Landscape of T Follicular Helper Cell Dynamics in Human Germinal Centers

Lymphomas in 3D and 4D spaces

The cellular compartments in the lymph node form dynamic networks, enabling coordinated innate and adaptive immunological responses. This compartmentalization of the lymph node into subcompartments, such as the T and B zones, has been proven to be beneficial. The study of lymph node microarchitecture has yielded new insights into a range of fields, including anatomy, pathology and biological processes. This review focuses on three-dimensional (3D) and four-dimensional (4D) investigations of human lymph nodes, with a particular emphasis on comparisons with data obtained from mice. It will discuss the findings of 3D/4D investigations of human lymph nodes. The investigation of the immune system in 3D space and time offers numerous advantages over the analysis of thin tissue sections. It provides data that is not visible in two-dimensional (2D) representations. A comparison of volumes, surfaces, cell speeds, cell contact numbers, contact duration times, morphologies and other variables can be made in the context of immune responses and lymphomas. The evaluation of data, the application of statistics and the use of machine learning have all been demonstrated to be valuable. In conditions of reactivity and neoplasia, T cells are the fastest-moving cells. In contrast, B cells show slower movement and higher turning angles in reactive lymphoid tissue and lymphomas. Even slower than B cells are reticulum cells, like follicular dendritic reticulum cells (FDC) of the B zones and macrophages. Fast T cells are especially found in Hodgkin lymphomas and mantle cell lymphomas. Contact times between T and B cells differ between different lymphoma types and may prove useful in defining lymphomas. 4D technologies, which evaluate living tissue slices, are suitable for use in testing checkpoint blockers (such as nivolumab) and other therapeutic drugs or cells. Following incubation with nivolumab, the duration of contacts between CD4-positive T cells and CD30-positive Hodgkin-Reed-Sternberg cells was documented. The preliminary data indicate that 3D and 4D experiments in hematopathology may facilitate new insights into diagnostics, biology, and clinical applications, including the development of new lymphoma classifications.

[3D/4D strategic lymph node diagnostics : The 4D representation of the human lymph node enables the observation and interpretation of the immune system in space and time]

BACKGROUND

Lymph-node diagnostics is performed using thin sections, with help of immunohistochemistry by light microscopy and supplemented by molecular pathology.

OBJECTIVES

Which are the scientific and diagnostic perspectives of 3D and 4D lymph node investigations, using laser, scanning, and computer technologies? What is the impact of machine learning in complex data analysis.

RESULTS

It was shown in different investigations that the analysis in space and time (3D/4D) of lymph node tissue is able to provide a lot of new information concerning biology and diagnostics and enable excellent evaluations applying machine learning.

CONCLUSION OR DISCUSSION

3D and 4D analysis of human lymphoid tissue gives new insights into immunologic mechanisms and malignant lymphomas.

Holistic View on the Structure of Immune Response: Petri Net Model

The simulation of immune response is a challenging task because quantitative data are scarce. Quantitative theoretical models either focus on specific cell-cell interactions or have to make assumptions about parameters. The broad variation of, e.g., the dimensions and abundance between lymph nodes as well as between individual patients hampers conclusive quantitative modeling. No theoretical model has been established representing a consensus on the set of major cellular processes involved in the immune response. In this paper, we apply the Petri net formalism to construct a semi-quantitative mathematical model of the lymph nodes. The model covers the major cellular processes of immune response and fulfills the formal requirements of Petri net models. The intention is to develop a model taking into account the viewpoints of experienced pathologists and computer scientists in the field of systems biology. In order to verify formal requirements, we discuss invariant properties and apply the asynchronous firing rule of a place/transition net. Twenty-five transition invariants cover the model, and each is assigned to a functional mode of the immune response. In simulations, the Petri net model describes the dynamic modes of the immune response, its adaption to antigens, and its loss of memory.

Imaging bridges pathology and radiology

In recent years, medical disciplines have moved closer together and rigid borders have been increasingly dissolved. The synergetic advantage of combining multiple disciplines is particularly important for radiology, nuclear medicine, and pathology to perform integrative diagnostics. In this review, we discuss how medical subdisciplines can be reintegrated in the future using state-of-the-art methods of digitization, data science, and machine learning. Integration of methods is made possible by the digitalization of radiological and nuclear medical images, as well as pathological images. 3D histology can become a valuable tool, not only for integration into radiological images but also for the visualization of cellular interactions, the so-called connectomes. In human pathology, it has recently become possible to image and calculate the movements and contacts of immunostained cells in fresh tissue explants. Recording the movement of a living cell is proving to be informative and makes it possible to study dynamic connectomes in the diagnosis of lymphoid tissue. By applying computational methods including data science and machine learning, new perspectives for analyzing and understanding diseases become possible.

New definitions of human lymphoid and follicular cell entities in lymphatic tissue by machine learning

Histological sections of the lymphatic system are usually the basis of static (2D) morphological investigations. Here, we performed a dynamic (4D) analysis of human reactive lymphoid tissue using confocal fluorescent laser microscopy in combination with machine learning. Based on tracks for T-cells (CD3), B-cells (CD20), follicular T-helper cells (PD1) and optical flow of follicular dendritic cells (CD35), we put forward the first quantitative analysis of movement-related and morphological parameters within human lymphoid tissue. We identified correlations of follicular dendritic cell movement and the behavior of lymphocytes in the microenvironment. In addition, we investigated the value of movement and/or morphological parameters for a precise definition of cell types (CD clusters). CD-clusters could be determined based on movement and/or morphology. Differentiating between CD3- and CD20 positive cells is most challenging and long term-movement characteristics are indispensable. We propose morphological and movement-related prototypes of cell entities applying machine learning models. Finally, we define beyond CD clusters new subgroups within lymphocyte entities based on long term movement characteristics. In conclusion, we showed that the combination of 4D imaging and machine learning is able to define characteristics of lymphocytes not visible in 2D histology.

L-type amino acid transporter 1 as a target for inflammatory disease and cancer immunotherapy

Ingestion of amino acids is fundamental for cellular activity. Amino acids are important components for protein synthesis but are also crucial for intracellular metabolic reactions and signal transduction. Following activation, immune cells induce metabolic reprogramming to generate adequate energy and constitutive substances. Hence, the delivery of amino acids by transporters is necessary for the progression of metabolic rewiring. In this review, we discuss how amino acids and their transporters regulate immune cell functions, with emphasis on LAT1, a transporter of large neutral amino acids. Furthermore, we explore the possibility of targeting amino acid transporters to improve immune disorders and cancer immune therapies.

Landscape of 4D Cell Interaction in Hodgkin and Non-Hodgkin Lymphomas

Simple Summary

Little is known about the motility and interaction of primary human lymphoma cells in lymph nodes. The aim of this study therefore was to analyze for the first time if there are differences in motility and interaction with bystander cells between different lymphoma types and normal lymph nodes. We observed systematic differences between B cells and PD1-positive T cells. Furthermore, most cases of Hodgkin lymphomas had fast moving PD1-positive T cells, whereas there was little movement in other lymphoma types. Some lymphomas, particularly Hodgkin lymphomas, presented enhanced cell contacts between neoplastic and reactive cells, suggesting a dependency of lymphoma growth on cellular interaction.

Abstract

Profound knowledge exists about the clinical, morphologic, genomic, and transcriptomic characteristics of most lymphoma entities. However, information is currently lacking on the dynamic behavior of malignant lymphomas. This pilot study aimed to gain insight into the motility of malignant lymphomas and bystander cells in 20 human lymph nodes. Generally, B cells were faster under reactive conditions compared with B cells in malignant lymphomas. In contrast, PD1-positive T cells did not show systematic differences in velocity between reactive and neoplastic conditions in general. However, lymphomas could be divided into two groups: one with fast PD1-positive T cells (e.g., Hodgkin lymphoma and mantle cell lymphoma; means 8.4 and 7.8 µm/min) and another with slower PD1-positive T cells (e.g., mediastinal grey zone lymphoma; mean 3.5 µm/min). Although the number of contacts between lymphoma cells and PD1-positive T cells was similar in different lymphoma types, important differences were observed in the duration of these contacts. Among the lymphomas with fast PD1-positive T cells, contacts were particularly short in mantle cell lymphoma (mean 54 s), whereas nodular lymphocyte-predominant Hodgkin lymphoma presented prolonged contact times (mean 6.1 min). Short contact times in mantle cell lymphoma were associated with the largest spatial displacement of PD1-positive cells (mean 12.3 µm). Although PD1-positive T cells in nodular lymphocyte-predominant Hodgkin lymphoma were fast, they remained in close contact with the lymphoma cells, in line with a dynamic immunological synapse. This pilot study shows for the first time systematic differences in the dynamic behavior of lymphoma and bystander cells between different lymphoma types.

In Situ Characterization of Human Lymphoid Tissue Immune Cells by Multispectral Confocal Imaging and Quantitative Image Analysis; Implications for HIV Reservoir Characterization

CD4 T cells are key mediators of adaptive immune responses during infection and vaccination. Within secondary lymphoid organs, helper CD4 T cells, particularly those residing in germinal centers known as follicular helper T cells (Tfh), provide critical help to B-cells to promote their survival, isotype switching and selection of high affinity memory B-cells. On the other hand, the important role of Tfh cells for the maintenance of HIV reservoir is well documented. Thus, interrogating and better understanding the tissue specific micro-environment and immune subsets that contribute to optimal Tfh cell differentiation and function is important for designing successful prevention and cure strategies. Here, we describe the development and optimization of eight multispectral confocal microscopy immunofluorescence panels designed for in depth characterization and immune-profiling of relevant immune cells in formalin-fixed paraffin-embedded human lymphoid tissue samples. We provide a comprehensive library of antibodies to use for the characterization of CD4+ T-cells -including Tfh and regulatory T-cells- as well as CD8 T-cells, B-cells, macrophages and dendritic cells and discuss how the resulting multispectral confocal datasets can be quantitatively dissected using the HistoCytometry pipeline to collect information about relative frequencies and immune cell spatial distributions. Cells harboring actively transcribed virus are analyzed using an in-situ hybridization assay for the characterization of HIV mRNA positive cells in combination with additional protein markers (multispectral RNAscope). The application of this methodology to lymphoid tissues offers a means to interrogate multiple relevant immune cell targets simultaneously at increased resolution in a reproducible manner to guide CD4 T-cell studies in infection and vaccination.

Frontiers of Autoantibodies in Autoimmune Disorders: Crosstalk Between Tfh/Tfr and Regulatory B Cells

Balance of Tfh/Tfr cell is critically important for the maintenance of immune tolerance, as evidenced by the fact that T follicular helper (Tfh) cells are central to the autoantibodies generation through providing necessary help for germinal center (GC) B cells, whereas T follicular regulatory (Tfr) cells significantly inhibit autoimmune inflammation process through restraining Tfh cell responses. However, signals underlying the regulation of Tfh and Tfr cells are largely undefined. Regulatory B cells (Bregs) is a heterogeneous subpopulation of B cells with immunosuppressive function. Considerable advances have been made in their functions to produce anti‐inflammatory cytokines and to regulate Th17, Th1, and Treg cells in autoimmune diseases. The recent identification of their correlations with dysregulated Tfr/Tfh cells and autoantibody production makes Bregs an important checkpoint in GC response. Bregs exert profound impacts on the differentiation, function, and distribution of Tfh and Tfr cells in the immune microenvironment. Thus, unraveling mechanistic information on Tfh-Breg and Tfr-Breg interactions will inspire novel implications for the establishment of homeostasis and prevention of autoantibodies in diverse diseases. This review summarizes the dysregulation of Tfh/Tfr cells in autoimmune diseases with a focus on the emerging role of Bregs in regulating the balance between Tfh and Tfr cells. The previously unsuspected crosstalk between Bregs and Tfh/Tfr cells will be beneficial to understand the cellular mechanisms of autoantibody production and evoke a revolution in immunotherapy for autoimmune diseases.