women compared with breast cancer patients. Clin Epidemiol 2018; 10:931-940. [PMID: 30123005 PMCID: PMC6084086 DOI: 10.2147/clep.s163208] [Citation(s) in RCA: 3] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background There is a large body of evidence demonstrating long-lasting protective effect of each full-term pregnancy (FTP) on the development of breast cancer (BC) later in life, a phenomenon that could be related to both hormonal and immunological changes during pregnancies. In this work, we studied the pregnancy-associated differences in peripheral blood gene expression profiles between healthy women and women diagnosed with BC in a prospective design. Methods Using an integrated system epidemiology approach, we modeled BC incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort (165,000 women) and then tested the resulting mathematical model using gene expression profiles in blood in a nested case-control study (460 invasive case-control pairs) of women from the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. Results A linear trend fitted the dataset precisely showing an 8% decrease in risk of BC for each FTP, independent of stratification on other risk factors and lasting for decades after a woman's last FTP. Women with six children demonstrated 48% reduction in the incidence of BC compared to nulliparous. When we looked at gene expression, we found that 756 genes showed linear trends in cancer-free controls (false discovery rate [FDR] 5%), but this was not the case for any of the genes in BC cases. Gene set enrichment analysis of immunologic gene sets (C7 collection in Molecular Signatures Database) revealed 215 significantly enriched human gene sets (FDR 5%). Conclusion We found marked differences in gene expression and enrichment profiles of immunologic gene sets between BC cases and healthy controls, suggesting an important protective effect of the immune system on BC risk.
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Affiliation(s)
- Eiliv Lund
- Department of Community Medicine, UiT The Arctic University of Norway, Tromso, Norway, .,The Cancer Registry of Norway, Oslo, Norway,
| | - Aurelie Nakamura
- Department of Social Epidemiology, Pierre Louis Institute of Epidemiology and Public Health, Sorbonne University, INSERM, Paris, France.,French School of Public Health (EHESP), Doctoral Network, Rennes, France
| | - Igor Snapkov
- Department of Community Medicine, UiT The Arctic University of Norway, Tromso, Norway,
| | | | - Karina Standahl Olsen
- Department of Community Medicine, UiT The Arctic University of Norway, Tromso, Norway,
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Tümmler C, Snapkov I, Wickström M, Moens U, Ljungblad L, Maria Elfman LH, Winberg JO, Kogner P, Johnsen JI, Sveinbjørnsson B. Inhibition of chemerin/CMKLR1 axis in neuroblastoma cells reduces clonogenicity and cell viability in vitro and impairs tumor growth in vivo. Oncotarget 2017; 8:95135-95151. [PMID: 29221117 PMCID: PMC5707011 DOI: 10.18632/oncotarget.19619] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [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: 12/10/2016] [Accepted: 07/06/2017] [Indexed: 02/06/2023] Open
Abstract
Pro-inflammatory cells, cytokines, and chemokines are essential in promoting a tumor supporting microenvironment. Chemerin is a chemotactic protein and a natural ligand for the receptors CMKLR1, GPR1, and CCRL2. The chemerin/CMKLR1 axis is involved in immunity and inflammation, and it has also been implicated in obesity and cancer. In neuroblastoma, a childhood tumor of the peripheral nervous system we identified correlations between high CMKLR1 and GPR1 expression and reduced overall survival probability. CMKLR1, GPR1, and chemerin RNA and protein were detected in neuroblastoma cell lines and neuroblastoma primary tumor tissue. Chemerin induced calcium mobilization, increased MMP-2 synthesis as well as MAP-kinase- and Akt-mediated signaling in neuroblastoma cells. Stimulation of neuroblastoma cells with serum, TNFα or IL-1β increased chemerin secretion. The small molecule CMKLR1 antagonist α-NETA reduced the clonogenicity and viability of neuroblastoma cell lines indicating the chemerin/CMKLR1 axis as a promoting factor in neuroblastoma tumorigenesis. Furthermore, nude mice carrying neuroblastoma SK-N-AS cells as xenografts showed impaired tumor growth when treated daily with α-NETA from day 1 after tumor cell injection. This study demonstrates the potential of the chemerin/CMKLR1 axis as a prognostic factor and possible therapeutic target in neuroblastoma.
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Affiliation(s)
- Conny Tümmler
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Igor Snapkov
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Malin Wickström
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Ugo Moens
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Linda Ljungblad
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Lotta Helena Maria Elfman
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Jan-Olof Winberg
- Tumor Biology Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Per Kogner
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John Inge Johnsen
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Baldur Sveinbjørnsson
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway.,Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
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Øie CI, Snapkov I, Elvevold K, Sveinbjørnsson B, Smedsrød B. FITC Conjugation Markedly Enhances Hepatic Clearance of N-Formyl Peptides. PLoS One 2016; 11:e0160602. [PMID: 27494406 PMCID: PMC4975464 DOI: 10.1371/journal.pone.0160602] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 07/21/2016] [Indexed: 12/19/2022] Open
Abstract
In both septic and aseptic inflammation, N-formyl peptides may enter the circulation and induce a systemic inflammatory response syndrome similar to that observed during septic shock. The inflammatory response is brought about by the binding of N-formyl peptide to formyl peptide receptors (FPRs), specific signaling receptors expressed on myeloid as well as non-myeloid cells involved in the inflammatory process. N-formyl peptides conjugated with fluorochromes, such as fluorescein isothiocyanate (FITC) are increasingly experimentally used to identify tissues involved in inflammation. Hypothesizing that the process of FITC-conjugation may transfer formyl peptide to a ligand that is efficiently cleared from the circulation by the natural powerful hepatic scavenging regime we studied the biodistribution of intravenously administered FITC-fNLPNTL (Fluorescein-isothiocyanate- N-Formyl-Nle-Leu-Phe-Nle-Tyr-Lys) in mice. Our findings can be summarized as follows: i) In contrast to unconjugated fNLPNTL, FITC-fNLPNTL was rapidly taken up in the liver; ii) Mouse and human liver sinusoidal endothelial cells (LSECs) and hepatocytes express formyl peptide receptor 1 (FRP1) on both mRNA (PCR) and protein (Western blot) levels; iii) Immunohistochemistry showed that mouse and human liver sections expressed FRP1 in LSECs and hepatocytes; and iv) Uptake of FITC-fNLPNTL could be largely blocked in mouse and human hepatocytes by surplus-unconjugated fNLPNTL, thereby suggesting that the hepatocytes in both species recognized FITC-fNLPNTL and fNLPNTL as indistinguishable ligands. This was in contrast to the mouse and human LSECs, in which the uptake of FITC-fNLPNTL was mediated by both FRP1 and a scavenger receptor, specifically expressed on LSECs. Based on these results we conclude that a significant proportion of FITC-fNLPNTL is taken up in LSECs via a scavenger receptor naturally expressed in these cells. This calls for great caution when using FITC-fNLPNTL and other chromogen-conjugated formyl peptides as a probe to identify cells in a liver engaged in inflammation. Moreover, our finding emphasizes the role of the liver as an important neutralizer of otherwise strong inflammatory signals such as formyl peptides.
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Affiliation(s)
- Cristina Ionica Øie
- Vascular Biology Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- * E-mail:
| | - Igor Snapkov
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | | | - Baldur Sveinbjørnsson
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Astrid Lindgren Children's Hospital, Stockholm, Sweden
| | - Bård Smedsrød
- Vascular Biology Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
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Snapkov I, Öqvist CO, Figenschau Y, Kogner P, Johnsen JI, Sveinbjørnsson B. The role of formyl peptide receptor 1 (FPR1) in neuroblastoma tumorigenesis. BMC Cancer 2016; 16:490. [PMID: 27432059 PMCID: PMC4950242 DOI: 10.1186/s12885-016-2545-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [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: 11/09/2015] [Accepted: 07/11/2016] [Indexed: 12/26/2022] Open
Abstract
Background Formyl peptide receptor 1 (FPR1) is a G protein-coupled receptor mainly expressed by the cells of myeloid origin, where it mediates the innate immune response to bacterial formylated peptides. High expression of FPR1 has been detected in various cancers but the function of FPR1 in tumorigenesis is poorly understood. Methods Expression of FPR1 in neuroblastoma cell lines and primary tumors was studied using RT-PCR, western blotting, immunofluorescence and immunohistochemistry. Calcium mobilization assays and western blots with phospho-specific antibodies were used to assess the functional activity of FPR1 in neuroblastoma. The tumorigenic capacity of FPR1 was assessed by xenografting of neuroblastoma cells expressing inducible FPR1 shRNA, FPR1 cDNA or control shRNA in nude mice. Results FPR1 is expressed in neuroblastoma primary tumors and cell lines. High expression of FPR1 corresponds with high-risk disease and poor patient survival. Stimulation of FPR1 in neuroblastoma cells using fMLP, a selective FPR1 agonist, induced intracellular calcium mobilization and activation of MAPK/Erk, PI3K/Akt and P38-MAPK signal transduction pathways that were inhibited by using Cyclosporin H, a selective receptor antagonist for FPR1. shRNA knock-down of FPR1 in neuroblastoma cells conferred a delayed xenograft tumor development in nude mice, whereas an ectopic overexpression of FPR1 promoted augmented tumorigenesis in nude mice. Conclusion Our data demonstrate that FPR1 is involved in neuroblastoma development and could represent a therapy option for the treatment of neuroblastoma. Electronic supplementary material The online version of this article (doi:10.1186/s12885-016-2545-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Igor Snapkov
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway.
| | - Carl Otto Öqvist
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Yngve Figenschau
- Endocrinology Research Group, Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway.,Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway.,Department of Laboratory Medicine, University Hospital of North Norway, Tromsø, Norway
| | - Per Kogner
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John Inge Johnsen
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Baldur Sveinbjørnsson
- Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
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Snapkov I, Öqvist CO, Figenschau YA, Kogner P, Johnsen JI, Sveinbjørnsson B. Abstract 3283: The role of formyl peptide receptor 1 (FPR1) in neuroblastoma tumorigenesis. Cancer Res 2015. [DOI: 10.1158/1538-7445.am2015-3283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
The formyl peptide receptor 1 (FPR1) is a G protein-coupled receptor with pattern recognition properties and is mainly expressed by myeloid cells. It is involved in a broad range of host defense mechanisms and a variety of host-derived agonists of FPR1 have been identified, including formyl peptides released from disrupted mitochondria of necrotic cells.
In the present study, we demonstrate the expression of FPR1 in 7 different neuroblastoma cell lines and in primary tumors. Furthermore, FPR1 is expressed at increased levels in high stage tumors. Addition of the FPR1 agonist N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLP) to neuroblastoma cells in vitro caused enhanced proliferative activity, increase of intracellular calcium response and activation of STAT3 and MAPK/ERK signal transduction pathways. All these signal transduction events were abrogated by the use of Cyclosporin H, a specific FPR1 antagonist.
To assess the significance of this receptor in vivo, we developed a set of neuroblastoma cell clones with different expression levels of FPR1. Xenograft models showed that cells with overexpression of the receptor developed tumors significantly faster compared to control group.
Our findings so far suggest that FPR1 may play a significant role in neuroblastoma tumorigenesis and that therapeutic intervention of the FPR1 pathway may be an important clinical strategy in neuroblastoma therapy.
Citation Format: Igor Snapkov, Carl Otto Öqvist, Yngve Anton Figenschau, Per Kogner, John Inge Johnsen, Baldur Sveinbjørnsson. The role of formyl peptide receptor 1 (FPR1) in neuroblastoma tumorigenesis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3283. doi:10.1158/1538-7445.AM2015-3283
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Affiliation(s)
- Igor Snapkov
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromso, Tromso, Norway
| | - Carl Otto Öqvist
- 2Division of Pediatric Oncology, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Yngve Anton Figenschau
- 3Endocrinology Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromso, Tromso, Norway
| | - Per Kogner
- 2Division of Pediatric Oncology, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John Inge Johnsen
- 2Division of Pediatric Oncology, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Baldur Sveinbjørnsson
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Sciences, University of Tromso, Tromso, Norway
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Tuemmler C, Snapkov I, Moens UL, Kogner P, Johnsen JI, Sveinbjørnsson B. Abstract 3279: Expression of chemerin and chemerin receptors in neuroblastoma: implications in tumorigenesis. Cancer Res 2015. [DOI: 10.1158/1538-7445.am2015-3279] [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: 11/16/2022]
Abstract
Abstract
Chemerin is an adipokine and immunomodulating factor that promotes chemotaxis of immature dendritic cells, natural killer cells, macrophages and endothelial cells. Secreted as prochemerin with low activity, it can be C-terminally processed by different proteases expressed by a broad range of cell types and tissues. The resulting isoforms vary in receptor affinity and biological activity and are natural ligands for the G protein-coupled receptors (GPCRs) CMKLR1, GPR1 and CCLR2. To date, the activation of CMKLR1 (chemokine-like receptor 1) by chemerin and its role in metabolism and metabolic disorders as well as inflammation is best understood.
Neuroblastoma (NB) is a malignancy of the sympathetic nervous system and the most common extracranial solid pediatric tumor. Several chemoattractant GPCRs have been suggested to promote tumor progression, angiogenesis and metastasis in NB. Although for some cancers a potential function has been suggested, the role of chemerin and its receptors in the NB tumor microenvironment remains unknown.
In our study, the screening of microarray databases and analysis of neuroblastoma expression data showed a correlation between high CMKLR1, GPR1 and CCLR2 expression and a reduction in the overall survival probability. Expression of CMKLR1, GPR1, and chemerin was shown in nine neuroblastoma cell lines using RT-PCR, Western blot and immunocytochemistry. Furthermore, chemerin and CMKLR1 were also detected in neuroblastoma tumor tissue by immunohistochemistry. Stimulation of NB cell lines with active chemerin induced calcium mobilization and increased phosphorylation of MEK1/2 and ERK1/2 indicating an activation of the MAPK signaling pathway. Furthermore, chemerin stimulation led to increased NF-κB phosphorylation and translocation to the nucleus. The induction of NF-κB mediated signaling was observed by luciferase reporter assay. TNFα, IL-1β or serum stimulation increased chemerin protein expression and secretion in neuroblastoma cells.
To assess the functional significance of chemerin and its receptors in neuroblastoma tumorigenesis, cell clones overexpressing or silenced for CMKLR1/ Chemerin/ GPR1 are used in NB animal models.
Citation Format: Conny Tuemmler, Igor Snapkov, Ugo L. Moens, Per Kogner, John Inge Johnsen, Baldur Sveinbjørnsson. Expression of chemerin and chemerin receptors in neuroblastoma: implications in tumorigenesis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3279. doi:10.1158/1538-7445.AM2015-3279
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Affiliation(s)
- Conny Tuemmler
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Igor Snapkov
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Ugo L. Moens
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
| | - Per Kogner
- 2Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John Inge Johnsen
- 2Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Baldur Sveinbjørnsson
- 1Molecular Inflammation Research Group, Department of Medical Biology, Faculty of Health Science, University of Tromsø, Tromsø, Norway
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Gerits N, Johannessen M, Tümmler C, Walquist M, Kostenko S, Snapkov I, van Loon B, Ferrari E, Hübscher U, Moens U. Agnoprotein of polyomavirus BK interacts with proliferating cell nuclear antigen and inhibits DNA replication. Virol J 2015; 12:7. [PMID: 25638270 PMCID: PMC4318453 DOI: 10.1186/s12985-014-0220-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [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: 02/06/2014] [Accepted: 12/01/2014] [Indexed: 12/25/2022] Open
Abstract
Background The human polyomavirus BK expresses a 66 amino-acid peptide referred to as agnoprotein. Though mutants lacking agnoprotein are severely reduced in producing infectious virions, the exact function of this peptide remains incompletely understood. To elucidate the function of agnoprotein, we searched for novel cellular interaction partners. Methods Yeast-two hybrid assay was performed with agnoprotein as bait against human kidney and thymus libraries. The interaction between agnoprotein and putative partners was further examined by GST pull down, co-immunoprecipitation, and fluorescence resonance energy transfer studies. Biochemical and biological studies were performed to examine the functional implication of the interaction of agnoprotein with cellular target proteins. Results Proliferating cell nuclear antigen (PCNA), which acts as a processivity factor for DNA polymerase δ, was identified as an interaction partner. The interaction between agnoprotein and PCNA is direct and occurs also in human cells. Agnoprotein exerts an inhibitory effect on PCNA-dependent DNA synthesis in vitro and reduces cell proliferation when ectopically expressed. Overexpression of PCNA restores agnoprotein-mediated inhibition of cell proliferation. Conclusion Our data suggest that PCNA is a genuine interaction partner of agnoprotein and the inhibitory effect on PCNA-dependent DNA synthesis by the agnoprotein may play a role in switching off (viral) DNA replication late in the viral replication cycle when assembly of replicated genomes and synthesized viral capsid proteins occurs. Electronic supplementary material The online version of this article (doi:10.1186/s12985-014-0220-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Ugo Moens
- UiT - The Arctic University of Norway, Faculty of Health Sciences, Department of Medical Biology, Molecular Inflammation Research Group, Tromsø NO-9037, Norway.
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Kiselev Y, Valkov A, Mikkola I, Snapkov I, Sorbye S, Bremnes R, Busund LT. Abstract 4722: Transcription factor PAX6 is expressed in human soft tissue sarcomas and confers negative impact on patients' survival. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-4722] [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: 11/16/2022]
Abstract
Abstract
AIM:
We investigated the expression of PAX6 in soft tissue sarcomas to evaluate its prognostic value.
BACKGROUND:
Transcription factor PAX6 has a decisive role in the development of the CNS, eye, pancreas and olfactory epithelium, and the pattern of PAX6 normal expression is restricted to those tissues. PAX6 is detected in various cancer cell lines, but very little is known about its expression in tumors, possible cancer-relevant functions and prognostic value. PAX6 is generally believed to be a tumor suppressor, based mainly on studies in glioblastoma. PAX6 has been detected in tumors of eye and pancreas, but the prognostic significance remains unclear. Soft tissue sarcomas (STS) are a relatively uncommon but deadly group of tumors with poor prognosis and few treatment options. Improving therapy efficacy requires discovery of novel biomarkers to identify high-risk patients who may benefit from adjuvant therapy, as well as to improve our understanding of the molecular pathology of STS.
METHODS:
Tissue microarrays from 249 STS patients were constructed from duplicate cores of viable and representative neoplastic tumor areas. Immunohistochemistry was used to evaluate the expression of PAX6 and TGF-beta. Western blotting was used to evaluate expression levels of PAX6 and TGF-beta in B3 lens epithelium cell line.
RESULTS:
PAX6 expression was detected in STS tissue samples. Both nuclear and cytoplasmic expression was observed, and there was a positive correlation between them (r=0.47; P<0.001). In univariate analyses, tumor expression of PAX6 correlated (p=0,029) with reduced disease-specific survival (DSS). Rhabdomyosarcoma, synovial sarcoma, undifferentiated pleomorphic sarcoma and leiomyosarcoma appeared to be the tumor types with highest number of PAX6-positive samples (73,3%, 68,8%, 54,5%, 50,8%, respectively). Multivariate analysis (after the exclusion of possible confounders) indicated that PAX6 expression was a negative prognostic factors for DSS of all patients, irrespective of age, gender, tumor size, histological type, grade or presence of metastasis at the time of diagnosis (P=0,025, HR=1.5, CI=1.1-2.2). We also observed a correlation between expression levels of PAX6 and TGF-beta, with an apparent synergistic negative effect on DSS: double-positive patients had worst DSS compared to single-positives or negatives. In the B3 cell line PAX6knockdown caused downregulation of TGF-beta, while stimulation of cells with TGF-beta protein activated expression of PAX6.
CONCLUSIONS:
We detected PAX6 in STS - the first tumor group with no developmental links to the normal sites of PAX6 expression. PAX6 appeared to confer a universal negative prognostic impact on DSS, irrespectively of clinical and pathological subgroups analyzed. PAX6 expression correlated with TGF-beta, and reciprocal upregulation may explain their synergistic negative effect on DSS.
Citation Format: Yury Kiselev, Andrej Valkov, Ingvild Mikkola, Igor Snapkov, Sveinung Sorbye, Roy Bremnes, Lill-Tove Busund. Transcription factor PAX6 is expressed in human soft tissue sarcomas and confers negative impact on patients' survival. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4722. doi:10.1158/1538-7445.AM2014-4722
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Affiliation(s)
- Yury Kiselev
- 1UiT The Arctic University of Norway, Tromsoe, Norway
| | - Andrej Valkov
- 2University Hospital of North Norway, Tromsoe, Norway
| | | | - Igor Snapkov
- 1UiT The Arctic University of Norway, Tromsoe, Norway
| | | | - Roy Bremnes
- 1UiT The Arctic University of Norway, Tromsoe, Norway
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Snapkov I, Kogner P, Johnsen JI, Sveinbjørnsson B. Abstract 3976: Expression of formyl peptide receptor 1 (FPR1) in neuroblastoma: Implications in tumorigenesis. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-3976] [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: 11/16/2022]
Abstract
Abstract
The formyl peptide receptor 1 (FPR1) is a G protein-coupled receptor with pattern recognition properties. It is mainly expressed by myeloid cells and is involved in a broad range of host defense mechanisms. However, a variety of host-derived agonists of FPR1 have been identified, including formyl peptides released from disrupted mitochondria of necrotic cells. In the present study, we demonstrate that FPR1 is expressed in neuroblastoma cell lines and primary tumors and high expression is correlated with poor overall survival. Addition of the FPR1 agonist N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLP) to neuroblastoma cells in vitro causes enhanced proliferative activity, increase of intracellular calcium response and activation of STAT3 and MAPK/Erk signaling pathways. Currently, clonal neuroblastoma cell line with inducible activity of FPR1 gene is under testing in a mouse model to assess the significance of this receptor in vivo. Our findings so far suggest that FPR1 may play a significant role in neuroblastoma tumorigenesis and that therapeutic intervention of the FPR1 pathway may become an important clinical strategy in neuroblastoma therapy.
Citation Format: Igor Snapkov, Per Kogner, John-Inge Johnsen, Baldur Sveinbjørnsson. Expression of formyl peptide receptor 1 (FPR1) in neuroblastoma: Implications in tumorigenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3976. doi:10.1158/1538-7445.AM2014-3976
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Affiliation(s)
- Igor Snapkov
- 1University of Tromsø, Faculty of Health Sciences, Institute of Medical Biology, Tromsø, Norway
| | - Per Kogner
- 2Karolinska Institutet, Department of Women's and Children's Health, Stockholm, Sweden
| | - John-Inge Johnsen
- 2Karolinska Institutet, Department of Women's and Children's Health, Stockholm, Sweden
| | - Baldur Sveinbjørnsson
- 1University of Tromsø, Faculty of Health Sciences, Institute of Medical Biology, Tromsø, Norway
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Tuemmler C, Snapkov I, Moens UL, Sveinbjørnsson B. Abstract 3990: Chemerin and chemerin receptors in neuroblastoma tumor microenvironment. Cancer Res 2014. [DOI: 10.1158/1538-7445.am2014-3990] [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: 11/16/2022]
Abstract
Abstract
Tumor promoting inflammatory cells as well as inflammatory mediators such as chemokines are important contributors to the tumor microenvironment as they can support tumor progression, angiogenesis and metastasis. Chemerin (also known as TIG-2 or RARRES2) is a chemoattractant factor for macrophages, immature DCs and NK-cells and a known adipokine involved in inflammation, metabolism and adipogenesis. Synthesized as a 163aa preproprotein, chemerin is N-terminally cleaved and secreted as inactive prochemerin. Following secretion, chemerin can be cleaved at the C-terminus by a variety of extracellular proteases resulting in several isoforms with varying length and biological activity. During inflammation initiation, maintenance and resolution the different chemerin isoforms may function pro- and/ or anti- inflammatory. Chemerin is a natural ligand for the G protein- coupled receptors CMKLR1 (Chem23) and GPR1. The role of chemerin and CMKLR1 in the tumor microenvironment has not been extensively studied.
The aim of this work is to study the function of chemerin and its receptors in neuroblastoma (NB). Screening of mRNA expression arrays showed a correlation between high expression of CMKLR1 and GPR1 and a worsened prognosis in NB. Chemerin, CMKLR1 and GPR1 expression was detected in different neuroblastoma cell lines by RT-PCR, immunocytochemistry and Western Blot. Stimulation with chemerin resulted in rapid and transient ERK1/2 and Akt phosphorylation.
TNF-α and IL-1β treatment increased chemerin and CMKLR1 protein levels. The functional significance of chemerin/ CMKLR1 in NB will be assessed by the use of NB animal models using cell clones silenced for chemerin/ CMKLR1.
Citation Format: Conny Tuemmler, Igor Snapkov, Ugo L. Moens, Baldur Sveinbjørnsson. Chemerin and chemerin receptors in neuroblastoma tumor microenvironment. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3990. doi:10.1158/1538-7445.AM2014-3990
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