Extra-cranial malignant rhabdoid tumors (MRTs) and cranial atypical teratoid RTs (ATRTs) are heterogeneous pediatric cancers driven primarily by SMARCB1 loss. To understand the genome-wide molecular relationships between MRTs and ATRTs, we analyze multi-omics data from 140 MRTs and 161 ATRTs. We detect similarities between the MYC subgroup of ATRTs (ATRT-MYC) and extra-cranial MRTs, including global DNA hypomethylation and overexpression of HOX genes and genes involved in mesenchymal development, distinguishing them from other ATRT subgroups that express neural-like features. We identify five DNA methylation subgroups associated with anatomical sites and SMARCB1 mutation patterns. Groups 1, 3, and 4 exhibit cytotoxic T cell infiltration and expression of immune checkpoint regulators, consistent with a potential role for immunotherapy in rhabdoid tumor patients.

Best-practice data models harmonize semantics and data structure of medical variables in clinical or epidemiological studies. While there exist several published data sets, it remains challenging to find and reuse published eligibility criteria or other data items that match specific needs of a newly planned study or registry. A novel Internet-based method for rapid comparison of published data models was implemented to enable reuse, customization, and harmonization of item catalogs for the early planning and development phase of research databases.

Rhabdoid tumors (RT) are malignant neoplasms of early childhood. Despite intensive therapy, survival is poor and new treatment approaches are required. The only recurrent mutations in these tumors affect SMARCB1 and less commonly SMARCA4, both subunits of the chromatin remodeling complex SWItch/Sucrose Non-Fermentable (SWI/SNF). Loss of these two core subunits alters the function of the SWI/SNF complex, resulting in tumor development. We hypothesized that inhibition of aberrant SWI/SNF function by selective blockade of the BRD9 subunit of the SWI/SNF complex would reduce tumor cell proliferation. The cytotoxic and anti-proliferative effects of two specific chemical probes (I-BRD9 and BI-9564) which target the bromodomain of SWI/SNF protein BRD9 were evaluated in 5 RT cell lines. Combinatorial effects of I-BRD9 and cytotoxic drugs on cell proliferation were evaluated by cytotoxicity assays. Single compound treatment of RT cells with I-BRD9 and BI-9564 resulted in decreased cell proliferation, G1-arrest and apoptosis. Combined treatment of doxorubicin or carboplatin with I-BRD9 resulted in additive to synergistic inhibitory effects on cell proliferation. In contrast, the combination of I-BRD9 with vincristine demonstrated the antagonistic effects of these two compounds. We conclude that the BRD9 bromodomain is an attractive target for novel therapies in this cancer.

A thorough analysis of clonal evolution commonly requires integration of diverse sources of data (e.g., karyotyping, next-generation sequencing, and clinical information). Subsequent to actual reconstruction of clonal evolution, detailed analysis and interpretation of the results are essential. Often, however, only few tumor samples per patient are available. Thus, information on clonal development and therapy effect may be incomplete. Furthermore, analysis of biallelic events-considered of high relevance with respect to disease course-can commonly only be realized by time-consuming analysis of the raw results and even raw sequencing data.

The human heart controls blood flow, and therewith enables the adequate supply of oxygen and nutrients to the body. The correct function of the heart is coordinated by the interplay of different cardiac cell types. Thereby, one can distinguish between cells of the working myocardium, the pace-making cells in the sinoatrial node (SAN) and the conduction system cells in the AV-node, the His-bundle or the Purkinje fibres. Tissue-engineering approaches aim to generate hiPSC-derived cardiac tissues for disease modelling and therapeutic usage with a significant improvement in the differentiation quality of myocardium and pace-making cells. The differentiation of cells with cardiac conduction system properties is still challenging, and the produced cell mass and quality is poor. Here, we describe the generation of cardiac cells with properties of the cardiac conduction system, called conduction system-like cells (CSLC). As a primary approach, we introduced a CrispR-Cas9-directed knockout of the NKX2-5 gene in hiPSC. NKX2-5-deficient hiPSC showed altered connexin expression patterns characteristic for the cardiac conduction system with strong connexin 40 and connexin 43 expression and suppressed connexin 45 expression. Application of differentiation protocols for ventricular- or SAN-like cells could not reverse this connexin expression pattern, indicating a stable regulation by NKX2-5 on connexin expression. The contraction behaviour of the hiPSC-derived CSLCs was compared to hiPSC-derived ventricular- and SAN-like cells. We found that the contraction speed of CSLCs resembled the expected contraction rate of human conduction system cells. Overall contraction was reduced in differentiated cells derived from NKX2-5 knockout hiPSC. Comparative transcriptomic data suggest a specification of the cardiac subtype of CSLC that is distinctly different from ventricular or pacemaker-like cells with reduced myocardial gene expression and enhanced extracellular matrix formation for improved electrical insulation. In summary, knockout of NKX2-5 in hiPSC leads to enhanced differentiation of cells with cardiac conduction system features, including connexin expression and contraction behaviour.

The utilisation of smart devices, such as smartwatches and smartphones, in the field of movement disorders research has gained significant attention. However, the absence of a comprehensive dataset with movement data and clinical annotations, encompassing a wide range of movement disorders including Parkinson's disease (PD) and its differential diagnoses (DD), presents a significant gap. The availability of such a dataset is crucial for the development of reliable machine learning (ML) models on smart devices, enabling the detection of diseases and monitoring of treatment efficacy in a home-based setting. We conducted a three-year cross-sectional study at a large tertiary care hospital. A multi-modal smartphone app integrated electronic questionnaires and smartwatch measures during an interactive assessment designed by neurologists to provoke subtle changes in movement pathologies. We captured over 5000 clinical assessment steps from 504 participants, including PD, DD, and healthy controls (HC). After age-matching, an integrative ML approach combining classical signal processing and advanced deep learning techniques was implemented and cross-validated. The models achieved an average balanced accuracy of 91.16% in the classification PD vs. HC, while PD vs. DD scored 72.42%. The numbers suggest promising performance while distinguishing similar disorders remains challenging. The extensive annotations, including details on demographics, medical history, symptoms, and movement steps, provide a comprehensive database to ML techniques and encourage further investigations into phenotypical biomarkers related to movement disorders.

Posterior fossa type A (PF-EPN-A, PFA) ependymoma are aggressive tumors that mainly affect children and have a poor prognosis. Histopathology shows significant intratumoral heterogeneity, ranging from loose tissue to often sharply demarcated, extremely cell-dense tumor areas. To determine molecular differences in morphologically different areas and to understand their clinical significance, we analyzed 113 PF-EPN-A samples, including 40 corresponding relapse samples. Cell-dense areas ranged from 0 to 100% of the tumor area and displayed a higher proportion of proliferating tumor cells (p < 0.01). Clinically, cell density was associated with poor progression-free and overall survival (pPFS = 0.0026, pOS < 0.01). Molecularly, tumor areas with low and high cell density showed diverging DNA methylation profiles regarding their similarity to distinct previously discovered PF-EPN-A subtypes in 9/21 cases. Prognostically relevant chromosomal changes at 1q and 6q showed spatial heterogeneity within single tumors and were significantly enriched in cell-dense tumor areas as shown by single-cell RNA (scRNA)-sequencing as well as copy number profiling and fluorescence in situ hybridization (FISH) analyses of different tumor areas. Finally, spatial transcriptomics revealed cell-dense areas of different tumors to be more similar than various different areas of the same tumor. High-density areas distinctly overexpressed genes encoding histone proteins, WNT5A, TGFB1, or IGF2. Relapsing tumors displayed a higher proportion of cell-dense areas (p = 0.036), a change in PF-EPN-A methylation subtypes (13/32 patients), and novel chromosome 1q gains and 6q losses (12/32 cases) compared to corresponding primary tumors. Our data suggest that PF-EPN-A ependymomas habor a previously unrecognized intratumoral heterogeneity with clinical implications, which has to be accounted for when selecting diagnostic material, inter alia, by histological evaluation of the proportion of cell-dense areas.

Information systems are a key success factor for medical research and healthcare. Currently, most of these systems apply heterogeneous and proprietary data models, which impede data exchange and integrated data analysis for scientific purposes. Due to the complexity of medical terminology, the overall number of medical data models is very high. At present, the vast majority of these models are not available to the scientific community. The objective of the Portal of Medical Data Models (MDM, https://medical-data-models.org) is to foster sharing of medical data models.

Rhabdoid tumors are caused by the deletion of SMARCB1, whose protein encodes the SMARCB1 subunit of the chromatin remodeling complex SWI/SNF that is involved in global chromatin organization and gene expression control. Simultaneously inhibiting the main players involved in the deregulated transcription machinery is a promising option for preventing exaggerated tumor cell proliferation and survival as it may bypass compensatory mechanisms. In support of this hypothesis, we report efficient impairment of cellular proliferation and strong induction of cell death elicited by inhibition of bromodomain protein BRD4 and transcription kinase CDK9 using small molecular compounds. Combination of both compounds efficiently represses antiapoptotic genes and the oncogene MYC. Our results provide a novel approach for the treatment of RT.

The application of next-generation sequencing in research and particularly in clinical routine requires valid variant calling results. However, evaluation of several commonly used tools has pointed out that not a single tool meets this requirement. False positive as well as false negative calls necessitate additional experiments and extensive manual work. Intelligent combination and output filtration of different tools could significantly improve the current situation.

Atypical teratoid/rhabdoid tumor (AT/RT) is a highly malignant brain tumor in infants that is characterized by loss of nuclear expression of SMARCB1 or SMARCA4 proteins. Recent studies show that AT/RTs comprise three molecular subgroups, namely AT/RT-TYR, AT/RT-MYC and AT/RT-SHH. The subgroups show distinct expression patterns of genes involved in ciliogenesis, however, little is known about the functional roles of primary cilia in the biology of AT/RT. Here, we show that primary cilia are present across all AT/RT subgroups with specific enrichment in AT/RT-TYR patient samples. Furthermore, we demonstrate that primary ciliogenesis contributes to AT/RT biology in vitro and in vivo. Specifically, we observed a significant decrease in proliferation and clonogenicity following disruption of primary ciliogenesis in AT/RT cell line models. Additionally, apoptosis was significantly increased via the induction of STAT1 and DR5 signaling, as detected by proteogenomic profiling. In a Drosophila model of SMARCB1 deficiency, concomitant knockdown of several cilia-associated genes resulted in a substantial shift of the lethal phenotype with more than 20% of flies reaching adulthood. We also found significantly extended survival in an orthotopic xenograft mouse model of AT/RT upon disruption of primary ciliogenesis. Taken together, our findings indicate that primary ciliogenesis or its downstream signaling contributes to the aggressiveness of AT/RT and, therefore, may constitute a novel therapeutic target.

Pediatric low-grade gliomas (pLGG) show heterogeneous responses to MAPK inhibitors (MAPKi) in clinical trials. Thus, more complex stratification biomarkers are needed to identify patients likely to benefit from MAPKi therapy. Here, we identify MAPK-related genes enriched in MAPKi-sensitive cell lines using the GDSC dataset and apply them to calculate class-specific MAPKi sensitivity scores (MSSs) via single-sample gene set enrichment analysis. The MSSs discriminate MAPKi-sensitive and non-sensitive cells in the GDSC dataset and significantly correlate with response to MAPKi in an independent PDX dataset. The MSSs discern gliomas with varying MAPK alterations and are higher in pLGG compared to other pediatric CNS tumors. Heterogenous MSSs within pLGGs with the same MAPK alteration identify proportions of potentially sensitive patients. The MEKi MSS predicts treatment response in a small set of pLGG patients treated with trametinib. High MSSs correlate with a higher immune cell infiltration, with high expression in the microglia compartment in single-cell RNA sequencing data, while low MSSs correlate with low immune infiltration and increased neuronal score. The MSSs represent predictive tools for the stratification of pLGG patients and should be prospectively validated in clinical trials. Our data supports a role for microglia in the response to MAPKi.

Growth factor independence 1 (GFI1) is a DNA-binding transcription factor and a key regulator of hematopoiesis. GFI1-36N is a germ line variant, causing a change of serine (S) to asparagine (N) at position 36. We previously reported that the GFI1-36N allele has a prevalence of 10% to 15% among patients with acute myeloid leukemia (AML) and 5% to 7% among healthy Caucasians and promotes the development of this disease. Using a multiomics approach, we show here that GFI1-36N expression is associated with increased frequencies of chromosomal aberrations, mutational burden, and mutational signatures in both murine and human AML and impedes homologous recombination (HR)-directed DNA repair in leukemic cells. GFI1-36N exhibits impaired binding to N-Myc downstream-regulated gene 1 (Ndrg1) regulatory elements, causing decreased NDRG1 levels, which leads to a reduction of O6-methylguanine-DNA-methyltransferase (MGMT) expression levels, as illustrated by both transcriptome and proteome analyses. Targeting MGMT via temozolomide, a DNA alkylating drug, and HR via olaparib, a poly-ADP ribose polymerase 1 inhibitor, caused synthetic lethality in human and murine AML samples expressing GFI1-36N, whereas the effects were insignificant in nonmalignant GFI1-36S or GFI1-36N cells. In addition, mice that received transplantation with GFI1-36N leukemic cells treated with a combination of temozolomide and olaparib had significantly longer AML-free survival than mice that received transplantation with GFI1-36S leukemic cells. This suggests that reduced MGMT expression leaves GFI1-36N leukemic cells particularly vulnerable to DNA damage initiating chemotherapeutics. Our data provide critical insights into novel options to treat patients with AML carrying the GFI1-36N variant.

Standardization in clinical documentation can increase efficiency and can save time and resources.

Deciphering cell-cell communication is a key step in understanding the physiology and pathology of multicellular systems. Recent advances in single-cell transcriptomics have contributed to unraveling the cellular composition of tissues and enabled the development of computational algorithms to predict cellular communication mediated by ligand-receptor interactions. Despite the existence of various tools capable of inferring cell-cell interactions from single-cell RNA sequencing data, the analysis and interpretation of the biological signals often require deep computational expertize. Here we present InterCellar, an interactive platform empowering lab-scientists to analyze and explore predicted cell-cell communication without requiring programming skills. InterCellar guides the biological interpretation through customized analysis steps, multiple visualization options, and the possibility to link biological pathways to ligand-receptor interactions. Alongside convenient data exploration features, InterCellar implements data-driven analyses including the possibility to compare cell-cell communication from multiple conditions. By analyzing COVID-19 and melanoma cell-cell interactions, we show that InterCellar resolves data-driven patterns of communication and highlights molecular signals through the integration of biological functions and pathways. We believe our user-friendly, interactive platform will help streamline the analysis of cell-cell communication and facilitate hypothesis generation in diverse biological systems.

Spiral drawings on paper are used as routine measures in hospitals to assess Parkinson's Disease motor deficiencies. In the age of emerging mobile health tools and Artificial Intelligence a comprehensive digital setup enables granular biomarker analyses and improved differential diagnoses in movement disorders. This study aims to evaluate on discriminatory features among Parkison's Disease patients, healthy subjects and diverse movement disorders. Overall, 24 Parkinson's Disease patients, 27 healthy controls and 26 patients with similar differential diagnoses were assessed with a novel tablet-based system. It utilizes an integrative assessment by combining a structured symptoms questionnaire-the Parkinson's Disease Non-Motor Scale-and 2-handed spiral drawing captured on a tablet device. Three different classification tasks were evaluated: Parkinson's Disease patients versus healthy control group (Task 1), all Movement disorders versus healthy control group (Task 2) and Parkinson's Disease patients versus diverse other movement disorder patients (Task 3). To systematically study feature importances of digital biomarkers a Machine Learning classifier is cross-validated and interpreted with SHapley Additive exPlanations (SHAP) values. The number of non-motor symptoms differed significantly for Tasks 1 and 2 but not for Task 3. The proposed drawing features partially differed significantly for all three tasks. The diagnostic accuracy was on average 94.0% in Task 1, 89.4% in Task 2, and 72% in Task 3. While the accuracy in Task 3 only using the symptom questionnaire was close to the baseline, it greatly improved when including the tablet-based features from 60 to 72%. The accuracies for all three tasks were significantly improved by integrating the two modalities. These results show that tablet-based drawing features can not only be captured by consumer grade devices, but also capture specific features to Parkinson's Disease that significantly improve the diagnostic accuracy compared to the symptom questionnaire. Therefore, the proposed system provides an objective type of disease characterization of movement disorders, which could be utilized for home-based assessments as well.Clinicaltrials.gov Study-ID: NCT03638479.

Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to NOTCH inhibitors, which corresponded to high expression of NOTCH receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

Cladribine is a highly effective immunotherapy that is applied in two short-term courses over 2 years and reduces relapse rate and disease progression in patients with relapsing multiple sclerosis (MS). Despite the short treatment period, cladribine has a long-lasting effect on disease activity even after recovery of lymphocyte counts, suggesting a yet undefined long-term immune modulating effect.

StudyPortal was implemented as the first multilingual search platform for geographic visualization of clinical trials and scientific articles. The platform queries information from ClinicalTrials.gov, PubMed, a geodatabase and geographic maps to enable geospatial study search and real-time rendering of study locations or research networks on a map. Thus, disease-specific clinical studies or whole research networks can be shown in a geographic proximity. Moreover, a semantic layer enables multilingual disease input and autosuggestion of medical terms based on the Unified Medical Language System. The portal is accessible on https://studyportal.uni-muenster.de. This paper presents details on implementation of the novel search platform, its search evaluation and future work.

Chimeric antigen receptor (CAR) engineering of T cells allows one to specifically target tumor cells via cell surface antigens. A candidate target in Ewing sarcoma is the ganglioside GD2, but heterogeneic expression limits its value. Here we report that pharmacological inhibition of Enhancer of Zeste Homolog 2 (EZH2) at doses reducing H3K27 trimethylation, but not cell viability, selectively and reversibly induces GD2 surface expression in Ewing sarcoma cells. EZH2 in Ewing sarcoma cells directly binds to the promoter regions of genes encoding for two key enzymes of GD2 biosynthesis, and EZH2 inhibition enhances expression of these genes. GD2 surface expression in Ewing sarcoma cells is not associated with distinct in vitro proliferation, colony formation, chemosensitivity, or in vivo tumorigenicity. Moreover, disruption of GD2 synthesis by gene editing does not affect its in vitro behavior. EZH2 inhibitor treatment sensitizes Ewing sarcoma cells to effective cytolysis by GD2-specific CAR gene-modified T cells. In conclusion, we report a clinically applicable pharmacological approach for enhancing efficacy of adoptively transferred GD2-redirected T cells against Ewing sarcoma, by enabling recognition of tumor cells with low or negative target expression.