The t(8;21)(q22;q22) rearrangement represents the most common chromosomal translocation in acute myeloid leukemia (AML). It results in a transcript encoding for the fusion protein AML1-ETO (AE) with transcription factor activity. AE is considered to be an attractive target for treating t(8;21) leukemia. However, AE expression alone is insufficient to cause transformation, and thus the potential of such therapy remains unclear. Several genes are deregulated in AML cells, including KIT that encodes a tyrosine kinase receptor. Here, we show that AML cells transduced with short hairpin RNA vector targeting AE mRNAs have a dramatic decrease in growth rate that is caused by induction of apoptosis and deregulation of the cell cycle. A reduction in KIT mRNA levels was also observed in AE-silenced cells, but silencing KIT expression reduced cell growth but did not induce apoptosis. Transcription profiling of cells that escape cell death revealed activation of a number of signaling pathways involved in cell survival and proliferation. In particular, we find that the extracellular signal-regulated kinase 2 (ERK2; also known as mitogen-activated protein kinase 1 (MAPK1)) protein could mediate activation of 23 out of 29 (79%) of these upregulated pathways and thus may be regarded as the key player in establishing the t(8;21)-positive leukemic cells resistant to AE suppression.
Acute myeloid leukemia (AML) is a complex malignant disease driven by a small population of leukemic stem cells. The t(8;21)(q22;q22) rearrangement represents the most common chromosomal translocation in AML and results in appearance of a transcript encoding for the fusion protein AML1-ETO (AE) (also known as RUNX1-RUNX1T1).1, 2 The AE transcript is found in ∼40% of the patients with AML M2 (French–American–British (FAB) classification).3 AE exerts a dominant negative effect on RUNX1-dependent transcriptional activation, mostly through interaction of its ETO moiety with nuclear corepressors N-CoR and Sin3A that recruit the histone deacetylases, and lead to a lower level of histone acetylation and less-accessible chromatin.4, 5, 6, 7 As a result, AE leads to suppression of a number of specific RUNX1 target genes. Nearly 40–60% of AML patients with the t(8;21) translocation fail to achieve long-term (at least 5 years) disease-free survival.8
The AE protein was shown to impair myeloid differentiation and expand a hematopoietic stem/progenitor cell pool, but was insufficient to cause leukemia, as secondary mutations were required for induction of an AML.9, 10, 11, 12, 13, 14 Point mutations affecting the gene encoding the KIT tyrosine kinase receptor lead to ligand-independent signal activation and are especially frequent in AML M2 with the t(8;21) translocation.15, 16, 17, 18, 19 Overexpression of KIT is even more frequent and was found in 60–80% of all AML patients.15, 20, 21, 22 Previously, it has been reported that ectopic expression of AE leads to activation of KIT expression, but the mechanism of this activation remains unclear.23 It was hypothesized that it may act via inhibition of MIR222/221 induced by AE24 or through the inhibition of transforming growth factor-β1 signaling pathway.23 It is known that the expression of the KIT gene in hematopoietic cells is specifically regulated by a transcriptional complex including SCL, LMO2, GATA-1/GATA-2 and ubiquitous E2A and LDB-1 factors.25, 26 GATA-1 is a transcriptional repressor of KIT and genes encoding its downstream substrates (RAC-1, AKT and MYC) and induces G1-phase arrest of myeloid cells.27 AE, in turn, inhibits GATA-1 by impairing its acetylation.28 Thus, the silencing of AE should lead to the restoration of GATA-1 function that could result in inhibition of KIT.
AE is considered to be one of the most attractive targets for the specific suppression of the t(8;21) translocation-positive tumors,29 and new potential therapeutic approaches have been recently reported.8 However, the effectiveness of this therapy remains unclear because it is still unknown whether the AE-driven activation of key genes, participating in tumor progression, may be sufficiently reversed by downregulation of AE.
In this study we used the RNA interference approach for elucidation of the functional consequences of AE suppression in the t(8;21)-positive AML Kasumi-1 cell line. Following AE silencing with the specific short hairpin RNA (shRNA), we observed significant decrease of KIT expression accompanied by inhibited growth and enhanced apoptosis of the leukemic cells. These effects were distinct from those observed when KIT was targeted by shRNAs directly. We obtained a model cell line of AE-suppressed Kasumi-1 cells that were able to proliferate for many passages, and performed a genome-wide microarray-based screening of gene expression. We found at least 29 intracellular signaling pathways that had been activated in these cells that enhance their survival and proliferation. The majority is connected with extracellular signal-regulated kinase 2 (ERK2; also known as mitogen-activated protein kinase 1 (MAPK1)) signaling and seemed to be negatively controlled by AE. These results reveal the complexity of the AE regulatory function and suggest that the inhibition of AE gene product may require a supplementary therapy to have therapeutic effect. Our study provides important clues for understanding the mechanisms responsible for maintenance of the t(8;21)-positive leukemic cells and establishes a new practical model for studying AML.
Materials and methods
Human acute leukemia cells Kasumi-1, which carry the t(8;22)-generating AE and an activated KIT gene, were cultured in RPMI-1640 medium supplemented with 20% fetal calf serum, 100 units/ml penicillin, 100 μg/ml streptomycin and 1 mM sodium pyruvate at 37 °C and 5% CO2. HEK293T cells were used for generation of lentiviral stock and were cultured in Dulbecco’s modified Eagle’s medium plus 10% fetal calf serum containing 100 units/ml penicillin, 100 μg/ml streptomycin and 1 mM sodium pyruvate at 37 °C and 5% CO2. Kasumi-1 and HEK293T cells were obtained from the Heinrich-Pette Institute, Leibniz Institute for Experimental Virology (Hamburg, Germany).
shRNA coding lentiviral plasmid constructs
The DNA sequences encoding anti-AE, anti-KIT or nonspecific control SCR shRNAs (precursors of small interfering RNAs) were subcloned into the BamHI/EcoRI sites of pLSLP plasmid containing the puromycin resistance marker as previously described.30, 31 Three lentiviral vectors were used that target nonspecific mRNA sequence (shSCR); the junction point of AE mRNA (shAE); and the 5′ region of the KIT mRNA, encoding the extracellular domain (shKIT).
Infectious pseudotyped viral particle production and transduction
The viral stocks containing infectious pseudotyped viral particles were generated by transfecting 5 × 105 HEK293T cells plated in 10 cm Petri dish with 3 μg of shRNA coding lentiviral plasmid, 3 μg gag-pol plasmid and 3 μg pVSV-G expression vector using Lipofectamine 2000 reagent (Invitrogen, Carlsbad, CA, USA). At 6 h after transfection, the medium was changed with RPMI containing 20 mM HEPES. After 16 h, supernatants containing VSV-G pseudotyped viral particles and 8 μg/ml hexadimethrin bromide (Sigma-Aldrich, St Louis, MO, USA) were used to infect Kasumi-1 cells. Medium was changed 24 h after infection with fresh RPMI containing 0.5 μg/ml puromycin. Selection was performed for 10 days. Thus, transduced Kasumi-1 cells expressing shRNA specific to junction region of AE oncogene, and those expressing shRNA specific to KIT, were obtained. Kasumi-1 cells expressing scrambled shRNA with no obvious sequence homology to any cellular RNA were used as a control.
Quantitative real-time PCR
RNA extraction was performed from 1 × 106 cells using Trisol reagent (Invitrogen) in accordance with the manufacturer’s protocol. Approximately 2 μg of RNA was used for the synthesis of complementary (c)DNAs. Real-time PCR was performed in triplicate using the Bio-Rad iQ SYBR Green Supermix and Bio-Rad Mini Opticon System (Bio-Rad laboratories, Hercules, CA, USA) with the following three specific primer pairs:
For AE: sen-5′-IndexTermCGAAGTGGAAGAGGGAAAAG-3′; asen-5′-IndexTermTGAGTCTGGCATTGTGGAGT-3′;
For KIT: sen-5′-IndexTermCATCATGGAGGATGACGAGT-3′; asen-5′-IndexTermCGACCATGAGTAAGGAGGAT-3′;
For human ACTB: sen-5′-IndexTermTGGCACCACACCTTCTACAA-3′; asen-5′-IndexTermGCATACAGGGACAGCACAGC-3′. The expression levels of AE and KIT were normalized to that of the human ACTB.
Cell pellets were resuspended in lysis buffer (150 mM NaCl, 1% Triton X-100, 1% deoxycholate, 0.1% SDS, 50 mM Tris-HCl, pH 7.4, EDTA 1 mM) supplemented with protease inhibitor complete (Roche Diagnostics, Mannheim, Germany) and incubated for 15 min on ice. After centrifugation at 10 000 g for 10 min at 4 °C, the supernatants were collected as whole cell lysates. Protein concentration was determined with BCA assay (Pierce Chemical, Rockford, IL, USA). Western blotting was performed with equal amounts of total protein separated by SDS-PAGE and transferred to nitrocellulose membrane. After blocking, the membrane was incubated with primary antibody for 3 h, and washed and incubated with horseradish peroxidase-conjugated secondary antibody. Immunoreactive staining was performed with ECL plus (GE Healthcare, Waukesha, WI, USA). An autoradiograph on film was obtained with an appropriate exposure time. Blots were probed with antibodies for KIT (Santa Cruz Biotechnology, Santa Cruz, CA, USA) raised against the epitopes amino acids 23–322 of KIT of human origin or with antibodies raised against the epitopes amino acids 186–250 mapping within RHD domain of RUNX1 common with AE (Santa Cruz). As internal loading control, anti-β-actin antibodies (Santa Cruz) were used.
Analysis of cell growth and identification of apoptotic cells by flow cytometry
Transduced Kasumi-1 cells expressing shRNAs were plated into 96-well plates in concentrations of 4 × 104, 2 × 104, 1 × 104 and 0.5 × 104 cells per ml. For the following 10 days, the amounts of cells in each well were counted every second day. Apoptosis was measured by double staining with Annexin V-FITC (Molecular Probes, Eugene, OR, USA) and propidium iodide as it was described previously.32 All measurements were performed on a Beckman Coulter Epix XL4 flow cytometer (Beckman Coulter, Miami, FL, USA). All reported values are means of three independent measurements with s.d.
Analysis of cell cycle
Flow cytometry was used to detect the cell cycle distribution. 1 × 106 Kasumi-1 cells expressing shRNA were harvested and washed with phosphate-buffered saline. The cells were then fixed with ice-cold 70% ethanol at −20 °C overnight. The next day, the cells were washed with phosphate-buffered saline, stained with 50 μg/ml propidium iodide (Sigma-Aldrich) and dissolved in 100 μg/ml RNase A (Sigma-Aldrich). All measurements were performed on a Beckman Coulter Epix XL4 flow cytometer (Beckman Coulter) and analyzed with WinMDI software. All reported values are means of three independent measurements with s.d.
Analysis of KIT protein surface expression analysis by flow cytometry
1 × 106 Kasumi-1 cells expressing shRNA were stained with monoclonal anti-KIT antibodies (Invitrogen). Antibodies were diluted in the ratio of 1:400 in 100 μl of 0.1% bovine serum albumin in phosphate-buffered saline and incubated for 30 min on ice. All measurements were performed on a Beckman Coulter Epix XL4 flow cytometer (Beckman Coulter). All reported values are means of three independent measurements with s.d.
Gene expression microarray experiments
A total of six cell culture samples, including three shAE and three control shSCR specimens, were selected for microarray analysis. Total RNA was extracted using TRIzol (Life Technologies, Gaithersburg, MD, USA) and then reverse-transcribed to cDNA and complementary (c)RNA using the Ambion TotalPrep cRNA Amplification Kit (Invitrogen). The cRNA was quantified using a NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) and adjusted to a concentration of 150 ng/ml. Next, 750 ng of each library was hybridized onto the bead arrays using Illumina HumanHT-12v4 Expression BeadChip (Illumina, San Diego, CA, USA). It has >25 000 annotated human genes and >48 000 probes derived from the National Center for Biotechnology Information (NCBI) RefSeq (Build 36.2, Rel 22) and UniGene (Build 199) databases. The microarray hybridization experiments were done at Genoalalytica (Moscow, Russia).
Analysis of the Interactome databases
In this study, we utilized literature searches of the National Institutes of Health (NIH) PubMed database in order to examine pathways that are regulated by AE expression. This was accomplished by using the following keywords during searches: gene expression, regulation and AE.
To expand the literature search and identify additional targets for AE- positive and -negative regulation, we employed a manually curated proprietary database (MetaCore, GeneGo, St Joseph, MI, USA), and the MetaCore pathway analysis software. In order to visualize the molecular interactions between AE and other proteins, the Ingenuity Pathway Analysis (IPA, Ingenuity Systems, www.ingenuity.com) software and knowledge base and its pathway designer graphical module were utilized.
Functional annotation of gene expression data
For the functional annotation of the primary microarray genome-wide expression data, we applied our original algorithm for the calculation of regulatory pathways activation. Our approach to the transcriptome-wide gene expression analysis implies processing of these results with the signalome knowledge base developed by SABiosciences (http://www.sabiosciences.com/pathwaycentral.php). Our algorithm utilizes the scheme that takes into account only the overall impact of each gene product in the signaling pathway but ignores its position in the pathway graph. The formula used to calculate the pathway strength (PS) for a given sample and a given pathway p is as follows:
Here the case-to-normal ratio, CNRn, is the ratio of expression levels for a gene n in the sample under investigation to the same average value for the control group of samples. The Boolean flag of BTIF (beyond tolerance interval flag) equals to zero when the CNR value has passed simultaneously the two criteria that demark the significantly perturbed expression level from essentially normal: first, the expression level for the sample lies within the tolerance interval, where P>0.05, and second, the value of CNR differs from 1 considerably, or . The discrete value of ARR (activator/repressor role) equals to the following numbers: −1, when the gene/protein n is a repressor of pathway excitation; 1, if the gene/protein n is an activator of pathway excitation; 0, when the gene/protein n can be both an activator and a repressor of the pathway; 0.5 and −0.5, respectively, if the gene/protein n is rather an activator or repressor of the signaling pathway p, respectively. Statistical tests were done with the MATLAB software (Mathworks Inc., Natick, MA, USA).
Downregulation of AE leads to decrease in KIT expression
To obtain a stable reduction in AE expression and to explore its effects on cell growth and KIT expression level, we used shRNA expressing lentiviral vectors described by us before.30, 31 Three different lentiviral vectors were used: shAE that targeted the AML1-ETO junction region; shKIT corresponding to exon 9 of the KIT mRNA; and shSCR encoded for a nonspecific (scrambled) shRNA (Figure 1a). AML Kasumi-1 cells were transduced by either of these vectors, cultivated on puromycin-containing media for 10 days and then total RNA was isolated. Levels of AE and KIT mRNA in transduced cells were measured by real-time reverse transcriptase-PCR. For all the following analyses, Kasumi-1 cells transduced with shSCR vector were used as a control. The shAE-expressing cells showed an ∼90% decrease in AE mRNA level compared with the control (Figure 1b). We also observed an ∼50% reduction in KIT expression after silencing of AE, whereas specific anti-KIT shRNA (shKIT) showed a slightly weaker effect on KIT expression, causing an ∼40% decrease (Figure 1b). Importantly, the cells transduced with shKIT vector showed no change in AE expression, illustrating the lack of a feedback loop in AE and KIT regulation. These results were confirmed by AE and KIT protein level analysis by western blotting and by measuring KIT protein expression on a cell surface using flow cytometry approach (Figures 1c and d).
The shRNA-mediated silencing of AE or KIT leads to suppression of the Kasumi-1 cell growth
Kasumi-1 cells transduced with shRNA lentiviral vectors were plated in the concentration 4 × 104 cells per ml, cultivated for 10 days and the amounts of the cells were quantified. We observed more than twofold decrease in a number of cells transduced with the shAE- or the shKIT-lentiviral vectors compared with the cells transduced with the shSCR construct (Figure 2a). These data suggest that both AE and KIT downregulation have negative effect on Kasumi-1 proliferation.
Importantly, we observed that the growth rate of cells with downregulated AE depends on the density of plated cells, unlike for the control Kasumi-1 cells. When the cells transduced with the shRNA lentiviral vectors were plated at four different concentrations (40 × , 20 × , 10 × and 5 × 103 cells per ml) and cultivated for 10 days, a dramatic reduction of AE-targeted cells proliferation was observed in the plates with lower concentration of cells (Figure 2b). This effect may be caused by the increased requirements of transformed Kasumi-1 cells for an intercellular communication (mediated either by their contacts or by secreted messenger molecules). The growth rate of cells with downregulated AE plated at concentration of 20 000 cells per ml was significantly lower in comparison with cells transduced with the control vector starting from day 6 (Figure 2c).
AE and KIT suppression have different effects on apoptosis and the cell cycle progression
To elucidate the nature of the cell growth suppression, we measured an impact of AE and KIT downregulation on the apoptosis and the cell cycle progression. The percentage of Annexin V-positive/propidium iodide-negative Kasumi-1 cells (with intact membrane and exposed phosphatidylserine) expressing shAE was fourfold higher than in shSCR-expressing cells (Figure 3a). The cells expressing shKIT showed no significant change in the amount of apoptotic cells compared with a control. These data suggest that suppression of AE promotes apoptosis in Kasumi-1 cells and that it is unlikely caused by downregulation of KIT expression.
The cell cycle analysis by flow cytometry showed that 72% of Kasumi-1 shKIT cells were in the G0/G1 phase versus 66% of Kasumi-1 shSCR cells in the same phase (Figure 3b). Downregulation of AE expression led to increase in G0/G1 cell population (70%). The percentage of Kasumi-1 shKIT cells in the G2/M phase was accordingly decreased (from 16% in control cells (shSCR) to 12%).
Transcriptome signature of Kasumi-1 cells with downregulated AE
Although suppression of AE by the shRNA-encoding construct resulted in decrease of Kasumi-1 cell viability, a fraction of the transduced cells stably expressing the shAE RNA was viable, and we were able to culture these cells for 10 passages and more. This cell line may be considered as a model of the resistant leukemic t(8;21) cell population after treatment with the drugs targeting AE.
Thus, we tried to identify molecular changes in these cells that allowed them to survive after silencing of the AE gene. The total RNA was extracted from the shAE and control cells expressing shSCR. We performed genome-wide investigation of gene expression in the shAE and the shSCR cells using an Illumina human HT-12v4 bead array, and experiments were performed in triplicate. In order to identify altered regulatory intracellular pathways, we used our original bioinformatic algorithm. It utilizes the signalome knowledge base developed by SABiosciences, a Qiagen company (http://www.sabiosciences.com/pathwaycentral.php), and allows estimation of activation/downregulation of various pathways. We examined 68 regulatory pathways most frequently associated with cancer (Supplementary Table S1). Among the 68 cancer-associated pathways, 37 are known to have a positive impact on cell survival and proliferation, 15have a negative impact and the remaining 16 are neutral or ambiguous (Supplementary Table S1). The shAE cells were compared with the controls, and the pathway strength (PS) values were calculated. PS index depends on the case-to-norm ratio of the expression signals for all the participants of the particular pathway. PS reflects functional status of the pathway and indicates whether it is up- or down-regulated or intact. The negative PS values correspond to the suppressed pathways and positive to the activated pathways. The absolute values reflect the degree of pathway up/down-regulation (Supplementary Table S1).
With a 0.5 cutoff rate for the absolute value of PS, we identified that in shAE Kasumi-1 cells, 40 of 68 (59%) cancer-associated pathways were upregulated and only 3 of 68 (4%) were downregulated compared with the control shSCR cells. The remaining 25 (37%) pathways were intact (Supplementary Table S1). Overall, these data demonstrate that most of the pathways are implicated in survival of Kasumi-1 cells after AE repression. Among the positive proliferation and survival regulatory pathways (promitotic pathways), 78% were upregulated, whereas only 3% and 19%, respectively, were downregulated or neutral (Figure 4). However, for the negative proliferation and survival regulator pathways (proapoptotic pathways), only 5/15 (33%) were upregulated, 2/15 (13%) were downregulated and the remaining 54% were intact. In good agreement, the median PS values—normalized to the number of pathways in each group—were 1.6 for the promitotic pathways, 0.8 for the neutral and as low as 0.1 for the proapoptotic pathways. This clearly indicates that the persistent shAE cells have an enhanced proportion of intracellular regulatory pathways promoting cell survival and proliferation (Figure 4).
Activation of promitotic signaling in the persistent shAE cells may be directly driven by the inhibition of AE
All the differential gene products included in the intracellular signaling pathways analyzed in this study, and their relative expression levels, can be found in Supplementary Table S2. The pathway architecture and the impact of the differential genes are also visualized in Supplementary Data Set S1. To uncover the AE regulatory network, we used the Ingenuity Pathway Analysis software and database (IPA, Ingenuity Systems) and the MetaCore pathway analysis software (GeneGo), and screened the NCBI PubMed literature database. We identified a total of 75 AE interactions, 29 of which result in AE-dependent activation (Supplementary Figure S1) and 46 in AE-dependent inhibition (Supplementary Figure S2). Among others, AE both promotes and downregulates genes encoding transcription factors (2 and 16, respectively) or microRNA genes (12 and 3, respectively). The literature references for the AE interactions are provided in Supplementary Tables S3 and S4.
The analysis of intracellular signaling pathways enabled to link the repression of AE with essentially all the apparent changes in the intracellular signaling pathways and phenotypic effects detected for the shAE cells (Figure 5).
(i) Promotion of apoptosis. Silencing of AE directly activates transcriptional factors SMAD3 and MEIS1, accessory proteins p300 and CBP, regulatory protein PTEN and tumor suppressor protein p14 (CDKN2A). In concert, inhibition of AE downregulates genes encoding CyclinD1, ID1 and CD44, as well as microRNAs 27 and 181. This effect leads to upregulation of SMAD and p53 signaling pathways and activation of tumor suppressors p14, p15, p16, p21 and p27 that initiate DNA damage-induced repair and response mechanisms and caspase cascade, arrest of the cell cycle and apoptosis.
(ii) Decreased level of KIT. Silencing of AE restores transcription of microRNAs 221 and 222 that directly downregulate expression of KIT.
(iii) Increased promitotic signaling in persistent shAE cells. Besides proapoptotic effects, AE silencing also directly releases expression of proteins promoting cell cycle progression, such as BCL2, GATA1, TCF12, Sp1 and, most importantly, ERK2 (MAPK1). These components combined with the accessory proteins p300 and CBP, in turn, are likely responsible for the apparent activation of several other signaling pathways, including Androgen, Akt, CREB, EGF, ERbB, ERK, Erythropoeitin, Estrogen, FLT3, GPCR, Growth hormone, HGF, HIF1, IGF1, IL2, ILK, Integrin, JAK/STAT, MAPK, NGF, PPAR, Ras, TGF-β, VEGF and Wnt. Together, this leads to the inhibition of apoptosis, increased cell viability and cell cycle progression. Notably, ERK2 alone may be responsible for the activation of at least 23 of the promitotic signaling pathways mentioned above (Figure 5 and Supplementary Table S4).
We conclude, therefore, that both apoptotic and proliferative effects seen in the shAE cells can be explained at the molecular level by the silencing of AE gene. The experimental data have demonstrated the inhibition of cell growth and increase of apoptosis in shAE cells (Figures 2 and 3), but analysis of signaling pathways revealed the activation of both proapoptotic and promitotic signaling that may be responsible for survival of Kasumi-1 cells with suppressed AML1-ETO.
In this study we used RNA interference approach to elucidate the functional consequences of AE suppression in the t(8;21)-positive AML Kasumi-1 cell line. We used lentiviral vectors containing short stretches of inverted DNA sequence that resulted in production of a short hairpin RNA targeting either AE or KIT.
The direct correlation between activation of AE and activation/overexpression of tyrosine kinase receptor KIT has been documented before.15, 23 The full-length AE cooperates with activated KIT to induce acute myeloid leukemia in mice.19 There are a number of hypotheses of how AE cooperates with KIT and how AE may induce KIT overexpression in leukemic cell, but they are largely based on limited experimental data. In particular, it remains unknown whether there is a feedback in AE-inducible KIT overexpression and whether the KIT, in turn, can affect the AE expression.
Previously, we constructed the lentiviral vectors, effectively targeting AE or KIT.30, 31 These vectors were used to obtain stably producing shRNAs specifically silencing AE or KIT in Kasumi-1 cells, derived from an AML patient.33 Here, we report that the suppression of AE oncogene in Kasumi-1 cells affects KIT expression. We studied the functional changes in cells with inhibited expression of activated oncogene AE and the effect of AE suppression on intracellular signaling pathways.
In this study we show for the first time that silencing of AE oncogene in AML cells promotes downregulation of KIT mRNA level and decreases the expression of KIT tyrosine kinase receptor on the cell surface. In contrast, the level of KIT does not affect the AE expression in Kasumi-1.
Next, we showed the significant decrease in Kasumi-1 growth rate after transduction with shRNA lentiviral vector specifically targeting the junction point of mRNA encoding AE. These data are in a good agreement with the previous results of cell culture transfection with exogenous chemically synthesized small interfering RNA and confirm the positive role of AE in leukemic cell growth.34, 35 We showed that the transduction of the Kasumi-1 cells with shRNA-expressing lentiviral vector targeting KIT leads to reduction in cell growth rate, in comparison with the same cells transduced with the control vector.
We found that the shRNA-mediated silencing of AE significantly increases the amount of apoptotic cells in Kasumi-1 population, but silencing of KIT does not stimulate apoptosis. We also found increased percentage of cells in the G0/G1 phase of the cell cycle and reduced portion of cells in the S and G2/M phases for both cell lines expressing shKIT or shAE. Thus, the decreased population growth of Kasumi-1 cells transduced with shAE may be caused by stimulation of apoptosis and reduced proliferation rate mediated by AE-dependent downregulation of KIT. Further investigation of this phenomenon is essential for understanding the underlying mechanisms.
In leukemic cells the oncoprotein AE directly and indirectly disregulates functions of genes responsible for normal hematopoiesis. We showed that the shRNA silencing of AE can lead to up- or down-regulation of various gene products responsible for apoptosis, proliferation and self-renewal of cells. We obtained stable population of AE-suppressed Kasumi-1 cells. We suggest these cells as the model cell line for studying t(8;21)-positive leukemia resistant to AE inhibition.4, 8, 29 We provide evidence that the inhibition of AE protein or gene alone may be insufficient to treat the leukemic cells. We obtained the model Kasumi-1 cell line with suppressed AE that escapes cell death by activating signaling pathways enhancing cell survival and proliferation. In particular, we identified 29 upregulated pathways promoting proliferation in the persistent shAE cells. Importantly, activation of all these pathways may be explained by the molecular events that occur in leukemic cells with suppressed AE. We identified that the protein ERK2 (MAPK1), one of the key regulators responsible for normal and tumor cell proliferation,36, 37 can mediate activation of 23/29 (79%) of these pathways and, thus, may be regarded as the key player in establishing the anti-AE therapy-resistant phenotype. We speculate that supplementing AE-specific therapy with targeting ERK2 and/or other members of AE regulatory network may be advantageous in developing treatments of t(8;21)-positive leukemia.
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This work was supported by the Programs of the Presidium of the Russian Academy of Sciences: ‘Molecular and Cell Biology’, ‘Fundamental Research Basics in Nanotechnology and Nanomaterials’, ‘Dynamics and Conservation of Genomes’ and the Russian Foundation for Basic Research (grant nos. 13-04-00599-a, 14-04-00821-a, 14-04-32108, 12-0433094 and 10-04-00593-a). We thank ‘UMA Foundation’ for their support in preparation of the manuscript.
The authors declare no conflict of interest.
Supplementary Information accompanies this paper on the Leukemia website
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Spirin, P., Lebedev, T., Orlova, N. et al. Silencing AML1-ETO gene expression leads to simultaneous activation of both pro-apoptotic and proliferation signaling. Leukemia 28, 2222–2228 (2014) doi:10.1038/leu.2014.130
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