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

T-Cell-Rich Hodgkin Lymphoma With Features of Classic Hodgkin Lymphoma and Nodular Lymphocyte-Predominant Hodgkin Lymphoma: A Borderline Category With Overlapping Morphologic and Immunophenotypic Features

CONTEXT.—

It is known that a subset of cases of classic Hodgkin lymphoma (CHL) with B-cell-rich nodules (lymphocyte-rich CHL) exhibits morphologic and immunophenotypic features that overlap with nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL), raising diagnostic difficulties that can be resolved in most cases by performing an adequate battery of immunohistochemical studies.

OBJECTIVE.—

To fully characterize cases of T-cell-rich Hodgkin lymphoma where a specific diagnosis of NLPHL (ie, pattern D) or CHL could not be made even after complete immunophenotypic investigation.

DESIGN.—

The clinical, immunomorphologic, and molecular (when applicable) presentation of 3 cases of T-cell-rich Hodgkin lymphoma was thoroughly investigated.

RESULTS.—

These 3 cases harbored lymphocyte-predominant-like and Hodgkin and Reed-Sternberg-like cells that partially expressed B-cell and CHL markers and were negative for Tiftein-Barr virus-encoded small RNA, in a T-cell-rich background with residual follicular dendritic cell meshworks; 1 case had frequent and the other 2 cases scant/absent eosinophils and plasma cells. Two patients with advanced-stage (III or IV) disease presented with axillary and supraclavicular lymphadenopathy, respectively, and without B symptoms. These patients underwent NLPHL-like therapeutic management with 6 cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin hydrochloride [hydroxydaunorubicin], vincristine sulfate [Oncovin], and prednisone) chemotherapy; both are in complete remission 7 years posttherapy. One patient presented with stage I disease involving an internal mammary lymph node without B-symptoms and was treated with surgical excision alone; this patient is also in complete remission 1 year later.

CONCLUSIONS.—

These cases illustrate overlapping features of T-cell-rich NLPHL and CHL with neoplastic cells expressing both B-cell program and CHL markers. This underrecognized overlap has not been fully illustrated in the literature, although it portrays a therapeutic challenge. These neoplasms may deserve in-depth investigation in the future that may bring up diagnostic or theragnostic implications.

Histopathologic Features and Differential Diagnosis in Challenging Cases of Nodular Lymphocyte Predominant B-cell Lymphoma/Nodular Lymphocyte Predominant Hodgkin Lymphoma

Nodular lymphocyte predominant Hodgkin lymphoma was termed "nodular lymphocyte predominant B-cell lymphoma" in the International Consensus Classification (ICC), to emphasize clinical and biological differences from classic Hodgkin lymphoma (CHL). The abbreviation "NLP" represents both terms in the ICC and World Health Organization classifications. Variations in the growth pattern, originally reported as Fan patterns A-F, are designated as either grade 1 or grade 2 in the ICC. NLP is uncommon, and in some cases an accurate diagnosis is challenging. The objectives of this article were to review the histopathologic features of NLP and the differential diagnosis from other key entities including de novo T-cell/histiocyte-rich large B-cell lymphoma (THRLBL) and lymphocyte-rich classic Hodgkin lymphoma (LRCHL). Histologically, NLP Fan pattern E (THRLBL-like) can be indistinguishable from de novo THRLBL. However, focal nodular areas, clustering of tumor cells, presence of few admixed small B-cells or FDC meshworks, and T-cell rosettes favor NLP Fan pattern E and argue against de novo THRLBL. NLP may also be confused with LRCHL. Patients with NLP are younger than those with LRCHL, and LRCHL may show mediastinal involvement. In LRCHL, the nodular pattern often contains eccentrically located small regressed germinal centers and intact small dense FDC meshworks, in contrast to the expanded, and fragmented FDC meshworks in NLP. Neoplastic cells that are positive for CD30 and CD15 but negative for CD20 and CD79a are characteristic of LRCHL. Additionally, Fascin and Gata3 are commonly positive in LRCHL but usually negative in NLP.

[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.

Hodgkin Lymphoma-The Spectrum from Diagnostics to Molecular Science, Movement and Current Treatment Approaches

A total of fourteen papers on Hodgkin lymphoma (HL) are published within this Special Issue, including six reviews, seven original articles and one commentary [...].

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.

Immune phenotypes and checkpoint molecule expression of clonally expanded lymph node-infiltrating T cells in classical Hodgkin lymphoma

Lymph node-infiltrating T cells have been of particular interest in classical Hodgkin lymphoma (cHL). High rates of complete therapeutic responses to antibody-mediated immune checkpoint blockade, even in relapsed/refractory patients, suggest the existence of a T cell-dominated, antigen-experienced, functionally inhibited and lymphoma-directed immune microenvironment. We asked whether clonally expanded T cells (1) were detectable in cHL lymph nodes, (2) showed characteristic immune phenotypes, and (3) were inhibited by immune checkpoint molecule expression. We applied high-dimensional FACS index sorting and single cell T cell receptor αβ sequencing to lymph node-infiltrating T cells from 10 treatment-naïve patients. T cells were predominantly CD4+ and showed memory differentiation. Expression of classical immune checkpoint molecules (CTLA-4, PD-1, TIM-3) was generally low (< 12.0% of T cells) and not different between CD4+ and CD8+ T cells. Degrees of clonal T cell expansion varied between patients (range: 1-18 expanded clones per patient) and was almost exclusively restricted to CD8+ T cells. Clonally expanded T cells showed non-naïve phenotypes and low checkpoint molecule expression similar to non-expanded T cells. Our data suggest that the therapeutic effects of immune checkpoint blockade require mechanisms in addition to dis-inhibition of pre-existing lymphoma-directed T cell responses. Future studies on immune checkpoint blockade-associated effects will identify molecular T cell targets, address dynamic aspects of cell compositions over time, and extend their focus beyond lymph node-infiltrating T cells.

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.

T-cell-derived Hodgkin lymphoma has motility characteristics intermediate between Hodgkin and anaplastic large cell lymphoma

Classic Hodgkin lymphoma (cHL) is usually characterized by a low tumour cell content, derived from crippled germinal centre B cells. Rare cases have been described in which the tumour cells show clonal T-cell receptor rearrangements. From a clinicopathological perspective, it is unclear if these cases should be classified as cHL or anaplastic large T-cell lymphoma (ALCL). Since we recently observed differences in the motility of ALCL and cHL tumour cells, here, we aimed to obtain a better understanding of T-cell-derived cHL by investigating their global proteomic profiles and their motility. In a proteomics analysis, when only motility-associated proteins were regarded, T-cell-derived cHL cell lines showed the highest similarity to ALK- ALCL cell lines. In contrast, T-cell-derived cHL cell lines presented a very low overall motility, similar to that observed in conventional cHL. Whereas all ALCL cell lines, as well as T-cell-derived cHL, predominantly presented an amoeboid migration pattern with uropod at the rear, conventional cHL never presented with uropods. The migration of ALCL cell lines was strongly impaired upon application of different inhibitors. This effect was less pronounced in cHL cell lines and almost invisible in T-cell-derived cHL. In summary, our cell line-derived data suggest that based on proteomics and migration behaviour, T-cell-derived cHL is a neoplasm that shares features with both cHL and ALCL and is not an ALCL with low tumour cell content. Complementary clinical studies on this lymphoma are warranted.

3D analyses reveal T cells with activated nuclear features in T-cell/histiocyte-rich large B-cell lymphoma

Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) can show variable histological growth patterns and present remarkable overlap with T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL). Previous studies suggest that NLPHL histological variants represent progression forms of NLPHL and THRLBCL transformation in aggressive disease. Since molecular studies of both lymphomas are limited due to the low number of tumor cells, the present study aimed to learn if a better understanding of these lymphomas is possible via detailed measurements of nuclear and cell size features in 2D and 3D sections. Whereas no significant differences were visible in 2D analyses, a slightly increased nuclear volume and a significantly enlarged cell size were noted in 3D measurements of the tumor cells of THRLBCL in comparison to typical NLPHL cases. Interestingly, not only was the size of the tumor cells increased in THRLBCL but also the nuclear volume of concomitant T cells in the reactive infiltrate when compared with typical NLPHL. Particularly CD8⁺ T cells had frequent contacts to tumor cells of THRLBCL. However, the nuclear volume of B cells was comparable in all cases. These results clearly demonstrate that 3D tissue analyses are superior to conventional 2D analyses of histological sections. Furthermore, the results point to a strong activation of T cells in THRLBCL, representing a cytotoxic response against the tumor cells with unclear effectiveness, resulting in enhanced swelling of the tumor cell bodies and limiting proliferative potential. Further molecular studies combining 3D tissue analyses and molecular data will help to gain profound insight into these ill-defined cellular processes.