Refine
Year of publication
Document Type
- Article (43)
- Conference Proceeding (1)
- Preprint (1)
Has Fulltext
- yes (45)
Is part of the Bibliography
- no (45) (remove)
Keywords
- Hodgkin lymphoma (5)
- classical Hodgkin lymphoma (3)
- B-cell lymphoma (2)
- DNA methylation (2)
- Histology (2)
- Lymphocytes (2)
- anaplastic large cell lymphoma (2)
- Antiviral therapy (1)
- B cell malignancies (1)
- B cells (1)
Institute
TNFAIP3 (A20) is a tumor suppressor gene in Hodgkin lymphoma and primary mediastinal B cell lymphoma
(2009)
Proliferation and survival of Hodgkin and Reed/Sternberg (HRS) cells, the malignant cells of classical Hodgkin lymphoma (cHL), are dependent on constitutive activation of nuclear factor {kappa}B (NF-{kappa}B). NF-{kappa}B activation through various stimuli is negatively regulated by the zinc finger protein A20. To determine whether A20 contributes to the pathogenesis of cHL, we sequenced TNFAIP3, encoding A20, in HL cell lines and laser-microdissected HRS cells from cHL biopsies. We detected somatic mutations in 16 out of 36 cHLs (44%), including missense mutations in 2 out of 16 Epstein-Barr virus–positive (EBV+) cHLs and a missense mutation, nonsense mutations, and frameshift-causing insertions or deletions in 14 out of 20 EBV– cHLs. In most mutated cases, both TNFAIP3 alleles were inactivated, including frequent chromosomal deletions of TNFAIP3. Reconstitution of wild-type TNFAIP3 in A20-deficient cHL cell lines revealed a significant decrease in transcripts of selected NF-{kappa}B target genes and caused cytotoxicity. Extending the mutation analysis to primary mediastinal B cell lymphoma (PMBL), another lymphoma with constitutive NF-{kappa}B activity, revealed destructive mutations in 5 out of 14 PMBLs (36%). This report identifies TNFAIP3 (A20), a key regulator of NF-{kappa}B activity, as a novel tumor suppressor gene in cHL and PMBL. The significantly higher frequency of TNFAIP3 mutations in EBV– than EBV+ cHL suggests complementing functions of TNFAIP3 inactivation and EBV infection in cHL pathogenesis.
Aims: The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues.
Materials and results: Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL.
Conclusion: In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.
In contrast to the commonly indolent clinical behavior of nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), T cell/histiocyte rich large B cell lymphoma (THRLBCL) is frequently diagnosed in advanced clinical stages and has a poor prognosis. Besides the different clinical presentations of these lymphoma entities, there are variants of NLPHL with considerable histopathologic overlap compared to THRLBCL. Especially THRLBCL-like NLPHL, a diffuse form of NLPHL, often presents a histopathologic pattern similar to THRLBCL, suggesting a close relationship between both lymphoma entities. To corroborate this hypothesis, we performed gene expression profiling of microdissected tumor cells of NLPHL, THRLBCL-like NLPHL and THRLBCL. In unsupervised analyses, the lymphomas did not cluster according to their entity. Moreover, even in supervised analyses, very few consistently differentially expressed transcripts were found, and for these genes the extent of differential expression was only moderate. Hence, there are no clear and consistent differences in the gene expression of the tumor cells of NLPHL, THRLBCL-like NLPHL and THRLBCL. Based on the gene expression studies, we identified BAT3/BAG6, HIGD1A, and FAT10/UBD as immunohistochemical markers expressed in the tumor cells of all three lymphomas. Characterization of the tumor microenvironment for infiltrating T cells and histiocytes revealed significant differences in the cellular composition between typical NLPHL and THRLBCL cases. However, THRLBCL-like NLPHL presented a histopathologic pattern more related to THRLBCL than NLPHL. In conclusion, NLPHL and THRLBCL may represent a spectrum of the same disease. The different clinical behavior of these lymphomas may be strongly influenced by differences in the lymphoma microenvironment, possibly related to the immune status of the patient at the timepoint of diagnosis.
The human immune system is determined by the functionality of the human lymph node. With the use of high-throughput techniques in clinical diagnostics, a large number of data is currently collected. The new data on the spatiotemporal organization of cells offers new possibilities to build a mathematical model of the human lymph node - a virtual lymph node. The virtual lymph node can be applied to simulate drug responses and may be used in clinical diagnosis. Here, we review mathematical models of the human lymph node from the viewpoint of cellular processes. Starting with classical methods, such as systems of differential equations, we discuss the values of different levels of abstraction and methods in the range from artificial intelligence techniques formalism.
Background: Alterations in the DNA methylation pattern are a hallmark of leukemias and lymphomas. However, most epigenetic studies in hematologic neoplasms (HNs) have focused either on the analysis of few candidate genes or many genes and few HN entities, and comprehensive studies are required. Methodology/Principal Findings: Here, we report for the first time a microarray-based DNA methylation study of 767 genes in 367 HNs diagnosed with 16 of the most representative B-cell (n = 203), T-cell (n = 30), and myeloid (n = 134) neoplasias, as well as 37 samples from different cell types of the hematopoietic system. Using appropriate controls of B-, T-, or myeloid cellular origin, we identified a total of 220 genes hypermethylated in at least one HN entity. In general, promoter hypermethylation was more frequent in lymphoid malignancies than in myeloid malignancies, being germinal center mature B-cell lymphomas as well as B and T precursor lymphoid neoplasias those entities with highest frequency of gene-associated DNA hypermethylation. We also observed a significant correlation between the number of hypermethylated and hypomethylated genes in several mature B-cell neoplasias, but not in precursor B- and T-cell leukemias. Most of the genes becoming hypermethylated contained promoters with high CpG content, and a significant fraction of them are targets of the polycomb repressor complex. Interestingly, T-cell prolymphocytic leukemias show low levels of DNA hypermethylation and a comparatively large number of hypomethylated genes, many of them showing an increased gene expression. Conclusions/Significance: We have characterized the DNA methylation profile of a wide range of different HNs entities. As well as identifying genes showing aberrant DNA methylation in certain HN subtypes, we also detected six genes—DBC1, DIO3, FZD9, HS3ST2, MOS, and MYOD1—that were significantly hypermethylated in B-cell, T-cell, and myeloid malignancies. These might therefore play an important role in the development of different HNs.