A high-content small molecule screen identifies sensitivity of glioblastoma stem cells to inhibition of polo-like kinase 1

Glioblastoma multiforme (GBM) is the most common primary brain cancer in adults and there are few effective treatments. GBMs contain cells with molecular and cellular characteristics of neural stem cells that drive tumour growth. Here we compare responses of human glioblastoma-derived neural stem (GNS) cells and genetically normal neural stem (NS) cells to a panel of 160 small molecule kinase inhibitors. We used live-cell imaging and high content image analysis tools and identified JNJ-10198409 (J101) as an agent that induces mitotic arrest at prometaphase in GNS cells but not NS cells. Antibody microarrays and kinase profiling suggested that J101 responses are triggered by suppression of the active phosphorylated form of polo-like kinase 1 (Plk1) (phospho T210), with resultant spindle defects and arrest at prometaphase. We found that potent and specific Plk1 inhibitors already in clinical development (BI 2536, BI 6727 and GSK 461364) phenocopied J101 and were selective against GNS cells. Using a porcine brain endothelial cell blood-brain barrier model we also observed that these compounds exhibited greater blood-brain barrier permeability in vitro than J101. Our analysis of mouse mutant NS cells (INK4a/ARF(-/-), or p53(-/-)), as well as the acute genetic deletion of p53 from a conditional p53 floxed NS cell line, suggests that the sensitivity of GNS cells to BI 2536 or J101 may be explained by the lack of a p53-mediated compensatory pathway. Together these data indicate that GBM stem cells are acutely susceptible to proliferative disruption by Plk1 inhibitors and that such agents may have immediate therapeutic value

The origin and properties of naïve and primed pluriopotent stem cells.

<p>The origin and properties of naïve and primed pluriopotent stem cells.</p

Branching topology of the human embryo transcriptome revealed by Entropy Sort Feature Weighting.

Analysis of single cell transcriptomics (scRNA-seq) data is typically performed after sub-setting to highly variable genes (HVGs). Here we show that Entropy Sorting provides an alternative mathematical framework for feature selection. On synthetic datasets, continuous entropy sort feature weighting (cESFW) outperforms HVG selection in distinguishing cell state specific genes. We apply cESFW to six merged scRNA-seq datasets spanning human early embryo development. Without smoothing or augmenting the raw counts matrices, cESFW generates a high-resolution embedding displaying coherent developmental progression from 8-cell to post-implantation stages and delineating 15 distinct cell states. The embedding highlights sequential lineage decisions during blastocyst development while unsupervised clustering identifies branch point populations obscured in previous analyses. The first branching region, where morula cells become specified for inner cell mass or trophectoderm, includes cells previously asserted to lack a developmental trajectory. We quantify the relatedness of different pluripotent stem cell cultures to distinct embryo cell types and identify marker genes of naïve and primed pluripotency. Finally, by revealing genes with dynamic lineage-specific expression we provide markers for staging progression from morula to blastocyst

Protocol for the generation of oligodendrocytes from NS cells.

<p>NS cells propagated in NS-A medium plus N2 in the presence of EGF and FGF2 (A) were cultured in DMEM/F12 plus N2 in the presence of FGF2, PDGF and forskolin for 4 days on polyornithine/laminin coated plastic (B) before they were induced to differentiate by growth factor withdrawal in the presence of 3,3,5-tri-iodothyronine hormone (T3) and ascorbic acid (AA) (C,D). After four days, immunostaining for the O4 antigen revealed differentiation into oligodendrocytes (C). The differentiated cultures also contained GFAP-positive astrocytes and ß-III tubulin/TUJ1-positive neurons (C,D), demonstrating the tripotential differentiation capacity of these cells.</p

Generation of <i>Rex1</i> reporter cells.

<p><b>A</b>. qRT-PCR analysis of <i>Rex1</i> and <i>Oct4</i> mRNA during monolayer differentiation in N2B27. <b>B</b>. Strategy to create the <i>Rex1^GIP</i> knock in allele. <b>C</b>. Flow cytometry of a representative Rex1-Egfp profile in undifferentiated NN97-5 cells. E. Flow cytometry of Rex1-Egfp population in NN97-5 cells during monolayer differentiation in N2B27.</p

Tripotential differentiation of NS cells in vitro and generation of myelinating oligodendrocytes in vivo.

<p>(A–E) Quantitative marker expression and representative immunofluorescence images. The specific culture conditions used to differentiate NS cells resulted in the generation of oligodendrocytes (∼20%) positive for O4 (B), Rip (D) and PLP (E), GFAP-expressing astrocytes (∼40%; C–D) and neurons positive for ß-III tubulin/TUJ1 (∼10%; C). (F–H) NS cells cultured in N2 medium and proliferated for 4 days in the presence of FGF2, PDGF and forskolin were transplanted into the brain of 2- to 3-day-old myelin-deficient rats. Two weeks after transplantation, the engrafted cells had formed PLP-positive myelin internodes. Shown are representative pictures from septum (F) and corpus callosum (G–H). Scale bars B–D, 100 µm; F–H, 20 µm.</p

Mechanistic explanation and simulation results for the LIF/serum scenario.

<p>(A) Model scheme. Autocrine FGF4/Erk signalling is proposed to inhibit the transcription of Nanog at rate p. In the LIF/serum scenario Erk signalling is active (i.e. p>0). (B) Bifurcation diagram. Assuming a constant transcription rate s4 (vertical red line) under LIF/serum mESCs are captured in a bistable region (p = 15) with respect to Nanog expression. (C) Single cell trajectories. The diagram shows simulated trajectories of Oct4-Sox2 (grey), Nanog (green) and Rex1 (blue) concentrations for the LIF/serum scenario. (D) Simulated TF distributions of Nanog (green) and Oct4-Sox2 (grey) within mESC populations at time point t = 4320 min (i.e. 3 days of in silico culture). In the LIF/serum scenario Nanog is subject to state changes establishing a bimodal TF distribution. The curves are normalized to match the local maxima for high expression states under LIF/serum conditions. (E) Comparison of the simulation result for Rex1 (blue line) with experimental data (grey histogram) obtained from flow cytometry analysis of Rex1GFPd2 mESCs maintained in LIF/serum. The parameter set used for these simulations is given in Table S1 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092496#pone.0092496.s001" target="_blank">File S1</a>.</p

Model scheme of the regulatory network of mESC pluripotency.

<p>The core network (inner grey square) is composed of the TFs Oct4-Sox2, Nanog and Rex1, which are linked by positive feedback and feedforward loops (black arrows). The respective transcription rates are denoted by s_i. The extended network (outer grey square) includes FGF4/Erk signalling and a differentiation signal Y, the latter facilitating the double-negative feedback loop from Nanog on all factors of the core network. FGF4/Erk is activated by Oct4-Sox2 and represses Nanog with rate p. High Nanog levels block the transmission of differentiation signal Y. The internal part of the differentiation cascade (denoted by Y_in) negatively regulates the expression of Oct4-Sox2, Nanog and Rex1.</p

The regulation of Dusp1 and Dusp6 activity and ES cell differentiation.

<p>(A–C) RT-qPCR analysis of <i>dusp1</i> and <i>dusp6</i> mRNA expression in mouse ES cells. Data are normalised by the average values of three reference genes (ref) and are presented as means ± SEM and are the average of three biological replicates (n = 3). (A) The kinetics of <i>dusp1</i> and <i>dusp6</i> expression at the indicated times following 2i withdrawal. (B) The effects of the indicated inhibitors, either alone or in combination, on the expression of <i>dusp1</i> and <i>dusp6</i> at the indicated times following inhibitor withdrawal. (C) The effects of depletion of the indicated genes on <i>dusp1</i> and <i>dusp6</i> mRNA expression in the presence of 2i. The blue dashed line indicates the threshold level (2× SD above the mean of the negative controls) and levels below this are indicated by red bars. The average activity in the presence of control siRNA (ctrl) is shown by the solid grey line (taken as 100). (D and E) Active ERK levels were determined by the ratio of phospho-ERK (pERK)/total ERK (ERK) levels at the indicated times following 2i release in the presence of the indicated siRNAs (red lines) or control siRNA (blue lines). The data are plotted relative to maximal levels with the control siRNA (taken as 100) and are presented as means ± SEM from the average of two biological replicates (n = 2). (F and G) The change in the ratio of GFP negative to GFP positive <i>Rex1</i>GFPd2 cells 28 hrs after 2i withdrawal in the presence of the siRNAs against the indicated <i>dusp</i>s relative to control siRNAs is shown. Data are the average of two biological replicates. (H) RT-qPCR analysis of the changes in <i>nanog</i> mRNA expression in <i>Rex1</i>GFPd2 cells upon 2i withdrawal for 28 hrs and depletion of the indicated <i>dusp</i>s. The data are normalised by the average of three reference genes, and presented relative to control siRNAs. Data are presented as means ± SEM and are the average of two biological replicates (n = 2). (I) RT-qPCR analysis of the expression of the indicated lineage marker genes following treatment of cells with siRNAs against <i>dusp1</i> or <i>dusp6</i> or a non-targeting control (ctrl) and release from “2i” for 3 (top) or 5 days (bottom). Data are presented as means ± SEM (n = 2). (J) Summary diagram illustrating the key regulatory role of the Dusps in mediating the action of the ERK pathway in early cell fate decisions during loss of pluripotency and onset of differentiation.</p

Dependency of stable Nanog states on Nanog autoregulation and noise.

<p>(A) The bifurcation diagram indicates the existence of Nanog states depending on the autoregulatory transcription rate s₄. The lower solid line shows the existence of Nanog-low (NL) states and the upper solid line shows the existence of Nanog-high (NH) states. Within the bistable region (shaded in grey) coexisting stable states are separated by unstable states (dashed line). (B) Simulating a cell population, the heat map illustrates the proportion of NL cells depending on the transcription rate s₄ and on the transcriptional noise σ_N at time point t = 4320min (i.e. 3 days of in silico culture). For any value of the background noise, an increase in the transcription rate s₄ reduces the proportion of NL cells.</p