Dasatinib is an ATP-competitive, multi-targeted SRC and ABL kinase inhibitor that can bind BCR-ABL in both the active and inactive conformations. From a clinical standpoint, dasatinib is particularly attractive because it has been shown to induce hematologic and cytogenetic responses in imatinib-resistant chronic myeloid leukemia patients. The fact because the combination of imatinib and dasatinib shows the additive/synergistic growth inhibition on wild-type p210 BCR-ABL-expressing cells, we reasoned that these ABL kinase inhibitors might induce the different molecular pathways. To address this question, we used DNA microarrays to identify genes whose transcription was altered by imatinib and dasatinib. K562 cells were cultured with imatinib or dasatinib for 16 h, and gene expression data were obtained from three independent microarray hybridizations. Almost all of the imatinib- and dasatinib-responsive genes appeared to be similarly increased or decreased in K562 cells; however, small subsets of genes were identified as selectively altered expression by either imatinib or dasatinib. The distinct genes that are selectively modulated by dasatinib are cyclin-dependent kinase 2 (CDK2) and CDK8, which had a maximal reduction of <5-fold in microarray screen. To assess the functional importance of dasatinib regulated genes, we used RNA interference to determine whether reduction of CDK2 and CDK8 affected the growth inhibition. K562 and TF-1BCR-ABL cells, pretreated with CDK2 or CDK8 small interfering RNA, showed additive growth inhibition with imatinib, but not with dasatinib. These findings demonstrate that the additive/synergistic growth inhibition by imatinib and dasatinib may be mediated in part by CDK2 and CDK8.
SRC family kinases regulate multiple cellular events such as proliferation, differentiation, survival, cytoskeletal organization, adhesion and migration as a consequence of their ability to couple with many diverse classes of cellular receptors and many distinct cellular targets (Thomas and Brugge, 1997). SRC kinases are involved in BCR-ABL-mediated transformation and have been implicated in imatinib resistance (Donato et al., 2003; Dai et al., 2004). Multiple domains of BCR-ABL interact with and activate SRC kinases independently of BCR-ABL kinase activity (Warmuth et al., 1997; Stanglmaier et al., 2003). The studies with dominant-negative mutants suggest that SRC kinases may contribute to the proliferation and survival of myeloid cell lines expressing BCR-ABL in vitro (Lionberger et al., 2000). HCK and LYN are expressed and activated in the acute phase of chronic myeloid leukemia (CML) patients, and their upregulation correlates with disease progression and resistance in patients with imatinib (Hofmann et al., 2002; Donato et al., 2003; Dai et al., 2004; Ptasznik et al., 2004). Therefore, dual SRC and ABL kinase inhibitors are attractive for the treatment of imatinib-resistant CML.
Dasatinib is an orally available multitargeted SRC and ABL kinase inhibitor with two-log increased potency relative to imatinib (Shah et al., 2004). Mutations in BCR-ABL that favor the adoption of an active, imatinib-resistant conformation are effectively targeted by dasatinib, as shown in cell lines expressing 14 imatinib-resistant mutants (Shah et al., 2004; Burgess et al., 2005; O'Hare et al., 2005). Dasatinib prolonged survival of mice with BCR-ABL-driven disease, and inhibited proliferation of BCR-ABL-positive bone marrow progenitor cells from patients with imatinib-sensitive or imatinib-resistant CML (Shah et al., 2004). A recent saturation mutagenesis screening of BCR-ABL also found that the spectrum of mutations that would allow for dasatinib resistance is reduced compared with that of imatinib, including L248R, Q252H, E255K, V299L, T315I/A and F317V (Burgess et al., 2005). Molecular docking studies also showed that dasatinib is likely to bind the inactive form of BCR-ABL, although requiring a lower conformational stringency, with the ability of binding more intermediate conformations than imatinib (Gambacorti-Passerini et al., 2005). From a clinical standpoint, dasatinib is particularly hopeful because it has been shown to induce hematologic and cytogenetic responses in imatinib-resistant CML patients (Talpaz et al., 2006). The fact that because the combination of imatinib and dasatinib shows additive/synergistic growth inhibition on wild-type p210 BCR-ABL-expressing cells, we reasoned that these ABL kinase inhibitors might induce different molecular pathways. To address this question, we used DNA microarrays to identify genes whose transcription was altered by imatinib and dasatinib. The distinct genes that are selectively modulated by dasatinib are cyclin-dependent kinase 2 (CDK2) and CDK8. To assess the functional importance of dasatinib-regulated genes, we used RNA interference to determine whether reduction of CDK2 and CDK8 affected the growth inhibition. K562 and TF-1BCR-ABL cells, pretreated with CDK2 or CDK8 small interfering RNA (siRNA), showed additive growth inhibition with imatinib but not with dasatinib. These findings demonstrate that the additive growth inhibition by imatinib and dasatinib may be mediated by CDK2 and CDK8.
Analysis of combined drug effects
First, we investigated the combined use of dasatinib with the anti-leukemic agents imatinib, daunorubicin (DNR), AraC and VP16 in vitro. Previous study demonstrated that imatinib showed additive or synergistic effects in combination with some leukemic agents (Nakajima et al., 2003). We therefore determined whether dasatinib could increase the effects of some anti-leukemic agents, including imatinib, in CML blastic crisis cell line K562. The concentration of anti-leukemic agents is plotted against percentage inhibition of proliferation, and each anti-leukemic agent alone is compared with each anti-leukemic agent in combination with 0.2 nM of dasatinib (Figure 1a). Regression lines generated by Microsoft Excel represent the best-fit relationship between drug concentration and the percentage inhibition of proliferation. R2 values are the square of the correlation coefficient. When imatinib was combined with 0.2 nM of dasatinib, the curve showed a substantial shift downward, consistent with increased antiproliferative activity of the drug combination (Figure 1a). Similarly, with the combination of DNR or VP-16 and dasatinib, the curve also shifted down (Figure 1a). When AraC was combined with dasatinib, the two curves crossed at 500 nM of AraC (Figure 1a). There was no additive effect of the combination of AraC and dasatinib. Although dasatinib and imatinib bind to overlapping sites within the BCR-ABL kinase domain, the clinically available concentrations of imatinib may not exert an interfering effect by restricting the dasatinib's access to its binding site.
Next, we determined whether inhibition of BCR-ABL-tyrosine kinase by co-treatment with dasatinib and imatinib would attenuate the downstream molecules of BCR-ABL (Figure 1b–d). As compared with treatment with either agent alone, co-treatment with imatinib (0.5 μ M) and dasatinib (5 nM) or imatinib (1.0 μ M) and dasatinib (10 nM) for 24 h caused more inhibition of BCR-ABL autophosphorylation (Figure 1b). Combined treatment with imatinib and dasatinib also caused more attenuation of the levels of p-Akt, phosphor-nuclear factor kappa B (NF-κB) and c-Myc, which are downstream of BCR-ABL (Figure 1c and d).
Dasatinib and imatinib-induced gene expression profiles
K562 cells were cultured with dasatinib or imatinib for 16 h, and gene expression data from three independent microarray hybridizations were analysed (GPL 2523) (Figure 2a and b). The microarray experiment data were deposited in GEO (GSE 2810). Although the data in this result demonstrated genuine differential expression, most of these genes showed changes that were relatively small in magnitude. We, therefore, restricted to genes that showed at least a 1.5-fold change. Almost all of the dasatinib or imatinib responsible genes appeared to be similarly changed; however, small subsets of genes were identified as selectively altered in expression by either dasatinib or imatinib (Figures 3 and 4). In 16 h, 155 of the 667 unique dasatinib genes and 144 of the 667 unique imatinib genes were regulated >1.5-fold. This finding suggests that these two structurally diverse BCR-ABL tyrosine kinase inhibitors initially regulate highly overlapping common target genes and pathway. The common genes whose expression was affected by dasatinib and imatinib were categorized into different functional groups based on their biological function, and genes in the cell proliferation and apoptosis categories were examined in greater detail (Figures 3 and 4).
Cell proliferation-related genes
Dasatinib and imatinib affected the expression of several cyclin-dependent kinases (CDK2, CDK4, CDC5R, CDK6 and CDK8), cell division cycle genes (CDC2L5, CDC7, CDC25A and CDC25B) and cyclines (CCNA2, CCNC, CCND2, CCND3, CCNE1, CCNE2 and CCNH) (Figure 3a and b). These regulators are known to be involved in G1/S and G2/M transition, and their decreased gene expression levels and thus reduced activities are essential for cell cycle arrest at early stage. Dasatinib and imatinib also affected the expression of mitotic inhibitors (CDKN1A, CDKN1B, CDKN1C, CDHN2C and CDK2AP1) (Figure 3b). Obviously, downregulation/inactivation of such a large number of cell cycle-related genes may abolish the cell cycle machinery, probably a prerequisite for apoptosis in dasatinib- or imatinib-treated CML cells. The distinct genes that are selectively modulated by dasatinib are CDK2 and CDK8, which had a maximal reduction of <5-fold in microarray screen. CDK2 and CDK8 appeared to be candidates involved in the additive/synergistic growth inhibition by dasatinib and imatinib. Downregulation of these genes can be largely the result of chain reactions of transcriptional inactivation. For instance, CCD2 is known to be directly regulated by MYC at transcriptional sites, and its downregulation is logically linked to downregulated MYC (Figure 3a).
Oncogenic signals genes
Inactivation of BCR-ABL tyrosine kinase by dasatinib or imatinib blocks the transcription factors, and thus represses expression of target genes such as those encoding signal transduction molecules, as highlighted by members of STAT pathway (STAT1, STAT3, STAT4, STAT5A, STAT5B and STAT6) (Figure 3c).
The intrinsic apoptotic pathway is important for dasatinib- or imatinib-mediated apoptosis. Both ABL kinase inhibitors modulated the expression of many genes that play a key role in this pathway, such as BAX, BAK1, BID, BCL2, BCL6, BCL9, MCL1, CASP1, CASP2, CASP3, CASP6, CASP7 CASP8, CASP9 and CASP10 (Figure 4a). Moreover, genes that regulate the induction or prolongation of this pathway, including NF-κB-pathway genes (NF-κB1 and NF-κB1A), were also transcriptionally reduced (Figure 4b). GADD45B, which induces cell cycle arrest at G2/M, was also reduced by dasatinib and imatinib (Figure 4b). Furthermore, genes coding tumor necrosis factor (TNF) family receptors and ligands (TNF, TNFAIP3, TNFRSR5 and TNFRSF12) were activated by dasatinib or imatinib (Figure 4b).
DNA-damage repair genes
BCR-ABL-transformed cells appeared to be better equipped to survive genotoxic damage because of enhanced ability to repair DNA lesions, prolonged activation of the G/2M checkpoint to provide more time for repair, and inhibited apoptosis mechanisms. Dasatinib and imatinib reduced the expression of several DNA-damage repair pathway genes, such as RAD50, RAD51L3, RECQL, XRCC1, XRCC3 and XRCC4 (Figure 4c). Diverse modulation of these DNA-damage repair genes by both ABL kinase inhibitors may participate in the reduced possibility of therapeutic drug resistance.
Validation of expression profiles of selected genes
To verify the changes of CDKs expression, which were identified as selectively altered by either dasatinib or imatinib, we performed the immunoblot analysis focusing on CDK2, CDK3, CDK4, CDK6, CDK8 and CDK9 (Figure 5a). K562 cells were cultured with indicated concentrations of either dasatinib or imatinib for 48 h, and the cell lysates were immunoblotted with the indicated antibodies (Figure 5a). Protein expressions of CDK2 and CDK8 were selectively reduced by dasatinib treatment (Figure 5a). Quantitative real-time PCR analysis of these CDKs confirmed that protein expression changes induced by dasatinib and imatinib correlated with changes in gene expression (data not shown). We also determined the protein expression of CDK2 and CDK8 in TF-1-BCR-ABL cells after dasatinib or imatinib treatment (Figure 5b). Expressions of CDK2 and CDK8 was mainly reduced by dasatinib-treatment (Figure 5b). As caspase-3 activity might affect the reduction of CDK2 or CDK8, therefore, we determined the time-dependent changes of CDK2/CDK8 expression and caspase-3 and poly(ADP-ribose)polymerase (PARP) activation in K562 cells (Figure 5c and d). K562 cells were cultured with either 100 nM of dasatinib or 10 μ M of imatinib for the indicated time, and the cell lysates were immunoblotted with indicated antibodies (Figure 5c and d). The expression of CDK2 or CDK8 proteins was reduced after 24 h of dasatinib treatment (Figure 5c); however, the expression of CDK2 or CDK8 proteins was nearly unchanged after imatinib treatment (Figure 5d). As activation of caspase-3 or PARP was observed 12–24 h after dasatinib or imatinib treatment (Figure 5c and d), it is likely that caspase-3 activity may not be required for the reduction of CDK2/CDK8 protein level.
siRNA-mediated knock down of CDK2 and CDK8 in K562 cells and TF-1BCR-ABL cells
To assess the functional importance of dasatinib- and imatinib-regulated gene, we used RNA interference to determine whether reduction in CDK2 and CDK8 affect the proliferation. K562 and TF-1BCR-ABL cells were transfected with control siRNA or CDK2 siRNA or CDK8 siRNA; then the CDK2 and CDK8 expression was analysed by immunoblotting after 48 h (Figure 6a). The siRNA to CDK2 or CDK8 specifically reduced CDK2 or CDK8 expression (Figure 6a). At 48 h after transfection, K562 and TF-1BCR-ABL cells were treated with the indicated concentration of dasatinib or imatinib for 48 h, and viable cells were counted (Figure 6b and c). Increasing doses of imatinib, in the presence of CDK2 siRNA or CDK8 siRNA, shifted the dose–response curve substantially downward, consistent with increased antiproliferative activity (Figure 6b and c). When dasatinib was treated in the presence of CDK2 siRNA or CDK8 siRNA, the two curves crossed at 200 nM of dasatinib (Figure 6b and c). These results demonstrated that transcriptional repression of CDK2 or CDK8 can play an important role in the combined growth inhibitory effects of dasatinib and imatinib.
Imatinib and dasatinib are clinically active ABL tyrosine kinase inhibitors that show the additive/synergistic growth inhibition on BCR-ABL-expressing cells (Figure 1a). Earlier studies demonstrated that dasatinib and imatinib largely activated common apoptotic pathways, although there were differences in the activities of the two compounds. Dasatinib is capable of binding BCR-ABL with less stringent conformational requirements with respect to imatinib (Gambacorti-Passerini et al., 2005). Although both compounds inhibit BCR-ABL tyrosine kinase, whether these two structurally diverse compounds mediate similar or disparate gene expression changes has not been addressed. In the present study, we used microarray gene expression profiles to identify the genes commonly and selectively regulated by dasatinib and imatinib.
On the basis of clustering, the transcriptional responses induced by dasatinib and imatinib were remarkably similar (Figure 2a). Some degree of overlap was expected because both compounds target BCR-ABL kinase. Compatible with this phenotype, some proapoptotic genes were upregulated, a number of antiapoptotic genes were downregulated by both ABL kinase inhibitors, and a number of genes within the same molecular pathway were coordinately regulated (Figures 3 and 4). These include BAX, BCL-2, MCL-1, CASP2 and CASP10 (Figure 4a). Although some of the proapoptotic genes were repressed (i.e., BID, CASP3 and CASP6), the overall response was one that would provide a strong proapoptotic signal (Figure 4a and b). Moreover, repression of the NF-κB pathway is also associated with apoptotic stimulus (Figure 4b). Furthermore, the transcription of TNF superfamily genes and genes involved in death-receptor signaling (DEDD) was altered by dasatinib or imatinib (Figure 4b).
In addition to inducing apoptosis, ABL kinase inhibitors can suppress cell cycle progression (Gesbert et al., 2000; Parada et al., 2001). The transcriptional response was consistent with growth suppression, and a number of genes within key growth-regulatory pathways were coordinately regulated (Figure 3a and b). For example, decreased expression of MYC, E2F3, E2F4 and E2F5 is consistent with suppression of the MYC pathway (Figure 3a). The number of CDKs and CDK inhibitors, whose expression is highly coordinated to regulate appropriate cell cycle progression, was aberrantly expressed in dasatinib- or imatinib-treated cells (Figure 3b). CDK2 and CDK8 are selectively modulated by dasatinib, which had a maximal reduction of <5-fold in microarray screen (Figure 3a). We have shown that dasatinib and imatinib and the combination of these compounds differently suppress the expression of c-Myc protein (Figure 1d). Recently, Samanta et al. (2006) demonstrated that signal transduction by BCR-ABL/Jak2 network results in phosphorylation of Akt, which leads to the stabilization of c-Myc and activates NF-κB to cause elevation of c-Myc transcripts. As compared with treatment with either agent alone, co-treatment with dasatinib and imatinib caused more attenuation of the levels of phospho-Akt, phospho-NFκB and c-Myc (Figure 1c and d).
As CDK2 is a c-Myc transcriptional target (Prathapam et al., 2006), downregulation of a large number of cell cycle-related genes, including CDK2 and CDK8, could be largely the result of chain reactions of transcriptional inactivation by these ABL tyrosine kinase inhibitors. Earlier study (Riley et al., 2001) demonstrated that v-SRC induces the expression of CDK2 in Rat-1 cells. Therefore, inactivation of c-SRC and SRC-family kinase by dasatinib may decrease the expression of CDK2. Progression through the cell cycle from G1 to S phase requires sequential activation of CDK2 and CDK4 (Sherr and Roberts, 1999). The role of CDK4 is well established; however, CDK2 may be regulated differently in somatic cells and in cancer cells (Tetsu and McCormick, 2003). In BCR-ABL-transformed cells, cyclin D activates CDK4/CDK6, which inturn transactivates cyclin E by releasing E2F. Cyclin E activates CDK2, and BCR-ABL causes relocation of p27 to the cytoplasm, further stimulating CDK2 (Jiang et al., 2000). Therefore, CDK2 seems to have a critical role in cell cycle progression in BCR-ABL-transformed cells. Downregulation of CDK2 or CDK8 by siRNA increased antiproliferative activity in imatinib-treated cells, but not in dasatinib-treated cells (Figure 6a–c). Our results clearly demonstrate that diverse regulation of CDKs by ABL kinase inhibitors may contribute at least in part to additive growth inhibition in these compounds. The pleiotropic molecular sequel of SRC/ABL inhibition does not allow us to conclude which pathways are most important for anti-tumor effect, but potentially offer a major therapeutic advantage, namely the simultaneous targeting of different proliferative/antiapoptotic pathways in tumor cells (Supplementary Figure).
One of the objectives of this study of the molecular profile of dasatinib-treated BCR-ABL-transformed cells was to establish a framework for designing of combination therapies with conventional anti-leukemia agents. This study identified the enhanced antiproliferative activity of combinations with dasatinib with anti-leukemia agents, such as imatinib, daunorubicine and VP-16 (Figure 1a). The ability of dasatinib to suppress genes involved in cell proliferation-related genes (i.e., CDK2, CDK6, CDK8, CDC7, CCNA2, CCNC, CCNE1, CCNE2 and MYC) and antiapoptotic genes (BCL2, MCL1 and NFκB) superior to imatinib constitute a molecular basis for the chemo-sensitizing effect of SRC/ABL kinase inhibition.
This study provides comparative gene expression profiling analysis of the effect of dasatinib and imatinib, two compounds that are clinically active for BCR-ABL-positive leukemia. Both agents commonly target a number of important molecular pathways that regulate cell growth and survival. A single proapoptotic or anti-proliferative pathway may not be critical for the therapeutic effects of ABL kinase inhibitors. The present findings have important implications for the clinical use of dasatinib and imatinib as an anti-leukemia agent, either alone or in combination with other agents.
Materials and methods
Antibodies and reagents
Anti-CDK2 Ab (D-12), anti-CDK3 Ab (Y-20), anti-CDK4 Ab (H-22), anti-CDK6 Ab (C-21), anti-CDK8 Ab (D-9), anti-CDK9 Ab (C-20), anti-actin Ab (C-2) and anti-ABL Ab (24-11) were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA, USA). Antiphosphotyrosine mAb (PY20) was purchased from Becton Dickinson and Company (Franklin Lakes, NJ, USA). Anti-Akt Ab, anti-phospho-Akt (Ser473) Ab, anti-NF-κB p65 Ab and anti-phospho-NF-κB p65 (Ser536) Ab were purchased from Cell Signaling (Beverly, MA, USA). Anti-c-Myc Ab was purchased from NOVUS (Littleton, CO, USA). Dasatinib was kindly provided by Bristol-Myers Squibb (New York, NY, USA). DNR, cytosine arabinoside (Ara C) and etoposide (VP-16) were obtained from Sigma (St Louis, MO, USA).
Cells and cell culture
K562 cells were obtained from the American Type Culture Collection (Rockville, MD, USA). TF-1BCR-ABL cells were described previously (Komatsu et al., 2003). These cell lines were cultured in RPMI1640 (Life Technology Inc., Rockville, MD, USA), supplemented with 10% FCS (Hyclone Laboratories, Logan, UT, USA).
Analysis of combined drug effects
K562 cells were suspended to a final concentration of 1 × 105 cells/ml in fresh medium, plated in 24-well dishes and incubated with anti-leukemic agents alone or in combination with 0.2 nM of dasatinib at 37°C for 72 h. The anti-leukemic agents used were imatinib, DNR, AraC or VP16. The number of cells in each well was counted by flow cytometry, and the cell numbers were normalized by dividing the number of cells in the absence of anti-leukemic agents or with dasatinib alone. The data were plotted as the concentration of anti-leukemic agents against the percentage inhibition of proliferation. To determine the relationship between the percentage inhibition of proliferation and drug concentration, a best-fit regression line was generated by Microsoft Excel.
Oligonucleotide DNA microarray hybridization
We have designed two types of pathway focusing on low-density oligonucleotide microarrays (Novusgene Inc., Tokyo, Japan), which contain 667 selected genes related to cell growth, cell cycle, apoptosis, transcription, DNA repair and cell stress responses (GEO accession number: GPL2523). This DNA chip was made up of tetra-plicate spots of 60-mer highly specific oligonucleotide probes. For DNA microarray analysis of genes, we used 1 μg of mRNA from K562 cells treated with dasatinib or imatinib for 16 h. Hybridization was carried out automatically using Gene TAC Hybridization (Genomic Solution, Ann Arbor, MI, USA) according to the supplier's instructions. The conditions of hybridization were 55°C for 2 h, 50°C for 2 h and 46°C for 2 h, then 42°C for 12 h.
Data analysis and statistic validation
The hybridization signals were scanned by GenePix 4000B Microarray Scanner (Axon Instruments, Union City, CA, USA) as raw data. The scanned data were normalized, verified and analysed using the Genomic Profiler software (Mitsui Knowledge Industry, Tokyo, Japan) as described previously (Ohyashiki et al., 2005; Takaku et al., 2005; Zhang et al., 2006). First, the value was adjusted by subtraction of background fluorescence of an equivalent area. Analysis was carried out by taking the median signal of the probe value for each transcription set, and the 75% rank for the total hybridization was calculated. Microarray data obtained from three independent experiments were then verified in a single file. The normalized log data of fluorescence ratio (Cy5–Cy3) which was quantified for each gene to reflect the relative abundance of gene in each experimental sample compared with reference sample, were deposited with GEO. For statistical analysis of host gene expression, we also utilized a GeneSifter (VizXLabs, Seattle, WA, USA). Analysis of variance, and Student's t-test were performed using GeneSifter. Values of P<0.05 were considered to indicate a statistically significant difference, and the Benjamini–Hochberg algorithm was used for estimation of false discovery rates.
Immunoblotting and immunoprecipitation
Immunoblotting and immunoprecipitation were performed as described previously (Tauchi et al., 1994). Quantitative analysis of CDK2 and CDK8 expression was carried out by analysing hyper-enhanced chemiluminescence (ECL) films of immunoblotting by using a densitometer (Bio-Rad, Hercules, CA, USA).
Small interfering RNA experiments
siRNA oligonucleotides for CDK2 and CDK8 were purchased from Santa Cruz Biotechnology Inc. (Santa Cruz, CA, USA), and resuspended in RNase-free H2O at 20 μ M. siRNA (1.25 μ M) was added to prechilled 0.4 cm-gap electroporation cuvettes (Bio-Rad). K562 (5 × 106) or TF-1BCR-ABL cells (5 × 106) were washed twice in serum-free media and resuspended to 5 × 106 cells per 250 μl of cold, serum-free RPMI 1640. Cells were added to the cuvettes, mixed, and further mixed for 5 min on ice. Cells were then pulsed once at 250 mV, 960 μF and 200 Ω by using a Bio-Rad electroporator. At 48 h after electroporation, protein knock down was determined by immunoblotting, cells were treated with the indicated concentration of dasatinib or imatinib for 48 h, and viable cells were counted by using a Vi-cell XR automated cell viability analyzer (Beckman Coulter, Fullerton, CA, USA). The mean number of viable cells at different concentrations of drug was normalized to the mean number of viable cells in the no-drug sample.
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Cite this article
Nunoda, K., Tauchi, T., Takaku, T. et al. Identification and functional signature of genes regulated by structurally different ABL kinase inhibitors. Oncogene 26, 4179–4188 (2007). https://doi.org/10.1038/sj.onc.1210179
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