Functional analyses of Src-like adaptor (SLA), a glucocorticoid-regulated gene in acute lymphoblastic leukemia

Leukemia Research 34 (2010) 529–534

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Functional analyses of Src-like adaptor (SLA), a glucocorticoid-regulated gene in acute lymphoblastic leukemia Muhammad Mansha a,b , Michela Carlet a , Christian Ploner a , Georg Gruber a , Muhammad Wasim a,b , Gerrit Jan Wiegers c , Johannes Rainer a,b , Stephan Geley a , Reinhard Kofler a,b,∗ a b c

Division Molecular Pathophysiology, Biocenter, Medical University of Innsbruck, 6020, Austria Tyrolean Cancer Research Institute, Innsbruck 6020, Austria Division Developmental Immunology, Biocenter, Medical University of Innsbruck, 6020, Austria

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Article history: Received 1 May 2009 Received in revised form 23 June 2009 Accepted 26 June 2009 Available online 24 July 2009 Keywords: Glucocorticoid-induced apoptosis Functional gene analysis Signal transduction Lentiviral construct Stable transfected cell line CCRF-CEM NALM6 PreB697

a b s t r a c t Glucocorticoids (GCs) cause apoptosis and cell cycle arrest in lymphoid cells and are used in the therapy of lymphoid malignancies. SLA (Src-like-adaptor), an inhibitor of T- and B-cell receptor signaling, is a promising candidate derived from expression profiling analyses in children with acute lymphoblastic leukemia (ALL). Over-expression and knock-down experiments in ALL in vitro model revealed that transgenic SLA alone had no effect on survival or cell cycle progression, nor did it affect sensitivity to, or kinetics of, GC-induced apoptosis. Although SLA is a prominent GC response gene, it does not seem to contribute to the anti-leukemic effects of GC. © 2009 Elsevier Ltd. All rights reserved.

1. Introduction Glucocorticoids (GCs) induce apoptosis in certain cells of the lymphoid lineage, a trait that is exploited in the treatment of lymphoid malignancies, most notably childhood acute lymphoblastic leukemia (ALL) [1]. GCs mediate their effects via the GC receptor (GR), a ligand-activated transcription factor of the nuclear receptor super-family that resides in the cytoplasm and, upon ligand binding, translocates into the nucleus, where it modulates gene expression via binding to specific DNA response elements or by protein–protein interactions with other transcription factors [2]. A large number of genes have been identified that are regulated by GCs in lymphoid lineage cells in experimental systems [3] and related clinical samples [4,5], but the genes responsible for cell death induction and other effects of GCs on the immune system are not well understood (for recent reviews see [3,6–8]). One of the most interesting GC-regulated candidate genes is the Src-like adaptor gene (SLA). It was induced by GC in the majority of

∗ Corresponding author at: Division of Molecular Pathophysiology, Biocenter, Medical University of Innsbruck. Fritz-Pregl-Straße 3, A-6020 Innsbruck, Austria. Tel.: +43 512 9003 70360; fax: +43 512 9003 73960. E-mail address: Reinhard.Kofl[email protected] (R. Kofler). 0145-2126/$ – see front matter © 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.leukres.2009.06.029

children with precursor B-cell and T-cell ALL, in one patient with adult ALL and in 2 ALL cell lines, but not in peripheral blood lymphocytes from 2 healthy donors treated with GC [4]. More recently, we re-analyzed these data using a normalization procedure that better resolves regulations of low abundance genes (GeneChip Robust Multi-array Average, GC-RMA) [9] and also performed additional expression profiling studies of 14 more ALL children (unpublished); we found that SLA was induced by GC in 24 of 27 investigated children. SLA encodes an adaptor protein that negatively regulates cellular signaling initiated by tyrosine kinases in several systems. The mouse homologue was originally cloned in a yeast two hybrid screen as Eck (a member of the Eph family of receptor protein tyrosine kinases) binding protein [10]. Human SLA cDNA [11,12] was mapped to chromosome 8q22 [13] where the gene resides in an intron of the thyroglobulin gene and is read in opposite direction [12]. SLA negatively affects signaling of platelet derived growth factor (PDGF) in fibroblasts [14] and antigen receptors in T- and B-cells [15,16]. In the latter cell types, SLA reduces levels of the antigen–receptor complexes by adapting the E3 ubiquitin ligase c-CBL to components of the complex (such as CD3 zeta and/or epsilon, ZAP70) and targeting them for degradation [15–17]. Presumably as a consequence thereof, SLA knock-out affects both Band T-lymphocyte development [16,18]. Taken together, its welldocumented inhibitory role in lymphocyte signaling raised the

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attractive possibility that its induction might play a critical role in GC-induced cell cycle arrest and/or apoptosis. In this study, we extended our analysis of GC regulation of SLA to several leukemic cell lines and performed functional analysis addressing the question of whether SLA regulation accounts for, or is critically involved in, the anti-leukemic effects of GC. These studies revealed that, in the 9 cell lines tested, SLA induction by GC, but not its basal expression levels prior to GC exposure, correlated with responsiveness to GC as reflected in apoptosis induction and/or cell cycle arrest. However, SLA induction did not appear to be functionally relevant for these 2 anti-leukemic GC effects. 2. Materials and methods 2.1. Cell lines and tissue culture The T-ALL cell lines CCRF-CEM-C7H2 [19], CEM-C7H2-2C8 [20] (a CEM-C7H2 derivative with constitutive expression of the tetracycline-regulated reverse transactivator, rtTA [21]), MOLT4 (CRL-1582, ATCC, Rockville, MD), and Jurkat (untransfected and a rat GR-transfected derivative [22]), the precursor B-cell lines PreB697 (ACC 42, DSMZ, Braunschweig, Germany), NALM6 (ACC 128, DSMZ), RS4;11 (ACC 508, DSMZ) and AT-1 [23] (kindly provided by R. Panzer Grümeier, Vienna), and the Burkitt’s lymphoma Daudi (CCL-213, ATCC) were cultured in RPMI 1640 supplemented with 10% fetal calf serum and 2 mM l-glutamine at 37 ◦ C, 5% carbon-dioxide and saturated humidity. Human embryonic kidney (HEK) 293T packaging cells (American Type Culture Collection, ATCC, Manassas, VA) were cultured in DMEM supplemented as above. The authenticity of the cell lines was verified by DNA fingerprinting, as detailed previously [24]. Doxycycline (Sigma, Vienna Austria) was dissolved in phosphate buffered saline, ␤-dexamethasone (Sigma, Vienna Austria) in 100% ethanol. The final ethanol-concentration in the dexamethasone-treated and control cultures was maintained at 0.1%.

The construct was sequence-verified and subsequently recombined into the “destination vector” pHR-tetCMV-Dest (U311) to generate pHR-tetCMV-SLA (U329). The latter plasmid was transfected into 293T packaging cells and the lentiviruscontaining supernatant used to transduce CEM-C7H2-2C8, which constitutively express rtTA [20]. After limiting dilution cloning, 2 clonal cell lines, termed CEMC7H2-2C8-SLA#1 (SLA#1) and CEM-C7H2-2C8-SLA#4 (SLA#4), were selected for further experiments. 2.5. Generation of NALM6 and PreB697 cells with constitutive SLA expression The lentiviral constitutive expression plasmid pHR-SFFV-SLA-iresPuro (U432) was generated by recombining pENTR207-hSLA (U305, see above) into the “destination vector” pHR-SFFV-Dest-ires-Puro (U416). U416 was generated by cloning a PCR-amplified ires-Puro cassette (forward primer 5 -TATAGGATCCAAGCTTCCTAGGGTCGACG-3 , reverse primer derived from pLib-rtTA25 -TATAGCGGCCGCTCAGGCACCGGGCTTGCG-3 ) M2-ires-Puro (U122) [31] into the BamHI and blunt-ended NotI sites of TM pHR-SIN-CSGW-Not [30]. The vector was rendered GATEWAY compatible by insertion of an AttR-site flanked ccdB-CM cassette (Invitrogen, Carlsbad, CA) into the filled-in BamHI site of the above-generated vector. For control purposes, pENTR207-Venus (U411) was generated by amplifying the GFP derivative Venus [32] from pCS2-Venus (a kind gift of Dr. A. Miyawaki, Hirosawa, Japan) using 5 -CAAAAAAGCAGGCTCCGCCACCATGGTGAGCAAGGGCG and 5 CAAGAAAGCTGGGTCCTTGTACAGCTCGTCCATGC as primers, re-amplifying the product using primers 5 -GGGGACAAGTTTGTACAAAAAAGCAGGCTCC and 5 GGGGACCACTTTGTACAAGAAAGCTGGGTC, and recombining it after gel-purification into pDONR-207 using BP clonase (Invitrogen). U411 was recombined with pHR-SFFV-Dest-ires-Puro (++ generating pHR-SFFV-Venus-ires-Puro (U417). U432 or the control plasmid U417 were transfected into 293T packaging cells and lentivirus-containing supernatants used to transduce NALM6 or PreB697 cells. The cells were cultured in the presence of 1 ␮g/ml puromycin for 1 week and subsequently analyzed for their response to GC. 2.6. Real-time RT-PCR

2.2. Apoptosis determinations and cell cycle analyses Apoptosis was determined by fluorescence activated cell sorter (FACS) analyses of propidum iodide (PI)-treated permeabilized cells [25], as previously detailed [26]. In brief, cells were analyzed with a FACScan cytometer (Becton Dickinson Biosciences, San Jose, CA) in combination with CellQuest Pro software (Becton Dickinson Biosciences) acquiring forward scatter/sideward scatter, FL-2 (log), and FL-3 (linear). In FL-2, the percentage of nuclei with reduced DNA-content (subG1 peak) was assessed. GFP expression was detected by FACS analyses as above. In some instances (knock-down experiments with CEM-C7H2), we used the Annexin-V/7-aminoactinomycin D (7-AAD) method [27,28]. For this, 5 × 105 cells were double-stained with APC-Annexin-V and 7-AAD according to the protocol provided by Pharmingen (BD-Pharmingen, Heidelberg, Germany), and analyzed by FACS. Cells in the lower left quadrant were considered viable, and all others “apoptotic”. For cell cycle determination, the FACS data from PI-treated nuclei were analyzed using ModFit LT 2.0 (Verity, Topsham, ME). All the 3 of the following quality parameters had to be fulfilled: minimal number of events analyzed: 10,000; maximal %CV: 8; RCS between 0.8 and 6. 2.3. Immunoblotting Our immunoblotting procedure has been described in detail recently [29]. Briefly, proteins were extracted from 5 × 106 cells in 100 ␮l radio-immunoprecipitation assay (RIPA) buffer, quantified by Bradford analyses, mixed with 40 ␮l loading buffer (4×SSB, 5% ␤-mercaptoethanol), denatured, fractionated on a 12.5% SDS-PAGE and electroblotted onto nitrocellulose. The membranes were incubated overnight with rabbit polyclonal antibodies against SLA (H-106, Santa Cruz Biotechnology, CA, USA), or mouse monoclonal antibodies against ␣-tubulin (DM1A, CalBiochem, Nottingham, UK) as loading controls and specifically bound antibodies were detected with anti-mouse or anti-rabbit horseradish-peroxidaseconjugated secondary antibodies (ECLTM, Amersham Pharmacia Biotech, Uppsala, Sweden) visualised by chemiluminescence (ECL, Amersham) and exposure to AGFA Curix X-ray films. 2.4. Generation of CCRF-CEM derivatives with doxycycline-induced SLA expression The lentiviral conditional expression construct pHR-tetCMV-hSLA (U329) was generated using the GATEWAYTM technology (Invitrogen, Carlsbad, CA). The details of this procedure and the generation of stable clonal cell lines with tetracyclineregulated expression of cDNAs cloned into such constructs have been described previously [30]. In brief, human SLA mRNA was reverse transcribed into cDNA from total RNA of preB697 cells exposed to 10−7 M dexamethasone for 24 h, PCR-amplified using forward primer 5 -CAAAAAAGCAGGCTCCATGGGAAACAGCATGAAATCCACCC3 and reverse primer 5 -CAAGAAAGCTGGGTCTTAGTCCTCAAAGTAAGGTGGTGATGA3 , and recombined into pENTR207 (Invitrogen) resulting in pENTR207-hSLA (U305).

For real-time polymerase chain reaction (PCR), 50 ␮l of diluted cDNA (2 ng/␮l) were added to 50 ␮l of TaqMan Universal MasterMix (Applied Biosystems, Foster City, CA) and introduced into microfluidic cards containing real-time reverse transcriptase (RT)-PCR mixes for human SLA (Hs00277129 m1, Applied Biosystems) and TATA-box binding protein (TBP, Hs00427620 m1) according to the manufacturer’s guidelines: after equilibration at RT, the canals were filled with 100 ␮l of reaction mix and centrifuged 2 times for 1 min at 1000 rpm. Thereafter, the cards were sealed, loaded into the HT7900 real-time machine (Applied Biosystems), and run with a 2step PCR thermo-protocol that included an initial 94.5 ◦ C step for 10 min followed by 40 cycles of 97 ◦ C for 15 s alternating with 60 ◦ C for 1 min. Fluorescence signal intensities were read during the 60 ◦ C temperature step. Primary real-time PCR data analysis was performed with SDS software version 2.2.1, and further analysis was performed in R. Data from 3 technically replicated measurements were averaged and normalized to the internal TBP control. Log 2-fold change values (M values) were calculated for 3 biological replicates by comparing normalized real-time PCR data from GC-treated samples against data from the corresponding control samples. M values were averaged for the 3 biological replicates and p values were calculated (Student’s t-test) to test against the null hypothesis of no differential expression (mean M = 0).

3. Results 3.1. SLA is regulated in several GC-sensitive, but not in GC-resistant, leukemia cell lines To identify suitable models for testing the functional role of SLA in the anti-leukemic GC effects, we determined SLA expression and regulation by GC in various in vitro leukemia models using realtime RT-PCR for SLA and 9 leukemia cell lines treated with 10−7 M dexamethasone for 2, 6, 12 and 24 h in biological triplicates. The extent of GC sensitivity in these cell lines was markedly different (Fig. 1), i.e., untransfected Jurkats and MOLT4 T-ALL cell lines as well as AT-1 precursor B-ALL and Daudi Burkitt lymphoma cells were resistant to GC-induced apoptosis, while all others were GCsensitive, although with varying kinetics. GR-transfected Jurkats died after 24 h exposure to 10−7 M dexamethasone, the response in CEM-C7H2 was about 24 h delayed, NALM6 and RS4;11 showed a somewhat slower death response than CEM-C7H2, while PreB697 cells required 96 h to reach ∼40% apoptosis. In addition to apoptosis induction, we assessed possible effects of GC on cell cycle

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Fig. 1. GC-induced apoptosis and cell cycle arrest in various leukemia cell lines. CCRF-CEM-C7H2, Jurkat (untransfected and transfected with rat GR), MOLT4, NALM6, PreB697, RS4;11, AT-1 and Daudi cells were cultured in the presence of 10−7 M dexamethasone (Dex “+”) or 0.1% ethanol as vehicle control (Dex “−”) for the indicated time and subjected to apoptosis (•—•) or cell cycle (G1: dark gray bars; G2/M: light gray bars; S: open bars) determination using flow cytometric analyses of propidium iodide-stained nuclei. Shown are the mean values ± SD of specific apoptosis (apoptosis in GC-treated samples minus apoptosis in corresponding vehicle controls) or mean values of cells in the 3 phases of the cell cycle derived from biological triplicates. In some cases, cell cycle determinations did not fulfill the required quality requirements due to high degree of apoptosis and hence were not included in the figure. The apoptosis (but not the cell cycle) results from all cell lines except AT-1 have been reported previously [37].

progression as measured by analysis of DNA content (Fig. 1). This showed that GC-induced apoptosis was frequently preceded or accompanied by an increase of cells in the G1 phase of the cell division cycle, whereas the cell lines resistant to GC-induced apoptosis were also resistant to the GC effects on the cell cycle. The notable exception was AT-1, in which G1 cell cycle arrest was observed in the complete absence of apoptosis, making this an interesting model for studying GC-induced cell cycle arrest in the absence of apoptosis. Relative SLA expression levels among these cell lines were dramatically different (Fig. 2A), reflecting the situation in children with ALL [4]. SLA expression was not strongly related to GC sensitivity or T- or precursor B-cell origin of the cell lines (Fig. 1). No significant GC regulation (M > 1 and p < 0.05) of SLA was seen in GC-resistant Jurkat, MOLT4, and Daudi cells, whereas all 5 GC-sensitive cell lines, i.e., CEM-C7H2, GR-transfected Jurkats, NALM6, PreB697, RS4;11 and AT-1 (the latter showing GC-induced cell cycle effects but no apoptosis) induced SLA upon exposure to GC although to varying degrees (Fig. 2B). For functional analyses we selected CCRF-CEM as a model for T-ALL, and NALM6 and PreB697 as examples for precursor B-cell ALL. 3.2. SLA does not appear to participate in the anti-leukemic effects of GC To assess a possible contribution of SLA to the anti-leukemic GC effects in ALL, we generated 2 stable transduced derivatives of the CCRF-CEM T-ALL cell line with conditional expression of SLA. As revealed by quantitative RT-PCR and immunoblotting, SLA mRNA and protein expression in such cell lines could be controlled by the addition of the tetracycline analogue doxycycline to the cul-

ture medium (Fig. 3). As little as 3.12 ng/ml doxycycline led to a detectable induction of SLA mRNA that increased up to 50 ng/ml and reached a plateau thereafter (Fig. 3A, left panel), and close to maximal induction was seen after 2 h (shown for 200 ng/ml doxycycline in the right panel of Fig. 3A). Similar observations were made on the protein level (Fig. 3B), i.e., increasing protein levels were seen starting from 3.12 ng/ml doxycycline and plateaued at 50 ng/ml. The protein levels appeared to have reached a steady state after 6 h (the earliest time point analyzed) and did not further increase (the decrease in protein at the 24 h time point with doxycycline concentrations up to 50 ng/ml might be explained by doxycycline degradation combined with an apparently relatively short half life of the SLA protein). The above-mentioned clonal cell lines were then used for functional analyses to address the question of whether SLA expression affects cell survival or cell cycle progression and/or modulates the anti-leukemic effects of GC. As shown in Fig. 4, transgenic expression of SLA, even at levels that clearly exceeded those induced by GC, had no detectable effect on survival or cell cycle progression on its own, nor did it change extent or kinetics of GC-induced apoptosis or cell cycle arrest in this T-ALL in vitro model. To address the above question for precursor B-ALL cells, we transduced NALM6 and PreB697 cells with a lentiviral construct for constitutive expression of SLA (or the green fluorescent protein Venus as control). Although these cells expressed SLA at high levels on the mRNA and protein levels (Fig. 5A and B, respectively), they grew with kinetics indistinguishable from those of the Venusexpressing controls. Moreover, expression of transgenic SLA had no consistent significant effect on extent and kinetics of GC-induced apoptosis or cell cycle arrest (Fig. 5C).

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Fig. 2. Basal and GC-regulated SLA expression in various leukemia cell lines. The indicated cell lines were cultured for the indicated times in the presence of 10−7 M dexamethasone or 0.1% ethanol as vehicle control, and analyzed for SLA (and TBP as internal control) mRNA expression using quantitative real-time RT-PCR for SLA. (A) TBP-normalized SLA expression levels in the absence of dexamethasone expressed as mean CT . For each biological replicate of the 2 h vehicle controls, the CT value for SLA was subtracted from the corresponding TBP CT value; subsequently, mean and standard deviations were calculated (mean CT , values of +1 or −1 indicate 2-fold higher or lower expression than TBP, respectively). (B) GC regulation of SLA in the indicated cell lines at the indicated time points expressed as mean M values ± SD (M value of +1 or −1 indicates 2-fold up- or down-regulation, respectively). Asterisks indicate p values of <0.05 for the corresponding M value.

While the above experiments suggested that SLA alone is not sufficient to cause cell cycle arrest or apoptosis, the possibility was not excluded that SLA induction, in combination with some other GC-triggered signals, might be required for the anti-leukemic GC effect. To address this issue, we applied siRNA-mediated gene knock-down. As shown in Fig. 6A, doxycycline-induced SLA expression in C7H2-2C8-SLA#1 and C7H2-2C8-SLA#4 cells was reduced by ∼50% in cells treated with a mixture of modified siRNAs directed against SLA (Dharmacon “smart pool”), whereas a control siRNA mixture had no detectable effect despite transfection efficiencies of ∼80% in both instances. Using the same technology and transfection efficiency, we knocked-down SLA in untransfected CEM-C7H2, NALM6 and PreB697 cells, but observed no effect on GC-induced apoptosis (Fig. 6B). Hence, within the limitations of the siRNA technology applied, these data supported the notion derived from the SLA over-expression experiments that induction of SLA does not contribute to the anti-leukemic effect of GC, at least in the cell line systems investigated. 4. Discussion In this study, SLA, one of the most promising GC-regulated candidate genes for the anti-leukemic effects of GC, was functionally tested in T- and B-ALL cell lines. We have previously published

Fig. 3. Characterization of T-ALL cell lines with conditional SLA expression. C7H22C8-SLA#1 and #4 cells (expressing SLA in a doxycycline-dependent manner) were cultured in the presence of increasing concentration of doxycycline (Dox) for the indicated time and analyzed for SLA (and TBP as internal control) mRNA expression using quantitative real-time RT-PCR (A) or immunoblotting with antibodies against SLA and ␣-tubulin as loading control (B). The real-time RT-PCR data are expressed as −CT (i.e., CT value of SLA minus CT value of TBP). A dose response curve is shown for the 2 h time point (left panel of A) and a time course (right panel of A) for the 200 ng/ml doxycycline concentration compared to the mean expression levels for the 2, 6 and 24 h time points in the absence of doxycycline (“0”). Shown are the mean values ± SD from both cell lines each analyzed in 3 biological replicates. (B) A representative dose response at the protein level for the 6 h (left panel) and 24 h (right panel) time points for both cell lines.

Fig. 4. Conditional SLA over-expression in CCRF-CEM T-ALL cells has no effect on cell cycle progression, survival or GC anti-leukemic properties. C7H2-2C8-SLA#1 and #4 cells (expressing SLA in a doxycycline-dependent manner) were cultured in the absence or presence of 10−7 M dexamethasone (Dex), with and without 200 ng/ml doxycycline (Dox) for the indicated time and subjected to apoptosis (•—•) or cell cycle (G1: dark gray bars; G2/M: light gray bars; S: open bars) determination using flow cytometric analyses of propidium iodide-stained nuclei. Shown are the mean values ± SD of specific apoptosis (apoptosis in GC-treated samples minus apoptosis in corresponding vehicle controls) or mean values of cells in the 3 phases of the cell cycle derived from biological triplicates. In some cases, cell cycle determinations did not fulfill the required quality requirements due to high degree of apoptosis and hence were not included in the figure.

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Fig. 6. SLA knock-down by siRNA does not interfere with GC-induced apoptosis. (A) CEM-C7H2-2C8-SLA#1 and SLA#4 cells with conditional expression of SLA were treated with 200 ng/ml doxycycline to induce SLA expression to levels detectable by immunoblotting and transfected with either siRNAs directed against SLA (“+”) or the corresponding control siRNA (“−”) using Amaxa transfection technology. Cell lysates were prepared 24 h later and subjected to immunoblotting with an antibody specific to human SLA (SLA) or ␣-tubulin (␣-Tub) as a loading control. (B) CEM-C7H2, PreB697 and NALM6 cells were transfected with SLA siRNA or corresponding controls, as outlined above. Twenty-four hours after transfection, the cells were exposed to 10−7 M dexamethasone or 0.1% ethanol as vehicle control for the times indicated and subjected to apoptosis determination as outlined in Section 2. Shown are the mean percentage values ± SD of specific apoptosis (apoptosis in GC-treated samples minus apoptosis in corresponding vehicle controls) of 3 biological replicates.

Fig. 5. SLA over-expression does not affect the anti-leukemic effects of GC in PreB697 and NALM6 precursor B-cell leukemia cells. PreB697 and NALM6 precursor B-cell ALL cell lines were transfected with lentiviral constructs enabling constitutive expression of SLA or Venus (a modified green fluorescent protein) cDNA, respectively. Expression of SLA was determined at the mRNA level by quantitative RT-PCR (A); expressed as negative difference of CT values obtained for SLA and TBP, −CT ) and on the protein level by Western blotting (B) using an antibody against human SLA. An unknown protein (“non-specific”) recognized by this antibody equally well in transfected, sham-transfected or untransfected cells served as loading control. (C) The same cells (Venus-transfected cells are denoted “SLA −”, and SLA-transfected cells “SLA +” in the graphs) were treated with 10−7 M dexamethasone (Dex “+”) or 0.1% ethanol as vehicle control (Dex “−”) for the indicated time and subjected to apoptosis (•—•) or cell cycle (G1: dark gray bars; G2/M: light gray bars; S: open bars) determination using flow cytometric analyses of propidium iodide-stained nuclei. Shown are the mean percentage values ± SD of specific apoptosis (apoptosis in GCtreated samples minus apoptosis in corresponding vehicle controls) or mean values of cells in the 3 phases of the cell cycle derived from biological triplicates. In some cases, cell cycle determinations did not fulfill the required quality requirements due to high degree of apoptosis and hence were not included in the figure.

that SLA was more than 2-fold induced in 9 of 13 children with ALL during systemic GC monotherapy [4]. Re-analysis of the above microarray data using an improved normalization procedure and inclusion of additional 14 children revealed 2-fold induction in 24/27 children, all of whom showed significant blast reduction within the first 2–3 days of treatment (unpublished). Moreover, as shown in Fig. 2B, all leukemia in vitro models that responded to GC with apoptosis (CEM-C7H2, GR-transfected Jurkat, NALM6, PreB697, RS4;11) or G1 arrest (AT-1) showed clear induction (M > 1 and p < 0.05) of SLA. The early onset of regulation (after 2 h, Fig. 2B) and our unpublished ChIP-on-CHIP data in CEM-C7H2 showing GRbinding sites in the SLA gene strongly suggest that SLA is a direct GC response gene in lymphoid cells and perhaps other cell types, where GC induction has been observed as well [33]. Although SLA seems to be a primary GC response gene, our gene over-expression and siRNA-mediated knock-down experi-

ments suggested that its induction by GC is neither sufficient nor required for GC-induced apoptosis in 3 in vitro models for GC-induced apoptosis. This raises the question of the biological significance of SLA induction. Since several studies have shown that SLA interferes with T-cell [15,17,18,34,35] and B-cell [16,36] receptor signaling, SLA appears to be an attractive candidate for a mediator of the immunosuppressive action of GCs. Acknowledgements We thank A. Kofler, S. Lobenwein and C. Mantinger for technical assistance, and M. Kat Occhipinti-Bender for editing the manuscript. This work is supported by grants from the Austrian Science Fund (SFB-F021, P18747, P18571), the Austrian Ministry for Education, Science and Culture (GENAU-Ch.I.L.D.) and Higher Education Commission of Pakistan (HEC). The Tyrolean Cancer Research Institute is supported by the “Tiroler Landeskrankenanstalten Ges.m.b.H. (TILAK)”, the “Tyrolean Cancer Aid Society”, various businesses, financial institutions and the People of Tyrol. References [1] Pui CH, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med 2004;350:1535–48. [2] Laudet V, Gronemeyer H. The nuclear receptor facts book. London: Academic Press; 2002. [3] Schmidt S, Rainer J, Ploner C, Presul E, Riml S, Kofler R. Glucocorticoid-induced apoptosis and glucocorticoid resistance: molecular mechanisms and clinical relevance. Cell Death Differ 2004;11(Suppl. 1):S45–55. [4] Schmidt S, Rainer J, Riml S, Ploner C, Jesacher S, Achmüller C, et al. Identification of glucocorticoid response genes in children with acute lymphoblastic leukemia. Blood 2006;107:2061–9. [5] Tissing WJ, den Boer ML, Meijerink JP, Menezes RX, Swagemakers S, van der Spek PJ, et al. Genome-wide identification of prednisolone-responsive genes in acute lymphoblastic leukemia cells. Blood 2007;109:3929–35. [6] Distelhorst CW. Recent insights into the mechanism of glucocorticosteroidinduced apoptosis. Cell Death Differ 2002;9:6–19.

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