Publications by authors named "Nicola Bonzanni"

11 Publications

  • Page 1 of 1

Next-Generation Immunosequencing Reveals Pathological T-Cell Architecture in Autoimmune Hepatitis.

Hepatology 2020 Jul 21. Epub 2020 Jul 21.

Department of Internal Medicine IV, Oncology/Hematology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.

Background And Aims: Autoimmune hepatitis (AIH) is a chronic liver disease that regularly relapses when immunosuppression is tapered. It is thought to be driven by T-cells, whereas the etiologic impact of an apparently deregulated B lineage system, as evidenced by hypergammaglobulinemia and autoantibodies, remains elusive. We set out to investigate T and B cell repertoires supporting chronic inflammation in AIH.

Approach And Results: T and B cell receptor (TCR/BCR) and human leukocyte antigen (HLA) next-generation immunosequencing were used to record immune signatures from a cohort of 60 patients with AIH and disease controls. Blood and liver B lineage immune metrics were not indicative of a dominant directional antigen selection apart from a slight skewing of IGHV-J genes. More importantly, we found strong AIH-specific TRBV-J skewing not attributable to the HLA-DRB1 specificities of the cohort. This TCR repertoire bias was generated as a result of peripheral T cell (de)selection and persisted in disease remission. Using a clustering algorithm according to antigenic specificity, we identified liver TCR clusters that were shared between patients with AIH but were absent or deselected in patients with other liver pathologies.

Conclusions: Patients with AIH show profound and persisting T-cell architectural changes that may explain high relapse rates after tapering immunosuppression. Liver T-cell clusters shared between patients may mediate liver damage and warrant further study.
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http://dx.doi.org/10.1002/hep.31473DOI Listing
July 2020

Response of metastatic mouse invasive lobular carcinoma to mTOR inhibition is partly mediated by the adaptive immune system.

Oncoimmunology 2020 12;9(1):1724049. Epub 2020 Feb 12.

Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

Effective treatment of invasive lobular carcinoma (ILC) of the breast is hampered by late detection, invasive growth, distant metastasis, and poor response to chemotherapy. Phosphoinositide 3-kinase (PI3K) signaling, one of the major druggable oncogenic signaling networks, is frequently activated in ILC. We investigated treatment response and resistance to AZD8055, an inhibitor of mammalian target of rapamycin (mTOR), in the (KEP) mouse model of metastatic ILC. Inhibition of mTOR signaling blocked the growth of primary KEP tumors as well as the progression of metastatic disease. However, primary tumors and distant metastases eventually acquired resistance after long-term AZD8055 treatment, despite continued effective suppression of mTOR signaling in cancer cells. Interestingly, therapeutic responses were associated with increased expression of genes related to antigen presentation. Consistent with this observation, increased numbers of tumor-infiltrating major histocompatibility complex class II-positive (MHCII+) immune cells were observed in treatment-responsive KEP tumors. Acquisition of treatment resistance was associated with loss of MHCII+ cells and reduced expression of genes related to the adaptive immune system. The therapeutic efficacy of mTOR inhibition was reduced in mice lacking mature T and B lymphocytes, compared to immunocompetent mice. Furthermore, therapy responsiveness could be partially rescued by transplanting AZD8055-resistant KEP tumors into treatment-naïve immunocompetent hosts. Collectively, these data indicate that the PI3K signaling pathway is an attractive therapeutic target in invasive lobular carcinoma, and that part of the therapeutic effect of mTOR inhibition is mediated by the adaptive immune system.
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http://dx.doi.org/10.1080/2162402X.2020.1724049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028325PMC
February 2020

High-Throughput Immunogenetics Reveals a Lack of Physiological T Cell Clusters in Patients With Autoimmune Cytopenias.

Front Immunol 2019 21;10:1897. Epub 2019 Aug 21.

Department of Internal Medicine IV, Oncology and Hematology, Martin-Luther-University Halle-Wittenberg, Halle, Germany.

Autoimmune cytopenias (AIC) such as immune thrombocytopenia or autoimmune hemolytic anemia are claimed to be essentially driven by a dysregulated immune system. Using next-generation immunosequencing we profiled 59 T and B cell repertoires ( and ) of 25 newly diagnosed patients with primary or secondary (lymphoma-associated) AIC to test the hypothesis if these patients present a disease-specific immunological signature that could reveal pathophysiological clues and eventually be exploited as blood-based biomarker. Global and repertoire metrics as well as gene usage distribution showed uniform characteristics for all lymphoma patients (high clonality and preferential usage of specific - and genes), but no AIC-specific signature. Since T cell immune reactions toward antigens are unique and polyclonal, we clustered TCRβ clones based on target recognition using the GLIPH (grouping of lymphocyte interactions by paratope hotspots) algorithm. This analysis revealed a considerable lack of physiological T cell clusters in patients with primary AIC. Interestingly, this signature did not discriminate between the different subentities of AIC and was also found in an independent cohort of 23 patients with active autoimmune hepatitis. Taken together, our data suggests that the identified T cell cluster signature could represent a blood biomarker of autoimmune conditions in general and should be functionally validated in future studies.
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http://dx.doi.org/10.3389/fimmu.2019.01897DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713037PMC
October 2020

Deep sequencing of bone marrow microenvironments of patients with del(5q) myelodysplastic syndrome reveals imprints of antigenic selection as well as generation of novel T-cell clusters as a response pattern to lenalidomide.

Haematologica 2019 07 17;104(7):1355-1364. Epub 2019 Jan 17.

Department of Oncology and Hematology, BMT with Pneumology section, Hubertus Wald Tumorzentrum / UCCH, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

In myelodysplastic syndromes with a partial deletion of the long arm of chromosome 5, del(5q), lenalidomide is believed to reverse anergic T-cell immunity in the bone marrow resulting in suppression of the del(5q) clone. In this study we used next-generation sequencing of immunoglobulin heavy chain ( and T-cell receptor beta () rearrangements in bone marrow-residing and peripheral blood-circulating lymphocytes of patients with del(5q) myelodysplastic syndromes to assess the immune architecture and track adaptive immune responses during treatment with lenalidomide. The baseline bone marrow B-cell space in patients was comparable to that of age-matched healthy controls in terms of gene usage and clonality, but showed a higher percentage of hypermutated sequences, indicating an expanded number of antigen-experienced B lineage cells. Bone marrow B lineage clonality decreased significantly and hypermutated clones normalized upon lenalidomide treatment, well in line with the proliferative effect on healthy antigen-inexperienced B-cell precursors previously described for this drug. The T-cell space in bone marrow of patients with del(5q) myelodysplastic syndromes showed higher clonality compared to that of healthy controls. Upon lenalidomide treatment, myelodysplastic syndrome-specific T-cell clusters with low to medium spontaneous generation probabilities emerged; these clusters were shared across patients, indicating a common antigen-driven T-cell response pattern. Hence, we observed B lineage diversification and generation of new, antigen-dependent T-cell clusters, compatible with a model of adaptive immunity induced against the del(5q) clone by lenalidomide. Overall, this supports the concept that lenalidomide not only alters the functional T-cell state, but also the composition of the T- and B-cell repertoires in del(5q) myelodysplastic syndromes.
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http://dx.doi.org/10.3324/haematol.2018.208223DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601099PMC
July 2019

PTEN Loss in E-Cadherin-Deficient Mouse Mammary Epithelial Cells Rescues Apoptosis and Results in Development of Classical Invasive Lobular Carcinoma.

Cell Rep 2016 08 11;16(8):2087-2101. Epub 2016 Aug 11.

Division of Molecular Pathology, the Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Cancer Genomics Netherlands, 3584 CG Utrecht, the Netherlands. Electronic address:

Invasive lobular carcinoma (ILC) is an aggressive breast cancer subtype with poor response to chemotherapy. Besides loss of E-cadherin, a hallmark of ILC, genetic inactivation of PTEN is frequently observed in patients. Through concomitant Cre-mediated inactivation of E-cadherin and PTEN in mammary epithelium, we generated a mouse model of classical ILC (CLC), the main histological ILC subtype. While loss of E-cadherin induced cell dissemination and apoptosis, additional PTEN inactivation promoted cell survival and rapid formation of invasive mammary tumors that recapitulate the histological and molecular features, estrogen receptor (ER) status, growth kinetics, metastatic behavior, and tumor microenvironment of human CLC. Combined inactivation of E-cadherin and PTEN is sufficient to cause CLC development. These CLCs showed significant tumor regression upon BEZ235-mediated inhibition of PI3K signaling. In summary, this mouse model provides important insights into CLC development and suggests inhibition of phosphatidylinositol 3-kinase (PI3K) signaling as a potential therapeutic strategy for targeting CLC.
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http://dx.doi.org/10.1016/j.celrep.2016.07.059DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999419PMC
August 2016

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

Bioinformatics 2016 06;32(12):i60-i69

Centre for Integrative Bioinformatics (IBIVU) & Amsterdam Institute for Molecules Medicines and Systems (AIMMS), VU University Amsterdam, De Boelelaan 1081, Amsterdam, The Netherlands.

Motivation: Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model.

Results: To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language.

Availability And Implementation: The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl.
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http://dx.doi.org/10.1093/bioinformatics/btw250DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908334PMC
June 2016

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability.

Elife 2016 Feb 22;5:e11469. Epub 2016 Feb 22.

Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom.

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes.
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http://dx.doi.org/10.7554/eLife.11469DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4798972PMC
February 2016

ConBind: motif-aware cross-species alignment for the identification of functional transcription factor binding sites.

Nucleic Acids Res 2016 05 31;44(8):e72. Epub 2015 Dec 31.

Centre for Integrative Bioinformatics VU, VU University Amsterdam, Amsterdam 1081 HV, The Netherlands Computational Cancer Biology Group, Division of Molecular Carcinogenesis, The Netherlands Cancer Institute, Amsterdam 1066 CX, The Netherlands ENPICOM, Eindhoven 5632 CW, The Netherlands

Eukaryotic gene expression is regulated by transcription factors (TFs) binding to promoter as well as distal enhancers. TFs recognize short, but specific binding sites (TFBSs) that are located within the promoter and enhancer regions. Functionally relevant TFBSs are often highly conserved during evolution leaving a strong phylogenetic signal. While multiple sequence alignment (MSA) is a potent tool to detect the phylogenetic signal, the current MSA implementations are optimized to align the maximum number of identical nucleotides. This approach might result in the omission of conserved motifs that contain interchangeable nucleotides such as the ETS motif (IUPAC code: GGAW). Here, we introduce ConBind, a novel method to enhance alignment of short motifs, even if their mutual sequence similarity is only partial. ConBind improves the identification of conserved TFBSs by improving the alignment accuracy of TFBS families within orthologous DNA sequences. Functional validation of the Gfi1b + 13 enhancer reveals that ConBind identifies additional functionally important ETS binding sites that were missed by all other tested alignment tools. In addition to the analysis of known regulatory regions, our web tool is useful for the analysis of TFBSs on so far unknown DNA regions identified through ChIP-sequencing.
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http://dx.doi.org/10.1093/nar/gkv1518DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4856970PMC
May 2016

Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.

Bioinformatics 2013 Jul;29(13):i80-8

IBIVU Centre for Integrative Bioinformatics, VU University Amsterdam, AIMMS Amsterdam Institute for Molecules Medicines and Systems, VU University Amsterdam, De Boelelaan 1081, NKI-AVL The Netherlands.

Motivation: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes.

Results: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btt243DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694641PMC
July 2013

The role of proteosome-mediated proteolysis in modulating potentially harmful transcription factor activity in Saccharomyces cerevisiae.

Bioinformatics 2011 Jul;27(13):i283-7

Centre for Integrative Bioinformatics VU, VU University Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands.

Motivation: The appropriate modulation of the stress response to variable environmental conditions is necessary to maintain sustained viability in Saccharomyces cerevisiae. Particularly, controlling the abundance of proteins that may have detrimental effects on cell growth is crucial for rapid recovery from stress-induced quiescence.

Results: Prompted by qualitative modeling of the nutrient starvation response in yeast, we investigated in vivo the effect of proteolysis after nutrient starvation showing that, for the Gis1 transcription factor at least, proteasome-mediated control is crucial for a rapid return to growth. Additional bioinformatics analyses show that potentially toxic transcriptional regulators have a significantly lower protein half-life, a higher fraction of unstructured regions and more potential PEST motifs than the non-detrimental ones. Furthermore, inhibiting proteasome activity tends to increase the expression of genes induced during the Environmental Stress Response more than those in the rest of the genome. Our combined results suggest that proteasome-mediated proteolysis of potentially toxic transcription factors tightly modulates the stress response in yeast.

Contact: jasmin.fisher@microsoft.com
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http://dx.doi.org/10.1093/bioinformatics/btr211DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3117362PMC
July 2011

Executing multicellular differentiation: quantitative predictive modelling of C.elegans vulval development.

Bioinformatics 2009 Aug 10;25(16):2049-56. Epub 2009 Jun 10.

Centre for Integrative Bioinformatics and Department of Computer Science, Vrije Universiteit, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands.

Motivation: Understanding the processes involved in multi-cellular pattern formation is a central problem of developmental biology, hopefully leading to many new insights, e.g. in the treatment of various diseases. Defining suitable computational techniques for development modelling, able to perform in silico simulation experiments, is an open and challenging problem.

Results: Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here, we apply our modelling approach to the well-studied process of Caenorhabditis elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilizing cell pattern formation.
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http://dx.doi.org/10.1093/bioinformatics/btp355DOI Listing
August 2009