Epigenetische Veränderungen in Tumoren : Untersuchung der DNA-Methylierung in prognostischen Subgruppen der Chronischen Lymphatischen Leukämie und im Medulloblastom

Epigenetische Veränderungen können zur Entstehung und Progression von Krebs beitragen. Aberrante DNA-Methylierung von CpG-reichen Abschnitten der DNA in Promotorregionen kann zur Repression von Tumorsuppressorgenen oder Aktivierung von Onkogenen führen. In dieser Arbeit wurden zwei verschiedenen Tumorentitäten, die Chronische Lymphatische Leukämie (CLL) und das Medulloblastom, mittels aPRIMES, einer neuen Methode zur genomweiten Analyse von DNA-Methylierung, untersucht, um neue epigenetische Veränderungen zu identifizieren, die zur Pathogenese beitragen können. CLL ist eine neoplastische Erkrankung der B-Zellen und ist charakterisiert durch Apoptoseresistenz und die Akkumulation von reifen B-Zellen klonalen Ursprungs in peripherem Blut, Knochenmark und Lymphknoten. Hier wurden in allen untersuchten Patienten Veränderungen der DNA-Methylierung gegenüber den Kontrollen gefunden. Viele der aberrant methylierten CpG-Islands waren mit Genen assoziiert, die krebsrelevante Funktion besitzen. Durch Expression Profiling konnte gezeigt werden, dass die Expression einiger dieser Gene ebenfalls dereguliert war. Außerdem konnte ein diagnostischer Marker, der Methylierungsstatus des CpG-Islands CpG002172, identifiziert werden. Beim Vergleich von Patientengruppen mit unterschiedlicher Prognose zeigte sich, dass Patienten mit einer aggressiveren Form der CLL eine weit höhere Anzahl von aberrant methylierten CpG-Islands aufwiesen als Patienten mit guter Prognose, und dass sich die Methylierungsmuster dieser Gruppen signifikant unterscheiden. Außerdem konnte in funktionellen Analysen demonstriert werden, dass die Aktivität des PI3-Kinase-Signalwegs und die Expression des in diesen beiden prognostischen Subgruppen differenziell methylierten und exprimierten Gens MTP18 zur Variabilität bezüglich der Prognose beitragen könnte. Das Medulloblastom ist ein aggressiver Gehirntumor, der vor allem im Kindesalter auftritt. Er zeichnet sich durch eine hohe Proliferationsrate aus, ist stark invasiv und bildet Metastasen. In dieser Arbeit wurden zwei Medulloblastom-Mausmodelle (Ptch+/- und Ptch+/-;Nos-/-) der Methylierungsanalyse mit aPRIMES unterzogen. Die Dopplemutante Ptch+/-;Nos-/- weist eine gegenüber der Ptch+/--Einzelmutante höhere Tumorinzidenz und eine geringere Überlebensrate auf. Beim Vergleich der Cerebelli juveniler und adulter Mäuse wurde eine in den adulten Mäuse hypermethylierte CpG-reiche Region identifiziert, die viele regulatorische piRNAS (piwi-interacting RNA) enthält, die im sich entwickelnden Embryo exprimiert werden und in gene silencing involviert sind, vor allem in die Inaktivierung von Transposons. Beim Vergleich von gesunden Cerebelli und Tumorgewebe wurde Mcm5 als Kandidat identifiziert. Dieses Gen kodiert einen Replikations-Initiations-Faktor und könnte somit zur hohen Proliferationsrate von Medulloblastomzellen beitragen. Außerdem ist es in der Lage, p53-vermittelten Wachstumsarrest aufzuheben. Zwischen den untersuchten Maus-Tumormodellen wurden keine signifikanten Unterschiede im DNA-Methylierungsmuster gefunden. DNA-Methylierung spielt hier also - anders als bei der CLL - wahrscheinlich keine entscheidende Rolle bei der unterschiedlichen Aggressivität der Tumore. Zusammenfassend konnten in beiden untersuchten Entitäten Veränderungen der DNA-Methylierung gefunden werden, die zur Pathogenese beitragen können, im Falle der CLL möglicherweise auch zu der Variabilität bezüglich Prognose und Symptomatik

The impact of pulsed current waveforms on Li dendrite initiation and propagation in solid-state Li batteries

Lithium dendrites are amongst the key challenges hindering Solid-State Li Batteries (SSLB) from reaching their full potential in terms of energy and power density. The formation and growth of these dendrites cause an inevitable failure at charge rates far below the threshold set by industry (>5 mA/cm2) and are supposedly caused by stress accumulation stemming from the deposited lithium itself. Herein, we demonstrate that MHz pulsed currents can be used to increase the current density by a factor of six, reaching values as high as 6.6 mA/cm2 without forming Li dendrites. To understand the origin of this improvement we propose an extension of previous mechanisms by considering the Li activity as a critical factor. The Li activity becomes relevant when Li is geometrically constrained, and the local plating rate exceeds the exchange current density. Over a critical Li activity, the solid-state electrolyte close to the tip of the dendrite fractures and releases the accumulated elastic energy. These events deteriorate the functional and mechanical performance of the SSLB. Since the buildup of a critical Li activity requires a certain time, the application of current pulses at shorter time scales can be used to significantly improve the rate-performance of SSLB, representing a potential step towards the practical realization of electric vehicles and other emerging applications

Smart Medical Information Technology for Healthcare (SMITH): Data integration based on interoperability standards

Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. “Smart Medical Information Technology for Healthcare (SMITH)” is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH’s goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. Objectives: To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. Governance and Policies: SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals’ Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. Methodology and Architectural Framework: To share medical and research data, SMITH’s information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM2 for enterprise architecture modeling supports a consistent development process. The DIC reference architecture determines the services, applications and the standardsbased communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. Use Cases: The methodological use case “Phenotype Pipeline” (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case “Algorithmic Surveillance of ICU Patients” (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a “hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections” (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. Discussion: SMITH’s strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals’ information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period

Interference with energy metabolism by 5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside induces HPV suppression in cervical carcinoma cells and apoptosis in the absence of LKB11

Carcinogenesis is a dynamic and stepwise process, which is accompanied by a variety of somatic and epigenetic alterations in response to a changing microenvironment. Hypoxic conditions will select for cells that have adjusted their metabolic profile and can maintain proliferation by successfully competing for scarce nutritional and oxygen resources. In the present study we have investigated the effects of energy depletion in the context of HPV (human papillomavirus)-induced pathogenesis. We show that cervical carcinoma cell lines are susceptible to undergoing either growth arrest or cell death under conditions of metabolic stress induced by AICAR (5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside), a known activator of the AMPK (AMP-activated protein kinase). Our results reveal that AICAR treatment leads to a reduced binding affinity of the transcription factor AP-1 (activator protein-1) and in turn to a selective suppression of HPV transcription. Moreover, the outcome of AICAR on proliferation and survival was dependent on p53 activation and the presence of LKB1, the major upstream kinase of AMPK. Using non-malignant LKB1-expressing somatic cell hybrids, which lose expression after tumorigenic segregation, as well as small interfering RNA LKB1 knockdown approaches, we could further demonstrate that expression of LKB1 protects cells from cytotoxicity induced by agents which modulate the ATP/AMP ratio. Since simulation of low energy status can selectively eradicate LKB1-negative cervical carcinoma cells, AICAR may represent a novel drug in the treatment of cervical cancer

Epigenetic Upregulation of lncRNAs at 13q14.3 in Leukemia Is Linked to the <i>In Cis</i> Downregulation of a Gene Cluster That Targets NF-kB

<div><p>Non-coding RNAs are much more common than previously thought. However, for the vast majority of non-coding RNAs, the cellular function remains enigmatic. The two long non-coding RNA (lncRNA) genes <i>DLEU1</i> and <i>DLEU2</i> map to a critical region at chromosomal band 13q14.3 that is recurrently deleted in solid tumors and hematopoietic malignancies like chronic lymphocytic leukemia (CLL). While no point mutations have been found in the protein coding candidate genes at 13q14.3, they are deregulated in malignant cells, suggesting an epigenetic tumor suppressor mechanism. We therefore characterized the epigenetic makeup of 13q14.3 in CLL cells and found histone modifications by chromatin-immunoprecipitation (ChIP) that are associated with activated transcription and significant DNA-demethylation at the transcriptional start sites of <i>DLEU1</i> and <i>DLEU2</i> using 5 different semi-quantitative and quantitative methods (aPRIMES, BioCOBRA, MCIp, MassARRAY, and bisulfite sequencing). These epigenetic aberrations were correlated with transcriptional deregulation of the neighboring candidate tumor suppressor genes, suggesting a coregulation <i>in cis</i> of this gene cluster. We found that the 13q14.3 genes in addition to their previously known functions regulate NF-kB activity, which we could show after overexpression, siRNA–mediated knockdown, and dominant-negative mutant genes by using Western blots with previously undescribed antibodies, by a customized ELISA as well as by reporter assays. In addition, we performed an unbiased screen of 810 human miRNAs and identified the <i>miR-15/16</i> family of genes at 13q14.3 as the strongest inducers of NF-kB activity. In summary, the tumor suppressor mechanism at 13q14.3 is a cluster of genes controlled by two lncRNA genes that are regulated by DNA-methylation and histone modifications and whose members all regulate NF-kB. Therefore, the tumor suppressor mechanism in 13q14.3 underlines the role both of epigenetic aberrations and of lncRNA genes in human tumorigenesis and is an example of colocalization of a functionally related gene cluster.</p> </div

Downregulation of 13q14.3 candidate tumor suppressor genes and upregulation of lncRNA genes <i>DLEU1</i> and <i>DLEU2/Alt1</i> correlates with DNA-methylation.

<p>(A–C) Expression of the protein-coding genes <i>KPNA3, C13ORF1</i> and <i>RFP2</i>, the miRNA genes <i>miR-15a</i> and <i>miR-16-1</i> and the lncRNA transcripts from genes <i>DLEU1, DLEU2</i> and <i>alternative transcript Alt1</i> were quantified with qRT-PCR in CLL cells from patients with retention of both copies of 13q14.3 (“p”, n = 34; see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003373#pgen.1003373.s007" target="_blank">Table S1</a>) and compared to B-cells from healthy donors (“h”, n = 20). Mean expression is indicated by a black horizontal line. “HKG” = housekeeping genes, average of <i>PGK, LMNB1</i> and <i>PPIA</i>. (D, E) DNA-methylation levels correlate with transcript levels of genes in 13q14.3: While expression (y-axis) of candidate tumor suppressor genes is directly correlated to DNA-methylation of regions D6 and E6 (x-axis; left panel), lncRNA genes are anti-correlated (right panel). Pearson correlation coefficients are color-coded, blue = negative, yellow = positive correlation. (F) Pearson coefficients of correlation of gene expression (rows) and DNA-methylation at D6 and E6 (columns), colour coded (see legend). DLEU1a = exon1 to exon4; DLEU1b = exon 1 to exon 2; ALT1a/b = exon1, two different amplicons (G) Significance values of Pearson correlation coefficients (t-distribution), values p<0.05 are coded green. (H) The bidirectional promoter of <i>DLEU1</i> and <i>DLEU2</i> and the flanking CpG island was cloned into pCpGL luciferase vector, either including D6 (orange) or excluding D6 (green). (I) Constructs depicted in (H) were either methylated <i>in-vitro</i> using SSsI methylase (m, dark bars) or left unmethylated (u, light bars) and subsequently transfected into Mec1, Granta519 and HeLa cells and luciferase activity quantified. Grey: Luciferase CMV expression vector (V) not containing CpGs was used as negative control, green: excluding D6 region, orange: including D6 region. Error bars signify standard deviation of 2 independent experiments, each performed in duplicate. No changes were detected for E6 (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003373#pgen.1003373.s004" target="_blank">Figure S4G</a>–<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003373#pgen.1003373.s004" target="_blank">S4J</a>). (J) Binding of the DNA-methylation sensitive chromatin reader CTCF was enriched in CLL samples both in the D6 and E6 regions compared to non-malignant B-cells. CTCF-bound chromatin was immunoprecipitated and quantitated with qPCR. Specific binding was shown by quantification of a sequence not bound by CTCF 2 kb upstream of the DM1 insulator (“ctr”). Statistics were performed using Wilcoxon rank sum test (*** p<0.001, ** p 0.001 to 0.01, * 0.01 to 0.05 and ns not significant p>0.05).</p

The critical region at 13q14.3 displays relaxed chromatin at the transcriptional start site (TSS) of the long non-coding RNA genes <i>DLEU1</i> and <i>DLEU2</i> in CLL cells.

<p>The critical region on 13q14.3 was analyzed for DNA-methylation (lanes 1–3), distribution of histone modifications (lanes 4, 5) and gene expression (lanes 6, 7). DNA-hypomethylation was detected in CLL cells at the transcriptional start sites of the lncRNA genes <i>DLEU1</i> and <i>DLEU2</i> variant <i>Alt1</i>. This finding coincides with enrichment of H3K4me2 and depletion of macroH2A, corroborating relaxation of 13q14.3 in CLL. While expression of the protein coding genes and <i>DLEU2</i> is decreased in CLL cells, lncRNA genes <i>DLEU1</i> and <i>DLEU2/Alt1</i> show upregulation, suggesting a direct regulation by DNA-methylation. Base pair positions on top refer to genome GRCh37 build hg18. The conserved CpG islands (A–E) are shown in green, less stringent CpG islands shown in light green. <i>Lane 1</i>: Methyl-CpG Immunoprecipitation (MCIp) allowed semi-quantitative DNA-methylation analysis in non-malignant B-cells sorted from healthy donors (n = 7) and CLL samples (n = 25). Precipitated DNA was hybridized onto a custom tiling microarray covering the 13q14.3 critical region. Depicted is the median log2 fold enrichment of CLL samples from which the median of log2 fold enrichment of healthy donor B-cell samples has been subtracted. <i>Lane 2</i>: Restriction digest-based analysis of DNA-methylation (aPRIMES) was performed in CpG islands C–E at 13q14.3 at 1 kbp resolution. Shown is the median log2 signal intensity of CLL patients from which the median of non-malignant B cell samples has been subtracted. <i>Lane 3</i>: Hypomethylation at D6 and E6 was validated by BioCOBRA and MassARRAY/Sequenome analyses (for details see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003373#pgen-1003373-g002" target="_blank">Figure 2</a>). Shown is the difference of the median percentage of methylation in CLL cells and non-malignant B cells. <i>Lanes 4,5</i>: ChIP was performed for macroH2A (lane 4) and H3K4me2 (lane 5). Precipitated DNA was quantified using qPCR. Enrichment was normalized to non-specific IgG and two control promoters (CDH12, HK2) that displayed similar enrichment for the two histone marks in CLL samples (n = 7) and peripheral blood mononuclear cells (PBMC) from healthy probands (n = 5). Enrichment was calculated as median log2 fold enrichment in precipitate vs. input for CLL samples after subtraction of enrichment from non-malignant B-cells. <i>Lane 6</i>: Gene expression profiling (GEP) was performed using bead chip arrays (Illumina) in CLL patients (n = 25) and sorted B-cells from healthy donors (n = 9). Plotted is the difference of log fold changes of CLL samples and non-malignant B cells. <i>Lane 7</i>: QRT-PCR for gene expression analysis of 13q14.3 candidate genes (for details see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003373#pgen-1003373-g003" target="_blank">Figure 3</a>).</p