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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.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Objective: To evaluate prognostic factors in pediatric patients with gonadal germ cell tumors (GCT). Methods: Patients <18 years with ovarian and testicular GCT (respectively OGCT and TGCT) were prospectively registered according to the guidelines of MAKEI 96. After resection of the primary tumor, patients staged ≥II received risk-stratified cisplatin-based combination chemotherapy. Patients were analyzed in respect to age (six age groups divided into 3-year intervals), histology, stage, and therapy. The primary end point was overall survival. Results: Between January 1996 and March 2016, the following patients were registered: 1047 OGCT, of those, 630 had ovarian teratoma (OTER) and 417 had malignant OGCT (MOGCT); and 418 TGCT, of those, 106 had testicular teratoma (TTER) and 312 had malignant TGCT (MTGCT). Only in MTGCT, older age correlated with a higher proportion of advanced tumors. All 736 teratomas and 240/415 stage I malignant gonadal GCT underwent surgery and close observation alone. In case of watchful waiting, the progression rate of OGCT was higher than that of TGCT. However, death from disease was reported in 8/417 (1.9%) MOGCT and 8/312 (2.6%) MTGCT irrespective of adjuvant chemotherapy and repeated surgery. Conclusions: The different pathogenesis and histogenesis of gonadal GCT reflects sex- and age-specific patterns that define clinically relevant risk groups. Therefore, gender and age should be considered in further research on the biology and clinical practice of pediatric gonadal GCT.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Chronic granulomatous disease (CGD) is a primary immunodeficiency characterized by impaired antimicrobial activity in phagocytic cells. As a monogenic disease affecting the hematopoietic system, CGD is amenable to gene therapy. Indeed in a phase I/II clinical trial, we demonstrated a transient resolution of bacterial and fungal infections. However, the therapeutic benefit was compromised by the occurrence of clonal dominance and malignant transformation demanding alternative vectors with equal efficacy but safety-improved features. In this work we have developed and tested a self-inactivating (SIN) gammaretroviral vector (SINfes.gp91s) containing a codon-optimized transgene (gp91(phox)) under the transcriptional control of a myeloid promoter for the gene therapy of the X-linked form of CGD (X-CGD). Gene-corrected cells protected X-CGD mice from Aspergillus fumigatus challenge at low vector copy numbers. Moreover, the SINfes.gp91s vector generates substantial amounts of superoxide in human cells transplanted into immunodeficient mice. In vitro genotoxicity assays and longitudinal high-throughput integration site analysis in transplanted mice comprising primary and secondary animals for 11 months revealed a safe integration site profile with no signs of clonal dominance.
Nisin-producing Lactococcus lactis strains show a high degree of resistance to the action of nisin, which is based upon expression of the self-protection (immunity) genes nisI, nisF, nisE, and nisG. Different combinations of nisin immunity genes were integrated into the chromosome of a nisin-sensitive Bacillus subtilis host strain under the control of an inducible promoter. For the recipient strain, the highest level of acquired nisin tolerance was achieved after coordinated expression of all four nisin immunity genes. But either the lipoprotein NisI or the ABC transporter-homologous system NisFEG, respectively, were also able to protect the Bacillus host cells. The acquired immunity was specific to nisin and provided no tolerance to subtilin, a closely related lantibiotic. Quantitative in vivo peptide release assays demonstrated that NisFEG diminished the quantity of cell-associated nisin, providing evidence that one role of NisFEG is to transport nisin from the membrane into the extracellular space. NisI solubilized from B. subtilis membrane vesicles and recombinant hexahistidine-tagged NisI from Escherichia coli interacted specifically with nisin and not with subtilin. This suggests a function of NisI as a nisin-intercepting protein.
Gene-modified autologous hematopoietic stem cells (HSC) can provide ample clinical benefits to subjects suffering from X-linked chronic granulomatous disease (X-CGD), a rare inherited immunodeficiency characterized by recurrent, often life-threatening bacterial and fungal infections. Here we report on the molecular and cellular events observed in two young adults with X-CGD treated by gene therapy in 2004. After the initial resolution of bacterial and fungal infections, both subjects showed silencing of transgene expression due to methylation of the viral promoter, and myelodysplasia with monosomy 7 as a result of insertional activation of ecotropic viral integration site 1 (EVI1). One subject died from overwhelming sepsis 27 months after gene therapy, whereas a second subject underwent an allogeneic HSC transplantation. Our data show that forced overexpression of EVI1 in human cells disrupts normal centrosome duplication, linking EVI1 activation to the development of genomic instability, monosomy 7 and clonal progression toward myelodysplasia.
Im Jahre 2004 sind am Universitätsklinikum Frankfurt zwei Patienten mit X-CGD gentherapeutisch behandelt worden. Nach einer initialen Phase mit Nachweis ausreichender Mengen Oxidase-positiver Zellen im Blut der Patienten und einer deutlichen klinischen Besserung vorbestehender Infektionsherde kam es zu einem Verlust der Transgenexpression durch epigenetische Veränderungen des viralen Promotors. Ferner entwickelte sich durch Insertionsmutagenese eine klonale Expansion in der Hämatopoese und schließlich ein myelodysplastisches Syndrom mit Monosomie 7 bei beiden Patienten. In der Zusammenschau mit anderen Gentherapiestudien zur X-CGD zeigt sich, dass bislang ein langanhaltendes Engraftment funktionierender genkorrigierter Zellen nur im Zusammenhang mit einer Insertionsmutagenese beobachtet wurde. Zukünftige gentherapeutische Strategien zur Behandlung der X-CGD müssen das Risiko einer Insertionsmutagenese minimieren und gleichzeitig die Effektivität des Engraftments genkorrigierter Zellen steigern. Dies soll durch den Einsatz von SIN-Vektoren sowie einer Intensivierung der Konditionierung der Patienten erreicht werden.