Die Rolle des Wilms-Tumorproteins (WT1) in der Organentwicklung

Die Organogenese beschreibt den Prozess der Bildung der verschiedenen Organe und Gewebe in einem Organismus und wird durch verschiedene Signalwege streng kontrolliert. Transkriptionsfaktoren spielen hier für die Regulation der Genexpression eine wichtige Rolle. Die Mechanismen der Organogenese zu verstehen, ist für die Vorbeugung und die Behandlung von Krankheiten, sowie für die Entwicklung regenerativer Therapien, wichtig. Wilms-Tumorprotein (WT1) ist ein Transkriptionsfaktor, der in der Organogenese eine wichtige Rolle einnimmt. WT1 kontrolliert unter anderem die Expression von Genen, die für Wachstumsfaktoren und deren Rezeptoren, Transkriptionsfaktoren, extrazelluläre Proteine und Zellzyklusregulatoren kodieren. WT1 wird während der Embryonalentwicklung in einer Vielzahl von Geweben exprimiert, unter anderem in den Nieren, Gonaden, der Leber, dem Herzen und dem Mesothel. Mutationen im WT1-Gen werden mit verschiedenen Krankheiten in Verbindung gebracht, darunter Wilms-Tumor, Denys-Drash-, Frasier- und WAGR-Syndrom. Neben seiner Rolle in der Entwicklung wurde die WT1 Expression auch in erwachsenen Geweben und Zellen beobachtet, hauptsächlich in den Nieren und im Knochenmark. Aufgrund seiner möglichen Rolle in der Tumorgenese ist WT1 als Ziel therapeutischer Interventionen Gegenstand umfangreicher Forschungsarbeiten. WT1 wird spezifisch in Vorläuferzellen des viszeralen, nicht aber des subkutanen weißen Fettgewebes exprimiert. Neuere Erkenntnisse deuten darauf hin, dass thermogene Gene, die im braunen Fettgewebe exprimiert werden, vor allem im subkutanen weißen Fettgewebe induziert werden können. In dieser Arbeit konnte gezeigt werden, dass WT1 dieses thermogene Programm in weißen Fettzellen unterdrückt. WT1 zeigt eine starke Expression in hämatopoetischen Stammzellen und Vorläuferzellen. Es spielt eine wichtige Rolle bei der Bildung und Differenzierung dieser Zellen, indem es die Genexpression während der Zelldifferenzierung reguliert. Mutationen im WT1-Gen wurden mit einer Reihe von Blutkrankheiten in Verbindung gebracht, darunter akute und chronische myeloische Leukämie. In dieser Arbeit konnte gezeigt werden, dass WT1 ein direkter transkriptioneller Aktivator des Erythropoietin-Rezeptor Gens ist und hierdurch die Erythropoese beeinflusst. WT1 reguliert mehrere Schritte der Gonadenentwicklung. Fehlt bei Mäusen die WT1 Expression, dann wird die Gonadenbildung eingeleitet, jedoch degeneriert das Gewebe aufgrund von Apoptose. In dieser Arbeit konnte gezeigt werden, dass WT1 ein direkter transkriptioneller Aktivator des A Disintegrin-Like And Metalloprotease With Thrombospondin Type 1 Motif 16 (Adamts16) Gens ist und wie sich diese Aktivierung auf die Entwicklung der Gonade auswirkt. WT1 hat sich als wichtiger Regulator der Nierenentwicklung erwiesen, der eine entscheidende Rolle bei der Differenzierung und Erhaltung von Nierenvorläuferzellen spielt. In dieser Arbeit konnte gezeigt werden, dass WT1 ein transkriptioneller Regulator der kupferhaltigen Aminoxidase 1 (Aoc1) ist. AOC1 ist ein Regulator des Polyaminsystems, so dass WT1 über die Regulation des Polyaminsystems Einfluss auf die Nierenentwicklung nimmt. Zudem konnte gezeigt werden, dass Aoc1 bei verschiedenen experimentellen Nierenschädigungen Aoc1 in hohem Maße verstärkt exprimiert wird, was zu einer erheblichen Verringerung des Putrescin-Gehalts der Niere führte. Zudem konnte eine bemerkenswert ähnliche Veränderung der Polyamin regulierenden Enzyme in den meisten Nierenpathologien festgestellt werden. Hier zeigte sich eine verringerte Expression von Enzymen, die an der Polyaminsynthese beteiligt sind, zusammen mit einer erhöhten Expression von Polyamin-abbauenden Enzymen. In dieser Arbeit wurden wichtige Erkenntnisse über die Rolle von WT1 bei der Regulation von Genen gewonnen, die für die Entwicklung verschiedener Gewebe und Organe von Bedeutung sind. Die Ergebnisse dieser Studie können dazu beitragen, die Grundlagen der Organogenese besser zu verstehen und neue Ansätze zur Behandlung von Erkrankungen zu entwickeln, die mit Mutationen im WT1 Gen in Verbindung gebracht werden

Change point detection for clustered expression data

Background: To detect changes in biological processes, samples are often studied at several time points. We examined expression data measured at different developmental stages, or more broadly, historical data. Hence, the main assumption of our proposed methodology was the independence between the examined samples over time. In addition, however, the examinations were clustered at each time point by measuring littermates from relatively few mother mice at each developmental stage. As each examination was lethal, we had an independent data structure over the entire history, but a dependent data structure at a particular time point. Over the course of these historical data, we wanted to identify abrupt changes in the parameter of interest - change points. Results: In this study, we demonstrated the application of generalized hypothesis testing using a linear mixed effects model as a possible method to detect change points. The coefficients from the linear mixed model were used in multiple contrast tests and the effect estimates were visualized with their respective simultaneous confidence intervals. The latter were used to determine the change point(s). In small simulation studies, we modelled different courses with abrupt changes and compared the influence of different contrast matrices. We found two contrasts, both capable of answering different research questions in change point detection: The Sequen contrast to detect individual change points and the McDermott contrast to find change points due to overall progression. We provide the R code for direct use with provided examples. The applicability of those tests for real experimental data was shown with in-vivo data from a preclinical study. Conclusion: Simultaneous confidence intervals estimated by multiple contrast tests using the model fit from a linear mixed model were capable to determine change points in clustered expression data. The confidence intervals directly delivered interpretable effect estimates representing the strength of the potential change point. Hence, scientists can define biologically relevant threshold of effect strength depending on their research question. We found two rarely used contrasts best fitted for detection of a possible change point: the Sequen and McDermott contrasts

A link between the fibroblast growth factor axis and the miR‐16 family reveals potential new treatment combinations in mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive malignancy with very limited therapeutic options. Fibroblast growth factor (FGF) signals play important roles in mesothelioma cell growth. Several FGFs and FGF receptors (FGFRs) are predicted targets of the miR‐15/16 family, which is downregulated in MPM. The aim of this study was to explore the link between the miR‐15/16 family and the FGF axis in MPM. Expression analyses via RT‐qPCR showed downregulation of the FGF axis after transfection with miR‐15/16 mimics. Direct interaction was confirmed by luciferase reporter assays. Restoration of miR‐15/16 led to dose‐dependent growth inhibition in MPM cell lines, which significantly correlated with their sensitivity to FGFR inhibition. Treatment with recombinant FGF2 prevented growth inhibition and further reduced the levels of FGF/R‐targeting microRNAs, indicating a vicious cycle between miR‐15/16 down‐ and FGF/FGFR signaling upregulation. Combined inhibition of two independent miR‐15/16 targets, the FGF axis and Bcl‐2, resulted in additive or synergistic activity. Our data indicate that post‐transcriptional repression of FGF‐mediated signals contributes to the tumor suppressor function of the microRNA‐15/16 family. Inhibiting hyperactivated FGF signals and Bcl‐2 might serve as a novel therapeutic combination strategy in MPM

Transcriptional suppression of the miR-15/16 family by c-Myc in malignant pleural mesothelioma

MicroRNA downregulation is frequent in malignant pleural mesothelioma (MPM), but the mechanisms responsible for loss of miR-15/16 and miR-193a are yet to be elucidated and were investigated in this study. Copy Number Variation (CNV) of microRNA-coding genes was analyzed in MPM cells by digital droplet PCR (ddPCR) and revealed heterozygous loss of miR-193a and miR-15a/16-1, but no change in miR-15b/16-2. Epigenetic control of microRNA expression was inferred following decitabine and Trichostatin A (TSA) treatment which did not substantially affect microRNA expression. Knockdown of c-Myc expression led to upregulation of SMC4, miR-15b and 16, and to a lesser extent DLEU2 and miR-15a, whereas c-Myc overexpression repressed microRNA expression. Chromatin immunoprecipitation (ChIP) assays confirmed the interaction of c-Myc with the DLEU2 and SMC4 promoters. Tumor microRNA expression was determined in samples from MPM patients, with samples of pleura from cardiac surgery patients used as controls. In tumor samples, a strong correlation was observed between the expression of miR-15b and 16 (R$^{2}$=0.793), but not miR-15a and 16. Our data suggest that in MPM, the downregulation of miR-15/16 is due to transcriptional repression by c-Myc, primarily via control of the miR-15b/16-2 locus, while miR-193a-3p loss is due to genomic deletion

Adaptation of the Oxygen Sensing System during Lung Development

During gestation, the most drastic change in oxygen supply occurs with the onset of ventilation after birth. As the too early exposure of premature infants to high arterial oxygen pressure leads to characteristic diseases, we studied the adaptation of the oxygen sensing system and its targets, the hypoxia-inducible factor- (HIF-) regulated genes (HRGs) in the developing lung. We draw a detailed picture of the oxygen sensing system by integrating information from qPCR, immunoblotting, in situ hybridization, and single-cell RNA sequencing data in ex vivo and in vivo models. HIF1α protein was completely destabilized with the onset of pulmonary ventilation, but did not coincide with expression changes in bona fide HRGs. We observed a modified composition of the HIF-PHD system from intrauterine to neonatal phases: Phd3 was significantly decreased, while Hif2a showed a strong increase and the Hif3a isoform Ipas exclusively peaked at P0. Colocalization studies point to the Hif1a-Phd1 axis as the main regulator of the HIF-PHD system in mouse lung development, complemented by the Hif3a-Phd3 axis during gestation. Hif3a isoform expression showed a stepwise adaptation during the periods of saccular and alveolar differentiation. With a strong hypoxic stimulus, lung ex vivo organ cultures displayed a functioning HIF system at every developmental stage. Approaches with systemic hypoxia or roxadustat treatment revealed only a limited in vivo response of HRGs. Understanding the interplay of the oxygen sensing system components during the transition from saccular to alveolar phases of lung development might help to counteract prematurity-associated diseases like bronchopulmonary dysplasia

RT-qPCR validation reveals significant lncRNA expression differences in MPM cell lines and fresh-frozen tissue.

<p>Levels of lncRNA expression were normalised to 18S and relative expression levels compared to the average level in the control samples for MPM tissues and MeT-5A for cell lines using the 2^−ΔΔCq method. (a) Unsupervised cluster analysis of the top 44 lncRNAs found to be differentially expressed between MeT-5A and MPM (H226, H28, MSTO, MM05) cell lines using NCode Long Noncoding RNA microarrays. All cell lines were profiled in duplicate. Red  =  regions over-expressed, Blue  =  regions under-expressed. (b) Nine candidate lncRNAs were technically validated in MPM cell lines using RT-qPCR. For RT-qPCR, lncRNA expression levels were normalised to 18S and are expressed relative to MeT-5A. (c) NR_003548 and BX648695 were significantly elevated in MPM tissues compared to benign pleura. Turkey box plots have median values represented by the line within the boxes, and the 25^th and 75^th percentiles represented by the upper and lower lines of the box. (d) 7 candidate lncRNAs were biologically validated in an extended panel of 10MPM cell lines. All candidates demonstrated consistent up-regulation of expression. MPM – Malignant Pleural Mesothelioma, lncRNA – long noncoding RNA, Ctrl – Benign Pleura, * statistically significant at P<0.05 (two-tailed t-test).</p

Class prediction profiling using the six biologically validated lncRNAs demonstrates high sensitivity in predicting MPM class in the NCode Microarray data (data not shown) and cryopreserved MPM and benign pleural tissue.

<p>(a) Supervised cluster analysis shows that this predictor demonstrated overexpression (red areas) in MPM tumours compared to benign pleura. Roc curve analysis shows that (b) NR_003584 and (c) BX648695 can clearly separate benign tumour and MPM tissue with a high degree of accuracy. (d) AK054908 lncRNA expression is associated with hilar lymph node metastasis. (e) Higher EF177379 expression is associated with longer survival.</p

SYBR Green Primer Sequences used for microarray validation of the top 23 lncRNAs identified as being differentially expressed between MeT-5A mesothelial cells and MPM cell lines.

<p>SYBR Green Primer Sequences used for microarray validation of the top 23 lncRNAs identified as being differentially expressed between MeT-5A mesothelial cells and MPM cell lines.</p

Subject Demographics of the two independent validation cohorts.

<p>a*RNA extracted from FFPE for measurement of lncRNA expression; # RNA extracted from fresh-frozen tumour tissue, control tissue is benign pleura.</p

Long Non Coding RNAs (lncRNAs) are dysregulated in Malignant Pleural Mesothelioma (MPM)

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer that is often diagnosed at an advanced stage and is characterized by a long latency period (20-40 years between initial exposure and diagnosis) and prior exposure to asbestos. Currently accurate diagnosis of MPM is difficult due to the lack of sensitive biomarkers and despite minor improvements in treatment, median survival rates do not exceed 12 months. Accumulating evidence suggests that aberrant expression of long non-coding RNAs (lncRNAs) play an important functional role in cancer biology. LncRNAs are a class of recently discovered non-protein coding RNAs >200 nucleotides in length with a role in regulating transcription. Here we used NCode long noncoding microarrays to identify differentially expressed lncRNAs potentially involved in MPM pathogenesis. High priority candidate lncRNAs were selected on the basis of statistical (P3-fold difference). Expression levels of 9 candidate lncRNAs were technically validated using RT-qPCR, and biologically validated in three independent test sets: (1) 57 archived MPM tissues obtained from extrapleural pneumonectomy patients, (2) 15 cryopreserved MPM and 3 benign pleura, and (3) an extended panel of 10 MPM cell lines. RT-qPCR analysis demonstrated consistent up-regulation of these lncRNAs in independent datasets. ROC curve analysis showed that two candidates were able to separate benign pleura and MPM with high sensitivity and specificity, and were associated with nodal metastases and survival following induction chemotherapy. These results suggest that lncRNAs have potential to serve as biomarkers in MPM