The Cell Cycle Regulator CCDC6 Is a Key Target of RNA-Binding Protein EWS

<div><p>Genetic translocation of EWSR1 to ETS transcription factor coding region is considered as primary cause for Ewing sarcoma. Previous studies focused on the biology of chimeric transcription factors formed due to this translocation. However, the physiological consequences of heterozygous EWSR1 loss in these tumors have largely remained elusive. Previously, we have identified various mRNAs bound to EWS using PAR-CLIP. In this study, we demonstrate CCDC6, a known cell cycle regulator protein, as a novel target regulated by EWS. siRNA mediated down regulation of EWS caused an elevated apoptosis in cells in a CCDC6-dependant manner. This effect was rescued upon re-expression of CCDC6. This study provides evidence for a novel functional link through which wild-type EWS operates in a target-dependant manner in Ewing sarcoma.</p></div

EWS downregulation affects apoptosis, cell cycle and proliferation.

<p><b>A</b>. Decrease in the relative mRNA levels of FBXW7 upon knocking down EWS. <b>B</b>. Relative mRNA levels of FUS, EWS and TAF15 (FET family proteins) upon EWS knock down. <b>C</b>. Total percentage of living, necrotic and apoptotic cells after EWS and scrambled siRNA knockdown are represented on the bars. Apoptotic cells are defined by the sum of population of cells in early apoptosis and late apoptosis. Mock, scrambled and EWS KD had 10%, 11.8% and 20% apoptotic cells and 17%, 22% and 30% of necrotic cells respectively. The P values refer to the apoptotic cell population. <b>D</b>. Rescue effect upon co-transfection of EWS siRNA and CCDC6 overexpression. Bars represent total percentage of living, apoptotic and necrotic cells. 50nM siRNA, 100ng of empty vector and 100ng of CCDC6 expression vector were transfected. Mock and scrambled had 15% and 18.6% of apoptotic cells, EWS KD and EWS KD+ Empty vector had 39% and 40.5% apoptotic cells respectively and EWS KD+ CCDC6 vector had only 24% apoptotic cells. The P values refer to the apoptotic cell population. <b>E</b>. Proliferation rates on three consecutive days using CCK8 assay was calculated by measuring the absorbance which is proportional to the amount of living cells. <b>F</b>. Quantification of cell cycle distribution. The bars indicate the % of cells in each cell cycle phase subG1, G0/G1, S and G2/M phase. Mock has 11.3%, 44.7%, 16%, 28% of cells in subG1, G0/G1, S and G2/M phase respectively. 16%, 42%, 15%, 27% of cells for scrambled and 37%, 44%, 5%, 14% of cells for EWS KD in each phase respectively. The calculated P values refer to the cells in S phase. Data in all the above figures (A-F) is presented as mean SEM values (*P<0.05; where n = 3 per group).</p

Regulation of targets by EWS in vivo.

<p><b>A</b>. Protein domain organization of EWS and FLI1. The black vertical arrows indicate common breakpoints in Ewing sarcoma. Numbers correspond to exons and a typical EWS-FLI1 fusion protein is also shown. Note that the RNA-binding domain of EWS is lost in the process of translocation. <b>B</b>. Pie diagram showing the distribution of PAR-CLIP clusters across 3’UTR, 5’UTR, intronic and coding regions of Refseq RNAs. The three diagrams give the cluster distribution of all sequenced EWS PAR-CLIP targets, all targets regulated by EWS and the four targets we validated (FGF9, MDM2, CBFB, CCDC6). <b>C</b>. Relative mRNA levels of targets genes FGF9, MDM2, CBFB, CCDC6 and EWS in HEK293T cells following EWS knockdown assayed by qRT-PCR (mock: only transfection reagent used; scrambled: AllStars Negative Control siRNA; EWS: siRNA targeting EWS). Relative mRNA levels were normalized to beta actin and quantified relative to the mock and scrambled control levels. Results are shown as mean SEM values (*P < 0.05; n = 3 per group). <b>D</b>. Amount of CCDC6 mRNA transcript percentage is measured upon knocking down of EWS as compared to control. The level of transcript was measured by qRT-PCR after knocking down for 24 hours followed by treatment with actinomycin D. The linear regression and slopes were calculated and the data is presented as Mean and SEM on a linear scale. <b>E</b>. Luciferase activity of CCDC6 upon EWS transfection (normalized to empty psiCHECK-2 plasmid). Data is shown as the fold increase in luciferase activity (RLU units) relative to control. Results are shown as the mean SEM values (*P<0.05; n = 3 per group). <b>F</b>. Relative mRNA levels of CCDC6 and EWS in mock, control and EWS knockdown in MHH-ES-1 cells. Knockdown of EWS decreased the expression of CCDC6. The mRNA levels were normalized to beta actin. Data is represented as mean SEM values (*P<0.05; n = 3 per group). <b>G</b>. Western blot showing the downregulation of CCDC6 upon EWS knockdown in MHH-ES-1 cells. Antibodies are indicated.</p

Additional file 3: of Challenges of palliative care in children with inborn metabolic diseases

Figure S3. Overview of the different medication (A) and care tool (B) categories. Children with intercurrent metabolic crises are shown in black and children without metabolic crises in grey. To enable the comparison, relative prescription frequencies are reported. (JPG 252 kb

Additional file 2: of Challenges of palliative care in children with inborn metabolic diseases

Figure S2. Comparison of signs and symptoms of children with intercurrent metabolic crises (black) and children without metabolic crises (grey) at the end of care (last 30 days). P-values obtained from Wilcoxon rank sum tests with continuity correction are show on top. A) Comparison of overall signs and symptoms. B) Comparison of detailed respiratory symptoms. C) Comparison of detailed gastrointestinal symptoms. D) Comparison of detailed neurological symptoms. (JPG 159 kb

Additional file 1: of Challenges of palliative care in children with inborn metabolic diseases

Figure S1. Signs and symptoms of children with intercurrent metabolic crises (black) and children without metabolic crises (grey) at referral (first 30 days of care). P-values obtained from Wilcoxon rank sum tests with continuity correction are show on top. A) Comparison of overall signs and symptoms. B) Comparison of detailed respiratory symptoms. C) Comparison of detailed gastrointestinal symptoms. D) Comparison of detailed neurological symptoms. (JPG 135 kb

Genomic Inverse PCR for Exploration of Ligated Breakpoints (GIPFEL), a New Method to Detect Translocations in Leukemia

<div><p>Here we present a novel method “Genomic inverse PCR for exploration of ligated breakpoints” (GIPFEL) that allows the sensitive detection of recurrent chromosomal translocations. This technique utilizes limited amounts of DNA as starting material and relies on PCR based quantification of unique DNA sequences that are created by circular ligation of restricted genomic DNA from translocation bearing cells. Because the complete potential breakpoint region is interrogated, a prior knowledge of the individual, specific interchromosomal fusion site is not required. We validated GIPFEL for the five most common gene fusions associated with childhood leukemia (MLL-AF4, MLL-AF9, MLL-ENL, ETV6-RUNX1, and TCF3-PBX1). A workflow of restriction digest, purification, ligation, removal of linear fragments and precipitation enriching for circular DNA was developed. GIPFEL allowed detection of translocation specific signature sequences down to a 10⁻⁴ dilution which is close to the theoretical limit. In a blinded proof-of-principle study utilizing DNA from cell lines and 144 children with B-precursor-ALL associated translocations this method was 100% specific with no false positive results. Sensitivity was 83%, 65%, and 24% for t(4;11), t(9;11) and t(11;19) respectively. Translocation t(12;21) was correctly detected in 64% and t(1;19) in 39% of the cases. In contrast to other methods, the characteristics of GIPFEL make it particularly attractive for prospective studies.</p></div

Basic principle of GIPFEL.

<p>Upon restriction digest and circularization of genomic DNA only genomic DNA from translocation bearing cells will form circles that join DNA of two different chromosomes. The junction is predetermined by the location of the genomic breakpoint. By probing for all possible ligation junctions with PCR the presence of a translocation can be ascertained.</p

MicroRNAs Distinguish Cytogenetic Subgroups in Pediatric AML and Contribute to Complex Regulatory Networks in AML-Relevant Pathways

<div><h3>Background</h3><p>The role of microRNAs (miRNAs), important post-transcriptional regulators, in the pathogenesis of acute myeloid leukemia (AML) is just emerging and has been mainly studied in adults. First studies in children investigate single selected miRNAs, however, a comprehensive overview of miRNA expression and function in children and young adults is missing so far.</p> <h3>Methodology/Principal Findings</h3><p>We here globally identified differentially expressed miRNAs between AML subtypes in a survey of 102 children and adolescent. Pediatric samples with core-binding factor AML and promyelocytic leukemia could be distinguished from each other and from MLL-rearranged AML subtypes by differentially expressed miRNAs including miR-126, -146a, -181a/b, -100, and miR-125b. Subsequently, we established a newly devised immunoprecipitation assay followed by rapid microarray detection for the isolation of Argonaute proteins, the hallmark of miRNA targeting complexes, from cell line models resembling core-binding factor and promyelocytic leukemia. Applying this method, we were able to identify Ago-associated miRNAs and their targeted mRNAs.</p> <h3>Conclusions/Significance</h3><p>miRNAs as well as their mRNA-targets showed binding preferences for the different Argonaute proteins in a cell context-dependent manner. Bioinformatically-derived pathway analysis suggested a concerted action of all four Argonaute complexes in the regulation of AML-relevant pathways. For the first time, to our knowledge, a complete AML data set resulting from carefully devised biochemical isolation experiments and analysis of Ago-associated miRNAs and their target-mRNAs is now available.</p> </div

Ago-associated miRNAs and - mRNAs using the PAR-CLIP-Array method.

<p>(A) Western Blot analysis of immunoprecipitates of human Ago1-4 from AML cell lines, KASUMI-1 with t(8;21) and NB4 carrying t(15;17). The immunoprecipitates show a specific band of the Argonaute protein (∼97 kDa; ←) in contrast to the isotype control antibody (rat IgG2a) and empty-bead control. A representative sample of the biological triplicate is shown. Please note that more material was loaded for Ago3 and Ago4 since these two Ago proteins are much lower expressed as was also validated by qRT-PCR (not shown). Antibodies were tested for specificity for detection of native and denatured protein prior to this experiment with cell lines overexpressing tagged Ago protein (not shown) (B) Validation of miRNA- and mRNA-enrichment in immunoprecipitation experiments. Argonaute proteins (black bar) are compared to the isotype (white bar) and empty bead controls (grey bar) using TaqMan qRT-PCR assays for microRNA- (upper panel) and SYBR Green qRT-PCR assays for mRNA-quantification (lower panel). Shown are the measured levels (2^−CT) of six and five miRNAs of KASUMI-1 cells (upper left panel) and NB4 cells (upper right panel), respectively. Immunoprecipitation experiments as well as cDNA synthesis were each done in triplicates and the mean value of the nine values as well as one standard deviation is depicted. miRNAs differentially expressed in patient samples between the t(8;21) and t(15;17) were selected together with ubiquitously expressed miR-16. Please note that calculation of ΔC_T-values is not possible due to the lack of a housekeeping gene bound to Argonaute proteins. Six Ago-associated mRNAs in the KASUMI-1 cells (lower left panel) and NB4 cells (lower right panel), covering the whole range from low to high enrichment over isotype control according to microarray data, were selected for qRT-PCR validation. Graphs are centered around a C_T-value of 29.9 cycles (2^−CT = 0⁻⁹).</p