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Collins AM, Ohlin M, Corcoran M, Heather JM, Ralph D, Law M, Martínez-Barnetche J, Ye J, Richardson E, Gibson WS, Rodriguez OL, Peres A, Yaari G, Watson CT, Lees WD. AIRR-C IG Reference Sets: curated sets of immunoglobulin heavy and light chain germline genes. Front Immunol 2024; 14:1330153. [PMID: 38406579 PMCID: PMC10884231 DOI: 10.3389/fimmu.2023.1330153] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 12/27/2023] [Indexed: 02/27/2024] Open
Abstract
Introduction Analysis of an individual's immunoglobulin (IG) gene repertoire requires the use of high-quality germline gene reference sets. When sets only contain alleles supported by strong evidence, AIRR sequencing (AIRR-seq) data analysis is more accurate and studies of the evolution of IG genes, their allelic variants and the expressed immune repertoire is therefore facilitated. Methods The Adaptive Immune Receptor Repertoire Community (AIRR-C) IG Reference Sets have been developed by including only human IG heavy and light chain alleles that have been confirmed by evidence from multiple high-quality sources. To further improve AIRR-seq analysis, some alleles have been extended to deal with short 3' or 5' truncations that can lead them to be overlooked by alignment utilities. To avoid other challenges for analysis programs, exact paralogs (e.g. IGHV1-69*01 and IGHV1-69D*01) are only represented once in each set, though alternative sequence names are noted in accompanying metadata. Results and discussion The Reference Sets include less than half the previously recognised IG alleles (e.g. just 198 IGHV sequences), and also include a number of novel alleles: 8 IGHV alleles, 2 IGKV alleles and 5 IGLV alleles. Despite their smaller sizes, erroneous calls were eliminated, and excellent coverage was achieved when a set of repertoires comprising over 4 million V(D)J rearrangements from 99 individuals were analyzed using the Sets. The version-tracked AIRR-C IG Reference Sets are freely available at the OGRDB website (https://ogrdb.airr-community.org/germline_sets/Human) and will be regularly updated to include newly observed and previously reported sequences that can be confirmed by new high-quality data.
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Affiliation(s)
- Andrew M. Collins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Mats Ohlin
- Department of Immunotechnology, and SciLifeLab, Lund University, Lund, Sweden
| | - Martin Corcoran
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - James M. Heather
- Mass General Cancer Center, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Mansun Law
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, United States
| | - Jesus Martínez-Barnetche
- Centro de Investigación Sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, Mexico
| | - Jian Ye
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States
| | - Eve Richardson
- La Jolla Institute for Immunology, San Diego, CA, United States
| | - William S. Gibson
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, United States
| | - Oscar L. Rodriguez
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, United States
| | - Ayelet Peres
- Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
| | - Gur Yaari
- Bioengineering Program, Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
| | - Corey T. Watson
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Louisville, Louisville, KY, United States
| | - William D. Lees
- Institute of Structural and Molecular Biology, Birkbeck College, London, United Kingdom
- Human-Centered Computing and Information Science, Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
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Chang H, Ashlock DA, Graether SP, Keller SM. Anchor Clustering for million-scale immune repertoire sequencing data. BMC Bioinformatics 2024; 25:42. [PMID: 38273275 PMCID: PMC10809746 DOI: 10.1186/s12859-024-05659-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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/16/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND The clustering of immune repertoire data is challenging due to the computational cost associated with a very large number of pairwise sequence comparisons. To overcome this limitation, we developed Anchor Clustering, an unsupervised clustering method designed to identify similar sequences from millions of antigen receptor gene sequences. First, a Point Packing algorithm is used to identify a set of maximally spaced anchor sequences. Then, the genetic distance of the remaining sequences to all anchor sequences is calculated and transformed into distance vectors. Finally, distance vectors are clustered using unsupervised clustering. This process is repeated iteratively until the resulting clusters are small enough so that pairwise distance comparisons can be performed. RESULTS Our results demonstrate that Anchor Clustering is faster than existing pairwise comparison clustering methods while providing similar clustering quality. With its flexible, memory-saving strategy, Anchor Clustering is capable of clustering millions of antigen receptor gene sequences in just a few minutes. CONCLUSIONS This method enables the meta-analysis of immune-repertoire data from different studies and could contribute to a more comprehensive understanding of the immune repertoire data space.
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Affiliation(s)
- Haiyang Chang
- Department of Mathematics and Statistics, University of Guelph, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada
| | - Daniel A Ashlock
- Department of Mathematics and Statistics, University of Guelph, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada
| | - Steffen P Graether
- Department of Molecular and Cellular Biology, University of Guelph, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada
| | - Stefan M Keller
- Department of Pathology, Microbiology and Immunology, School of Veterinary Medicine, University of California Davis, One Shields Avenue, Davis, CA, 95616, USA.
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Vergani S, Bagnara D, Agathangelidis A, Ng AKY, Ferrer G, Mazzarello AN, Palacios F, Yancopoulos S, Yan XJ, Barrientos JC, Rai KR, Stamatopoulos K, Chiorazzi N. CLL stereotyped B-cell receptor immunoglobulin sequences are recurrent in the B-cell repertoire of healthy individuals: Apparent lack of central and early peripheral tolerance censoring. Front Oncol 2023; 13:1112879. [PMID: 37007084 PMCID: PMC10063922 DOI: 10.3389/fonc.2023.1112879] [Citation(s) in RCA: 1] [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: 11/30/2022] [Accepted: 02/23/2023] [Indexed: 03/19/2023] Open
Abstract
IntroductionThe leukemic cells of patients with chronic lymphocytic leukemia (CLL) are often unique, expressing remarkably similar IGHV-IGHD-IGHJ gene rearrangements, “stereotyped BCRs”. The B-cell receptors (BCRs) on CLL cells are also distinctive in often deriving from autoreactive B lymphocytes, leading to the assumption of a defect in immune tolerance.ResultsUsing bulk and single-cell immunoglobulin heavy and light chain variable domain sequencing, we enumerated CLL stereotype-like IGHV-IGHD-IGHJ sequences (CLL-SLS) in B cells from cord blood (CB) and adult peripheral blood (PBMC) and bone marrow (BM of healthy donors. CLL-SLS were found at similar frequencies among CB, BM, and PBMC, suggesting that age does not influence CLL-SLS levels. Moreover, the frequencies of CLL-SLS did not differ among B lymphocytes in the BM at early stages of development, and only re-circulating marginal zone B cells contained significantly higher CLL-SLS frequencies than other mature B-cell subpopulations. Although we identified CLL-SLS corresponding to most of the CLL major stereotyped subsets, CLL-SLS frequencies did not correlate with those found in patients. Interestingly, in CB samples, half of the CLL-SLS identified were attributed to two IGHV-mutated subsets. We also found satellite CLL-SLS among the same normal samples, and they were also enriched in naïve B cells but unexpectedly, these were ~10-fold higher than standard CLL-SLS. In general, IGHV-mutated CLL-SLS subsets were enriched among antigen-experienced B-cell subpopulations, and IGHV-unmutated CLL-SLS were found mostly in antigen-inexperienced B cells. Nevertheless, CLL-SLS with an IGHV-mutation status matching that of CLL clones varied among the normal B-cell subpopulations, suggesting that specific CLL-SLS could originate from distinct subpopulations of normal B cells. Lastly, using single-cell DNA sequencing, we identified paired IGH and IGL rearrangements in normal B lymphocytes resembling those of stereotyped BCRs in CLL, although some differed from those in patients based on IG isotype or somatic mutation.DiscussionCLL-SLS are present in normal B-lymphocyte populations at all stages of development. Thus, despite their autoreactive profile they are not deleted by central tolerance mechanisms, possibly because the level of autoreactivity is not registered as dangerous by deletion mechanisms or because editing of L-chain variable genes occurred which our experimental approach could not identify.
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Affiliation(s)
- Stefano Vergani
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Davide Bagnara
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Andreas Agathangelidis
- Centre for Research and Technology Hellas, Institute of Applied Biosciences, Thessaloniki, Greece
- Department of Biology, School of Science, National and Kapodistrian University of Athens, Athens, Greece
| | - Anita Kar Yun Ng
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Gerardo Ferrer
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Andrea N. Mazzarello
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Florencia Palacios
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | | | - Xiao-Jie Yan
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Jaqueline C. Barrientos
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Kanti R. Rai
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Kostas Stamatopoulos
- Centre for Research and Technology Hellas, Institute of Applied Biosciences, Thessaloniki, Greece
| | - Nicholas Chiorazzi
- Karches Center for Oncology Research, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
- *Correspondence: Nicholas Chiorazzi,
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Sampathi S, Chernyavskaya Y, Haney MG, Moore LH, Snyder IA, Cox AH, Fuller BL, Taylor TJ, Yan D, Badgett TC, Blackburn JS. Nanopore sequencing of clonal IGH rearrangements in cell-free DNA as a biomarker for acute lymphoblastic leukemia. Front Oncol 2022; 12:958673. [PMID: 36591474 PMCID: PMC9795051 DOI: 10.3389/fonc.2022.958673] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022] Open
Abstract
Background Acute Lymphoblastic Leukemia (ALL) is the most common pediatric cancer, and patients with relapsed ALL have a poor prognosis. Detection of ALL blasts remaining at the end of treatment, or minimal residual disease (MRD), and spread of ALL into the central nervous system (CNS) have prognostic importance in ALL. Current methods to detect MRD and CNS disease in ALL rely on the presence of ALL blasts in patient samples. Cell-free DNA, or small fragments of DNA released by cancer cells into patient biofluids, has emerged as a robust and sensitive biomarker to assess cancer burden, although cfDNA analysis has not previously been applied to ALL. Methods We present a simple and rapid workflow based on NanoporeMinION sequencing of PCR amplified B cell-specific rearrangement of the (IGH) locus in cfDNA from B-ALL patient samples. A cohort of 5 pediatric B-ALL patient samples was chosen for the study based on the MRD and CNS disease status. Results Quantitation of IGH-variable sequences in cfDNA allowed us to detect clonal heterogeneity and track the response of individual B-ALL clones throughout treatment. cfDNA was detected in patient biofluids with clinical diagnoses of MRD and CNS disease, and leukemic clones could be detected even when diagnostic cell-count thresholds for MRD were not met. These data suggest that cfDNA assays may be useful in detecting the presence of ALL in the patient, even when blasts are not physically present in the biofluid sample. Conclusions The Nanopore IGH detection workflow to monitor cell-free DNA is a simple, rapid, and inexpensive assay that may ultimately serve as a valuable complement to traditional clinical diagnostic approaches for ALL.
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Affiliation(s)
- Shilpa Sampathi
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States
| | - Yelena Chernyavskaya
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States
| | - Meghan G. Haney
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States,Markey Cancer Center, University of Kentucky, Lexington, KY, United States,College of Medicine, University of Kentucky, Lexington, KY, United States
| | - L. Henry Moore
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States,College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Isabel A. Snyder
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States
| | - Anna H. Cox
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States,College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Brittany L. Fuller
- Department of Pediatric Oncology, University of Kentucky, Lexington, KY, United States
| | - Tamara J. Taylor
- Department of Pediatric Oncology, University of Kentucky, Lexington, KY, United States
| | - Donglin Yan
- Markey Cancer Center, University of Kentucky, Lexington, KY, United States,Department of Biostatistics, University of Kentucky, Lexington, KY, United States
| | - Tom C. Badgett
- Department of Pediatric Oncology, University of Kentucky, Lexington, KY, United States
| | - Jessica S. Blackburn
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, United States,Markey Cancer Center, University of Kentucky, Lexington, KY, United States,*Correspondence: Jessica S. Blackburn,
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5
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Salvetti C, Vitale C, Griggio V, Drandi D, Jones R, Bonello L, Bomben R, Bragoni A, Bagnara D, Fais F, Gattei V, Cavallo F, Zamò A, Coscia M. Case Report: Sequential Development of Three Mature Lymphoid Neoplasms in a Single Patient: Clonal Relationship and Molecular Insights. Front Oncol 2022; 12:917115. [PMID: 35734588 PMCID: PMC9207196 DOI: 10.3389/fonc.2022.917115] [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: 04/10/2022] [Accepted: 05/09/2022] [Indexed: 12/29/2022] Open
Abstract
Two main variants of Richter syndrome (RS) are recognized, namely, the diffuse large B-cell lymphoma (DLBCL) and the Hodgkin’s lymphoma (HL) variant. Clonal relationship, defined as an identity of the immunoglobulin heavy chain variable (IGHV) region sequence between chronic lymphocytic leukemia (CLL) and RS clones, characterizes patients with a poor prognosis. Due to method sensitivity, this categorization is performed without considering the possibility of small-size ancillary clones, sharing the same phenotype with the preexisting predominant CLL clone, but with different IGHV rearrangements. Here we describe and molecularly profile the peculiar case of a patient with a CLL-like monoclonal B-cell lymphocytosis (MBL), who sequentially developed a DLBCL, which occurred concomitantly to progression of MBL to CLL, and a subsequent HL. Based on standard IGHV clonality analysis, DLBCL was considered clonally unrelated to the concomitantly expanded CLL clone and treated as a de novo lymphoma, achieving a persistent response. Three years later, the patient further developed a clonally unrelated HL, refractory to bendamustine, which was successfully treated with brentuximab vedotin and radiotherapy, and later with pembrolizumab. We retrospectively performed additional molecular testing, by applying next-generation sequencing (NGS) of immunoglobulin repertoire (Ig-rep) techniques and a more sensitive allele-specific oligonucleotide-droplet digital PCR (ASO-ddPCR) strategy, in order to quantitatively investigate the presence of the rearranged IGHV genes in tumor specimens collected during the disease course. In this highly complex case, the application of modern and sensitive molecular technologies uncovered that DLBCL, initially considered as a de novo lymphoma, was instead the result of the transformation of a preexisting ancillary B-cell clone, which was already present at the time of first MBL diagnosis. A similar approach was also applied on the HL sample, showing its clonal unrelatedness to the previous MBL and DLBCL.
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Affiliation(s)
- Chiara Salvetti
- Division of Hematology, University of Torino, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy.,Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Candida Vitale
- Division of Hematology, University of Torino, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy.,Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Valentina Griggio
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Daniela Drandi
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Rebecca Jones
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Lisa Bonello
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy.,Molecular Pathology Unit, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy
| | - Riccardo Bomben
- Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico, IRCCS, Aviano, Italy
| | - Alberto Bragoni
- Pathology Unit, Department of Medical Sciences, University of Torino, Torino, Italy
| | - Davide Bagnara
- Department of Experimental Medicine, University of Genova, Genova, Italy
| | - Franco Fais
- Department of Experimental Medicine, University of Genova, Genova, Italy.,U.O. Molecular Pathology, I.R.C.C.S. Policlinico San Martino, Genova, Italy
| | - Valter Gattei
- Clinical and Experimental Onco-Hematology Unit, Centro di Riferimento Oncologico, IRCCS, Aviano, Italy
| | - Federica Cavallo
- Division of Hematology, University of Torino, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy.,Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Alberto Zamò
- Institute of Pathology, University of Würzburg, Würzburg, Germany
| | - Marta Coscia
- Division of Hematology, University of Torino, A.O.U. Città della Salute e della Scienza di Torino, Torino, Italy.,Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
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6
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Bagnara D, Colombo M, Reverberi D, Matis S, Massara R, Cardente N, Ubezio G, Agostini V, Agnelli L, Neri A, Cardillo M, Vergani S, Ghiotto F, Mazzarello AN, Morabito F, Cutrona G, Ferrarini M, Fais F. Characterizing Features of Human Circulating B Cells Carrying CLL-Like Stereotyped Immunoglobulin Rearrangements. Front Oncol 2022; 12:894419. [PMID: 35837088 PMCID: PMC9275393 DOI: 10.3389/fonc.2022.894419] [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: 03/11/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Chronic Lymphocytic Leukemia (CLL) is characterized by the accumulation of monoclonal CD5+ B cells with low surface immunoglobulins (IG). About 40% of CLL clones utilize quasi-identical B cell receptors, defined as stereotyped BCR. CLL-like stereotyped-IG rearrangements are present in normal B cells as a part of the public IG repertoire. In this study, we collected details on the representation and features of CLL-like stereotyped-IG in the IGH repertoire of B-cell subpopulations purified from the peripheral blood of nine healthy donors. The B-cell subpopulations were also fractioned according to the expression of surface CD5 molecules and IG light chain, IGκ and IGλ. IG rearrangements, obtained by high throughput sequencing, were scanned for the presence of CLL-like stereotyped-IG. CLL-like stereotyped-IG did not accumulate preferentially in the CD5+ B cells, nor in specific B-cell subpopulations or the CD5+ cell fraction thereof, and their distribution was not restricted to a single IG light chain type. CLL-like stereotyped-IG shared with the corresponding CLL stereotype rearrangements the IGHV mutational status. Instead, for other features such as IGHV genes and frequency, CLL stereotyped-IGs presented a CLL-like subset specific behavior which could, or could not, be consistent with CLL stereotyped-IGs. Therefore, as opposed to the immuno-phenotype, the features of the CLL stereotyped-IG repertoire suggest a CLL stereotyped subset-specific ontogeny. Overall, these findings suggest that the immune-genotype can provide essential details in tracking and defining the CLL cell of origin.
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Affiliation(s)
- Davide Bagnara
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
- *Correspondence: Davide Bagnara,
| | - Monica Colombo
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Daniele Reverberi
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Serena Matis
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Rosanna Massara
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Niccolò Cardente
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Gianluca Ubezio
- Transfusion Centre, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Vanessa Agostini
- Transfusion Centre, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Luca Agnelli
- Department of Pathology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Antonino Neri
- Scientific Directorate, Azienza Unità Sanitaria Locale (USL)-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Martina Cardillo
- Karches Center for Oncology Research, The Feinstein Institute for Medical Research, Manhasset, NY, United States
| | - Stefano Vergani
- Developmental Immunology Unit, Division of Molecular Hematology, Department of Laboratory Medicine, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Fabio Ghiotto
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - Fortunato Morabito
- Hematology and Bone Marrow Transplant Unit, Hemato-Oncology Department, Augusta Victoria Hospital, East Jerusalem, Israel
- Biothecnology Research Unit, AO of Cosenza, Cosenza, Italy
| | - Giovanna Cutrona
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Manlio Ferrarini
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Franco Fais
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
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7
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Zhu Y, Yang X, Ma C, Tang H, Wang Q, Guan J, Xie W, Chen S, Chen Y, Wang M, Lan C, Sun D, Wei L, Sun C, Yu X, Zhang Z. Antibody upstream sequence diversity and its biological implications revealed by repertoire sequencing. J Genet Genomics 2021; 48:936-945. [PMID: 34420911 DOI: 10.1016/j.jgg.2021.06.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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: 04/30/2021] [Revised: 06/10/2021] [Accepted: 06/16/2021] [Indexed: 12/26/2022]
Abstract
The sequence upstream of the antibody variable region (antibody upstream sequence [AUS]) consists of a 5' untranslated region (5' UTR) and a preceding leader region. The sequence variations in AUS affect antibody engineering and PCR based antibody quantification and may also be implicated in mRNA transcription and translation. However, the diversity of AUSs remains elusive. Using 5' rapid amplification of cDNA ends and high-throughput antibody repertoire sequencing technique, we acquired full-length AUSs for human, rhesus macaque, cynomolgus macaque, mouse, and rat. We designed a bioinformatics pipeline and identified 3307 unique AUSs, corresponding to 3026 and 1457 unique sequences for 5' UTR and leader region, respectively. Comparative analysis indicated that 928 (63.69%) leader sequences are novel relative to those recorded in the international ImMunoGeneTics information system. Evolutionarily, leader sequences are more conserved than 5' UTR and seem to coevolve with their downstream V genes. Besides, single-nucleotide polymorphisms are position dependent for leader regions and may contribute to the functional reversal of the downstream V genes. Finally, the AUGs in AUSs were found to have little impact on gene expression. Taken together, our findings can facilitate primer design for capturing antibodies efficiently and provide a valuable resource for antibody engineering and molecule-level antibody studies.
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Affiliation(s)
- Yan Zhu
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China
| | - Xiujia Yang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China
| | - Cuiyu Ma
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Haipei Tang
- Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Qilong Wang
- Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Junjie Guan
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Wenxi Xie
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Sen Chen
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Yuan Chen
- Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Minhui Wang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Nephrology, Hainan Affiliated Hospital of Hainan Medical College, Haikou 570311, China; Department of Nephrology, Hainan General Hospital, Haikou 570311, China
| | - Chunhong Lan
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Deqiang Sun
- Department of Center Laboratory, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510700, China
| | - Lai Wei
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, China
| | - Caijun Sun
- School of Public Health, Sun Yat-sen University, Shenzhen 510006, China
| | - Xueqing Yu
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Division of Nephrology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
| | - Zhenhai Zhang
- State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China; Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Center for Precision Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China; Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China.
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8
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Yu G, Wu Y, Duan Z, Tang C, Xing H, Scharff MD, MacCarthy T. A Bayesian model based computational analysis of the relationship between bisulfite accessible single-stranded DNA in chromatin and somatic hypermutation of immunoglobulin genes. PLoS Comput Biol 2021; 17:e1009323. [PMID: 34491985 DOI: 10.1371/journal.pcbi.1009323] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 09/24/2021] [Accepted: 08/04/2021] [Indexed: 11/19/2022] Open
Abstract
The B cells in our body generate protective antibodies by introducing somatic hypermutations (SHM) into the variable region of immunoglobulin genes (IgVs). The mutations are generated by activation induced deaminase (AID) that converts cytosine to uracil in single stranded DNA (ssDNA) generated during transcription. Attempts have been made to correlate SHM with ssDNA using bisulfite to chemically convert cytosines that are accessible in the intact chromatin of mutating B cells. These studies have been complicated by using different definitions of "bisulfite accessible regions" (BARs). Recently, deep-sequencing has provided much larger datasets of such regions but computational methods are needed to enable this analysis. Here we leveraged the deep-sequencing approach with unique molecular identifiers and developed a novel Hidden Markov Model based Bayesian Segmentation algorithm to characterize the ssDNA regions in the IGHV4-34 gene of the human Ramos B cell line. Combining hierarchical clustering and our new Bayesian model, we identified recurrent BARs in certain subregions of both top and bottom strands of this gene. Using this new system, the average size of BARs is about 15 bp. We also identified potential G-quadruplex DNA structures in this gene and found that the BARs co-locate with G-quadruplex structures in the opposite strand. Using various correlation analyses, there is not a direct site-to-site relationship between the bisulfite accessible ssDNA and all sites of SHM but most of the highly AID mutated sites are within 15 bp of a BAR. In summary, we developed a novel platform to study single stranded DNA in chromatin at a base pair resolution that reveals potential relationships among BARs, SHM and G-quadruplexes. This platform could be applied to genome wide studies in the future.
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9
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Duan Z, Baughn LB, Wang X, Zhang Y, Gupta V, MacCarthy T, Scharff MD, Yu G. Role of Dot1L and H3K79 methylation in regulating somatic hypermutation of immunoglobulin genes. Proc Natl Acad Sci U S A 2021; 118:e2104013118. [PMID: 34253616 DOI: 10.1073/pnas.2104013118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Somatic hypermutation (SHM) and class-switch recombination (CSR) of the immunoglobulin (Ig) genes allow B cells to make antibodies that protect us against a wide variety of pathogens. SHM is mediated by activation-induced deaminase (AID), occurs at a million times higher frequency than other mutations in the mammalian genome, and is largely restricted to the variable (V) and switch (S) regions of Ig genes. Using the Ramos human Burkitt's lymphoma cell line, we find that H3K79me2/3 and its methyltransferase Dot1L are more abundant on the V region than on the constant (C) region, which does not undergo mutation. In primary naïve mouse B cells examined ex vivo, the H3K79me2/3 modification appears constitutively in the donor Sμ and is inducible in the recipient Sγ1 upon CSR stimulation. Knockout and inhibition of Dot1L in Ramos cells significantly reduces V region mutation and the abundance of H3K79me2/3 on the V region and is associated with a decrease of polymerase II (Pol II) and its S2 phosphorylated form at the IgH locus. Knockout of Dot1L also decreases the abundance of BRD4 and CDK9 (a subunit of the P-TEFb complex) on the V region, and this is accompanied by decreased nascent transcripts throughout the IgH gene. Treatment with JQ1 (inhibitor of BRD4) or DRB (inhibitor of CDK9) decreases SHM and the abundance of Pol II S2P at the IgH locus. Since all these factors play a role in transcription elongation, our studies reinforce the idea that the chromatin context and dynamics of transcription are critical for SHM.
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10
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Crickx E, Chappert P, Sokal A, Weller S, Azzaoui I, Vandenberghe A, Bonnard G, Rossi G, Fadeev T, Storck S, Fadlallah J, Meignin V, Rivière E, Audia S, Godeau B, Michel M, Weill JC, Reynaud CA, Mahévas M. Rituximab-resistant splenic memory B cells and newly engaged naive B cells fuel relapses in patients with immune thrombocytopenia. Sci Transl Med 2021; 13:13/589/eabc3961. [PMID: 33853929 DOI: 10.1126/scitranslmed.abc3961] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 10/29/2020] [Accepted: 03/22/2021] [Indexed: 01/19/2023]
Abstract
Rituximab (RTX), an antibody targeting CD20, is widely used as a first-line therapeutic strategy in B cell-mediated autoimmune diseases. However, a large proportion of patients either do not respond to the treatment or relapse during B cell reconstitution. Here, we characterize the cellular basis responsible for disease relapse in secondary lymphoid organs in humans, taking advantage of the opportunity offered by therapeutic splenectomy in patients with relapsing immune thrombocytopenia. By analyzing the B and plasma cell immunoglobulin gene repertoire at bulk and antigen-specific single-cell level, we demonstrate that relapses are associated with two responses coexisting in germinal centers and involving preexisting mutated memory B cells that survived RTX treatment and naive B cells generated upon reconstitution of the B cell compartment. To identify distinctive characteristics of the memory B cells that escaped RTX-mediated depletion, we analyzed RTX refractory patients who did not respond to treatment at the time of B cell depletion. We identified, by single-cell RNA sequencing (scRNA-seq) analysis, a population of quiescent splenic memory B cells that present a unique, yet reversible, RTX-shaped phenotype characterized by down-modulation of B cell-specific factors and expression of prosurvival genes. Our results clearly demonstrate that these RTX-resistant autoreactive memory B cells reactivate as RTX is cleared and give rise to plasma cells and further germinal center reactions. Their continued surface expression of CD19 makes them efficient targets for current anti-CD19 therapies. This study thus identifies a pathogenic contributor to autoimmune diseases that can be targeted by available therapeutic agents.
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Affiliation(s)
- Etienne Crickx
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France.,Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France
| | - Pascal Chappert
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France.,Inovarion, 75005 Paris, France
| | - Aurélien Sokal
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Sandra Weller
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Imane Azzaoui
- Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France.,INSERM U955, Université Paris Est Créteil (UPEC), 94000 Créteil, France
| | - Alexis Vandenberghe
- Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France.,INSERM U955, Université Paris Est Créteil (UPEC), 94000 Créteil, France
| | - Guillaume Bonnard
- INSERM U955, Université Paris Est Créteil (UPEC), 94000 Créteil, France
| | - Geoffrey Rossi
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Tatiana Fadeev
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Sébastien Storck
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Jehane Fadlallah
- Service d'immunologie clinique, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris, Université Paris Diderot, Sorbonne Paris Cité, 75010 Paris, France
| | - Véronique Meignin
- Service d'anatomopathologie, Hôpital Saint-Louis (AP-HP), 75010 Paris, France
| | - Etienne Rivière
- Service de médecine interne, Hôpital Haut-Lévêque, 33604 Pessac, France
| | - Sylvain Audia
- Service de médecine interne, Hôpital du Bocage, 21000 Dijon, France
| | - Bertrand Godeau
- Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France
| | - Marc Michel
- Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France
| | - Jean-Claude Weill
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Claude-Agnès Reynaud
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France
| | - Matthieu Mahévas
- Institut Necker-Enfants Malades, INSERM U1151/CNRS UMS8253, Université Paris Descartes, Sorbonne Paris Cité, 75993 Paris Cedex 14, France. .,Service de Médecine Interne, Centre national de référence des cytopénies auto-immunes de l'adulte, Hôpital Henri Mondor, Assistance Publique Hôpitaux de Paris (AP-HP), Université Paris Est Créteil, 94000 Créteil, France.,INSERM U955, Université Paris Est Créteil (UPEC), 94000 Créteil, France
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11
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Bagnara D, Tang C, Brown JR, Kasar S, Fernandes S, Colombo M, Vergani S, Mazzarello AN, Ghiotto F, Bruno S, Morabito F, Rai KR, Kolitz JE, Barrientos JC, Allen SL, Fais F, Scharff MD, MacCarthy T, Chiorazzi N. Post-Transformation IGHV-IGHD-IGHJ Mutations in Chronic Lymphocytic Leukemia B Cells: Implications for Mutational Mechanisms and Impact on Clinical Course. Front Oncol 2021; 11:640731. [PMID: 34113563 PMCID: PMC8186829 DOI: 10.3389/fonc.2021.640731] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [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: 12/12/2020] [Accepted: 04/27/2021] [Indexed: 11/13/2022] Open
Abstract
Analyses of IGHV gene mutations in chronic lymphocytic leukemia (CLL) have had a major impact on the prognostication and treatment of this disease. A hallmark of IGHV-mutation status is that it very rarely changes clonally over time. Nevertheless, targeted and deep DNA sequencing of IGHV-IGHD-IGHJ regions has revealed intraclonal heterogeneity. We used a DNA sequencing approach that achieves considerable depth and minimizes artefacts and amplification bias to identify IGHV-IGHD-IGHJ subclones in patients with prolonged temporal follow-up. Our findings extend previous studies, revealing intraclonal IGHV-IGHD-IGHJ diversification in almost all CLL clones. Also, they indicate that some subclones with additional IGHV-IGHD-IGHJ mutations can become a large fraction of the leukemic burden, reaching numerical criteria for monoclonal B-cell lymphocytosis. Notably, the occurrence and complexity of post-transformation IGHV-IGHD-IGHJ heterogeneity and the expansion of diversified subclones are similar among U-CLL and M-CLL patients. The molecular characteristics of the mutations present in the parental, clinically dominant CLL clone (CDC) differed from those developing post-transformation (post-CDC). Post-CDC mutations exhibit significantly lower fractions of mutations bearing signatures of activation induced deaminase (AID) and of error-prone repair by Polη, and most of the mutations were not ascribable to those enzymes. Additionally, post-CDC mutations displayed a lower percentage of nucleotide transitions compared with transversions that was also not like the action of AID. Finally, the post-CDC mutations led to significantly lower ratios of replacement to silent mutations in VH CDRs and higher ratios in VH FRs, distributions different from mutations found in normal B-cell subsets undergoing an AID-mediated process. Based on these findings, we propose that post-transformation mutations in CLL cells either reflect a dysfunctional standard somatic mutational process or point to the action of another mutational process not previously associated with IG V gene loci. If the former option is the case, post-CDC mutations could lead to a lesser dependence on antigen dependent BCR signaling and potentially a greater influence of off-target, non-IG genomic mutations. Alternatively, the latter activity could add a new stimulatory survival/growth advantage mediated by the BCR through structurally altered FRs, such as that occurring by superantigen binding and stimulation.
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Affiliation(s)
- Davide Bagnara
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Catherine Tang
- Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, NY, United States
| | - Jennifer R. Brown
- Chronic Lymphocytic Leukemia Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Siddha Kasar
- Chronic Lymphocytic Leukemia Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Stacey Fernandes
- Chronic Lymphocytic Leukemia Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
| | - Monica Colombo
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Stefano Vergani
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
| | - Andrea N. Mazzarello
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
| | - Fabio Ghiotto
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Silvia Bruno
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Fortunato Morabito
- Biotechnology Research Unit, Azienda Ospedaliera of Cosenza, Cosenza, Italy
- Hematology and Bone Marrow Transplant Unit, Hemato-Oncology Department, Augusta Victoria Hospital, East Jerusalem, Israel
| | - Kanti R. Rai
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Jonathan E. Kolitz
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Jacqueline C. Barrientos
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Steven L. Allen
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Franco Fais
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
- Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Matthew D. Scharff
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Thomas MacCarthy
- Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, NY, United States
| | - Nicholas Chiorazzi
- The Feinstein Institutes for Medical Research, Institute for Molecular Medicine, Northwell Health, Manhasset, NY, United States
- Department of Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
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12
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Yang X, Wang M, Wu J, Shi D, Zhang Y, Zeng H, Zhu Y, Lan C, Deng Y, Guo S, Xu L, Ma C, Zhang Y, Ou J, Liu CJ, Chen Y, Wang Q, Xie W, Guan J, Ding J, Wang Z, Chang C, Yang W, Zhang H, Chen J, Qin L, Zhou H, Bei JX, Wei L, Cao G, Yu X, Zhang Z. Large-scale analysis of 2,152 Ig-seq datasets reveals key features of B cell biology and the antibody repertoire. Cell Rep 2021; 35:109110. [PMID: 33979623 DOI: 10.1016/j.celrep.2021.109110] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 03/09/2021] [Accepted: 04/20/2021] [Indexed: 12/20/2022] Open
Abstract
Antibody repertoire sequencing enables researchers to acquire millions of B cell receptors and investigate these molecules at the single-nucleotide level. This power and resolution in studying humoral responses have led to its wide applications. However, most of these studies were conducted with a limited number of samples. Given the extraordinary diversity, assessment of these key features with a large sample set is demanded. Thus, we collect and systematically analyze 2,152 high-quality heavy-chain antibody repertoires. Our study reveals that 52 core variable genes universally contribute to more than 99% of each individual's repertoire; a distal interspersed preferences characterize V gene recombination; the number of public clones between two repertoires follows a linear model, and the positive selection dominates at RGYW motif in somatic hypermutations. Thus, this population-level analysis resolves some critical features of the antibody repertoire and may have significant value to the large cadre of scientists.
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13
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Krantsevich A, Tang C, MacCarthy T. Correlations in Somatic Hypermutation Between Sites in IGHV Genes Can Be Explained by Interactions Between AID and/or Polη Hotspots. Front Immunol 2021; 11:618409. [PMID: 33603748 PMCID: PMC7884765 DOI: 10.3389/fimmu.2020.618409] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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: 10/16/2020] [Accepted: 12/18/2020] [Indexed: 12/27/2022] Open
Abstract
The somatic hypermutation (SHM) of Immunoglobulin (Ig) genes is a key process during antibody affinity maturation in B cells. The mutagenic enzyme activation induced deaminase (AID) is required for SHM and has a preference for WRC hotspots in DNA. Error-prone repair mechanisms acting downstream of AID introduce further mutations, including DNA polymerase eta (Polη), part of the non-canonical mismatch repair pathway (ncMMR), which preferentially generates mutations at WA hotspots. Previously proposed mechanistic models lead to a variety of predictions concerning interactions between hotspots, for example, how mutations in one hotspot will affect another hotspot. Using a large, high-quality, Ig repertoire sequencing dataset, we evaluated pairwise correlations between mutations site-by-site using an unbiased measure similar to mutual information which we termed “mutational association” (MA). Interactions are dominated by relatively strong correlations between nearby sites (short-range MAs), which can be almost entirely explained by interactions between overlapping hotspots for AID and/or Polη. We also found relatively weak dependencies between almost all sites throughout each gene (longer-range MAs), although these arise mostly as a statistical consequence of high pairwise mutation frequencies. The dominant short-range interactions are also highest within the most highly mutating IGHV sub-regions, such as the complementarity determining regions (CDRs), where there is a high hotspot density. Our results suggest that the hotspot preferences for AID and Polη have themselves evolved to allow for greater interactions between AID and/or Polη induced mutations.
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Affiliation(s)
- Artem Krantsevich
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Catherine Tang
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Thomas MacCarthy
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, United States
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14
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Mikocziova I, Gidoni M, Lindeman I, Peres A, Snir O, Yaari G, Sollid LM. Polymorphisms in human immunoglobulin heavy chain variable genes and their upstream regions. Nucleic Acids Res 2020; 48:5499-5510. [PMID: 32365177 PMCID: PMC7261178 DOI: 10.1093/nar/gkaa310] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [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: 04/09/2020] [Accepted: 04/20/2020] [Indexed: 01/13/2023] Open
Abstract
Germline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 potential novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-REGION in the 5′UTR, L-PART1 and L-PART2 sequences, and found that identical V-REGION alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-REGION but also in the upstream sequences of IGHV genes. Our findings provide a new perspective for annotating immunoglobulin repertoire sequencing data.
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Affiliation(s)
- Ivana Mikocziova
- K.G.Jebsen Centre for Coeliac Disease Research and Department of Immunology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Moriah Gidoni
- Faculty of Engineering, Bar Ilan University, Ramat Gan 5290002, Israel
| | - Ida Lindeman
- K.G.Jebsen Centre for Coeliac Disease Research and Department of Immunology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Ayelet Peres
- Faculty of Engineering, Bar Ilan University, Ramat Gan 5290002, Israel
| | - Omri Snir
- K.G.Jebsen Centre for Coeliac Disease Research and Department of Immunology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
| | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, Ramat Gan 5290002, Israel
| | - Ludvig M Sollid
- K.G.Jebsen Centre for Coeliac Disease Research and Department of Immunology, University of Oslo and Oslo University Hospital, 0372 Oslo, Norway
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15
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Prechl J. Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model. Antibodies (Basel) 2020; 9:antib9020013. [PMID: 32384800 PMCID: PMC7345901 DOI: 10.3390/antib9020013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [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: 03/16/2020] [Revised: 04/09/2020] [Accepted: 04/15/2020] [Indexed: 02/06/2023] Open
Abstract
Adaptive immunity in vertebrates is a complex self-organizing network of molecular interactions. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper, a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RAdial ADjustment of System Resolution (RADARS), is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction corresponding to particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power law distribution of antibody-free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees, and B1 cells function as nodes with minimal degree. Overall, the RADARS model implies that a finite number of antibody structures can interact with an infinite number of antigens by immunologically controlled adjustment of interaction energy distribution. Understanding quantitative network properties of the system should help the organization of sequence-derived predicted structural data.
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Affiliation(s)
- József Prechl
- Diagnosticum Zrt., 126. Attila u., 1047 Budapest, Hungary
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16
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Tang C, Bagnara D, Chiorazzi N, Scharff MD, MacCarthy T. AID Overlapping and Polη Hotspots Are Key Features of Evolutionary Variation Within the Human Antibody Heavy Chain (IGHV) Genes. Front Immunol 2020; 11:788. [PMID: 32425948 PMCID: PMC7204545 DOI: 10.3389/fimmu.2020.00788] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [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: 11/29/2019] [Accepted: 04/07/2020] [Indexed: 01/09/2023] Open
Abstract
Somatic hypermutation (SHM) of the immunoglobulin variable (IgV) loci is a key process in antibody affinity maturation. The enzyme activation-induced deaminase (AID), initiates SHM by creating C → U mismatches on single-stranded DNA (ssDNA). AID has preferential hotspot motif targets in the context of WRC/GYW (W = A/T, R = A/G, Y = C/T) and particularly at WGCW overlapping hotspots where hotspots appear opposite each other on both strands. Subsequent recruitment of the low-fidelity DNA repair enzyme, Polymerase eta (Polη), during mismatch repair, creates additional mutations at WA/TW sites. Although there are more than 50 functional immunoglobulin heavy chain variable (IGHV) segments in humans, the fundamental differences between these genes and their ability to respond to all possible foreign antigens is still poorly understood. To better understand this, we generated profiles of WGCW hotspots in each of the human IGHV genes and found the expected high frequency in complementarity determining regions (CDRs) that encode the antigen binding sites but also an unexpectedly high frequency of WGCW in certain framework (FW) sub-regions. Principal Components Analysis (PCA) of these overlapping AID hotspot profiles revealed that one major difference between IGHV families is the presence or absence of WGCW in a sub-region of FW3 sometimes referred to as “CDR4.” Further differences between members of each family (e.g., IGHV1) are primarily determined by their WGCW densities in CDR1. We previously suggested that the co-localization of AID overlapping and Polη hotspots was associated with high mutability of certain IGHV sub-regions, such as the CDRs. To evaluate the importance of this feature, we extended the WGCW profiles, combining them with local densities of Polη (WA) hotspots, thus describing the co-localization of both types of hotspots across all IGHV genes. We also verified that co-localization is associated with higher mutability. PCA of the co-localization profiles showed CDR1 and CDR2 as being the main contributors to variance among IGHV genes, consistent with the importance of these sub-regions in antigen binding. Our results suggest that AID overlapping (WGCW) hotspots alone or in conjunction with Polη (WA/TW) hotspots are key features of evolutionary variation between IGHV genes.
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Affiliation(s)
- Catherine Tang
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Davide Bagnara
- Karches Center for Oncology Research, The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States.,Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Nicholas Chiorazzi
- Karches Center for Oncology Research, The Feinstein Institute for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Matthew D Scharff
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Thomas MacCarthy
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
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17
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Meacham PJ, Williams AM, Strawderman M, Baran AM, Archibald WJ, Wallace DS, Tschernia NP, Burack WR, Barr PM, Zent CS. Additional B-cell malignancies in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). Leuk Lymphoma 2020; 61:1636-1644. [PMID: 32175786 DOI: 10.1080/10428194.2020.1737690] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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: 12/20/2022]
Abstract
Family and migration studies suggest a genetic risk of developing chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL). We hypothesized that CLL patients have an increased risk of additional clonally unrelated B-cell malignancies. To test this, we studied 467 CLL patients (2743 person-years (PYs)) at a single institution over 17 years. The incidence rate (IR) of any additional B-cell lymphoid malignancy was 10.9 per 1000 PYs (n = 30, 6.4%). Eighteen (4%) patients had a clonally unrelated B-cell malignancy (IR = 6.6 per 1000 PYs). Standardized incidence ratios (SIRs) were used to compare the incidence of additional clonally unrelated B-cell malignancies in CLL patients to the age- and sex-matched expected rates in the USA generated from the Surveillance, Epidemiology, and End Results (SEER) database. For the subset of 13 patients having data for comparison in the SEER database, the SIR was 5.41 (95% CI = 2.9, 9.3) which is supportive of our hypothesis.
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Affiliation(s)
| | | | | | | | | | | | | | - Walter Richard Burack
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, USA
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18
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Colombo M, Bagnara D, Reverberi D, Matis S, Cardillo M, Massara R, Mastracci L, Ravetti JL, Agnelli L, Neri A, Mazzocco M, Squillario M, Mazzarello AN, Cutrona G, Agathangelidis A, Stamatopoulos K, Ferrarini M, Fais F. Tracing CLL-biased stereotyped immunoglobulin gene rearrangements in normal B cell subsets using a high-throughput immunogenetic approach. Mol Med 2020; 26:25. [PMID: 32156260 PMCID: PMC7063734 DOI: 10.1186/s10020-020-00151-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [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: 07/01/2019] [Accepted: 02/21/2020] [Indexed: 01/10/2023] Open
Abstract
Background B cell receptor Immunoglobulin (BcR IG) repertoire of Chronic Lymphocytic Leukemia (CLL) is characterized by the expression of quasi-identical BcR IG. These are observed in approximately 30% of patients, defined as stereotyped receptors and subdivided into subsets based on specific VH CDR3 aa motifs and phylogenetically related IGHV genes. Although relevant to CLL ontogeny, the distribution of CLL-biased stereotyped immunoglobulin rearrangements (CBS-IG) in normal B cells has not been so far specifically addressed using modern sequencing technologies. Here, we have investigated the presence of CBS-IG in splenic B cell subpopulations (s-BCS) and in CD5+ and CD5− B cells from the spleen and peripheral blood (PB). Methods Fractionation of splenic B cells into 9 different B cell subsets and that of spleen and PB into CD5+ and CD5− cells were carried out by FACS sorting. cDNA sequences of BcR IG gene rearrangements were obtained by NGS. Identification of amino acidic motifs typical of CLL stereotyped subsets was carried out on IGHV1-carrying gene sequences and statistical evaluation has been subsequently performed to assess stereotypes distribution. Results CBS-IG represented the 0.26% average of IGHV1 genes expressing sequences, were detected in all of the BCS investigated. CBS-IG were more abundant in splenic and circulating CD5+ B (0.57%) cells compared to CD5− B cells (0.17%). In all instances, most CBS IG did not exhibit somatic hypermutation similar to CLL stereotyped receptors. However, compared to CLL, they exhibited a different CLL subset distribution and a broader utilization of the genes of the IGHV1 family. Conclusions CBS-IG receptors appear to represent a part of the “public” BcR repertoire in normal B cells. This repertoire is observed in all BCS excluding the hypothesis that CLL stereotyped BcR accumulate in a specific B cell subset, potentially capable of originating a leukemic clone. The different relative representation of CBS-IG in normal B cell subgroups suggests the requirement for additional selective processes before a full transformation into CLL is achieved.
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Affiliation(s)
- Monica Colombo
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
| | - Davide Bagnara
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Daniele Reverberi
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Serena Matis
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Martina Cardillo
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Rosanna Massara
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Luca Mastracci
- U.O. Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Surgical Sciences and Integrated Diagnostics, University of Genoa, Genoa, Italy
| | | | - Luca Agnelli
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Antonino Neri
- Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy
| | - Michela Mazzocco
- U.O. Laboratorio di Istocompatibilità, E.O. Ospedali Galliera, Genoa, Italy
| | - Margherita Squillario
- Department of Informatic Bioengeneering, Robotic and System Engeneering, University of Genoa, Genoa, Italy
| | | | - Giovanna Cutrona
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Andreas Agathangelidis
- Institute of Applied Biosciences, Center for Research and Technology Hellas CERTH, Thessaloniki, Greece
| | - Kostas Stamatopoulos
- Institute of Applied Biosciences, Center for Research and Technology Hellas CERTH, Thessaloniki, Greece
| | - Manlio Ferrarini
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | - Franco Fais
- U.O. Molecular Pathology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Experimental Medicine, University of Genoa, Genoa, Italy
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19
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Pascual M, Mena-Varas M, Robles EF, Garcia-Barchino MJ, Panizo C, Hervas-Stubbs S, Alignani D, Sagardoy A, Martinez-Ferrandis JI, Bunting KL, Meier S, Sagaert X, Bagnara D, Guruceaga E, Blanco O, Celay J, Martínez-Baztan A, Casares N, Lasarte JJ, MacCarthy T, Melnick A, Martinez-Climent JA, Roa S. PD-1/PD-L1 immune checkpoint and p53 loss facilitate tumor progression in activated B-cell diffuse large B-cell lymphomas. Blood 2019; 133:2401-12. [PMID: 30975638 DOI: 10.1182/blood.2018889931] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 04/04/2019] [Indexed: 12/19/2022] Open
Abstract
Refractory or relapsed diffuse large B-cell lymphoma (DLBCL) often associates with the activated B-cell-like (ABC) subtype and genetic alterations that drive constitutive NF-κB activation and impair B-cell terminal differentiation. Here, we show that DNA damage response by p53 is a central mechanism suppressing the pathogenic cooperation of IKK2ca-enforced canonical NF-κB and impaired differentiation resulting from Blimp1 loss in ABC-DLBCL lymphomagenesis. We provide evidences that the interplay between these genetic alterations and the tumor microenvironment select for additional molecular addictions that promote lymphoma progression, including aberrant coexpression of FOXP1 and the B-cell mutagenic enzyme activation-induced deaminase, and immune evasion through major histocompatibility complex class II downregulation, PD-L1 upregulation, and T-cell exhaustion. Consistently, PD-1 blockade cooperated with anti-CD20-mediated B-cell cytotoxicity, promoting extended T-cell reactivation and antitumor specificity that improved long-term overall survival in mice. Our data support a pathogenic cooperation among NF-κB-driven prosurvival, genetic instability, and immune evasion mechanisms in DLBCL and provide preclinical proof of concept for including PD-1/PD-L1 blockade in combinatorial immunotherapy for ABC-DLBCL.
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20
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Vázquez Bernat N, Corcoran M, Hardt U, Kaduk M, Phad GE, Martin M, Karlsson Hedestam GB. High-Quality Library Preparation for NGS-Based Immunoglobulin Germline Gene Inference and Repertoire Expression Analysis. Front Immunol 2019; 10:660. [PMID: 31024532 PMCID: PMC6459949 DOI: 10.3389/fimmu.2019.00660] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [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] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 03/11/2019] [Indexed: 12/13/2022] Open
Abstract
Next generation sequencing (NGS) of immunoglobulin (Ig) repertoires (Rep-seq) enables examination of the adaptive immune system at an unprecedented level. Applications include studies of expressed repertoires, gene usage, somatic hypermutation levels, Ig lineage tracing and identification of genetic variation within the Ig loci through inference methods. All these applications require starting libraries that allow the generation of sequence data with low error rate and optimal representation of the expressed repertoire. Here, we provide detailed protocols for the production of libraries suitable for human Ig germline gene inference and Ig repertoire studies. Various parameters used in the process were tested in order to demonstrate factors that are critical to obtain high quality libraries. We demonstrate an improved 5'RACE technique that reduces the length constraints of Illumina MiSeq based Rep-seq analysis but allows for the acquisition of sequences upstream of Ig V genes, useful for primer design. We then describe a 5' multiplex method for library preparation, which yields full length V(D)J sequences suitable for genotype identification and novel gene inference. We provide comprehensive sets of primers targeting IGHV, IGKV, and IGLV genes. Using the optimized protocol, we produced IgM, IgG, IgK, and IgL libraries and analyzed them using the germline inference tool IgDiscover to identify expressed germline V alleles. This process additionally uncovered three IGHV, one IGKV, and six IGLV novel alleles in a single individual, which are absent from the IMGT reference database, highlighting the need for further study of Ig genetic variation. The library generation protocols presented here enable a robust means of analyzing expressed Ig repertoires, identifying novel alleles and producing individualized germline gene databases from humans.
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Affiliation(s)
- Néstor Vázquez Bernat
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Martin Corcoran
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Uta Hardt
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
- Division of Rheumatology, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Mateusz Kaduk
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Ganesh E. Phad
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Marcel Martin
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
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21
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Ohlin M, Scheepers C, Corcoran M, Lees WD, Busse CE, Bagnara D, Thörnqvist L, Bürckert JP, Jackson KJL, Ralph D, Schramm CA, Marthandan N, Breden F, Scott J, Matsen IV FA, Greiff V, Yaari G, Kleinstein SH, Christley S, Sherkow JS, Kossida S, Lefranc MP, van Zelm MC, Watson CT, Collins AM. Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming. Front Immunol 2019; 10:435. [PMID: 30936866 PMCID: PMC6431624 DOI: 10.3389/fimmu.2019.00435] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [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] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 02/19/2019] [Indexed: 11/13/2022] Open
Abstract
Immunoglobulins or antibodies are the main effector molecules of the B-cell lineage and are encoded by hundreds of variable (V), diversity (D), and joining (J) germline genes, which recombine to generate enormous IG diversity. Recently, high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) of recombined V-(D)-J genes has offered unprecedented insights into the dynamics of IG repertoires in health and disease. Faithful biological interpretation of AIRR-seq studies depends upon the annotation of raw AIRR-seq data, using reference germline gene databases to identify the germline genes within each rearrangement. Existing reference databases are incomplete, as shown by recent AIRR-seq studies that have inferred the existence of many previously unreported polymorphisms. Completing the documentation of genetic variation in germline gene databases is therefore of crucial importance. Lymphocyte receptor genes and alleles are currently assigned by the Immunoglobulins, T cell Receptors and Major Histocompatibility Nomenclature Subcommittee of the International Union of Immunological Societies (IUIS) and managed in IMGT®, the international ImMunoGeneTics information system® (IMGT). In 2017, the IMGT Group reached agreement with a group of AIRR-seq researchers on the principles of a streamlined process for identifying and naming inferred allelic sequences, for their incorporation into IMGT®. These researchers represented the AIRR Community, a network of over 300 researchers whose objective is to promote all aspects of immunoglobulin and T-cell receptor repertoire studies, including the standardization of experimental and computational aspects of AIRR-seq data generation and analysis. The Inferred Allele Review Committee (IARC) was established by the AIRR Community to devise policies, criteria, and procedures to perform this function. Formalized evaluations of novel inferred sequences have now begun and submissions are invited via a new dedicated portal (https://ogrdb.airr-community.org). Here, we summarize recommendations developed by the IARC-focusing, to begin with, on human IGHV genes-with the goal of facilitating the acceptance of inferred allelic variants of germline IGHV genes. We believe that this initiative will improve the quality of AIRR-seq studies by facilitating the description of human IG germline gene variation, and that in time, it will expand to the documentation of TR and IG genes in many vertebrate species.
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Affiliation(s)
- Mats Ohlin
- Department of Immunotechnology, Lund University, Lund, Sweden
| | - Cathrine Scheepers
- Center for HIV and STIs, National Institute for Communicable Diseases, Johannesburg, South Africa
- Faculty of Health Sciences, School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Martin Corcoran
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - William D. Lees
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, United Kingdom
| | - Christian E. Busse
- Division of B Cell Immunology, German Cancer Research Center, Heidelberg, Germany
| | - Davide Bagnara
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
| | | | | | | | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Chaim A. Schramm
- Vaccine Research Center, National Institutes of Health, Washington, DC, United States
| | - Nishanth Marthandan
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
| | - Felix Breden
- Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Jamie Scott
- Department of Molecular Biology and Biochemistry, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | - Victor Greiff
- Department of Immunology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
| | | | - Scott Christley
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Jacob S. Sherkow
- Innovation Center for Law and Technology, New York Law School, New York, NY, United States
| | - Sofia Kossida
- IMGT, The International ImMunoGenetics information system (IMGT), Laboratoire d'ImmunoGénétique Moléculaire (LIGM), CNRS, Institut de Génétique Humaine, Université de Montpellier, Montpellier, France
| | - Marie-Paule Lefranc
- IMGT, The International ImMunoGenetics information system (IMGT), Laboratoire d'ImmunoGénétique Moléculaire (LIGM), CNRS, Institut de Génétique Humaine, Université de Montpellier, Montpellier, France
| | - Menno C. van Zelm
- Department of Immunology and Pathology, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, VIC, Australia
| | - Corey T. Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville, Louisville, KY, United States
| | - Andrew M. Collins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
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22
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Abstract
BACKGROUND Single-cell genomics is an approach to investigate cell heterogeneity and to identify new molecular features correlated with clinical outcomes. This approach allows identification of the complexity of cell diversity in a sample without the loss of information that occurs when multicellular or bulk tissue samples are analyzed. CONTENT The first single-cell RNA-sequencing study was published in 2009, and since then many more studies and single-cell sequencing methods have been published. These studies have had a major impact on several fields, including microbiology, neurobiology, cancer, and developmental biology. Recently, improvements in reliability and the development of commercial single-cell isolation platforms are opening the potential of this technology to the clinical laboratory. SUMMARY In this review we provide an overview of the current state of single-cell genomics. We describe opportunities in clinical research and medical applications.
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Affiliation(s)
- Carmela Paolillo
- Division of Precision and Computational Diagnostics, Department of Clinical Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Eric Londin
- Computational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA
| | - Paolo Fortina
- Department of Cancer Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA; .,Department of Molecular Medicine, Sapienza University, Rome, Italy
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23
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Kovaltsuk A, Leem J, Kelm S, Snowden J, Deane CM, Krawczyk K. Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires. J Immunol 2018; 201:2502-2509. [PMID: 30217829 DOI: 10.4049/jimmunol.1800708] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 08/19/2018] [Indexed: 11/19/2022]
Abstract
Abs are immune system proteins that recognize noxious molecules for elimination. Their sequence diversity and binding versatility have made Abs the primary class of biopharmaceuticals. Recently, it has become possible to query their immense natural diversity using next-generation sequencing of Ig gene repertoires (Ig-seq). However, Ig-seq outputs are currently fragmented across repositories and tend to be presented as raw nucleotide reads, which means nontrivial effort is required to reuse the data for analysis. To address this issue, we have collected Ig-seq outputs from 55 studies, covering more than half a billion Ab sequences across diverse immune states, organisms (primarily human and mouse), and individuals. We have sorted, cleaned, annotated, translated, and numbered these sequences and make the data available via our Observed Antibody Space (OAS) resource at http://antibodymap.org The data within OAS will be regularly updated with newly released Ig-seq datasets. We believe OAS will facilitate data mining of immune repertoires for improved understanding of the immune system and development of better biotherapeutics.
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Affiliation(s)
- Aleksandr Kovaltsuk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Jinwoo Leem
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | | | | | - Charlotte M Deane
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
| | - Konrad Krawczyk
- Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom; and
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24
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Rosenfeld AM, Meng W, Chen DY, Zhang B, Granot T, Farber DL, Hershberg U, Luning Prak ET. Computational Evaluation of B-Cell Clone Sizes in Bulk Populations. Front Immunol 2018; 9:1472. [PMID: 30008715 PMCID: PMC6034424 DOI: 10.3389/fimmu.2018.01472] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [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: 12/07/2017] [Accepted: 06/13/2018] [Indexed: 12/27/2022] Open
Abstract
B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size-copy numbers, instances, and unique sequences-and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data.
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Affiliation(s)
- Aaron M. Rosenfeld
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Wenzhao Meng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Dora Y. Chen
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Bochao Zhang
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Tomer Granot
- Columbia Center for Translational Immunology, Columbia University, New York, NY, United States
| | - Donna L. Farber
- Columbia Center for Translational Immunology, Columbia University, New York, NY, United States
| | - Uri Hershberg
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States
- Department of Microbiology and Immunology, Drexel College of Medicine, Drexel University, Philadelphia, PA, United States
| | - Eline T. Luning Prak
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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25
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Correa I, Ilieva KM, Crescioli S, Lombardi S, Figini M, Cheung A, Spicer JF, Tutt ANJ, Nestle FO, Karagiannis P, Lacy KE, Karagiannis SN. Evaluation of Antigen-Conjugated Fluorescent Beads to Identify Antigen-Specific B Cells. Front Immunol 2018; 9:493. [PMID: 29628923 PMCID: PMC5876289 DOI: 10.3389/fimmu.2018.00493] [Citation(s) in RCA: 12] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Accepted: 02/26/2018] [Indexed: 11/30/2022] Open
Abstract
Selection of single antigen-specific B cells to identify their expressed antibodies is of considerable interest for evaluating human immune responses. Here, we present a method to identify single antibody-expressing cells using antigen-conjugated fluorescent beads. To establish this, we selected Folate Receptor alpha (FRα) as a model antigen and a mouse B cell line, expressing both the soluble and the membrane-bound forms of a human/mouse chimeric antibody (MOv18 IgG1) specific for FRα, as test antibody-expressing cells. Beads were conjugated to FRα using streptavidin/avidin-biotin bridges and used to select single cells expressing the membrane-bound form of anti-FRα. Bead-bound cells were single cell-sorted and processed for single cell RNA retrotranscription and PCR to isolate antibody heavy and light chain variable regions. Variable regions were then cloned and expressed as human IgG1/k antibodies. Like the original clone, engineered antibodies from single cells recognized native FRα. To evaluate whether antigen-coated beads could identify specific antibody-expressing cells in mixed immune cell populations, human peripheral blood mononuclear cells (PBMCs) were spiked with test antibody-expressing cells. Antigen-specific cells could comprise up to 75% of cells selected with antigen-conjugated beads when the frequency of the antigen-positive cells was 1:100 or higher. In PBMC pools, beads conjugated to recombinant antigens FRα and HER2 bound antigen-specific anti-FRα MOv18 and anti-HER2 Trastuzumab antibody-expressing cells, respectively. From melanoma patient-derived B cells selected with melanoma cell line-derived protein-coated fluorescent beads, we generated a monoclonal antibody that recognized melanoma antigen-coated beads. This approach may be further developed to facilitate analysis of B cells and their antibody profiles at the single cell level and to help unravel humoral immune repertoires.
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Affiliation(s)
- Isabel Correa
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom
| | - Kristina M Ilieva
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom.,Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King's College London, Guy's Cancer Centre, London, United Kingdom
| | - Silvia Crescioli
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom
| | - Sara Lombardi
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom
| | - Mariangela Figini
- Department of Applied Research and Technology Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Anthony Cheung
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King's College London, Guy's Cancer Centre, London, United Kingdom
| | - James F Spicer
- School of Cancer & Pharmaceutical Sciences, King's College London, Guy's Hospital, London, United Kingdom
| | - Andrew N J Tutt
- Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King's College London, Guy's Cancer Centre, London, United Kingdom.,Breast Cancer Now Toby Robins Research Centre, Institute of Cancer Research, London, United Kingdom
| | - Frank O Nestle
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom.,Immunology and Inflammation Therapeutic Research Area, Sanofi US, Cambridge, MA, United States
| | - Panagiotis Karagiannis
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom.,Department of Oncology, Haematology and Stem Cell Transplantation, University Hospital of Hamburg Eppendorf, Hamburg, Germany
| | - Katie E Lacy
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom
| | - Sophia N Karagiannis
- St. John's Institute of Dermatology, School of Basic & Medical Biosciences, King's College London, Guy's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Guy's and St. Thomas's Hospitals and King's College London, King's College London, London, United Kingdom.,Breast Cancer Now Research Unit, School of Cancer & Pharmaceutical Sciences, King's College London, Guy's Cancer Centre, London, United Kingdom
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