On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis

Background: Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. Methods: The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object’s centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. Results: After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field – were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. Conclusions: The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction

ANLN and TLE2 in Muscle Invasive Bladder Cancer: A Functional and Clinical Evaluation Based on In Silico and In Vitro Data

Anilin actin binding protein (ANLN) and transducing-like enhancer protein 2 (TLE2) are associated with cancer patient survival and progression. The impact of their gene expression on progression-free survival (PFS) of patients with muscle invasive bladder cancer (MIBC) treated with radical cystectomy (RC) and subtype association has not yet been investigated. qRT-PCR was used to measure the transcript levels of ANLN and TLE2 in the Mannheim cohort, and validated in silico by The Cancer Genome Atlas (TCGA) cohort. Uni- and multivariate Cox regression analyses identified predictors for disease-specific survival (DSS) and overall survival (OS). In the Mannheim cohort, tumors with high ANLN expression were associated with lower OS and DSS, while high TLE2 expression was associated with a favorable OS. The TCGA cohort confirmed that high ANLN and low TLE2 expression was associated with shorter OS and disease-free survival (DFS). In both cohorts, multivariate analyses showed ANLN and TLE2 expression as independent outcome predictors. Furthermore, ANLN was more highly expressed in cell lines and patients with the basal subtype, while TLE2 expression was higher in cell lines and patients with the luminal subtype. ANLN and TLE2 are promising biomarkers for individualized bladder cancer therapy including cancer subclassification and informed MIBC prognosis

The EEF1A2 gene expression as risk predictor in localized prostate cancer

Background: Besides clinical stage and Gleason score, risk-stratification of prostate cancer in the pretherapeutic setting mainly relies on the serum PSA level. Yet, this is associated with many uncertainties. With regard to therapy decision-making, additional markers are needed to allow an exact risk prediction. Eukaryotic translation elongation factor 1 alpha 2 (EEF1A2) was previously suggested as driver of tumor progression and potential biomarker. In the present study its functional and prognostic relevance in prostate cancer was investigated. Methods: EEF1A2 expression was analyzed in two cohorts of patients (n = 40 and n = 59) with localized PCa. Additionally data from two large expression dataset (MSKCC, Cell, 2010 with n = 131 localized, n = 19 metastatic PCa and TCGA provisional data, n = 499) of PCa patients were reanalyzed. The expression of EEF1A2 was correlated with histopathology features and biochemical recurrence (BCR). To evaluate the influence of EEF1A2 on proliferation and migration of metastatic PC3 cells, siRNA interference was used. Statistical significance was tested with t-test, Mann-Whitney-test, Pearson correlation and log-rank test. Results: qRT-PCR revealed EEF1A2 to be significantly overexpressed in PCa tissue, with an increase according to tumor stage in one cohort (p = 0.0443). In silico analyses in the MSKCC cohort confirmed the overexpression of EEF1A2 in localized PCa with high Gleason score (p = 0.0142) and in metastatic lesions (p = 0.0038). Patients with EEF1A2 overexpression had a significantly shorter BCR-free survival (p = 0.0028). EEF1A2 expression was not correlated with serum PSA levels. Similar results were seen in the TCGA cohort, where EEF1A2 overexpression only occurred in tumors with Gleason 7 or higher. Patients with elevated EEF1A2 expression had a significantly shorter BCR-free survival (p = 0.043). EEF1A2 knockdown significantly impaired the migration, but not the proliferation of metastatic PC3 cells. Conclusion: The overexpression of EEF1A2 is a frequent event in localized PCa and is associated with histopathology features and a shorter biochemical recurrence-free survival. Due to its independence from serum PSA levels, EEF1A2 could serve as valuable biomarker in risk-stratification of localized PCa

On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis

Background Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. Methods The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object’s centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. Results After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field – were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. Conclusions The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction

Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome

Background: Tumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in routine pathology is hampered due to the use of several slightly different assessment systems, a time-consuming manual counting process and a high inter-observer variability. Hence, we established and validated an automatic image processing approach to reliably quantify tumor budding in immunohistochemically (IHC) stained sections of CRC samples. Methods: This approach combines classical segmentation methods (like morphological operations) and machine learning techniques (k-means and hierarchical clustering, convolutional neural networks) to reliably detect tumor buds in colorectal carcinoma samples immunohistochemically stained for pan-cytokeratin. As a possible application, we tested it on whole-slide images as well as on tissue microarrays (TMA) from a clinically well-annotated CRC cohort. Results: Our automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86). Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. However, the number of spatial clusters of tumor buds (budding hotspots) significantly correlated to the nodal status (p-value = 0.003 for N0 vs. N1/N2). TMAs were not feasible for tumor budding evaluation, as the spatial relationship of tumor buds (especially hotspots) was not preserved. Conclusions: Automatic image processing is a feasible and valid assessment tool for tumor budding in CRC on whole-slide images. Interestingly, only the spatial clustering of the tumor buds in hotspots (and especially the number of hotspots) and not the absolute number of tumor buds showed a clinically relevant correlation with patient outcome in our data

A Novel Murine Model of Parvovirus Associated Dilated Cardiomyopathy Induced by Immunization with VP1-Unique Region of Parvovirus B19

Background. Parvovirus B19 (B19V) is a common finding in endomyocardial biopsy specimens from myocarditis and dilated cardiomyopathy patients. However, current understanding of how B19V is contributing to cardiac damage is rather limited due to the lack of appropriate mice models. In this work we demonstrate that immunization of BALB/c mice with the major immunogenic determinant of B19V located in the unique sequence of capsid protein VP1 (VP1u) is an adequate model to study B19V associated heart damage. Methods and Results. We immunized mice in the experimental group with recombinant VP1u; immunization with cardiac myosin derived peptide served as a positive reference and phosphate buffered saline served as negative control. Cardiac function and dimensions were followed echocardiographically 69 days after immunization. Progressive dilatation of left ventricle and decline of ejection fraction were observed in VP1u- and myosin-immunized mice. Histologically, severe cardiac fibrosis and accumulation of heart failure cells in lungs were observed 69 days after immunization. Transcriptomic profiling revealed ongoing cardiac remodeling and immune process in VP1u- and myosin-immunized mice. Conclusions. Immunization of BALB/c mice with VP1u induces dilated cardiomyopathy in BALB/c mice and it could be used as a model to study clinically relevant B19V associated cardiac damage

Molecular Classification of Neuroendocrine Tumors of the Thymus

INTRODUCTION: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. METHODS: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. RESULTS: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). CONCLUSIONS: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication. peerReviewe

In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer.

Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n = 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n = 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyte-enriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n = 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P = 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment. Cancer Res; 77(22); 6442-52. (c)2017 AACR

Inhibition of lysyl oxidases synergizes with 5-azacytidine to restore erythropoiesis in myelodysplastic and myeloid malignancies

Limited response rates and frequent relapses during standard of care with hypomethylating agents in myelodysplastic neoplasms (MN) require urgent improvement of this treatment indication. Here, by combining 5-azacytidine (5-AZA) with the pan-lysyl oxidase inhibitor PXS-5505, we demonstrate superior restoration of erythroid differentiation in hematopoietic stem and progenitor cells (HSPCs) of MN patients in 20/31 cases (65%) versus 9/31 cases (29%) treated with 5-AZA alone. This effect requires direct contact of HSPCs with bone marrow stroma components and is dependent on integrin signaling. We further confirm these results in vivo using a bone marrow niche-dependent MN xenograft model in female NSG mice, in which we additionally demonstrate an enforced reduction of dominant clones as well as significant attenuation of disease expansion and normalization of spleen sizes. Overall, these results lay out a strong pre-clinical rationale for efficacy of combination treatment of 5-AZA with PXS-5505 especially for anemic MN

Histopathology of thymectomy specimens from the MGTX-trial

Background: The thymectomy specimens from the “thymectomy trial in non-thymomatous myasthenia gravis patients receiving prednisone therapy” (MGTX) [1] underwent rigid and comprehensive work-up, which results in a unique, spatially mapped dataset. Fig. 1 Specimen work-up: Work-up scheme for the specimens in the MGTX trial [1, 2]. Thymuses were sub-divided into regions that underwent predefined evaluation (e.g. complete work-up of the central A-region, partial work-up of other regions) Content: A xlsx-file with one table for patient data (“dataPatients” with age, gender etc.), one table with histomorphological data for the specimen regions (“dataAllRegions” with grading atrophy, grading overall fat etc.) and one table for the follicle morphology in the A region (“dataARegion” with n follicle with germinal centre etc.). References: 1. Wolfe, G.I., et al., Randomized Trial of Thymectomy in Myasthenia Gravis. N Engl J Med, 2016. 375(6): p. 511-22. 2. Ströbel, P., et al., The ageing and myasthenic thymus: A morphometric study validating a standard procedure in the histological workup of thymic specimens. Journal of Neuroimmunology, 2008. 201–202: p. 64-73