The follicular lymphoma epigenome regulates its microenvironment

Follicular lymphoma (FL) is a B-cell non-Hodgkin lymphoma of germinal center (GC) origin with a distinctive tumor microenvironment (TME) and a unique spectrum of mutations. Despite the important therapeutic advances, FL is still incurable. During B-cell development, the GC reaction is a complex multistep process in which epigenetic regulators dynamically induce or suppress transcriptional programs. In FL, epigenetic gene mutations perturb the regulation of these programs, changing GC B-cell function and skewing differentiation towards tumor cells and altering the microenvironment interactions. FL pathogenesis and malignant transformation are promoted by epigenetic reprogramming of GC B cells that alters the immunological synapse and niche. Despite the extensive characterization of FL epigenetic signature and TME, the functional consequences of epigenetic dysregulation on TME and niche plasticity need to be better characterized. In this review, first we describe the most frequent epigenomic alterations in FL (KMT2D, CREBBP and EZH2) that affect the immunological niche, and their potential consequences on the informational transfer between tumor B cells and their microenvironment. Then, we discuss the latest progress to harness epigenetic targets for inhibiting the FL microenvironment. Finally, we highlight unexplored research areas and outstanding questions that should be considered for a successful long-term treatment of FL

Recent applications of quantitative systems pharmacology and machine learning models across diseases

Quantitative systems pharmacology (QSP) is a quantitative and mechanistic platform describing the phenotypic interaction between drugs, biological networks, and disease conditions to predict optimal therapeutic response. In this meta-analysis study, we review the utility of the QSP platform in drug development and therapeutic strategies based on recent publications (2019–2021). We gathered recent original QSP models and described the diversity of their applications based on therapeutic areas, methodologies, software platforms, and functionalities. The collection and investigation of these publications can assist in providing a repository of recent QSP studies to facilitate the discovery and further reusability of QSP models. Our review shows that the largest number of QSP efforts in recent years is in Immuno-Oncology. We also addressed the benefits of integrative approaches in this field by presenting the applications of Machine Learning methods for drug discovery and QSP models. Based on this meta-analysis, we discuss the advantages and limitations of QSP models and propose fields where the QSP approach constitutes a valuable interface for more investigations to tackle complex diseases and improve drug development

Stromal Cell Contribution to Human Follicular Lymphoma Pathogenesis

Follicular lymphoma (FL) is the prototypical model of indolent B cell lymphoma displaying a strong dependence on a specialized cell microenvironment mimicking normal germinal center. Within malignant cell niches in invaded lymph nodes and bone marrow, external stimuli provided by infiltrating stromal cells make a pivotal contribution to disease development, progression, and drug resistance. The crosstalk between FL B cells and stromal cells is bidirectional, causing activation of both partners. In agreement, FL stromal cells exhibit specific phenotypic, transcriptomic, and functional properties. This review highlights the critical pathways involved in the direct tumor-promoting activity of stromal cells but also their role in the organization of FL cell niche through the recruitment of accessory immune cells and their polarization to a B cell supportive phenotype. Finally, deciphering the interplay between stromal cells and FL cells provides potential new therapeutic targets with the aim to mobilize malignant cells outside their protective microenvironment and increase their sensitivity to conventional treatment

Making up meanings in a capital city: power, memory and monuments in Berlin

Much contemporary writing on cities focuses on their position within wider global networks, so there is a risk of underplaying the significance of other aspects of the urban experience.This paper explores the particular role of Berlin as capital city in the making of the (new) Berliner Republic and the ways in which it is defined (and defines itself) within that Republic. Berlin is the (and often literally the building) site on which a new Germany is being constructed. The making up of the new Berlin is dominated by attempts to reinterpret and reimagine its history: it is a city of memorials and of deliberate absences; of remembering and forgetting, or trying to forget; of reshaping the past as well as trying to build a new future. The juxtapositions of urban experience, the layering of memories and the attempt to imagine a different future come together to define Berlin as a contemporary capital city

Nuclear Heparanase Regulates Chromatin Remodeling, Gene Expression and PTEN Tumor Suppressor Function

Heparanase (HPSE) is an endoglycosidase that cleaves heparan sulfate and has been shown in various cancers to promote metastasis, angiogenesis, osteolysis, and chemoresistance. Although heparanase is thought to act predominantly extracellularly or within the cytoplasm, it is also present in the nucleus, where it may function in regulating gene transcription. Using myeloma cell lines, we report here that heparanase enhances chromatin accessibility and confirm a previous report that it also upregulates the acetylation of histones. Employing the Multiple Myeloma Research Foundation CoMMpass database, we demonstrate that patients expressing high levels of heparanase display elevated expression of proteins involved in chromatin remodeling and several oncogenic factors compared to patients expressing low levels of heparanase. These signatures were consistent with the known function of heparanase in driving tumor progression. Chromatin opening and downstream target genes were abrogated by inhibition of heparanase. Enhanced levels of heparanase in myeloma cells led to a dramatic increase in phosphorylation of PTEN, an event known to stabilize PTEN, leading to its inactivity and loss of tumor suppressor function. Collectively, this study demonstrates that heparanase promotes chromatin opening and transcriptional activity, some of which likely is through its impact on diminishing PTEN tumor suppressor activity

A multiscale mechanistic model of human dendritic cells for \u3ci\u3ein-silico\u3c/i\u3e investigation of immune responses and novel therapeutics discovery

Dendritic cells (DCs) are professional antigen-presenting cells (APCs) with the unique ability to mediate inflammatory responses of the immune system. Given the critical role of DCs in shaping immunity, they present an attractive avenue as a therapeutic target to program the immune system and reverse immune disease disorders. To ensure appropriate immune response, DCs utilize intricate and complex molecular and cellular interactions that converge into a seamless phenotype. Computational models open novel frontiers in research by integrating large-scale interaction to interrogate the influence of complex biological behavior across scales. The ability to model large biological networks will likely pave the way to understanding any complex system in more approachable ways. We developed a logical and predictive model of DC function that integrates the heterogeneity of DCs population, APC function, and cell-cell interaction, spanning molecular to population levels. Our logical model consists of 281 components that connect environmental stimuli with various layers of the cell compartments, including the plasma membrane, cytoplasm, and nucleus to represent the dynamic processes within and outside the DC, such as signaling pathways and cell-cell interactions. We also provided three sample use cases to apply the model in the context of studying cell dynamics and disease environments. First, we characterized the DC response to Sars-CoV-2 and influenza co-infection by in-silico experiments and analyzed the activity level of 107 molecules that play a role in this co-infection. The second example presents simulations to predict the crosstalk between DCs and T cells in a cancer microenvironment. Finally, for the third example, we used the Kyoto Encyclopedia of Genes and Genomes enrichment analysis against the model’s components to identify 45 diseases and 24 molecular pathways that the DC model can address. This study presents a resource to decode the complex dynamics underlying DC-derived APC communication and provides a platform for researchers to perform in-silico experiments on human DC for vaccine design, drug discovery, and immunotherapies

Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders

CD4+ T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immunerelated diseases. CD4+ T cells’ metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease. Here, we develop genome-scale models of naïve, Th1, Th2, and Th17 CD4+ T-cell subtypes to map metabolic perturbations in rheumatoid arthritis, multiple sclerosis, and primary biliary cholangitis. We subjected these models to in silico simulations for drug response analysis of existing FDA-approved drugs and compounds. Integration of disease-specific differentially expressed genes with altered reactions in response to metabolic perturbations identified 68 drug targets for the three autoimmune diseases. In vitro experimental validation, together with literature-based evidence, showed that modulation of fifty percent of identified drug targets suppressed CD4+ T cells, further increasing their potential impact as therapeutic interventions. Our approach can be generalized in the context of other diseases, and the metabolic models can be further used to dissect CD4+ T-cell metabolis

A myeloma translocation-like model associating CCND1 with the immunoglobulin heavy-chain locus 3' enhancers does not promote by itself B-cell malignancies.

International audienceCyclin D1 overexpression is associated with mantle cell lymphoma and multiple myeloma. In myeloma, it often results from chromosomal translocations linking the CCND1 gene to the 3' part of the IgH locus constant region. This region includes a single and potent transcriptional regulatory region (RR) 3' of the Calpha gene mostly active in mature B-cells. To check whether this RR alone was sufficient to deregulate CCND1, we generated mice carrying a 3'IgH RR-driven human CCND1 transgene and specifically up-regulating cyclin D1 expression in B-cells. In transgenic B-cells, cyclin D1 enforced cell cycle entry in response to various stimuli (LPS, anti-IgM, anti-CD40) but also increased cell death, so that exaggerated proliferation did not result in peripheral lymphocytosis. Despite exaggerated B-cell entry into G(1) phase, malignant lymphoproliferation did not occur either. Crossing of CCND1-3'IgH RR mice with c-myc-3'IgH RR mice did not reveal accelerated tumorigenesis as compared with c-myc-3'IgH RR mice alone. The data presented here demonstrate that the 3'IgH RR-mediated deregulation of CCND1 in mature B-cells cannot by itself trigger the development of lymphomas and strengthen the concept that cyclin D1 per se is not an armful proto-oncogene. Rather its overexpression in several malignancies might be only a stigma of lymphomagenesis or represent a single hit within a multiple hit process

Premature replacement of μ with α immunoglobulin chains impairs lymphopoiesis and mucosal homing but promotes plasma cell maturation

Sequentially along B cell differentiation, the different classes of membrane Ig heavy chains associate with the Igα/Igβ heterodimer within the B cell receptor (BCR). Whether each Ig class conveys specific signals adapted to the corresponding differentiation stage remains debated. We investigated the impact of the forced expression of an IgA-class receptor throughout murine B cell differentiation by knocking in the human Cα Ig gene in place of the Sμ region. Despite expression of a functional BCR, homozygous mutant mice showed a partial developmental blockade at the pro-B/pre-BI and large pre-BII cell stages, with decreased numbers of small pre-BII cells. Beyond this stage, peripheral B cell compartments of reduced size developed and allowed specific antibody responses, whereas mature cells showed constitutive activation and a strong commitment to plasma cell differentiation. Secreted IgA correctly assembled into polymers, associated with the murine J chain, and was transported into secretions. In heterozygous mutants, cells expressing the IgA allele competed poorly with those expressing IgM from the wild-type allele and were almost undetectable among peripheral B lymphocytes, notably in gut-associated lymphoid tissues. Our data indicate that the IgM BCR is more efficient in driving early B cell education and in mucosal site targeting, whereas the IgA BCR appears particularly suited to promoting activation and differentiation of effector plasma cells