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Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is an indolent lymphoma, but can transform into diffuse large B cell lymphoma (DLBCL), showing a more aggressive clinical behavior. Little is known about these cases on the molecular level. Therefore, the aim of the present study was to characterize DLBCL transformed from NLPHL (LP-DLBCL) by gene expression profiling (GEP). GEP revealed an inflammatory signature pinpointing to a specific host response. In a coculture model resembling this host response, DEV tumor cells showed an impaired growth behavior. Mechanisms involved in the reduced tumor cell proliferation included a downregulation of MYC and its target genes. Lack of MYC expression was also confirmed in 12/16 LP-DLBCL by immunohistochemistry. Furthermore, CD274/PD-L1 was upregulated in DEV tumor cells after coculture with T cells or monocytes and its expression was validated in 12/19 cases of LP-DLBCL. Thereby, our data provide new insights into the pathogenesis of LP-DLBCL and an explanation for the relatively low tumor cell content. Moreover, the findings suggest that treatment of these patients with immune checkpoint inhibitors may enhance an already ongoing host response in these patients.
In pathology, tissue images are evaluated using a light microscope, relying on the expertise and experience of pathologists. There is a great need for computational methods to quantify and standardize histological observations. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of tumor cells and their microenvironment are of special interest. Here, we systematically investigated tumor cell properties and their spatial neighborhood relations by a new application of statistical analysis to whole slide images of Hodgkin lymphoma, a tumor arising in lymph nodes, and inflammation of lymph nodes called lymphadenitis. We considered properties of more than 400, 000 immunohistochemically stained, CD30-positive cells in 35 whole slide images of tissue sections from subtypes of the classical Hodgkin lymphoma, nodular sclerosis and mixed cellularity, as well as from lymphadenitis. We found that cells of specific morphology exhibited significant favored and unfavored spatial neighborhood relations of cells in dependence of their morphology. This information is important to evaluate differences between Hodgkin lymph nodes infiltrated by tumor cells (Hodgkin lymphoma) and inflamed lymph nodes, concerning the neighborhood relations of cells and the sizes of cells. The quantification of neighborhood relations revealed new insights of relations of CD30-positive cells in different diagnosis cases. The approach is general and can easily be applied to whole slide image analysis of other tumor types.
Bioinformatics analysis quantifies neighborhood preferences of cancer cells in Hodgkin lymphoma
(2017)
Motivation Hodgkin lymphoma is a tumor of the lymphatic system and represents one of the most frequent lymphoma in the Western world. It is characterized by Hodgkin cells and Reed-Sternberg cells, which exhibit a broad morphological spectrum. The cells are visualized by immunohistochemical staining of tissue sections. In pathology, tissue images are mainly manually evaluated, relying on the expertise and experience of pathologists. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of cancer cells is of great interest.
Results Here, we systematically quantified and investigated cancer cell properties and their spatial neighborhood relations by applying statistical analyses to whole slide images of Hodgkin lymphoma and lymphadenitis, which describes a non-cancerous inflammation of the lymph node. We differentiated cells by their morphology and studied the spatial neighborhood relation of more than 400,000 immunohistochemically stained cells. We found that, according to their morphological features, the cells exhibited significant preferences for and aversions to cells of specific profiles as nearest neighbor. We quantified differences between Hodgkin lymphoma and lymphadenitis concerning the neighborhood relations of cells and the sizes of cells. The approach can easily be applied to other cancer types.
Introduction and Objective: Identifying patients that benefit from cisplatin-based adjuvant chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC). The purpose of this study is to correlate “luminal” and “basal” type protein expression with histological subtypes, to investigate the prognostic impact on survival after adjuvant chemotherapy and to define molecular consensus subtypes of “double negative” patients (i.e., without expression of CK5/6 or GATA3).
Materials and Methods: We performed immunohistochemical (IHC) analysis of CK5/6 and GATA3 for surrogate molecular subtyping in 181 MIBC samples. The mRNA expression profiles for molecular consensus classification were determined in CK5/6 and GATA3 (double) negative cases using a transcriptome panel with 19.398 mRNA targets (HTG Molecular Diagnostics). Data of 110 patients undergoing radical cystectomy were available for survival analysis.
Results: The expression of CK5/6 correlated with squamous histological subtype (96%) and expression of GATA3 was associated with micropapillary histology (100%). In the multivariate Cox-regression model, patients receiving adjuvant chemotherapy had a significant survival benefit (hazard ratio [HR]: 0.19 95% confidence interval [CI]: 0.1–0.4, p < 0.001) and double-negative cases had decreased OS (HR: 4.07; 95% CI: 1.5–10.9, p = 0.005). Double negative cases were classified as NE-like (30%), stroma-rich (30%), and Ba/Sq (40%) consensus molecular subtypes and displaying different histological subtypes.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
In gastric cancer (GC), there are four molecular subclasses that indicate whether patients respond to chemotherapy or immunotherapy, according to the TCGA. In clinical practice, however, not every patient undergoes molecular testing. Many laboratories have used well-implemented in situ techniques (IHC and EBER-ISH) to determine the subclasses in their cohorts. Although multiple stains are used, we show that a staining approach is unable to correctly discriminate all subclasses. As an alternative, we trained an ensemble convolutional neuronal network using bagging that can predict the molecular subclass directly from hematoxylin–eosin histology. We also identified patients with predicted intra-tumoral heterogeneity or with features from multiple subclasses, which challenges the postulated TCGA-based decision tree for GC subtyping. In the future, deep learning may enable targeted testing for molecular subtypes and targeted therapy for a broader group of GC patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Background: Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) usually presents in middle aged men and shows an indolent clinical behavior. However, up to 30% of the patients present a secondary transformation into aggressive diffuse large B cell lymphoma (DLBCL). The aim of the present study was to characterize morphology and immunophenotype of this kind of DLBCL in detail and compare it with conventional DLBCL.
Methods: Morphology and immunophenotype of 33 cases of NLPHL with simultaneous or sequential transformation into DLBCL were investigated. These cases were compared with 41 de novo DLBCL in Finnish men.
Results: The majority of cases exhibited different immunophenotypes in the NLPHL and the DLBCL components. The immunophenotype of the DLBCL secondary to NLPHL was heterogeneous. However, BCL6, EMA, CD75 and J-chain were usually expressed in both components (≥73% positive). Overall, the NLPHL component was more frequently positive for EMA, CD75 and J-chain than the DLBCL component. In contrast, B cell markers, CD10 and BCL2, were more frequently expressed and were expressed at higher levels in the DLBCL component than in the NLPHL component. In the independent series of de novo DLBCL 4 cases could be identified with a growth pattern and immunophenotype that suggested that they had arisen secondarily from NLPHL.
Conclusions: The morphology and immunophenotype of DLBCL arisen from NLPHL is heterogeneous. Further characterization of the particular molecular features of this subgroup is warranted to be able to better identify these cases among conventional DLBCL.
The mechanisms involved in malignant transformation of mature B and T lymphocytes are still poorly understood. In a previous study, we compared gene expression profiles of the tumor cells of Hodgkin lymphoma (HL) and anaplastic large cell lymphoma (ALCL) to their normal cellular counterparts and found the basic leucine zipper protein ATF-like 3 (BATF3) to be significantly upregulated in the tumor cells of both entities. To assess the oncogenic potential of BATF3 in lymphomagenesis and to dissect the molecular interactions of BATF3 in lymphoma cells, we retrovirally transduced murine mature T and B cells with a BATF3-encoding viral vector and transplanted each population into Rag1-deficient recipients. Intriguingly, BATF3-expressing B lymphocytes readily induced B-cell lymphomas after characteristic latencies, whereas T-cell transplanted animals remained healthy throughout the observation time. Further analyses revealed a germinal center B-cell-like phenotype of most BATF3-initiated lymphomas. In a multiple myeloma cell line, BATF3 inhibited BLIMP1 expression, potentially illuminating an oncogenic action of BATF3 in B-cell lymphomagenesis. In conclusion, BATF3 overexpression induces malignant transformation of mature B cells and might serve as a potential target in B-cell lymphoma treatment.
Classical Hodgkin lymphoma (cHL) is one of the most common malignant lymphomas in Western Europe. The nodular sclerosing subtype of cHL (NS cHL) is characterized by a proliferation of fibroblasts in the tumor microenvironment, leading to fibrotic bands surrounding the lymphoma infiltrate. Several studies have described a crosstalk between the tumour cells of cHL, the Hodgkin- and Reed-Sternberg (HRS) cells, and cancer-associated fibroblasts. However, to date a deep molecular characterization of these fibroblasts is lacking. Thus, the aim of the present study is a comprehensive characterization of these fibroblasts. Gene expression profiling and methylation profiles of fibroblasts isolated from primary lymph node suspensions revealed persistent differences between fibroblasts obtained from NS cHL and lymphadenitis. NS cHL derived fibroblasts exhibit a myofibroblastic phenotype characterized by myocardin (MYOCD) expression. Moreover, TIMP3, an inhibitor of matrix metalloproteinases, was strongly upregulated in NS cHL fibroblasts, likely contributing to the accumulation of collagen in sclerotic bands of NS cHL. As previously shown for other types of cancer-associated fibroblasts, treatment by luteolin could reverse this fibroblast phenotype and decrease TIMP3 secretion. NS cHL fibroblasts showed enhanced proliferation when they were exposed to soluble factors released from HRS cells. For HRS cells, soluble factors from fibroblasts were not sufficient to protect them from Brentuximab-Vedotin induced cell death. However, HRS cells adherent to fibroblasts were protected from Brentuximab-Vedotin induced injury. In summary, we confirm the importance of fibroblasts for HRS cell survival and identify TIMP3 which probably contributes as a major factor to the typical fibrosis observed in NS cHL.
Background: Increased glycolytic activity is a hallmark of cancer, allowing staging and restaging with 18F-fluorodeoxyglucose-positron-emission-tomography (PET). Since interim-PET is an important prognostic tool in Hodgkin lymphoma (HL), the aim of this study was to investigate the expression of proteins involved in the regulation of glucose metabolism in the different HL subtypes and their impact on clinical outcome.
Methods: Lymph node biopsies from 54 HL cases and reactive lymphoid tissue were stained for glucose transporter 1 (GLUT1), lactate dehydrogenase A (LDHA) and lactate exporter proteins MCT1 and MCT4. In a second series, samples from additional 153 HL cases with available clinical data were stained for GLUT1 and LDHA.
Results: Membrane bound GLUT1 expression was frequently observed in the tumor cells of HL (49% of all cases) but showed a broad variety between the different Hodgkin lymphoma subtypes: Nodular sclerosing HL subtype displayed a membrane bound GLUT1 expression in the Hodgkin-and Reed-Sternberg cells in 56% of the cases. However, membrane bound GLUT1 expression was more rarely observed in tumor cells of lymphocyte rich classical HL subtype (30%) or nodular lymphocyte predominant HL subtype (15%). Interestingly, in both of these lymphocyte rich HL subtypes as well as in progressively transformed germinal centers, reactive B cells displayed strong expression of GLUT1. LDHA, acting downstream of glycolysis, was also expressed in 44% of all cases. We evaluated the prognostic value of different GLUT1 and LDHA expression patterns; however, no significant differences in progression free or overall survival were found between patients exhibiting different GLUT1 or LDHA expression patterns. There was no correlation between GLUT1 expression in HRS cells and PET standard uptake values.
Conclusions: In a large number of cases, HRS cells in classical HL express high levels of GLUT1 and LDHA indicating glycolytic activity in the tumor cells. Although interim-PET is an important prognostic tool, a predictive value of GLUT1 or LDHA staining of the primary diagnostic biopsy could not be demonstrated. However, we observed GLUT1 expression in progressively transformed germinal centers and hyperplastic follicles, explaining false positive results in PET. Therefore, PET findings suggestive of HL relapse should always be confirmed by histology.