Inhibition of CK1 affects Viability and Survival of Glioblastoma Cells

In comparison to other fatal diseases cancer of the brain and the nervous system is quite rare. The majority of the primary intrinsic tumors which not arise from meninges or nerves is derived from glia cells and is therefore named “gliomas”. Complete tumor resection is usually impossible because these tumors penetrate deep into the brain leading to damage in brain circuits, alterations of blood vessels and blood flow, and tissue swelling. Patients with the diagnosis of the most common and deadly form “glioblastoma multiforme” (GBM) survive only in rare cases (< 30%) for more than two years after diagnosis even with the most aggressive treatments. Despite 30 years of research comprising diverse agents and delivery systems the survival rate for GBM patients has not changed significantly [1]. For the development of novel therapies, it is desirable to gain a deeper understanding of the biology of GBM. So far, the influence of different pathways, interacting in a concerted manner in GBM development has not been fully understood. Wnt/ β-catenin (Wnt) and sonic hedgehog (SHH) signaling are among the major pathways, which are known to be dysregulated in higher grade brain tumors and are responsible for cellular migration, proliferation, and improved survival of tumor cells. Furthermore, Wnt and SHH signaling contribute to maintenance, proliferation, and clonogenicity of glioma cancer stem cells playing a crucial role in initiation and pathogenesis of the malignancy ( reviewed in [2]. ) As central signal transduction molecules, protein kinases of the CK1 family are involved in regulating the activities of Wnt and SHH signaling pathways and therefore, members of the CK1 family represent promising new drug targets [3].


Introduction
In comparison to other fatal diseases cancer of the brain and the nervous system is quite rare. The majority of the primary intrinsic tumors which not arise from meninges or nerves is derived from glia cells and is therefore named "gliomas". Complete tumor resection is usually impossible because these tumors penetrate deep into the brain leading to damage in brain circuits, alterations of blood vessels and blood flow, and tissue swelling. Patients with the diagnosis of the most common and deadly form "glioblastoma multiforme" (GBM) survive only in rare cases (< 30%) for more than two years after diagnosis even with the most aggressive treatments. Despite 30 years of research comprising diverse agents and delivery systems the survival rate for GBM patients has not changed significantly [1]. For the development of novel therapies, it is desirable to gain a deeper understanding of the biology of GBM. So far, the influence of different pathways, interacting in a concerted manner in GBM development has not been fully understood. Wnt/ β-catenin (Wnt) and sonic hedgehog (SHH) signaling are among the major pathways, which are known to be dysregulated in higher grade brain tumors and are responsible for cellular migration, proliferation, and improved survival of tumor cells. Furthermore, Wnt and SHH signaling contribute to maintenance, proliferation, and clonogenicity of glioma cancer stem cells playing a crucial role in initiation and pathogenesis of the malignancy ( reviewed in [2]. ) As central signal transduction molecules, protein kinases of the CK1 family are involved in regulating the activities of Wnt and SHH signaling pathways and therefore, members of the CK1 family represent promising new drug targets [3].
The CK1 family is an independent phylogenetic family of highly conserved, monomeric, and second messenger-independent serine/threonine-specific kinases. Six CK1 isoforms (α, γ1-3, δ, and ε) as well as several splice variants were identified in humans [3]. Members of the CK1 family phosphorylate numerous proteins which are involved in the regulation of important cellular processes like proliferation, differentiation, apoptosis, DNA repair, and chromosomal segregation. Mutations and/or dysregulation of CK1 isoforms (expression and/or activity) might be critically involved in tumorigenesis [3,4]. Inhibition of CK1 family members can be achieved by various specific small molecule inhibitor compounds and peptides which have been described in literature in recent years [3,5,6]. Inhibition of CK1 isoforms has already shown beneficial effects on the viability and proliferation of tumor cells in vitro [5][6][7][8][9][10][11]. as well as in vivo [12][13][14]. Here, we report novel effects of two previously described CK1 isoform-selective inhibitors on established glioblastoma cell lines.

Cell lines
The established human glioblastoma cell lines used in this study were ordered from the German Collection of Microorganisms and Cell Cultures (Leibniz Institute DMSZ), Braunschweig, Germany. An overview of the characteristics and culture conditions of the used cell lines is given in Table 1.

MTT Viability Assay
MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays were performed in 96-microwell format in order to analyze possible effects of tested inhibitor compounds on cell proliferation or cytotoxic influence leading to cell death. Cells were seeded in a density of 5 x 10 4 viable cells/ml (SNB-19) or 1 x 10 5 cells/ml (DK-MG, LN-405, U-138) in a total volume of 200 µl per well and allowed to attach for 24 h under standard cultivation conditions. Cells were treated with the indicated concentrations of inhibitor compounds. Cells treated with DMSO (used as solvent for inhibitor compounds) served as controls. After 48 h cells were incubated for 4 h with 10 µl MTT solution (5 mg/ml in PBS) per well. MTT-containing medium was removed and 100 µl acidified isopropanol (0.04 N HCl in isopropanol) were added per well and while shaking the plates for 30 min the formed precipitate was solubilized. The resulting solution was finally measured spectrophotometrically at a wavelength of 570 nm and a reference wavelength of 650 nm. GraphPad Prism 6 software was used to generate charts for cell viability. The results obtained from treated cells were normalized by using the mean optical density of the DMSO-treated cells as reference. Each experiment was performed with four biological replicates. In order to determine the half maximal effective concentration (EC 50 ) for the tested inhibitor compounds cells were first treated for 48 h. Then the inhibitorcontaining medium was exchanged and cells were treated for another 72 h prior to photometric analysis.

Cell Cycle Analysis
For performing cell cycle analyses 5 x 10 5 viable cells/well (DK-MG, LN-405, U-138) or 2 x 10 5 cells/well (SNB-19), respectively, were seeded in 6-well cell culture plates and allowed to attach for 24 h. Cells were then treated with 20 µM concentration of inhibitor compounds. Untreated and DMSO-treated cells served as controls. After 48 h cells were washed once with PBS prior to preparation for cell cycle analysis using the CycleTEST™ PLUS DNA Reagent Kit (BD Bioscience) as indicated in the manufacturer's protocol. Briefly, 1 ml of buffer solution was added per well and the cells were scraped off the surface and collected by centrifugation at 400 x g for 5 min at room temperature. The cell pellet was re-dissolved in 200 µl of Solution A (trypsin buffer) by flicking the tube. After an incubation at room temperature for 10 min 180 µl of Solution B (trypsin inhibitor and RNase buffer) were added and gently mixed. After incubating the suspension for another 10 min at room temperature 180 µl of chilled Solution C (propidium iodide stain solution) were added to the mixture and a final incubation step was performed on ice for 10 min. Prior to measurement samples were filtered through a 50-µmnylon mesh and stored on ice until analysis in a FACScan flow cytometer (Becton-Dickinson, Franklin Lakes, USA). For each sample 20,000 events were counted. Doublets were discriminated and resulting data were used to study cell cycle distribution and DNA aneuploidy.  Since glioblastoma multiforme is highly resistant to common combined radio-and chemotherapy, there is a serious need to identify new targets for drug development. As indicated by a database research mRNA levels of CK1δ as well as other CK1 isoforms is increased in glioblastoma tumor tissue samples [4].

Viability of glioblastoma cell lines is affected by inhibition of CK1
With the purpose to test whether members of the CK1 family actually represent possible targets for new therapeutic approaches for glioblastoma, two previously published CK1 isoform-selective small molecule inhibitors were tested for their effects on established glioblastoma cell lines. These two difluoro-dioxolo-benzoimidazole derivatives, compounds Richter-1 (afterwards referred to as compound 1) and Richter-2 (compound 2), respectively, were previously characterized as highly potent inhibitors displaying remarkable selectivity toward CK1δ and inhibited cell proliferation of different tumor cell lines [10]. In order to determine whether these inhibitors are also able to affect the viability of various glioblastoma cell lines SNB-19, DK-MG, LN-405, and U-138-MG cells were initially treated with 20 µM of each compound for 48 h.
Following treatment with compound 1 only minor effects on cell viability could be observed for all tested glioblastoma cell lines. The strongest effect was observed for the fast-growing cell line SNB-19, which showed a reduction of cell viability by 18%. In contrast, treatment with compound 2 induced more remarkable reduction of cell viability in all cell lines while best effects could be determined for cell lines SNB-19 and DK-MG showing reduction of cell viability by 72% and 56%, respectively (Figure 1

CK1 isoform-specific inhibitors as effective inducers of glioblastoma cell death
In subsequent experiments flow cytometry was used to analyze the apoptosis rate and cell cycle distribution of glioblastoma cell lines SNB-19 and DK-MG, which showed most sensitive responses to inhibitor treatment in the previous experiments. Cells were exposed to 20 µM of the CK1δ-selective inhibitor compound 2 for 48 h, stained with propidium iodide as described in the materials and methods section, and the cellular DNA content was finally measured by flow cytometry. For both cell lines non-treated and DMSO-exposed cells displayed normal cell cycle distribution of asynchronously proliferating cells with only a small amount of dead cells (SubG 1 less than 1%). In both cell lines, treatment with compound 2 led to significant changes in cell cycle distribution. In SNB-19 cells inhibitor treatment resulted in a massive increase in the amount of dead cells (52.91%; Figures 3A & 3B).  In DK-MG cells both, the amount of dead cells (22.27%) as well as the amount of cells in G 2 /M phase (31.79%), was increased ( Figures 3A & 3B). Presented data are representative for analyses at least performed in triplicate. In Figure 3B distributionof cells to different cell cycle phases (SubG 1 , G 1 , S, G 2 /M, aneuploid cells) is shown as DNA content histograms for SNB-19 and DK-MG cells.

Discussion
Glioblastoma multiforme is the most common and most deadly type of primary brain tumors in adults. Despite multimodal therapy regimens comprising surgery, radiotherapy, and chemotherapy the median survival of patients remains poor. Therefore, interest has increased in identifying new targets for drug development. Members of the CK1 family represent such a new target. In the present study, we demonstrated that the tested difluoro-dioxolo-benzoimidazole derivative compound 2 led to significantly reduced cell viability and altered cell cycle distribution in established glioblastoma cell lines. We previously reported on compounds 1 and 2 as highly potent and CK1δ-selective small molecule inhibitors, which significantly affect the viability of established tumor cell lines when used in a low concentration range [10]. In comparison to the lead compound 1, which showed strongest inhibitory effects on CK1 isoform δ in vitro, treatment with the more advanced compound 2, however, resulted in more pronounced effects on cell viability and obtained EC 50 values were in the submicromolar range with 0.105 µM for BxPC3 and 0.112 µM for A2780 cells [10]. This massive improvement of intracellular availability for compound 2 was achieved by consequent improvement of molecule size, solubility, and cell permeability. Also in the present study, treatments with compound 2 led to more remarkable effects on cell viability and induction of cell death in the tested glioblastoma cell lines.
In general, these observations are in line with previously published results showing that CK1 inhibitors can influence colon, pancreatic, and lymphoma tumor cell kinetics by different mechanisms, resulting either in cell cycle arrest in G 2 /M phase or cell death, and that the effects of CK1-specific inhibitors depend on the cellular background of the cells, especially on their p53 status [7,15,16]. Differences in the cellular background might explain the differences in the sensitivity of the tested cell lines toward treatment with compound 1 or 2. On the one hand, cell lines SNB-19 and DK-MG might show more pronounced effects when treated with the inhibitor compounds because of their shorter doubling time compared to LN-405 and U-138-MG cells ( see Table 1). On the other hand, SNB-19 and DK-MG cells show different results in cell cycle distribution analyses because of differences in their p53 status. While DK-MG cells express wild-type p53 [17]. and treatment with compound 2 results in cell death as well as increased amount of cells arrested in G 2 /M, SNB-19 cells express mutant p53 [17][18][19]. and primarily respond with increased cell death following inhibitor treatment [7,15,20]. Thus, our data demonstrate that the cellular effects induced by the inhibitor treatment considerably depend on the cellular background, in particular on the mutation status of p53. In conclusion, our results for the first time showed that viability and survival of glioblastoma cells are massively affected following inhibition of CK1δ by CK1 isoform-selective small molecule inhibitors. These data might represent a starting point for new therapeutic strategies for glioblastoma and highlight the role of the cellular background which necessarily needs to be considered for developing strategies for personalized medicine [21,23].